Novel methods improve prediction of species’ distributions from occurrence data
Abstract
Prediction of species’ distributions is central to diverse applications in ecology, evolution and conservation science. There is increasing electronic access to vast sets of occurrence records in museums and herbaria, yet little effective guidance on how best to use this information in the context of numerous approaches for modelling distributions. To meet this need, we compared 16 modelling methods over 226 species from 6 regions of the world, creating the most comprehensive set of model comparisons to date. We used presence‐only data to fit models, and independent presence‐absence data to evaluate the predictions. Along with well‐established modelling methods such as generalised additive models and GARP and BIOCLIM, we explored methods that either have been developed recently or have rarely been applied to modelling species’ distributions. These include machine‐learning methods and community models, both of which have features that may make them particularly well suited to noisy or sparse information, as is typical of species’ occurrence data. Presence‐only data were effective for modelling species’ distributions for many species and regions. The novel methods consistently outperformed more established methods. The results of our analysis are promising for the use of data from museums and herbaria, especially as methods suited to the noise inherent in such data improve.
Detailed knowledge of species’ ecological and geographic distributions is fundamental for conservation planning and forecasting (Ferrier 2002, Funk and Richardson 2002, Rushton et al. 2004), and for understanding ecological and evolutionary determinants of spatial patterns of biodiversity (Rosenzweig 1995, Brown and Lomolino 1998, Ricklefs 2004, Graham et al. 2006). However, occurrence data for the vast majority of species are sparse, resulting in information about species distributions that is inadequate for many applications. Species distribution models attempt to provide detailed predictions of distributions by relating presence or abundance of species to environmental predictors. As such, distribution models have provided researchers with an innovative tool to explore diverse questions in ecology, evolution, and conservation. For example, they have been used to study relationships between environmental parameters and species richness (Mac Nally and Fleishman 2004), characteristics and spatial configuration of habitats that allow persistence of species in landscapes (Araújo and Williams 2000, Ferrier et al. 2002a, Scotts and Drielsma 2003), invasive potential of non‐native species (Peterson 2003, Goolsby 2004), species’ distributions in past (Hugall et al. 2002, Peterson et al. 2004) or future climates (Bakkenes et al. 2002, Skov and Svenning 2004, Araújo et al. 2004, Thomas et al. 2004, Thuiller et al. 2005), and ecological and geographic differentiation of the distributions of closely‐related species (Cicero 2004, Graham et al. 2004b).
Most research on development of distribution modelling techniques has focused on creating models using presence/absence or abundance data, where regions of interest have been sampled systematically (Austin and Cunningham 1981, Hirzel and Guisan 2002, Cawsey et al. 2002). However, occurrence data for most species have been recorded without planned sampling schemes, and the great majority of these data consist of presence‐only records from museum or herbarium collections that are increasingly accessible electronically (Graham et al. 2004a, Huettmann 2005, Soberón and Peterson 2005). The main problem with such occurrence data is that the intent and methods of collecting are rarely known, so that absences cannot be inferred with certainty. These data also have errors and biases associated with them, reflecting the frequently haphazard manner in which samples were accumulated (Hijmans et al. 2000, Reese et al. 2005). Thus, the considerable potential of occurrence data for analysis of biodiversity patterns, will only be realised if we can use them critically. Simultaneous with increasing accessibility of species’ occurrence data, environmental data layers of high spatial resolution, such as those derived from satellite images (Turner et al. 2003) and through sophisticated interpolation of climate data (Thornton et al. 1997, Hijmans et al. 2005), are now much more abundant and available. In parallel, development of methods for efficient exploration and summary of patterns in large databases has accelerated in other disciplines (Hastie et al. 2001), but only a few of these have been applied in ecological studies. Given the widespread use of distribution modelling, and the synergy of advances in data availability and modelling methods, a clear need exists for broad synthetic analyses of the predictive ability and accuracy of species’ distribution modelling methods for presence‐only data.
There is now a plethora of methods for modelling species’ distributions that vary in how they model the distribution of the response, select relevant predictor variables, define fitted functions for each variable, weight variable contributions, allow for interactions, and predict geographic patterns of occurrence (Guisan and Zimmerman 2000, Burgman et al. 2005, Wintle and Bardos in press). Initial attempts to analyze presence‐only data used methods developed specifically for that purpose, based either on calculations of envelopes or distance‐based measures (Gómez Pompa and Nevling 1970, Rapoport 1982, Silverman 1986, Busby 1991, Walker and Cocks 1991, Carpenter et al. 1993). Attention then turned to adapting presence‐absence methods (i.e. those that model a binomial response) to model presence‐only data, using samples of the background environment (random points throughout the study area), or of areas designated as “non‐use” or “pseudo‐absence” (Stockwell and Peters 1999, Boyce et al. 2002, Ferrier et al. 2002a, Zaniewski et al. 2002, Keating and Cherry 2004, Pearce and Boyce in press).
More recently several novel modelling methods have been proposed that have foundations in ecological and/or statistical research, that may perform well for distribution modelling with noisy data, such as presence‐only records. Some of these methods use information on the presences of other members of the community to supplement information for the species being modelled. Community methods are promising, especially for rare species, because the additional information carried by the wider community may help to inform the modelled relationships. Further, extensive research in the machine‐learning and statistical disciplines has produced methods that are able to capture complex responses, even with noisy input data. These have received very little exposure in distribution modelling, though the work that has been done is promising (Phillips et al. 2006, Leathwick et al. in press).
Regardless of the modelling method chosen, a major problem in evaluation is that species’ distributions are not known exactly. In many instances evaluation focuses on predictive performance, some known occurrences are withheld from model development (either by splitting the data set, k‐fold partitioning, or bootstrapping; Fielding and Bell 1997, Hastie et al. 2001, Araújo et al. 2005), and accuracy is assessed based on how well models predict the withheld data (Boyce et al. 2002, Hirzel et al. in press). In presence‐only modelling, such withheld data are unlikely to provide a general test of model accuracy in predicting species’ distributions, because the occurrence records often have biases in both geographic and environmental space (Bojórquez et al. 1995, Hijmans et al. 2000, Soberon et al. 2000, Kadmon et al. 2004) and such biases will persist in common resampling designs. More importantly, withheld data are presence‐only, which limits the options for, and power of, statistical evaluations of predictive performance. One step towards improving evaluation of model performance in predicting distributions of species is to use independent, well structured presence‐absence datasets for validation. Such datasets have rarely been used to evaluate predictions from presence‐only models (but see Ferrier and Watson (1997) for an earlier example of this type of evaluation). Further possibilities include modelling artificial data and assessing whether responses are correctly predicted (Austin et al. 1995), or modelling with both presence‐only and presence‐absence data and comparing the fitted functions (Ferrier and Watson 1997).
The primary aim of this research was to evaluate the capacity of presence‐only occurrence data for predicting species’ distributions. We chose to focus on evaluation at independent sites, using the performance of different modelling methods averaged over many species. Detailed evaluation of the ecological realism of all models was not practical. We tested the performance of a representative selection of modelling methods for presence‐only data, using data sets typical of the types of species and environmental data that are commonly employed. This exercise also provides insights into whether and how these increasingly available data can be used for improving knowledge of species’ ranges. We compiled data only for regions in which independent presence‐absence data were available for evaluation and invited participation from researchers experienced in a range of distribution modelling methods, including several novel methods that have not been used widely in ecology. Our model comparison is very broad, applying 16 methods to modelling the distributions of 226 species from 6 regions around the globe.
Materials and methods
Data for modelling and evaluation
Our intention in selecting data was to collect representative examples of the types of data and species that are commonly used in species distribution modelling. Species locality data were assembled for six regions of the world (Tables 1 and 2): birds and plants of the Australian Wet Tropics (AWT); birds of Ontario, Canada (CAN); plants, birds, mammals and reptiles of north‐east New South Wales, Australia (NSW), plants of New Zealand (NZ), plants from five countries (see footnote, Table 1) of South America (SA), and plants of Switzerland (SWI). The individual data sets had up to 54 species with a range of geographic extents and rarities. For each region, two sets of data were available: 1) presence‐only (PO) data, from unplanned surveys or incidental records, including those from museums and herbaria; and 2) independent presence‐absence (PA) data from planned surveys, with accurate location records. The independence of these two data sets for each region is an important underlying assumption of this study, and the totally different data collection methods for the two sets give us a high level of confidence that this assumption is well founded. Table 2 summarises the key characteristics of the data. One feature is that the accuracy and sample size of the modelling data vary between regions: mostly they were small‐to‐moderate (101–102 occurrences), but were larger (101–103) for SWI. Evaluation (PA) sets were larger for CAN, NZ and SWI than the other regions. Further, the PA data sets for AWT, NSW, NZ and SWI all provide better environmental and geographic coverage than those for CAN and SA.
| Region | Species records | Predictor variables | |||
|---|---|---|---|---|---|
| Groups (number species) | PO1: number (mean) | PA1: number sites; mean no. presence | Broad class | Cell size (m) and extent (km2×106) | |
| Australian Wet Tropics (AWT) | birds (20) | 155 | 340; 97 | 10 climate, | 80×80 m |
| plants (20) | 35 | 102; 30 | 3 topography | 0.024 | |
| Ontario, Canada (CAN) | birds (20) | 255 | 14571; 1282 | 6 climate, 3 topography, 1 distance, 1 vegetation | 1×1 km 1.088 |
| New South Wales, Australia (NSW) | birds (10) | 162 | mean3 920; 74 | 5 climate, 2 soil, | 100×100 m |
| plants (29) | 22 | mean3 1333; 214 | 1 site moisture, | 0.089 | |
| mammals (7) | 27 | 570; 76 | 3 topography, | ||
| reptiles (8) | 84 | 1008; 62 | 1 disturbance, | ||
| 1 vegetation | |||||
| New Zealand (NZ) | plants (52) | 18–211 | 19120; 1801 | 8 climate, | 100×100 m |
| 2 substrate, | 0.265 | ||||
| 3 topography | |||||
| South America2 (SA) | plants (30) | 17–216 | 152; 12 | 11 climate | 1×1 km |
| 14.654 | |||||
| Switzerland (SWI) | plants (30) | 36–5822 | 10013; 810 | 7 climate, | 100×100 m |
| 2 substrate, | 0.041 | ||||
| 2 topography, | |||||
| 2 vegetation | |||||
- 1 PO is the presence‐only modelling data and PA, the presence‐absence evaluation data.
- 2 Five countries: continental Brazil, Ecuador, Colombia, Bolivia, and Peru.
- 3 Means of subsets of sites appropriate to different groups of plants and birds (Table 2).
| Region | Species information | PO data | PA data |
|---|---|---|---|
| AWT | 20 birds and 20 plants. | Birds from incidental surveys (accurate locations1); plants from herbarium records within last 40 yr (±3 km) #presence records: Birds mean 155, range 32–265; 78% occupied cells have >1 species. Plants: mean 35, range 9–74; 37% occupied cells have >1 species. | Birds from planned field surveys at 340 sites (accurate locations); plants from planned surveys over 20 yr at 102 sites (accurate locations) #presence records: birds mean 97, range 32–265; plants: mean 30, range 13–214. |
| CAN | 20 birds. | Ontario Nest Records, Royal Ontario Museum (ROM). Temporal Span 1870–2002 (mostly 1960–2001). Coordinates derived from map by ROM; some locations with GPS. #presence records: mean: 255, range: 16–749; 26% occupied cells have >1 species. | Breeding Bird Atlas (BBA) for Ontario. 14571 sites #presence records: mean: 1282, range: 24–4512. |
| NSW | 54 species: 7 bats (ba); 8 diurnal birds (db); 2 nocturnal birds (nb); 8 open‐forest trees (ot); 8 open‐forest understorey plants (ou); 7 rainforest trees (rt); 6 rainforest understorey plants (ru); 8 small reptiles (sr). | Fauna incidental records from Atlas of NSW Wildlife; flora from herbaria. Across all groups, #presence records: mean: 62, range: 2–426; 21% occupied cells have >1 species. | From designed surveys (Ferrier and Watson 1996, Pearce et al. 2001). Accurate locations. #of sites: ba 570, db 702, nb 1137, ot 2076, ou 1309, rt 1036, ru 909, sr 1008. Across all groups, #presence records: mean: 148, range: 4–693. |
| NZ | 52 plants, mostly trees and shrubs. | Herbarium data. #presence records: mean: 59, range 18–211; 16% occupied cells have >1 species. | Designed surveys; 19?120 sites. Accurate locations. #presence records: mean: 1801, range 20–10?581. |
| SA | 30 plants, family Bignoniaceae. | Herbarium data. #presence records: mean: 74, range 17–216; 36% occupied cells have >1 species. | Al Gentry's data (Missouri Botanie Gardens); 152 sites. #presence records: mean: 12, range 7–29. |
| SWI | 30 trees. | Forest vegetation data from non‐systematic surveys. 1913–1998; 75% post‐1940. #presence records: mean: 1170, range 36–5822; 80% occupied cells have >1 species. | Forest inventory plots on regular lattice; 10?013 sites. Accurate locations. #presence records: mean: 810, range: 19–6953. |
- 1 Locations are considered accurate if location error is estimated to be ≤100 m. Where accurarcy data are not presented, no information was provided.
The environmental data used for each region were selected for their relevance to the species being modelled (Austin 2002), as determined by the data provider (Tables 1 and 3). Eleven to 13 predictors were supplied per region, with grid cell sizes ranging from ca 100 by 100 m (AWT, NSW, NZ, SWI) to 1000 by 1000 m (CAN, SA). Several regions had data sets where previous research informed the development of ecologically relevant predictors (NSW, NZ, SWI). Other regions simply used variables typical of those used in distribution modelling, with emphasis on climatic data (CAN, SA, AWT). None of the exact data sets used in our study have previously been used for modelling, but some published studies (Ferrier and Watson 1997, Guisan et al. 1998, Venier et al. 2001, Leathwick 2002) use subsets of these or closely related data.
| Region | Grid cell size | Projection | Variables | Correlated pairs (pearson r>0.85) |
|---|---|---|---|---|
| AWT | 80 m | UTM | 10 climate from BIOCLIM (1: annual mean temp, 2: temp seasonality, 3: max temp of warmest month, 4: min temp of coolest month, 5: annual precipitation, 6: precip seasonality, 7: precip driest quarter, 8: annual mean radiaton, 9: moisture index (MI) seasonality, 10: mean MI of lowest quarter MI), 11: slope, 12: topographic position, 13: terrain ruggedness index. | 1 with 3,4;5 and 8 with 7;6 and 8 with 9;10 with 6,7,8,9. |
| CAN | 1 km | unprojected | 6 climate from WORLDCLIM (1: annual mean temp, 2: april temp, 3: temperature seasonality, 4: annual precipitation, 5: precip seasonality, 6: precip driest quarter), 7: altitude, 8: aspect (northness), 9: slope, 10: distance from Hudson Bay, 11: vegetation class (5 classes). | 1 with 2,5,6,10;2 with 3,5,6,10;3 with 5,6;4 with 5,6; 5 with 6. |
| NSW | 100 m | unprojected | 5 climate (mean annual rainfall, mean rainfall of driest quarter, annual mean temperature, minimum temperature of the coldest month, annual mean solar radiation), moisture index, soil fertility, soil depth, ruggedness, topographic position, compound topographic index, disturbance, vegetation class (9 classes). | min temp with mean temp. |
| NZ | 100 m | NZ map grid | 8 climate (mean October vapour pressure deficit at 09:00 h, vapour pressure deficit, mean annual solar radiation, mean annual temperature, temperature seasonality, average monthly ratio of rainfall to potential evaporation(r2pet), annual precipitation, solar radiation seasonality), age of bedrock, toxic cations in soil, altitude, slope, hillshade. | r2pet with annual precip; mean annual temp with altitude. |
| SA | 1 km | unprojected | 11 climate variables from WORLDCLIM (1: annual mean temperature, 2: mean diurnal range, 3: temperature seasonality, 4: max temp of warmest month, 5: min temp of coldest month, 6: temp annual range, 7: mean temp of wettest quarter, 8: annual precipitation, 9: precip seasonality, 10: precip driest quarter, 11: precip warmest quarter). | 1 with 4,5,7;2 with 6,4 and 5 with 7. |
| SWI | 100 m | UTM | 7 climate (1: growing days above freezing, 2: average temp coldest month, 3: days of summer frost, 4: annual precip, 5: days rain >1 mm, 6: site water balance, 7: potential yearly global radiation), slope, topographic position, soil nutrient index, calcareous bedrock, broadleaf cover, conifer cover. | 1 with 2. |
The data as supplied required considerable grooming and manipulation to generate datasets of consistent quality both within and between regions. For each region, environmental predictor variables were manipulated so that projections, grid cell size and alignment, and spatial extent were consistent across all layers. Some species data (particularly in the PO datasets) had many records per grid cell because of either repeat observations over years, or sites in close proximity to each other. We reduced both the PO and PA datasets to one record per grid cell. For the PA data, if any record in the grid cell was a presence, presence was assigned to the one record that was kept regardless of whether there was also an absence in the same grid cell. This was not a common feature of the data, but it occurred at least once in all data sets except SA. In a small number of cases both a PO and PA record occurred in the same grid cell; in these the PA record was usually deleted in order to ensure that there was no spatial overlap between the modelling and evaluation data sets. The exception was for the AWT data, where the PO record was deleted due to limited PA data.
As some of the modelling methods required data akin to absences, background samples (sometimes also referred to as “pseudo‐absences”; Ferrier et al. 2002a) were generated by drawing a random sample of 10 000 sites for each region. These were intended as a sample of the whole region, and it is possible that a background sample coincided with a presence record. In another study we address alternative strategies for creating such data (and see Zaniewski et al. 2002, Graham et al. 2004a). It is important to note that the community methods (MARS‐COMM and GDM) described below use the species data differently to single species methods (see Appendix, Text S1). In particular, they define a model using all sites available for all the species of the relevant biological group, and assume absences at sites if presence is not recorded, effectively treating all presence sites for a group of species as indicating an absence for any species not recorded at a particular site. To preserve as much consistency as possible between the single species and community modelling approaches, we used background samples in addition to the community data for fitting the community models. Nevertheless, the inclusion of the community data sets these apart from the single‐species methods.
Modelling methods
Eleven distinct modelling methods were used, but a number of these were implemented in more than one way, resulting in the 16 approaches presented here (Table 4 and Appendix, Text S1). The methods form two broad groups based on the type of data they use: those that only use presence records (BIOCLIM, DOMAIN, LIVES), and those that characterise the background with a sample (all other methods). Among the techniques that characterise the background, a critical distinction exists between those that use only the presence records for the modelled species vs those that use data describing the presences of other species, i.e. community‐based techniques. Details and key references for each method are in Appendix, Text S1 and Table 4, and the following briefly introduces the methods, with more detail for lesser‐known techniques.
| Method | Class of model, and explanation | Data1 | Software | Uncert‐aintyest?2 | Contact person |
|---|---|---|---|---|---|
| BIOCLIM | envelope model | p | DIVA‐GIS | no | CG, RH |
| BRT | boosted decision trees | pa | R, gbm package | no | JE |
| BRUTO | regression, a fast implementation of a gam | pa | R and Splus, mda package | yes | JE |
| DK‐GARP | rule sets from genetic algorithms; desktop version | pa | DesktopGarp | no | ATP |
| DOMAIN | multivariate distance | p | DIVA‐GIS | no | CG, RH |
| GAM | regression: generalised additive model | pa | S‐Plus, GRASP add‐on | yes | AG,AL,JE |
| GDM | generalised dissimilarity modelling; uses community data | pacomm | Specialized program not general released; uses Arcview and Splus | no | SF |
| GDM‐SS | generalised dissimilarity modelling; implementation for single species | pa | as for GDM | no | SF |
| GLM | regression; generalised linear model | pa | S‐Plus, GRASP add‐on | yes | AG,AL,JE |
| LIVES | multivariate distance | p | Specialized program not general released | no | JLi |
| MARS | regression; multivariate adaptive regression splines | pa | R, mda package plus new code to handle binomial responses | yes | JE, FH |
| MARS‐COMM | as for MARS, but implemented with community data | pacomm | as for MARS | yes | JE |
| MARS‐INT | as or MARS; interactions allowed | pa | as for MARS | yes | JE |
| MAXENT | maximum entropy | pa | Maxent | no | SP |
| MAXENT‐T | maximum entropy with threshold features | pa | Maxent | no | SP |
| OM‐GARP | rule sets derived with genetic algorithms; open modeller version | pa | new version of GARP not yet available | no | ATP |
- 1 p=only presence data used; pa=presence and some form of absence required – e.g. a background sample; comm=community data contribute to model fitting.
- 2 any method can have an uncertainty estimate derived from bootstrapping the modelling; these data refer to estimates that are available as a statistical part of the method.
The first group of methods (those that only use presence records) includes one envelope‐style method (BIOCLIM) that characterises sites that are located within the environmental hyper‐space occupied by a species, and two distance‐based methods (DOMAIN and LIVES) that assess new sites in terms of their environmental similarity to sites of known presence. The two distance‐based methods differ both in their theoretical assumptions and the procedures used for calculating similarities.
The second group of methods includes several regression approaches (Table 4). Generalised linear models (GLMs) and generalised additive models (GAMs) are used extensively in species’ distribution modelling because of their strong statistical foundation and ability to realistically model ecological relationships (Austin 2002). GAMs use non‐parametric, data‐defined smoothers to fit non‐linear functions, whereas GLMs fit parametric terms, usually some combination of linear, quadratic and/or cubic terms. Because of their greater flexibility, GAMs are more capable of modelling complex ecological response shapes than GLMs (Yee and Mitchell 1991). BRUTO provides a rapid method to identify both the variables to include and the degree of smoothing to be applied in a GAM model, but has only recently been used in ecological applications (Leathwick et al. unpubl.). Multivariate adaptive regression splines (MARS) provide an alternative regression‐based method for fitting non‐linear responses, using piecewise linear fits rather than smooth functions. They are much faster to implement than GAMs, and simpler to use in GIS applications when making maps of predictions. An added feature that we investigate here is their ability to analyse community data (Leathwick et al. 2005), i.e. to simultaneously relate variation in the occurrence of all species to the environmental predictors in one analysis, and then estimate individual model coefficients for each species (MARS‐COMM). Most of our implementations of the regression methods did not attempt to model interactions, with the exception of the MARS models, where we allowed the fitting of first‐order interactions in single species models (MARS‐INT).
We implemented two versions of GARP: the desktop version that has been used widely for modelling data from natural history collections (DK‐GARP), and a new open modeller implementation (OM‐GARP), that has updated algorithms for developing rule sets. These both use a genetic algorithm to select a set of rules (e.g. adaptations of regression and range specifications) that best predicts the species distribution (Stockwell and Peters 1999).
Two methods have been developed within the machine learning community: maximum entropy models (MAXENT and MAXENT‐T) and boosted regression trees (BRT, also called stochastic gradient boosting). MAXENT estimates species’ distributions by finding the distribution of maximum entropy (i.e. closest to uniform) subject to the constraint that the expected value of each environmental variable (or its transform and/or interactions) under this estimated distribution matches its empirical average (Phillips et al. 2006). In the MAXENT application for modelling presence‐only species’ data, choices can be made about the complexity of the fitted functions. BRT combines two algorithms: the boosting algorithm iteratively calls the regression‐tree algorithm to construct a combination or “ensemble” of trees. Regression trees are used because they are good at selecting relevant variables and can model interactions; boosting is used to overcome the inaccuracies inherent in a single tree model. The regression trees are fitted sequentially on weighted versions of the data set, where the weights continuously adjust to take account of observations that are poorly fitted by the preceding models. Boosting can be seen as a method for developing a regression model in a forward stage‐wise fashion, at each step adding small modifications in parts of the model space to fit the data better (Friedman et al. 2000). When using BRT, we avoided overfitting by using cross‐validation to progressively grow models while testing predictive accuracy on withheld portions of the data.
Finally, generalised dissimilarity models (GDM) model spatial turnover in community composition (or “compositional dissimilarity”) between pairs of sites as a function of environmental differences between these sites. The approach combines elements of matrix regression and generalised linear modelling, thereby allowing it to model non‐linear responses to the environment that capture ecologically realistic relationships between dissimilarity and ecological distance (Ferrier 2002, Ferrier et al. 2002b). For predicting species’ distributions, an additional kernel regression algorithm (Lowe 1995) is applied within the transformed environmental space generated by GDM, to estimate likelihoods of occurrence of a given species at all sites. Two versions of this approach were applied in the current study: 1) “GDM” in which a single GDM was fitted to the combined data for all species in a given biological group, such that the output from this GDM was then used as a common basis for all of the subsequent kernel regression analyses; and 2) “GDM‐SS” in which a separate GDM was fitted to the data for each species alone, such that kernel regression analysis for each species was based on the output from a GDM tailored specifically to that species.
As the manner in which a particular method is implemented can have substantial effects on model performance, we deliberately used experienced analysts to develop all models. We also implemented batch processing of methods in order to run the large number of models presented here, using settings judged by the modellers to provide a robust and reliable implementation of the method. Details are contained in Appendix, Text S1 and Table S1.
Experimental design
All analyses were carried out by modellers (Appendix, Table S2) blind to the evaluation data, which was not examined until after all modelling was complete. We provided modellers with the presence‐only (PO) locations for each species and random background locations (one set for each of the 6 regions). For each region, environmental data were presented in two formats: either as a table that included the environmental variables for each PO and random locality, or as environmental grids. The modellers could use the modelling data in any way they chose, to decide how to develop their models (e.g. they could run cross‐validation testing on the PO data). Based on these decisions, modellers made predictions for each species using a set of evaluation data, one set of which was prepared for each region. This consisted of a table of environmental data for the evaluation sites, but it contained no species records, i.e., predictions were made from the PO data with no knowledge of the pattern of the species as described by the PA dataset. Modellers who applied more than one method to the data (Appendix, Table S2) approached each method as a new situation and aimed to implement the method in the best way possible for a multi‐species analysis (Appendix, Text S1).
Evaluation
The evaluation focussed on predictive performance at sites. We used three statistics, the area under the Receiver Operating Characteristic curve (AUC), correlation (COR) and Kappa, to assess the agreement between the presence‐absence records and the predictions. AUC has been used extensively in the species’ distribution modelling literature, and measures the ability of a model to discriminate between sites where a species is present, versus those where it is absent (Hanley and McNeil 1982). This provides an indication of the usefulness of the models for prioritising areas in terms of their relative importance as habitat for the particular species. The AUC ranges from 0 to 1, where a score of 1 indicates perfect discrimination, a score of 0.5 implies predictive discrimination that is no better than a random guess, and values <0.5 indicate performance worse than random. “Worse than random” can occur because a model may fit the modelling data but predict badly, and we tested predictive performance on independent data rather than model fit. AUC values can be interpreted as indicating the probability that, when a presence site and an absence site are drawn at random from the population, the first will have a higher predicted value than the second. It is closely related to a Mann‐Whitney U statistic, and it is in this context it is seen to be a rank‐based statistic – the prediction at the presence site can be higher than the prediction at the absence site by a small or large amount, and the value of the statistic will be the same. Standards errors were calculated with the methods of Hanley and McNeil (1982).
The correlation, COR, between the observation in the PA dataset (a dichotomous variable) and the prediction, is known as the point biserial correlation, and can be calculated as a Pearson correlation coefficient (COR; (Zheng and Agresti 2000)). It is similar to AUC, but carries with it extra information: instead of being rank‐based, it takes into account how far the prediction varies from the observation. This gives further insight into the distribution of the predictions, and in the technical evaluation framework of Murphy and Winkler (1992) further informs the user about the model's discrimination.
Kappa (Cohen 1960), which is a chance‐corrected measure of agreement, is commonly used in ecological studies with presence‐absence data. It requires a threshold to be applied to the predictions, to convert them to presence‐absence predictions. Kappa provides an index that considers both omission and commission errors. We calculated a maximum kappa (KAPPA) for each model by calculating kappa at all possible thresholds for each species‐specific set of predictions and identifying both the maximum kappa and the threshold at which this occurred. This method used information not available to the modeller – i.e. information from the evaluation data set. It returns the best possible KAPPA score for each method. Liu et al. (2005) have demonstrated that other methods are more reliable for selecting thresholds from the training data (i.e. that used in model development), but in this case we wanted to characterise the best possible KAPPA value that could be attained on these evaluation data, so that threshold selection did not confound the results.
Variation in AUC and COR values were analysed using Generalized Linear Mixed Models, with the statistic (e.g. AUC) as the response and modelling method fitted as a fixed effect. Both species and an interaction between modelling method and region were fitted as random effects, the interaction term allowing for differing performance of methods across regions. Analyses were performed using WinBUGS (Spiegelhalter et al. 2003a), which fits a Bayesian model. We assumed uninformative priors for all parameters, resulting in a GLMM that is equivalent to one fitted using maximum likelihood. Comparisons of the sixteen methods were summarized from 50 000 Monte Carlo iterations after a burn‐in period of 10 000. The performance of modelling method was summarized as the mean and standard deviation of the posterior distributions. The percentage of runs where the response (e.g. AUC) for method X is greater than that for method Y estimates the probability that the true difference between the methods is greater than zero. This is a 2‐tailed test, and values close to 1 mean that method X's response is greater than that of method Y, and vice‐versa for values close to zero. The importance of each term in the GLMM was assessed by change in the Deviance Information Criterion (DIC, Spiegelhalter et al. 2003b) for the full model compared with subsets where each term was excluded from the model. The DIC is the Bayesian equivalent of Akaike's Information Criterion, and rules of thumb suggest that changes in DIC of >10 units indicate that the excluded term had an important effect (Burnham and Anderson 2002, McCarthy and Masters 2005).
To further explore the results, we calculated a series of metrics that define the distances between sites, and the area occupied, in both environmental and geographic space. These are useful for assessing to what extent a species “fills” the regional space. The nearest neighbour (NN, also called p‐median) summarises the distances between points in multidimensional environmental space, using a Manhattan distance (Sneath and Sokal 1973). We used the 10 000 random points and the presences in the evaluation data set and calculated the median of the minimum distances between any one random point and all the presence points. In each dimension, the distance was scaled by the range of the random points. NN values are larger for species that occupy only part of the environmental space of the region. The range overlap method used the same sets of points but summarised the mean overlap in ranges over all environmental dimensions; high values indicate species that span most of the environmental space in the regions. In contrast to those two methods, maximum distance and area of convex polygons are measures in geographic space, calculated on presence only data but presented in relation to the maximum measures in the presence absence data for each biological group in each region. Small distances or areas indicate species that are restricted geographically.
Finally, we recorded time taken for modelling and made comments on potential improvements, and these are presented in Appendix, Table S2.
Results
To display mapped model results, we show distributions predicted with several modelling methods for species in NSW (Fig. 1 and Appendix, Fig. S1). These maps illustrate variation in model predictions among techniques. There is considerable agreement between some methods. The most obvious differences are in the proportion of the region that appears to be predicted most suitable for the species, and although these might stem from predictions that are scaled in different ways, the variation in AUC suggests actual differences between methods.

Maps for two species from NSW for each of three selected techniques. Details: ousp6, Poa sieberiana (53 records for modelling and 512 presence/797 absence for evaluation); srsp6 Ophioscincus truncatus (79 model, 74/932 eval). The first column shows modelling sites (grey triangles) and evaluation sites: presence=black circle, absence=black cross.
Evaluating the results at independent sites across all species and methods, we found clear indications that presence‐only data can provide the basis for accurate predictions, but also marked variation in modelling success (Fig. 2 and Appendix, Table S3). For example, although AUC varied from 0.07 to 0.97, 40% of models had an AUC>0.75 (a useful amount of discrimination; see methods), and 90% of methods performed better than random (AUC>0.5). The following analyses explore trends and sources of variation among methods, regions and species.

Distribution of AUC for all species and from all methods. The solid curve is a density plot, and the y axis is scaled to show the relative density of points; for the histogram bars the sum of the area below all bars is 1. The grey vertical solid line shows random predictions, and grey dashed indicates reasonable predictive performance.
A) Broad trends across regions and species
Assessments of modelling success using AUC and COR indicate that methods can be analysed in three groups (Fig. 3 and Appendix, Fig. S2). The first and highest‐performing group (above‐right of the solid black line in Fig. 3) included MARS community (MARS‐COMM), boosted regression trees (BRT), generalised dissimilarity (GDM and GDM‐SS) and maximum entropy (MAXENT and MAXENT‐T) models, all of which performed relatively well according to each of the evaluation measures (Figs. 3 and 4). A second group of methods (between the solid and dashed diagonal black lines, Fig. 3) showed intermediate performance for AUC and COR. It included most of the standard regression methods (generalised additive models – GAM and BRUTO; generalised linear models – GLM; individual multivariate adaptive regression splines – MARS), and OM‐GARP. Models in the third group all performed relatively poorly (lower left of the dashed black line, Fig. 3) and included the 3 methods that use only presence data with no inferred absences (BIOCLIM, LIVES, DOMAIN), along with DK‐GARP, and the MARS individual models fitted with interactions (MARS‐INT). This group also deviated from the generally linear relationship between AUC and COR results, i.e. assessment of their predictive success depends on which measure is used. DOMAIN was close to the middle group in relation to AUC but not COR, and DK‐GARP was close for COR but less successful with AUC. DK‐GARP results are not completely comparable to the others because this method could not be applied to for one region (NZ) because of computational constraints.

Mean AUC vs mean correlation (COR) for modelling methods, summarised across all species. The grey bars are standard errors estimated in the GLMM (see Appendix), reflecting variation for an average species in an average region. The labels are broad classifications of the methods: grey underlined=only use presence data, black capitals=use presence and background samples, black lower case italics=community methods.

Performance measured by maximum kappa and its variance across all species. Variance axis reversed so low is higher on plot; it is desirable to have high kappa and low variance (i.e. upper right in plot), for consistent and good performance. Labels as for Fig. 3.
The GLMMs confirmed our graphical interpretation and indicated that differences in the performance of modelling methods were statistically important, because the removal of the modelling method term from the full model resulted in a change in the Deviance Information Criterion of 472 units (Table 5). These results are for AUC, and those for COR are comparable. Results from the pair‐wise comparison of methods (Table 6) indicate that those methods occurring to the top right in Fig. 3 provide significantly better performance that those to the lower left, and also to several methods located in the central part of this figure. The error bars in Fig. 3 are those estimated from the model, and bars that do not overlap coincide with high probabilities that the methods are different (Fig. 3, Table 6).
| Model | DIC1 |
|---|---|
| Full model:AUC∼Method+Method×Region+Species | −8996 |
| Without Method | −8524 |
| Without Interaction (Method×Region) | −8803 |
| Without Species | −4071 |
- 1Deviance Information Criterion. Changes in DIC >10 are important.
| BIOCLIM | BRT | BRUTO | DOMAIN | GAM | GLM | DK‐GARP | OM‐GARP | GDM | GDM‐SS | LIVES | MAXENT | MAXENT‐T | MARS | MARS‐INT | MARS‐COMM | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| BIOCLIM | ||||||||||||||||
| BRT | 0.000 | |||||||||||||||
| BRUTO | 0.019 | 0.988 | ||||||||||||||
| DOMAIN | 0.013 | 0.979 | 0.422 | |||||||||||||
| GAM | 0.011 | 0.976 | 0.413 | 0.495 | ||||||||||||
| GLM | 0.012 | 0.982 | 0.447 | 0.527 | 0.534 | |||||||||||
| DK‐GARP | 0.200 | 0.999 | 0.882 | 0.914 | 0.916 | 0.909 | ||||||||||
| OM‐GARP | 0.010 | 0.976 | 0.400 | 0.475 | 0.487 | 0.449 | 0.078 | |||||||||
| GDM | 0.000 | 0.757 | 0.061 | 0.089 | 0.093 | 0.076 | 0.004 | 0.095 | ||||||||
| GDM‐SS | 0.000 | 0.791 | 0.076 | 0.107 | 0.110 | 0.095 | 0.006 | 0.119 | 0.549 | |||||||
| LIVES | 0.124 | 0.999 | 0.832 | 0.877 | 0.877 | 0.864 | 0.394 | 0.888 | 0.993 | 0.992 | ||||||
| MAXENT | 0.000 | 0.733 | 0.052 | 0.075 | 0.081 | 0.065 | 0.004 | 0.085 | 0.469 | 0.424 | 0.007 | |||||
| MAXENT‐T | 0.000 | 0.658 | 0.032 | 0.049 | 0.050 | 0.043 | 0.002 | 0.054 | 0.381 | 0.337 | 0.003 | 0.411 | ||||
| MARS | 0.017 | 0.986 | 0.479 | 0.552 | 0.560 | 0.530 | 0.111 | 0.580 | 0.933 | 0.918 | 0.151 | 0.942 | 0.964 | |||
| MARS‐INT | 0.169 | 0.999 | 0.877 | 0.914 | 0.916 | 0.900 | 0.465 | 0.924 | 0.996 | 0.995 | 0.576 | 0.997 | 0.998 | 0.888 | ||
| MARS‐COMM | 0.000 | 0.425 | 0.009 | 0.015 | 0.016 | 0.012 | 0.000 | 0.016 | 0.190 | 0.157 | 0.000 | 0.213 | 0.279 | 0.010 | 0.000 |
The same general trends are evident also for KAPPA (Fig. 4), although methods are not so clearly separated because KAPPA is a less sensitive measure, estimating performance at a single prediction threshold. Nevertheless, the highest‐performing methods as assessed by AUC and COR also had the highest KAPPA scores (to the right in Fig. 4) and the presence‐only methods also ranked among the lowest.
B) Comparison of regional results
Predictive success varied markedly across regions (Fig. 5, Appendix, Figs. S3 and S4; Table 7 and Appendix, Table S3). For example, AUC scores were generally high for SWI and SA (mean values of 0.77 and 0.76, Table 7, and details in Appendix, Table S3), intermediate for NSW, NZ and AWT (mean AUC 0.69, 0.71, 0.67 respectively) and mostly poor for CAN (mean AUC 0.58). Regional differences as assessed using COR (Table 7, Appendix, Table S3) and KAPPA (Appendix, Tables S3 and S4) indicated a slightly different ordering of regions: SA and AWT were better modelled than the next group (SWI, NSW, NZ), but again predictions for CAN species were generally poor. The relative success of different methods did not differ greatly across the three test statistics, therefore we focus on AUC statistics for the remainder of this section.

Predictive success across regions, for 10 methods. Regions are sorted by the mean AUC across all 16 methods and all species per region.
| Method | Mean AUC | Mean COR | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| AWT | CAN | NSW | NZ | SA | SWI | AWT | CAN | NSW | NZ | SA | SWI | |
| BIOCLIM | 0.65 | 0.63 | 0.63 | 0.61 | 0.75 | 0.71 | 0.22 | 0.08 | 0.12 | 0.08 | 0.29 | 0.15 |
| BRT | 0.68 | 0.60 | 0.71 | 0.73 | 0.80 | 0.81 | 0.24 | 0.08 | 0.19 | 0.18 | 0.32 | 0.24 |
| BRUTO | 0.64 | 0.55 | 0.68 | 0.72 | 0.75 | 0.79 | 0.20 | 0.04 | 0.15 | 0.17 | 0.22 | 0.20 |
| DK‐GARP | 0.68 | 0.56 | 0.66 | na1 | 0.75 | 0.70 | 0.28 | 0.05 | 0.15 | na1 | 0.21 | 0.13 |
| DOMAIN | 0.67 | 0.60 | 0.70 | 0.69 | 0.77 | 0.73 | 0.22 | 0.05 | 0.15 | 0.10 | 0.21 | 0.14 |
| GAM | 0.65 | 0.55 | 0.68 | 0.73 | 0.75 | 0.80 | 0.22 | 0.04 | 0.15 | 0.17 | 0.23 | 0.21 |
| GDM | 0.67 | 0.57 | 0.73 | 0.74 | 0.79 | 0.78 | 0.24 | 0.06 | 0.21 | 0.16 | 0.30 | 0.19 |
| GDM‐SS | 0.70 | 0.56 | 0.70 | 0.73 | 0.79 | 0.79 | 0.29 | 0.04 | 0.17 | 0.15 | 0.28 | 0.20 |
| GLM | 0.66 | 0.57 | 0.68 | 0.71 | 0.74 | 0.78 | 0.24 | 0.06 | 0.16 | 0.16 | 0.22 | 0.19 |
| LIVES | 0.66 | 0.61 | 0.66 | 0.66 | 0.77 | 0.72 | 0.23 | 0.06 | 0.12 | 0.08 | 0.21 | 0.13 |
| MARS | 0.66 | 0.55 | 0.67 | 0.72 | 0.75 | 0.79 | 0.23 | 0.04 | 0.15 | 0.17 | 0.24 | 0.21 |
| MARS‐COMM | 0.67 | 0.64 | 0.73 | 0.74 | 0.77 | 0.82 | 0.20 | 0.11 | 0.19 | 0.18 | 0.26 | 0.26 |
| MARS‐INT | 0.65 | 0.54 | 0.64 | 0.70 | 0.73 | 0.78 | 0.22 | 0.05 | 0.14 | 0.16 | 0.24 | 0.21 |
| MAXENT | 0.68 | 0.58 | 0.71 | 0.74 | 0.78 | 0.80 | 0.23 | 0.05 | 0.18 | 0.18 | 0.27 | 0.24 |
| MAXENT‐T | 0.69 | 0.58 | 0.71 | 0.73 | 0.77 | 0.80 | 0.24 | 0.06 | 0.18 | 0.18 | 0.26 | 0.25 |
| OM‐GARP | 0.69 | 0.55 | 0.68 | 0.70 | 0.77 | 0.77 | 0.29 | 0.04 | 0.15 | 0.13 | 0.25 | 0.19 |
| mean | 0.67 | 0.58 | 0.69 | 0.71 | 0.76 | 0.77 | 0.24 | 0.06 | 0.16 | 0.15 | 0.25 | 0.20 |
- 1 DK‐GARP could not be run for NZ; the large number of grid cells could not be accomodated by the available computers.
In some regions there were relatively large differences in mean AUC among methods, whereas in others differences were more muted, as shown by the vertical spread of the lines in Fig. 5 (and see Table 7). When data are analysed within regions there is less power to detect differences, so error bars were relatively larger (compare Fig. 3 and Appendix, Fig. S5) and fewer pairwise differences between methods were significant. Our ability to clearly distinguish between methods was partly related to the amount of evaluation data; SWI, NZ, and CAN had more data (i.e. number of records per species is to the right of Appendix, Fig. S6, leading to lower standard errors, Appendix, Fig. S7), and more records provide more opportunity to find differences in these regions. For example, Table 8 presents pairwise differences for SA and SWI, and demonstrates more distinctions between methods in SWI. Nevertheless, Nevertheless, relative rankings of methods were broadly consistent across regions (Fig. 5, Table 7, and see Appendix, Table S3, Fig. S5) and the group of highest‐performing methods identified in Fig. 3 was generally reliable across all regions, but with some variation depending on the evaluation statistic (Appendix, Fig. S5).
| BIOCLIM | BRT | BRUTO | DOMAIN | GAM | GLM | DK‐GARP | OM‐GARP | GDM | GDM‐SS | LIVES | MAXENT | MAXENT‐T | MARS | MARS‐INT | MARS‐COMM | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| (a) | ||||||||||||||||
| BIOCLIM | ||||||||||||||||
| BRT | 0.002 | |||||||||||||||
| RUTO | 0.653 | 0.999 | ||||||||||||||
| DOMAIN | 0.098 | 0.940 | 0.045 | |||||||||||||
| GAM | 0.521 | 0.998 | 0.367 | 0.912 | ||||||||||||
| GLM | 0.740 | 1.000 | 0.600 | 0.973 | 0.723 | |||||||||||
| DK‐GARP | 0.649 | 0.999 | 0.495 | 0.953 | 0.628 | 0.395 | ||||||||||
| OM‐GARP | 0.102 | 0.944 | 0.049 | 0.513 | 0.093 | 0.028 | 0.049 | |||||||||
| GDM | 0.011 | 0.706 | 0.003 | 0.155 | 0.009 | 0.002 | 0.003 | 0.147 | ||||||||
| GDM‐SS | 0.024 | 0.814 | 0.009 | 0.254 | 0.022 | 0.004 | 0.010 | 0.243 | 0.638 | |||||||
| LIVES | 0.223 | 0.982 | 0.124 | 0.706 | 0.206 | 0.081 | 0.126 | 0.694 | 0.939 | 0.886 | ||||||
| MAXENT | 0.083 | 0.931 | 0.038 | 0.467 | 0.074 | 0.022 | 0.039 | 0.456 | 0.826 | 0.721 | 0.268 | |||||
| MAXENT.T | 0.160 | 0.969 | 0.083 | 0.618 | 0.145 | 0.051 | 0.085 | 0.609 | 0.907 | 0.834 | 0.408 | 0.650 | ||||
| MARS | 0.598 | 0.999 | 0.444 | 0.939 | 0.577 | 0.347 | 0.448 | 0.936 | 0.995 | 0.987 | 0.844 | 0.949 | 0.893 | |||
| MARS‐INT | 0.906 | 1.000 | 0.824 | 0.996 | 0.897 | 0.748 | 0.825 | 0.995 | 1.000 | 1.000 | 0.980 | 0.997 | 0.989 | 0.857 | ||
| MARS‐COMM | 0.193 | 0.976 | 0.104 | 0.667 | 0.178 | 0.065 | 0.105 | 0.657 | 0.927 | 0.863 | 0.459 | 0.696 | 0.552 | 0.133 | 0.014 | |
| (b) | ||||||||||||||||
| BIOCLIM | ||||||||||||||||
| BRT | 0.000 | |||||||||||||||
| BRUTO | 0.000 | 0.995 | ||||||||||||||
| DOMAIN | 0.006 | 1.000 | 1.000 | |||||||||||||
| GAM | 0.000 | 0.954 | 0.193 | 0.000 | ||||||||||||
| GLM | 0.000 | 0.999 | 0.719 | 0.000 | 0.925 | |||||||||||
| DK‐GARP | 0.809 | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 | ||||||||||
| OM‐GARP | 0.000 | 1.000 | 0.996 | 0.000 | 1.000 | 0.981 | 0.000 | |||||||||
| GDM | 0.000 | 1.000 | 0.943 | 0.000 | 0.993 | 0.841 | 0.000 | 0.140 | ||||||||
| GDM‐SS | 0.000 | 0.992 | 0.439 | 0.000 | 0.762 | 0.231 | 0.000 | 0.002 | 0.041 | |||||||
| LIVES | 0.142 | 1.000 | 1.000 | 0.919 | 1.000 | 1.000 | 0.026 | 1.000 | 1.000 | 1.000 | ||||||
| MAXENT | 0.000 | 0.900 | 0.102 | 0.000 | 0.342 | 0.033 | 0.000 | 0.000 | 0.002 | 0.132 | 0.000 | |||||
| MAXENT‐T | 0.000 | 0.840 | 0.060 | 0.000 | 0.243 | 0.016 | 0.000 | 0.000 | 0.001 | 0.081 | 0.000 | 0.387 | ||||
| MARS | 0.000 | 0.988 | 0.391 | 0.000 | 0.719 | 0.194 | 0.000 | 0.002 | 0.032 | 0.448 | 0.000 | 0.839 | 0.899 | |||
| MARS‐INT | 0.000 | 1.000 | 0.853 | 0.000 | 0.971 | 0.676 | 0.000 | 0.053 | 0.295 | 0.886 | 0.000 | 0.989 | 0.995 | 0.907 | ||
| MARS‐COMM | 0.000 | 0.251 | 0.000 | 0.000 | 0.009 | 0.000 | 0.000 | 0.000 | 0.000 | 0.001 | 0.000 | 0.025 | 0.048 | 0.002 | 0.000 | |
Some interesting patterns and exceptions to model performance by region were apparent. Performance of methods in NSW, NZ, SA, and SWI was generally similar, with BRT, MAXENT and MAXENT‐T, MARS‐COMM, and GDM and GDM‐SS usually performing well. In NZ, presence‐only methods (BIOCLIM, DOMAIN and LIVES) performed particularly poorly. In most regions DOMAIN and LIVES had lower COR values in relation to AUC than the average method (i.e. they sit below the line fitted to the means in Appendix, Fig. S5).
The importance of the interaction term (method×region) in the GLMM (Table 5) indicated anomalies in the relative performance of methods in particular regions. These tended to occur in regions with lower overall performance – i.e. to the right in Fig. 5 (see also Table 7 and Appendix, S3), and with highest uncertainty in estimates (see standard errors, Appendix, Fig. S5). For example, in AWT, OM‐GARP ranked with the better methods (GDM‐SS and MAXENT‐T), whereas it generally had only intermediate overall performance in all other regions (Fig. 5, Table 7). However, AUC only varied from 0.64 to 0.70 in AWT and many differences were not statistically important (Appendix, Fig. S5). Canada had the lowest AUC, COR and KAPPA scores of any region, and many methods performed poorly, with evaluation statistics only marginally better than random (Table 7 and Appendix, Table S3; Figs S3, S4 and S5). Of the two methods with the highest AUC scores in CAN, one (MARS‐COMM) ranked consistently among the best across regions, whereas the other (BIOCLIM) tended to be among the lowest.
C) Results at the species level
The greatest variation in the performance of different methods was apparent at the species level, but with similar trends: methods shown above to perform well when averaged across species and regions (i.e. MARS‐COMM, BRT, MAXENT/MAXENT‐T and GDM/GDM‐SS) also tended to perform well when ranked against other methods on an individual species’ basis (Table 9 and Appendix, Fig. S2). Figure 6a shows results from SA that are typical for most regions, in that there is marked variation in which methods perform best for different species (i.e. lines cross in the graphs). Most methods occasionally failed badly, although the better methods tended to have more stable performance. The exception to this general pattern was SWI, in which we observed clear and reasonably consistent separation between methods (Fig. 6b), probably reflecting the larger amounts of accurately located data for both modelling and evaluation. Results for SWI using both AUC and COR indicate that the highest‐performing methods for most species were MARS‐COMM, BRT and MAXENT/MAXENT‐T, while the lowest were LIVES, BIOCLIM, and DK‐GARP (Appendix, Fig. S5). Across all species in all regions, and considering the best method only, 78% of species had AUC scores of 0.70 or more, and 64% had scores of 0.75 or more (Appendix, Table S3). In some cases a species was modelled well (or poorly) by most methods, whereas in others there was considerable variation in predictive accuracy depending on the method used. Mean AUC scores per species varied from 0.36 to 0.97, with coefficients of variation (cv) ranging from 2 to 47% (Appendix, Table S3). The correlation between mean AUC and cv was weakly negative (Pearson r=−0.39), indicating a slight trend for more variation across methods for species with low mean AUC scores.
| Method (sorted by column 2) | Mean AUC rank per species | Rank of mean AUC over all species |
|---|---|---|
| MARS‐COMM | 6.15 | 1 |
| BRT | 6.20 | 2 |
| MAXENT‐T | 6.42 | 3 |
| MAXENT | 6.69 | 5 |
| GDM‐SS | 7.38 | 6 |
| GDM | 7.53 | 4 |
| GAM | 8.26 | 7 |
| GLM | 8.64 | 10 |
| DOMAIN | 8.70 | 9 |
| BRUTO | 8.79 | 12 |
| MARS | 8.92 | 8 |
| OM‐GARP | 8.92 | 11 |
| MARS‐INT | 9.72 | 13 |
| LIVES | 10.22 | 14 |
| DK‐GARP | 10.47 | 15 |
| BIOCLIM | 10.85 | 16 |

Predictive performance for the 30 South American species (6a) and the 30 Swiss species (6b) for 10 methods. Species are sorted by the mean AUC across all 16 methods.
Predictive performance did not vary consistently with number of presence records available for modelling (Table 10, Fig. 7, Appendix, Table S5). Species that are rarer because they are environmentally or geographically restricted appeared to be modelled with greater accuracy than more common and generalist species (Table 10). We note here and discuss later that this result depends on the spatial extent of analysis and the type of evaluation.
| Sample sizes | Environmental space | Geographic space | ||||
|---|---|---|---|---|---|---|
| P in PO | Prevalence | Nearest neighbour | Range overlap | Relative maximum distance | Relative area of convex polygon | |
| AWT | −0.340* | −0.276 | 0.589* | −0.302 | −0.456* | −0.421* |
| CAN | 0.048* | −0.318 | 0.621* | −0.589* | −0.313 | −0.304 |
| NSW | −0.045 | −0.654* | 0.675* | −0.770* | −0.230 | −0.359* |
| NZ | 0.028 | −0.298* | 0.713* | −0.669* | −0.491* | −0.300* |
| SA | −0.601* | −0.714* | 0.541* | −0.922* | −0.667* | −0.708* |
| SWI | −0.186 | −0.165 | 0.619* | −0.520* | −0.534* | −0.620* |
- Asterisks indicate significant values (p<0.05). Prevalence is the frequency of occurrence records in the PA data. The measures are detailed in the methods.

The maximum AUC (o&v;er all methods) &v;s sample size in modelling data. Each point represents a species.
Discussion
The model comparison developed herein is unique for its broad geographic scope, application of numerous of modelling methods (including several new techniques) to the analysis of presence‐only data, and incorporation of extensive presence/absence data to enable well‐informed evaluations of predictive performance. We interpret results in the context of the feasibility of using such techniques to predict accurately species’ distributions in situations in which only presence data are available. Our explanation also explores the utility of the vast storehouse of occurrence information in resources such as world natural history museums.
We can draw two major conclusions from our results. First, presence‐only data are useful for modelling species’ distributions. This result bolsters the recent movement to capitalize on the growing availability of both species’ occurrence records (Soberon et al. 2000, Graham et al. 2004a) and high‐resolution spatial environmental data. Not all species were predicted well according to our evaluation data, but we found that 64% of the best models for each species had AUCs >0.75 and an additional 14% had AUCs between 0.7 and 0.75. These AUC scores indicate that predictions based on presence‐only data can be sufficiently accurate to be used in conservation planning (Pearce and Ferrier 2000a) and in numerous other applications in which estimates of species’ distribution are relevant. Second, new modelling methods that have only recently been applied to the challenge of modelling species’ distributions generally outperformed established methods. Some of these new methods originated in other disciplines and have had little exposure in ecological analyses. These methods appear to offer considerable promise across a much broader range of ecological applications, providing an exciting avenue for future research. The other strong performers were community methods, and these also deserve further scrutiny, particularly where data for the species in question are sparse.
Broad comparison of methods
We demonstrated differences in predictive performance among modelling methods, despite substantial variation at both regional and species levels. Within the suite of relatively commonly used methods, those that characterise the background environment and that can differentially weight variables outperform those that use presence data alone (BIOCLIM, LIVES, and – for some measures – DOMAIN). These results give no support to using methods that do not attempt to characterise the distribution of a species relative to the background environment in which it occurs. The various regression‐based methods are largely indistinguishable from one another in terms of predictive performance. The new version of GARP (OM‐GARP), first implemented for this study, is comparable to, but slower than, the regression methods and outperforms the widely used desktop version.
Results for the more common approaches are consistent with previous studies of presence‐absence modelling methods, and with the relatively few comparisons of methods used to model presence‐only data. Studies of presence‐absence modelling methods suggest that several non‐linear techniques (e.g. GAMs, artificial neural networks, and MARS) are comparable in terms of predictive ability, and are often superior to methods such as traditional single decision trees (Ferrier and Watson 1997, Elith and Burgman 2002, Moisen and Frescino 2002, Muñoz and Fellicísimo 2004, Segurado and Araujo 2004). Comparisons of methods using presence‐only records are less common, but tell a similar story: GLMs and GAMs generally outperform simpler methods (Ferrier and Watson 1997, Brotons et al. 2004), MAXENT outperforms GARP (Phillips et al. 2006) and some presence‐only methods (e.g. DOMAIN, ENFA, (Hirzel et al. 2002)) have advantages over BIOCLIM (Loiselle et al. 2003). Most of these studies, however, have focused on single geographic regions and/or smaller numbers of species. Several have been evaluated on the same data sets as were used for model development, and this makes it difficult to generalise results, and to discern whether models have good predictive performance or whether they are simply overfit (Leathwick et al. unpubl.). Our use of independent presence/absence test data across multiple geographic regions provides a broader basis for comparisons.
A novel aspect of our work is the inclusion of newer modelling methods that have had little exposure in previous comparative studies and few applications in ecology in general. These novel methods outperform the established methods, and this observation should provoke attention and scrutiny. Several of the novel methods have been developed and tested in fields other than species’ distribution modelling, and have been shown to handle noisy data and complex analytical challenges successfully. For example, boosted regression trees have been a focus of attention in the machine‐learning and statistical fields for a number of years (Ridgeway 1999, Hastie et al. 2001), but the present paper and a companion application to New Zealand fish (Leathwick et al. in press) are among the first in ecology. Similarly, maximum entropy methods are well known in other fields (Jaynes 1982) but only recently developed for questions of species’ distributions (Phillips et al. 2006).
One question of interest is whether our “best” methods share certain characteristics that set them apart from the others? One feature that they all share in common is a high level of flexibility in fitting complex responses. As a consequence they all have what we term here “expressiveness”– a well‐developed ability to express or demonstrate the complex relationships that exist in the data. In several methods this includes effective mechanisms for modelling interactions among variables. However, expressiveness needs to be controlled so that models are not overfit, and to that end several methods use “regularization” techniques (Hastie et al. 2001) to achieve balance between complexity and parsimony.
These methods achieve those goals in different ways. BRT achieves expressiveness by combining the strengths of regression trees, namely omission of irrelevant variables and ability to model interactions, with those of boosting, that is, the building of an ensemble of models that approximate the true response surface more accurately than a single model by overcoming the misclassification problems inherent in single tree models. Both the model building procedure (a penalized forward stepwise search) and our cross‐validation methods for finding optimal numbers of trees help to control overfitting. The application of maximum entropy methods to distribution modelling was developed specifically for use with presence‐only occurrence data (Phillips et al. 2006). In MAXENT, strong focus has been placed on the role of penalty functions (i.e. regularization) in parameter estimation. Regularization has most impact when sample sizes are small, so the MAXENT modellers tuned their regularization in relation to sample size (Phillips et al. 2004). MAXENT can also fit complex functions between response and predictor variables, and can include interaction terms but to a more limited extent than BRT. GDM‐SS models are single‐species versions of the community‐based GDM models. They are parameterized on data for individual species, not including community data. These models are developed in a 2‐step fashion, which together achieves controlled expressiveness. The first step operates effectively like a GAM, fitting additive smoothing functions (albeit to dissimilarities rather than raw observations). The second step, a kernel regression, incorporates interactions by modelling distances and densities within a truly multivariate predictor space, with no assumption of additivity. The success of the kernel regression step depends on the first step accurately transforming the predictor space, thereby addressing the “curse of dimensionality” normally associated with kernel regression type techniques (Lowe 1995).
The success of these new methods suggests that predictive performance of some more common methods such as GAMs might be improved substantially if better tradeoffs between expressiveness and complexity could be incorporated into the model fitting process. In the case of GAMs the issue is not whether it can fit complex responses – it can – but whether the model building methods commonly used are optimal for species distribution modelling. One aspect is modelling interactions, which is possible in regression but rarely implemented when many species are being modelled. Another is model selection: alternative techniques already exist, but are rarely implemented in ecology. For example, the “lasso,” used for regularization in MAXENT, can be applied to variable selection and coefficient estimation in regression (Hastie et al. 2001), and has been shown to perform better than stepwise selection for determining model complexity (Tibshirani 1996).
Ferrier et al. (2002b) developed and used GDM for reserve selection and survey design. The impetus for using GDM and other community modelling methods (e.g. MARS‐COMM) in distribution modelling is based on the understanding that important but subtle environmental trends may only be apparent in the response of multiple species, and, more pragmatically, that rare species are difficult to model with standard statistical methods and, hence, community signals may improve model performance. Community models use information from suites of species to inform variable selection and modelling. Relevant predictors are included because of their strong community signal, whereas that signal might be insufficient to trigger inclusion in single species models (Leathwick et al. unpubl.). GDM is the more ecologically sophisticated approach to community modelling, but the simpler MARS‐COMM models performed at least as well in this study. The comparison of MARS single species models with the MARS community models shows that the community models perform strongly in this trial. In contrast, a recent application of MARS and MARS‐COMM to modelling a large presence‐absence freshwater fish data set from New Zealand indicated no consistent advantage for community models (Leathwick et al. unpubl.). This difference probably reflects the advantage in using community data to infer absences for presence‐only data (see Materials and methods), the importance of the community signal in the more biased and noisier data analyzed here, and the small amounts of data available for fitting some species. Further comparisons of alternative community modelling approaches would be useful to identify the factors influencing success of the various techniques. It is likely that the inference of absences is important, and could be adopted as an alternative to random background samples for single species models.
In summary, we suggest that the good performance of the novel methods result from their ability to fit complex responses (often including interactions) and select a relevant set of variables. We do not expect that the fitted models are too complex – for example, MAXENT as used here is similar in expressiveness to a GLM without interactions (for species with <80 presences) or a GAM with pairwise interactions (Appendix, Text S1). However, for any method an ability to fit complex responses is not useful in itself, and has to be balanced against the requirement for model features to be ecologically realistic (Austin 2002). Systematic assessment of whether individual fitted responses were realistic was beyond the scope of the current research as our aim was to test models across numerous species and regions. Nonetheless, this would be a fruitful avenue for research and model assessment.
Regional patterns
The trend for good performance of the novel methods in our experiment (BRT, MAXENT, GDM and MARS‐COMM) was also apparent at the regional level. In regions such as SWI, where overall performance was high, the “best” methods performed well, but most methods were able to produce reasonable quality models for many of the species. Exceptions to the usual ranking of methods sometimes appeared in regions in which overall predictive performance was generally poor (AWT and CAN), with no clearly consistent cause. In these regions, the good methods usually still showed moderate success in prediction, and often were not impacted as severely as other methods. The fact that some regions had relatively poor average performance and even the best methods could not do well suggests that in such regions, modelling might most benefit from attempts to improve the training data set. This is particularly apparent in the CAN bird data set, in which the data display many of the biases possible in presence‐only data (Anderson 2003). Sampling is severely biased towards the southern extreme of the study area, species’ ranges are only partially represented, and environmental data may not capture the important conditions affecting bird distribution, especially those with large ranges. The effects of the partial sampling of ranges may be similar to those demonstrated by Randin et al. (in press) in their study of transferability of models. One would expect the sampling bias to be particularly problematic in cases, like CAN, where the gradient in sampling efforts corresponds to strong environmental gradients. As a consequence, only 4 of 20 species had a mean ROC>0.7, and the best methods (MARS‐COMM and BIOCLIM) had mean ROC scores of only 0.63 across species. With poor modelling success, the data and ecology of the species need to be further investigated to identify how to supplement or otherwise improve both the species’ occurrence records and the predictor variable set.
Species‐level patterns
Though not a primary focus of our analysis, we can highlight two results to guide those needing to understand what species’ attributes might affect model performance. Firstly, sample size (i.e. number of occurrence records) was not consistently related to modelling success. While other studies indicate that small sample size negatively influences modelling success (Pearce and Ferrier 2000a, Harrell 2001, Stockwell and Peterson 2002, Kadmon et al. 2003), this was not evident here, perhaps because in general we had adequate localities for modelling (mean number of modelling records=233; range=2–5822)
The other pattern that emerged is that species judged to be specialists by the distribution of records in environmental or geographic space tended to have higher AUC scores than generalists, an effect also observed elsewhere (Guisan and Hofer 2003, Segurado and Araújo 2004, Thuiller et al. 2004, Luoto et al. 2005). However, this result requires further scrutiny because it may well be largely a function of spatial extent of the analysis. If the extent is fixed (say, to a region) and the evaluation data are a constant set of sites, specialists by definition are those that exist in only a subset of that space. Therefore, the evaluation data set will have many zero records for such species, and any model that can restrict its non‐zero predictions to the zone that the species occupies will have a good AUC score, due to the comparison with the many absence sites. The question then becomes one of whether a constant extent of analysis is appropriate for all species in relation to the purpose of the predictions. This consideration needs to be defined by the end‐use of the predictions, and merits attention in any evaluation of modelling success.
Limitations
Whereas the present study points to both the potential informativeness of presence‐only data and to improved methods for predicting species distributions from them, we also need to emphasize what this doesn't tell us. Our evaluation strategy is specific to the question of how best to predict species distribution under current environmental conditions, which has broad relevance to conservation and ecological or macro‐ecological studies (Ferrier 2002, Funk and Richardson 2002, Rushton et al. 2004). Our approach, however, does not inform selection of methods for predicting potential ranges or extrapolation from the current to alternative climates. Modelling of potential ranges (Soberón and Peterson 2005) has applications to predicting expansions of invasive species and investigating speciation processes (Hugall et al. 2002, Peterson 2003). However, as the true potential range may differ from the realized range because of dispersal limitation, competition or other factors (Van Horne 1983, Hanski 1994, Tyre et al. 2001, Anderson et al. 2002), evaluating model performance is a complex task and use of observed absences may be misleading.
Projection of modelled relationships to alternative climates (past or future) is an increasingly popular application of distributional modelling, e.g. in relation to potential effects of global warming. However, strong performance of a particular method in the present climate does not guarantee similar performance under different climates (Thuiller 2004), particularly where this requires prediction outside the range of environments on which the original model was based (Araújo et al. 2005). Community‐based models could fail if patterns of species co‐occurrence change due to idiosyncratic responses by individual species to climate change. Similar caution should also be exercised in making predictions for sites distant from the geographic domain from which the modelling data were drawn, given the potential for accurate prediction to be confounded either by unrecognised environmental factors or by large‐scale geographic variation in disturbance regimes (Randin et al. in press). Clearly, different models may be necessary, and different approaches needed to evaluate relative performance of modelling methods under these scenarios. Araújo et al. (2005) argue that whilst evaluation of models to new climates and new regions is particularly difficult, evaluations of models even within one region are prone to over‐optimism. This occurs when modelling and evaluation data sets are not sufficiently independent. Because the data in this study were sourced from collections with substantially different survey protocols, the evaluation is unlikely to suffer from such problems. Nevertheless, further explorations of the ability of the novel methods to predict reliably to unsampled areas – for example, by spatially stratifying the evaluation data – would be useful.
A further qualification needs to be made. Whilst these models have been shown to produce predictions that are useful in their ability to rank sites for relative suitability for many species, we do not suggest that models built with presence‐only data will be well calibrated. That is, they do not accurately predict probability of presence because they do not have access to reliable information on the prevalence (frequency of occurrence) of the species in the region. Rather, they provide relative indices of suitability. Our implementations of most of the methods that take into account background were simple applications of the methods, not attempting to make sophisticated adjustments at might improve this aspect. Alternative approaches such as case control methods for regression (Keating and Cherry 2004, Pearce and Boyce in press), and Bayesian methods (Gelfand et al. 2006) continue to be developed and have potentially important contributions because they deal more appropriately with the presence‐only paradigm.
This is by no means a complete analysis, and important questions remain. To advance our understanding of the strengths and weaknesses of methods and the differences between them requires theoretical investigations of the techniques (Austin 2002), testing on simulated data (Austin et al. 1995), analysis of the modelled response shapes (e.g. Austin et al. 1994, Bio 2000, Leathwick 2002) and evaluation of the spatial trends in errors (Fielding and Bell 1997, Barry and Elith in press). Our method of evaluation relies on the evaluation site data and summarises over these, but this might mask effects that can only be clarified with these more detailed evaluations. Operator expertise will affect model performance, and tests of the sensitivity of the methods to how they are applied would be informative. These were beyond the scope of this paper but are necessary for a deeper understanding of the models and their predictive capacities and limitations.
Finally, we stress that modelling can never provide a complete substitute for detailed, ongoing collection of field data, including data on species’ distribution, demography, abundance, and interactions (Guisan and Thuiller 2005). Modelling approaches which attempt to integrate such information include Bayesian approaches (Gelfand et al. 2006), investigation of competitors (Leathwick and Austin 2001, Anderson et al. 2002), and studies of connectivity (Ferrier et al. 2002a, Moilanen et al. 2005). To date, few models have been validated via collection of new data (but see Ferrier and Watson 1997, Elith and Burgman 2002, Raxworthy et al. 2003, Peterson 2005). Likewise, collaborative efforts between modellers and users such as conservation managers are rare (Pielke Jr 2003). Ideally, models should be developed and tested in iterative cycles that take account of the desired uses of model, investigate the ecological rationality of the modelled responses and explore errors in predictions (Burgman et al. 2005, Barry and Elith in press). We hope that our model comparisons will stimulate more research into both modelling methods, further development of efficient user interfaces for the more successful methods, and greater integration among modellers and end‐users. Subject Editor: Miguel Araujo.Download the appendix as file E4596 from <www.oikos.ekol.lu.se/appendix>
Acknowledgements
Data were kindly provided by organizations for whom a number of authors worked. We also thank Mark and George Peck, Royal Ontario Museum, for access to Ontario nest record data (<http://www.birdsontario.org/onrs/onrsmain.html>); Mike Cadman, Bird Studies Canada, Canadian Wildlife Service of Environment Canada, for access to BBS data; Missouri Botanical Garden, especially Robert Magill and Trisha Consiglio, for access to TROPICOS and Gentry transect databases; T. Wohlgemuth and U. Braendli from WSL Switzerland for access to the NFI and forest plots data, and Andrew Ford, CSIRO Atherton, for AWT PA plant records. Michael McCarthy helped with the GLMM analysis and WinBUGs programming. The comments of Mike Austin and Miguel Araújo improved the manuscript substantially. J. E. was funded by ARC Grant DP0209303. This research was initiated in a working group at the National Center for Ecological Analysis and Synthesis (NCEAS), Santa Barbara, USA: “Testing Alternative Methodologies for Modelling Species’ Ecological Niches and Predicting Geographic Distributions”, conceived of and led by Peterson and Moritz.
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- Daiana Cardoso Silva, Thiago Bernardi Vieira, Joaquim Manoel da Silva and Karina de Cassia Faria, Biogeography and priority areas for the conservation of bats in the Brazilian Cerrado, Biodiversity and Conservation, 10.1007/s10531-017-1464-z, 27, 4, (815-828), (2017).
- Veronica Zamora‐Gutierrez, Richard G. Pearson, Rhys E. Green and Kate E. Jones, Forecasting the combined effects of climate and land use change on Mexican bats, Diversity and Distributions, 24, 3, (363-374), (2017).
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- Yanjing Lou, Chuanyu Gao, Yanwen Pan, Zhenshan Xue, Ying Liu, Zhanhui Tang, Ming Jiang, Xianguo Lu and Håkan Rydin, Niche modelling of marsh plants based on occurrence and abundance data, Science of The Total Environment, 10.1016/j.scitotenv.2017.10.300, 616-617, (198-207), (2018).
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- Rebecca L. Selden, Ryan D. Batt, Vincent S. Saba and Malin L. Pinsky, Diversity in thermal affinity among key piscivores buffers impacts of ocean warming on predator–prey interactions, Global Change Biology, 24, 1, (117-131), (2017).
- Brunno Freire Oliveira, Gabriel Corrêa Costa and Carlos Roberto Fonseca, Niche dynamics of two cryptic Prosopis invading South American drylands, Biological Invasions, 20, 1, (181), (2018).
- Jose L.P. Cordeiro, Gabriel S. Hofmann, Carlos Fonseca and Luiz Flamarion B. Oliveira, Achilles heel of a powerful invader: restrictions on distribution and disappearance of feral pigs from a protected area in Northern Pantanal, Western Brazil, PeerJ, 6, (e4200), (2018).
- Violaine Nicolas, Abderrahmane Mataame, Pierre‐André Crochet, Philippe Geniez, Soumia Fahd and Annemarie Ohler, Phylogeography and ecological niche modeling unravel the evolutionary history of the African green toad, Bufotes boulengeri boulengeri (Amphibia: Bufonidae), through the Quaternary, Journal of Zoological Systematics and Evolutionary Research, 56, 1, (102-116), (2017).
- J. E. Stewart, A. L. Ross‐Davis, R. N. Graҫa, A. C. Alfenas, T. L. Peever, J. W. Hanna, J. Y. Uchida, R. D. Hauff, C. Y. Kadooka, M.‐S. Kim, P. G. Cannon, S. Namba, S. Simeto, C. A. Pérez, M. B. Rayamajhi, D. J. Lodge, M. Arguedas, R. Medel‐Ortiz, M. A. López‐Ramirez, P. Tennant, M. Glen, P. S. Machado, A. R. McTaggart, A. J. Carnegie and N. B. Klopfenstein, Genetic diversity of the myrtle rust pathogen (Austropuccinia psidii) in the Americas and Hawaii: Global implications for invasive threat assessments, Forest Pathology, 48, 1, (2017).
- Mohsen Kalboussi and Hammadi Achour, Modelling the spatial distribution of snake species in northwestern Tunisia using maximum entropy (Maxent) and Geographic Information System (GIS), Journal of Forestry Research, 29, 1, (233), (2018).
- John B. Baumgartner, Manuel Esperón‐Rodríguez and Linda J. Beaumont, Identifying in situ climate refugia for plant species, Ecography, 41, 11, (1850-1863), (2018).
- Frances E. C. Stewart, Jason T. Fisher, A. Cole Burton and John P. Volpe, Species occurrence data reflect the magnitude of animal movements better than the proximity of animal space use, Ecosphere, 9, 2, (2018).
- Borja Jiménez‐Alfaro, Susana Suárez‐Seoane, Milan Chytrý, Stephan M. Hennekens, Wolfgang Willner, Michal Hájek, Emiliano Agrillo, Jose M. Álvarez‐Martínez, Ariel Bergamini, Henry Brisse, Jörg Brunet, Laura Casella, Daniel Dítě, Xavier Font, François Gillet, Petra Hájková, Florian Jansen, Ute Jandt, Zygmunt Kącki, Jonathan Lenoir, John S. Rodwell, Joop H. J. Schaminée, Lucia Sekulová, Jozef Šibík, Željko Škvorc and Ioannis Tsiripidis, Modelling the distribution and compositional variation of plant communities at the continental scale, Diversity and Distributions, 24, 7, (978-990), (2018).
- Daniela Silvia Pace, Antonella Arcangeli, Barbara Mussi, Carlotta Vivaldi, Cristina Ledon, Serena Lagorio, Giancarlo Giacomini, Gianni Pavan and Giandomenico Ardizzone, Habitat suitability modeling in different sperm whale social groups, The Journal of Wildlife Management, 82, 5, (1062-1073), (2018).
- Elaheh Parvizi, Reza Naderloo, Alireza Keikhosravi, Samaneh Solhjouy‐Fard and Christoph D. Schubart, Multiple Pleistocene refugia and repeated phylogeographic breaks in the southern Caspian Sea region: Insights from the freshwater crab Potamon ibericum, Journal of Biogeography, 45, 6, (1234-1245), (2018).
- Daniel Slodowicz, Patrice Descombes, David Kikodze, Olivier Broennimann and Heinz Müller‐Schärer, Areas of high conservation value at risk by plant invaders in Georgia under climate change, Ecology and Evolution, 8, 9, (4431-4442), (2018).
- Sarah C. Barga, Thomas E. Dilts and Elizabeth A. Leger, Contrasting climate niches among co‐occurring subdominant forbs of the sagebrush steppe, Diversity and Distributions, 24, 9, (1291-1307), (2018).
- B. Lowrey, R. A. Garrott, D. E. McWhirter, P. J. White, N. J. DeCesare and S. T. Stewart, Niche similarities among introduced and native mountain ungulates, Ecological Applications, 28, 5, (1131-1142), (2018).
- Frank M Fontanella, Pedro F Victoriano and Jack W Sites, Secondary contact, gene flow and clinal variation between two mtDNA lineages of the Northeastern ringneck snake Diadophis punctatus edwardsii (Colubroidea: Dipsadidae), Zoological Journal of the Linnean Society, 182, 2, (444), (2018).
- Gianluca Sarà, Erika M.D. Porporato, Maria Cristina Mangano and Nova Mieszkowska, Multiple stressors facilitate the spread of a non‐indigenous bivalve in the Mediterranean Sea, Journal of Biogeography, 45, 5, (1090-1103), (2018).
- Laura Poggio, Enrico Simonetti and Alessandro Gimona, Enhancing the WorldClim data set for national and regional applications, Science of The Total Environment, 10.1016/j.scitotenv.2017.12.258, 625, (1628-1643), (2018).
- Yuke Zhang, Yongjie Wu, Qiongyue Zhang, Jianghong Ran and Megan Price, Distribution of a giant panda population influenced by land cover, The Journal of Wildlife Management, 82, 6, (1199-1209), (2018).
- Eric Ariel L. Salas, Raul Valdez, Stefan Michel and Kenneth G. Boykin, Habitat assessment of Marco Polo sheep (Ovis ammon polii) in Eastern Tajikistan: Modeling the effects of climate change, Ecology and Evolution, 8, 10, (5124-5138), (2018).
- Nick Golding, Tom A. August, Tim C. D. Lucas, David J. Gavaghan, E. Emiel Loon and Greg McInerny, The zoon r package for reproducible and shareable species distribution modelling, Methods in Ecology and Evolution, 9, 2, (260-268), (2017).
- Qianlong Liang, Xiaoting Xu, Kangshan Mao, Mingcheng Wang, Kun Wang, Zhenxiang Xi and Jianquan Liu, Shifts in plant distributions in response to climate warming in a biodiversity hotspot, the Hengduan Mountains, Journal of Biogeography, 45, 6, (1334-1344), (2018).
- Marine Le Louarn, Philippe Clergeau, Diederik Strubbe and Magali Deschamps‐Cottin, Dynamic species distribution models reveal spatiotemporal habitat shifts in native range‐expanding versus non‐native invasive birds in an urban area, Journal of Avian Biology, 49, 4, (2018).
- Luis E. Escobar, Huijie Qiao, Javier Cabello and A. Townsend Peterson, Ecological niche modeling re‐examined: A case study with the Darwin's fox, Ecology and Evolution, 8, 10, (4757-4770), (2018).
- Xinping Ye, Xiaoping Yu, Changqing Yu, Aletai Tayibazhaer, Fujun Xu, Andrew K. Skidmore and Tiejun Wang, Impacts of future climate and land cover changes on threatened mammals in the semi-arid Chinese Altai Mountains, Science of The Total Environment, 10.1016/j.scitotenv.2017.08.191, 612, (775-787), (2018).
- Ana M. M. Sequeira, Phil J. Bouchet, Katherine L. Yates, Kerrie Mengersen and M. Julian Caley, Transferring biodiversity models for conservation: Opportunities and challenges, Methods in Ecology and Evolution, 9, 5, (1250-1264), (2018).
- Christian Berriozabal‐Islas, João Fabrício Mota Rodrigues, Aurelio Ramírez‐Bautista, Jorge L. Becerra‐López and Adrián Nieto‐Montes de Oca, Effect of climate change in lizards of the genus Xenosaurus (Xenosauridae) based on projected changes in climatic suitability and climatic niche conservatism, Ecology and Evolution, 8, 14, (6860-6871), (2018).
- Maik Rehnus, Kurt Bollmann, Dirk R. Schmatz, Klaus Hackländer and Veronika Braunisch, Alpine glacial relict species losing out to climate change: The case of the fragmented mountain hare population (Lepus timidus) in the Alps, Global Change Biology, 24, 7, (3236-3253), (2018).
- Solene Derville, Leigh G. Torres, Corina Iovan and Claire Garrigue, Finding the right fit: Comparative cetacean distribution models using multiple data sources and statistical approaches, Diversity and Distributions, 24, 11, (1657-1673), (2018).
- Brittni J. Brown, Blair C. McLaughlin, Rachel V. Blakey and Naia Morueta‐Holme, Future vulnerability mapping based on response to extreme climate events: Dieback thresholds in an endemic California oak, Diversity and Distributions, 24, 9, (1186-1198), (2018).
- David T. Y. Wong, William S. Osborne, Stephen D. Sarre and Bernd Gruber, Remotely sensed agricultural modification improves prediction of suitable habitat for a threatened lizard, International Journal of Geographical Information Science, (1), (2018).
- Daniel Scherrer, Manuela D'Amen, Rui F. Fernandes, Rubén G. Mateo and Antoine Guisan, How to best threshold and validate stacked species assemblages? Community optimisation might hold the answer, Methods in Ecology and Evolution, 9, 10, (2155-2166), (2018).
- Iulian Gherghel, François Brischoux and Monica Papeş, Using biotic interactions in broad‐scale estimates of species’ distributions, Journal of Biogeography, 45, 9, (2216-2225), (2018).
- Tiago S. Vasconcelos, Bruno T. M. Nascimento and Vitor H. M. Prado, Expected impacts of climate change threaten the anuran diversity in the Brazilian hotspots, Ecology and Evolution, 8, 16, (7894-7906), (2018).
- Charlène Guillaumot, Salomé Fabri‐Ruiz, Alexis Martin, Marc Eléaume, Bruno Danis, Jean‐Pierre Féral and Thomas Saucède, Benthic species of the Kerguelen Plateau show contrasting distribution shifts in response to environmental changes, Ecology and Evolution, 8, 12, (6210-6225), (2018).
- Ursula Torres, William Godsoe, Hannah L. Buckley, Matthew Parry, Audrey Lustig and Susan P. Worner, Using niche conservatism information to prioritize hotspots of invasion by non‐native freshwater invertebrates in New Zealand, Diversity and Distributions, 24, 12, (1802-1815), (2018).
- Corey Rovzar, Thomas W. Gillespie, Matthew K. Shirman, Anna F. Hubel and Kapua Kawelo, Management implications for the reintroduction of the endangered Hawaiian state flower , Restoration Ecology, 26, 3, (516-524), (2017).
- Sié Sylvestre Da, Jaime Ricardo García Márquez, Jan Henning Sommer, Adjima Thiombiano, Georg Zizka, Stefan Dressler, Marco Schmidt, Cyrille Chatelain and Wilhelm Barthlott, Plant biodiversity patterns along a climatic gradient and across protected areas in West Africa, African Journal of Ecology, 56, 3, (641-652), (2018).
- M. Esperón‐Rodríguez, J. B. Baumgartner, L. J. Beaumont, K. Berthon, A. J. Carnegie, M. A. Alfonzetti, V. L. Barradas and M. Leishman, The risk to Myrtaceae of Austropuccinia psidii, myrtle rust, in Mexico, Forest Pathology, 48, 4, (2018).
- Yuchi Zheng, Junhua Hu and Xiaomao Zeng, Examining the interglacial high‐elevation refugia scenario in East Asian subtropical mountain systems with the frog species Leptobrachium liui, Ecology and Evolution, 8, 18, (9326-9340), (2018).
- Pablo Pérez Chaves, Kalle Ruokolainen and Hanna Tuomisto, Using remote sensing to model tree species distribution in Peruvian lowland Amazonia, Biotropica, 50, 5, (758-767), (2018).
- Fatima Syeda Hira, Ali Asad, Zaidi Farrah, Rasheed Syed Basit, Fatima Mehreen and Khisroon Muhammad, Patterns of occurrence of dengue and chikungunya, and spatial distribution of mosquito vector Aedes albopictus in Swabi district, Pakistan, Tropical Medicine & International Health, 23, 9, (1002-1013), (2018).
- John M. Drake and Robert L. Richards, Estimating environmental suitability, Ecosphere, 9, 9, (2018).
- Helen R. Sofaer, Catherine S. Jarnevich, Curtis H. Flather and Salit Kark, Misleading prioritizations from modelling range shifts under climate change, Global Ecology and Biogeography, 27, 6, (658-666), (2018).
- Melanie Walter, Katharina Brugger and Franz Rubel, Usutu virus induced mass mortalities of songbirds in Central Europe: Are habitat models suitable to predict dead birds in unsampled regions?, Preventive Veterinary Medicine, 10.1016/j.prevetmed.2018.09.013, 159, (162-170), (2018).
- Daniele Baroni and Giulia Masoero, Complex influence of climate on the distribution and body size of an Alpine species, Insect Conservation and Diversity, 11, 5, (435-448), (2018).
- Stephan Feldmeier, Lukas Schefczyk, Axel Hochkirch, Stefan Lötters, Manfred A. Pfeifer, Günther Heinemann and Michael Veith, Climate versus weather extremes: Temporal predictor resolution matters for future rather than current regional species distribution models, Diversity and Distributions, 24, 8, (1047-1060), (2018).
- Maria Grazia Pennino, Raul Vilela and Jose M. Bellido, Effects of environmental data temporal resolution on the performance of species distribution models, Journal of Marine Systems, 10.1016/j.jmarsys.2018.10.001, (2018).
- J. Chaiyos, K. Suwannatrai, K. Thinkhamrop, K. Pratumchart, C. Sereewong, S. Tesana, S. Kaewkes, B. Sripa, T. Wongsaroj and A. T. Suwannatrai, MaxEnt modeling of soil-transmitted helminth infection distributions in Thailand, Parasitology Research, 10.1007/s00436-018-6048-7, 117, 11, (3507-3517), (2018).
- Arjun Thapa, Ruidong Wu, Yibo Hu, Yonggang Nie, Paras B. Singh, Janak R. Khatiwada, Li Yan, Xiaodong Gu and Fuwen Wei, Predicting the potential distribution of the endangered red panda across its entire range using MaxEnt modeling, Ecology and Evolution, 8, 21, (10542-10554), (2018).
- Dasvinder Kambo and Ryan K. Danby, Factors influencing the establishment and growth of tree seedlings at Subarctic alpine treelines, Ecosphere, 9, 4, (2018).
- Thomas Mang, Franz Essl, Dietmar Moser, Ingrid Kleinbauer and Stefan Dullinger, An integrated, spatio‐temporal modelling framework for analysing biological invasions, Diversity and Distributions, 24, 5, (652-665), (2018).
- Kenneth J. Chapin, Daniel E. Winkler, Patrick Wiencek and Ingi Agnarsson, Island biogeography and ecological modeling of the amblypygid Phrynus marginemaculatus in the Florida Keys archipelago, Ecology and Evolution, 8, 18, (9139-9151), (2018).
- Curtis Champion, Alistair J. Hobday, Sean R. Tracey and Gretta T. Pecl, Rapid shifts in distribution and high‐latitude persistence of oceanographic habitat revealed using citizen science data from a climate change hotspot, Global Change Biology, 24, 11, (5440-5453), (2018).
- Emiliano Mori, Andrea Sforzi, Giuseppe Bogliani and Pietro Milanesi, Range expansion and redefinition of a crop-raiding rodent associated with global warming and temperature increase, Climatic Change, 10.1007/s10584-018-2261-8, 150, 3-4, (319-331), (2018).
- Fabrice Stephenson, John R. Leathwick, Shane W. Geange, Richard H. Bulmer, Judi E. Hewitt, Owen F. Anderson, Ashley A. Rowden and Carolyn J. Lundquist, Using Gradient Forests to summarize patterns in species turnover across large spatial scales and inform conservation planning, Diversity and Distributions, 24, 11, (1641-1656), (2018).
- Irene D. Alabia, Jorge García Molinos, Sei‐Ichi Saitoh, Toru Hirawake, Takafumi Hirata and Franz J. Mueter, Distribution shifts of marine taxa in the Pacific Arctic under contemporary climate changes, Diversity and Distributions, 24, 11, (1583-1597), (2018).
- Hélida F. Cunha, Érica D. Ferreira, Geiziane Tessarolo and João C. Nabout, Host plant distributions and climate interact to affect the predicted geographic distribution of a Neotropical termite, Biotropica, 50, 4, (625-632), (2018).
- Celine Bellard, Jonathan M. Jeschke, Boris Leroy and Georgina M. Mace, Insights from modeling studies on how climate change affects invasive alien species geography, Ecology and Evolution, 8, 11, (5688-5700), (2018).
- Alberto S. Gonçalves, Gabriel C. Costa, Georgina Bond‐Buckup, Marlise L. Bartholomei‐Santos and Sandro Santos, Priority areas for conservation within four freshwater ecoregions in South America: A scale perspective based on freshwater crabs (Anomura, Aeglidae), Aquatic Conservation: Marine and Freshwater Ecosystems, 28, 5, (1077-1088), (2018).
- Henry Ndaimani, Amon Murwira and Mhosisi Masocha, A new method for correcting locational error from aerial surveys improves habitat model performance, African Journal of Ecology, 56, 4, (928-937), (2018).
- F.J. Valesini, M.D. Wildsmith and J.R. Tweedley, Predicting estuarine faunal assemblages using enduring environmental surrogates, with applications in systematic conservation planning, Ocean & Coastal Management, 10.1016/j.ocecoaman.2018.08.007, 165, (80-98), (2018).
- Falk Huettmann, Erica H. Craig, Keiko A. Herrick, Andrew P. Baltensperger, Grant R. W. Humphries, David J. Lieske, Katharine Miller, Timothy C. Mullet, Steffen Oppel, Cynthia Resendiz, Imme Rutzen, Moritz S. Schmid, Madan K. Suwal and Brian D. Young, Use of Machine Learning (ML) for Predicting and Analyzing Ecological and ‘Presence Only’ Data: An Overview of Applications and a Good Outlook, Machine Learning for Ecology and Sustainable Natural Resource Management, 10.1007/978-3-319-96978-7_2, (27-61), (2018).
- Trevor H. Booth, Why understanding the pioneering and continuing contributions of BIOCLIM to species distribution modelling is important, Austral Ecology, 43, 8, (852-860), (2018).
- Rodrigo Antônio de Souza and Paulo De Marco, Improved spatial model for Amazonian deforestation: An empirical assessment and spatial bias analysis, Ecological Modelling, 10.1016/j.ecolmodel.2018.08.015, 387, (1-9), (2018).
- Juan A. Sarquis, Maximiliano A. Cristaldi, Vanesa Arzamendia, Gisela Bellini and Alejandro R. Giraudo, Species distribution models and empirical test: Comparing predictions with well‐understood geographical distribution of Bothrops alternatus in Argentina, Ecology and Evolution, 8, 21, (10497-10509), (2018).
- Darius Stiels and Kathrin Schidelko, Modeling Avian Distributions and Niches: Insights into Invasions and Speciation in Birds, Bird Species, 10.1007/978-3-319-91689-7_9, (147-164), (2018).
- A. Townsend Peterson, Marlon E. Cobos and Daniel Jiménez‐García, Major challenges for correlational ecological niche model projections to future climate conditions, Annals of the New York Academy of Sciences, 1429, 1, (66-77), (2018).
- Shalini Dhyani, Rakesh Kadaverugu, Deepak Dhyani, Parikshit Verma and Paras Pujari, Predicting impacts of climate variability on habitats of Hippophae salicifolia (D. Don) (Seabuckthorn) in Central Himalayas: Future challenges, Ecological Informatics, 10.1016/j.ecoinf.2018.09.003, 48, (135-146), (2018).
- Alexis Marchesini, Cristiano Vernesi, Andrea Battisti and Gentile Francesco Ficetola, Deciphering the drivers of negative species–genetic diversity correlation in Alpine amphibians, Molecular Ecology, 27, 23, (4916-4930), (2018).
- J. Eric Williams and Jessica L. Blois, Range shifts in response to past and future climate change: Can climate velocities and species’ dispersal capabilities explain variation in mammalian range shifts?, Journal of Biogeography, 45, 9, (2175-2189), (2018).
- Ricardo Enrique Hernández‐Lambraño, José Ángel Sánchez‐Agudo and Roberto Carbonell, Where to start? Development of a spatial tool to prioritise retrofitting of power line poles that are dangerous to raptors, Journal of Applied Ecology, 55, 6, (2685-2697), (2018).
- E. L. Estallo, F. Sangermano, M. Grech, F. Ludueña‐Almeida, M. Frías‐Cespedes, M. Ainete, W. Almirón and T. Livdahl, Modelling the distribution of the vector Aedes aegypti in a central Argentine city, Medical and Veterinary Entomology, 32, 4, (451-461), (2018).
- Daren C. Card, Blair W. Perry, Richard H. Adams, Drew R. Schield, Acacia S. Young, Audra L. Andrew, Tereza Jezkova, Giulia I.M. Pasquesi, Nicole R. Hales, Matthew R. Walsh, Michael R. Rochford, Frank J. Mazzotti, Kristen M. Hart, Margaret E. Hunter and Todd A. Castoe, Novel ecological and climatic conditions drive rapid adaptation in invasive Florida Burmese pythons, Molecular Ecology, 27, 23, (4744-4757), (2018).
- J. Sebastian Hernandez‐Suarez and A. Pouyan Nejadhashemi, A review of macroinvertebrate‐ and fish‐based stream health modelling techniques, Ecohydrology, 11, 8, (2018).
- Jorge Orestes Cerdeira, Tiago Monteiro‐Henriques, Maria João Martins, Pedro C. Silva, Diogo Alagador, Aldina M. A. Franco, Manuel L. Campagnolo, Pedro Arsénio, Francisca C. Aguiar and Mar Cabeza, Revisiting niche fundamentals with Tukey depth, Methods in Ecology and Evolution, 9, 12, (2349-2361), (2018).
- Thomas Trancart, Stéphane Tétard, Anthony Acou, Eric Feunteun, Frédéric Schaeffer and Eric de Oliveira, Silver eel downstream migration in the River Rhine, route choice, and its impacts on escapement: A 6-year telemetry study in a highly anthropized system, Ecological Engineering, 10.1016/j.ecoleng.2018.09.002, 123, (202-211), (2018).
- Claire M. Curry, Jeremy D. Ross, Andrea J. Contina and Eli S. Bridge, Varying dataset resolution alters predictive accuracy of spatially explicit ensemble models for avian species distribution, Ecology and Evolution, 8, 24, (12867-12878), (2018).
- I.V. Doronin, L.F. Mazanaeva and M.A. Doronina, The use of GIS-modeling for the analysis of the distribution of three-lined lizard, Lacerta media Lantz et Cyren, 1920, in the territory of Dagestan (Russia), Proceedings of the Zoological Institute RAS, 10.31610/trudyzin/2018.322.4.463, 322, 4, (463-480), (2018).
- Wanwan Liang, Monica Papeş, Liem Tran, Jerome Grant, Robert Washington-Allen, Scott Stewart and Gregory Wiggins, The effect of pseudo-absence selection method on transferability of species distribution models in the context of non-adaptive niche shift, Ecological Modelling, 10.1016/j.ecolmodel.2018.09.018, 388, (1-9), (2018).
- Juan Fernandez-Manjarrés, Using Ecological Modelling Tools to Inform Policy Makers of Potential Changes in Crop Distribution: An Example with Cacao Crops in Latin America, Economic Tools and Methods for the Analysis of Global Change Impacts on Agriculture and Food Security, 10.1007/978-3-319-99462-8_2, (11-23), (2019).
- Miguel A. Llapapasca, Aldo S. Pacheco, Paul Fiedler, Elisa Goya, Jesús Ledesma, Cecilia Peña and Luis Vásquez, Modeling the potential habitats of dusky, commons and bottlenose dolphins in the Humboldt Current System off Peru: The influence of non-El Niño vs. El Niño 1997-98 conditions and potential prey availability, Progress in Oceanography, 10.1016/j.pocean.2018.09.003, 168, (169-181), (2018).
- Fernando de Oliveira Santos, Bernardo Rodrigues Teixeira, José Luis Passos Cordeiro, Rute Hilário Albuquerque de Sousa, Camila dos Santos Lucio, Pablo Rodrigues Gonçalves, Hudson Lemos, Renata Carvalho de Oliveira, Jorlan Fernandes, Gabriel Rosa Cavalcanti, Elba Regina Sampaio de Lemos and Paulo Sérgio D'Andrea, Expansion of the range of Necromys lasiurus (Lund, 1841) into open areas of the Atlantic Forest biome in Rio de Janeiro state, Brazil, and the role of the species as a host of the hantavirus, Acta Tropica, 10.1016/j.actatropica.2018.08.026, 188, (195-205), (2018).
- Diego Gómez, Pablo Salvador, Julia Sanz, Carlos Casanova, Daniel Taratiel and Jose Luis Casanova, Machine learning approach to locate desert locust breeding areas based on ESA CCI soil moisture, Journal of Applied Remote Sensing, 10.1117/1.JRS.12.036011, 12, 03, (1), (2018).
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- Linn Sekund and Simon Pittman, Explaining island‐wide geographical patterns of Caribbean fish diversity: A multi‐scale seascape ecology approach, Marine Ecology, 38, 3, (2017).
- Margaret E. Andrew and Jill M. Shephard, Semi‐automated detection of eagle nests: an application of very high‐resolution image data and advanced image analyses to wildlife surveys, Remote Sensing in Ecology and Conservation, 3, 2, (66-80), (2017).
- Cristiana Barbosa, Juan Manuel Otalora, Eduardo L. H. Giehl, Fabricio Villalobos, Rafael Loyola, Geiziane Tessarolo, Nathália Machado and Tânia Tarabini Castellani, Changes in the realized niche of the invasive succulent CAM plant Furcraea foetida, Austral Ecology, 42, 6, (643-654), (2017).
- Jemima Connell, Simon J. Watson, Rick S. Taylor, Sarah C. Avitabile, Rohan H. Clarke, Andrew F. Bennett and Michael F. Clarke, Testing the effects of a century of fires: Requirements for post‐fire succession predict the distribution of threatened bird species, Diversity and Distributions, 23, 9, (1078-1089), (2017).
- George Ashiagbor and Emmanuel Danquah, Seasonal habitat use by Elephants (Loxodonta africana) in the Mole National Park of Ghana, Ecology and Evolution, 7, 11, (3784-3795), (2017).
- David R. Roberts, Volker Bahn, Simone Ciuti, Mark S. Boyce, Jane Elith, Gurutzeta Guillera‐Arroita, Severin Hauenstein, José J. Lahoz‐Monfort, Boris Schröder, Wilfried Thuiller, David I. Warton, Brendan A. Wintle, Florian Hartig and Carsten F. Dormann, Cross‐validation strategies for data with temporal, spatial, hierarchical, or phylogenetic structure, Ecography, 40, 8, (913-929), (2017).
- Eric Meineri and Kristoffer Hylander, Fine‐grain, large‐domain climate models based on climate station and comprehensive topographic information improve microrefugia detection, Ecography, 40, 8, (1003-1013), (2016).
- Marcelo M. Weber, Richard D. Stevens, José Alexandre F. Diniz‐Filho and Carlos Eduardo V. Grelle, Is there a correlation between abundance and environmental suitability derived from ecological niche modelling? A meta‐analysis, Ecography, 40, 7, (817-828), (2016).
- Juliette Boiffin, Vincent Badeau and Nathalie Bréda, Species distribution models may misdirect assisted migration: insights from the introduction of Douglas‐fir to Europe, Ecological Applications, 27, 2, (446-457), (2017).
- Natasha D. Phillips, Neil Reid, Tierney Thys, Chris Harrod, Nicholas L. Payne, Cheryl A. Morgan, Hannah J. White, Siobhán Porter and Jonathan D.R. Houghton, Applying species distribution modelling to a data poor, pelagic fish complex: the ocean sunfishes, Journal of Biogeography, 44, 10, (2176-2187), (2017).
- Sofie Clauson‐Kaas, Katherine Richardson, Carsten Rahbek and Ben G. Holt, Species‐specific environmental preferences associated with a hump‐shaped diversity/temperature relationship across tropical marine fish assemblages, Journal of Biogeography, 44, 10, (2343-2353), (2017).
- Stephanie Ortega‐García, Lázaro Guevara, Joaquín Arroyo‐Cabrales, Roberto Lindig‐Cisneros, Enrique Martínez‐Meyer, Ernesto Vega and Jorge E. Schondube, The thermal niche of Neotropical nectar‐feeding bats: Its evolution and application to predict responses to global warming, Ecology and Evolution, 7, 17, (6691-6701), (2017).
- James S. Clark, Diana Nemergut, Bijan Seyednasrollah, Phillip J. Turner and Stacy Zhang, Generalized joint attribute modeling for biodiversity analysis: median‐zero, multivariate, multifarious data, Ecological Monographs, 87, 1, (34-56), (2017).
- Emma P. Gómez‐Ruiz and Thomas E. Lacher, Modelling the potential geographic distribution of an endangered pollination corridor in Mexico and the United States, Diversity and Distributions, 23, 1, (67-78), (2016).
- R. Keller Kopf, Casey Shaw and Paul Humphries, Trait‐based prediction of extinction risk of small‐bodied freshwater fishes, Conservation Biology, 31, 3, (581-591), (2017).
- Alex Bush and Andrew J. Hoskins, Does dispersal capacity matter for freshwater biodiversity under climate change?, Freshwater Biology, 62, 2, (382-396), (2016).
- Paul D. Mathewson, Lucas Moyer‐Horner, Erik A. Beever, Natalie J. Briscoe, Michael Kearney, Jeremiah M. Yahn and Warren P. Porter, Mechanistic variables can enhance predictive models of endotherm distributions: the American pika under current, past, and future climates, Global Change Biology, 23, 3, (1048-1064), (2016).
- Phillip P.A. Staniczenko, Prabu Sivasubramaniam, K. Blake Suttle and Richard G. Pearson, Linking macroecology and community ecology: refining predictions of species distributions using biotic interaction networks, Ecology Letters, 20, 6, (693-707), (2017).
- Yan Sun, Olivier Brönnimann, George K. Roderick, Alexander Poltavsky, Suzanne T. E. Lommen and Heinz Müller‐Schärer, Climatic suitability ranking of biological control candidates: a biogeographic approach for ragweed management in Europe, Ecosphere, 8, 4, (2017).
- Malahat Dianat, Jamshid Darvish, Raphael Cornette, Mansour Aliabadian and Violaine Nicolas, Evolutionary history of the Persian Jird, Meriones persicus, based on genetics, species distribution modelling and morphometric data, Journal of Zoological Systematics and Evolutionary Research, 55, 1, (29-45), (2016).
- Xiao Feng and Monica Papeş, Can incomplete knowledge of species’ physiology facilitate ecological niche modelling? A case study with virtual species, Diversity and Distributions, 23, 10, (1157-1168), (2017).
- Steven J. Phillips, Robert P. Anderson, Miroslav Dudík, Robert E. Schapire and Mary E. Blair, Opening the black box: an open‐source release of Maxent, Ecography, 40, 7, (887-893), (2017).
- Nathan Ranc, Luca Santini, Carlo Rondinini, Luigi Boitani, Françoise Poitevin, Anders Angerbjörn and Luigi Maiorano, Performance tradeoffs in target‐group bias correction for species distribution models, Ecography, 40, 9, (1076-1087), (2016).
- Steven D. Collins, John C. Abbott and Nancy E. McIntyre, Quantifying the degree of bias from using county‐scale data in species distribution modeling: Can increasing sample size or using county‐averaged environmental data reduce distributional overprediction?, Ecology and Evolution, 7, 15, (6012-6022), (2017).
- Violaine Nicolas, Jessica Martínez‐Vargas and Jean‐Pierre Hugot, Molecular data and ecological niche modelling reveal the evolutionary history of the common and Iberian moles (Talpidae) in Europe, Zoologica Scripta, 46, 1, (12-26), (2016).
- Jean‐Sauveur Ay, Joannès Guillemot, Nicolas Martin‐StPaul, Luc Doyen, Paul Leadley and Arndt Hampe, The economics of land use reveals a selection bias in tree species distribution models, Global Ecology and Biogeography, 26, 1, (65-77), (2016).
- Nixie C. Boddy and Angus R. McIntosh, Temperature, invaders and patchy habitat interact to limit the distribution of a vulnerable freshwater fish, Austral Ecology, 42, 4, (456-467), (2016).
- Denise M. Thompson, Day B. Ligon, Jason C. Patton and Monica Papeş, Effects of life‐history requirements on the distribution of a threatened reptile, Conservation Biology, 31, 2, (427-436), (2016).
- Holger Jänes, Jonne Kotta, Merli Pärnoja, Tasman P. Crowe, Fabio Rindi and Helen Orav‐Kotta, Functional traits of marine macrophytes predict primary production, Functional Ecology, 31, 4, (975-986), (2016).
- Hannah S. Wauchope, Justine D. Shaw, Øystein Varpe, Elena G. Lappo, David Boertmann, Richard B. Lanctot and Richard A. Fuller, Rapid climate‐driven loss of breeding habitat for Arctic migratory birds, Global Change Biology, 23, 3, (1085-1094), (2016).
- Alejandra Morán‐Ordóñez, José J. Lahoz‐Monfort, Jane Elith, Brendan A. Wintle and Antoine Guisan, Evaluating 318 continental‐scale species distribution models over a 60‐year prediction horizon: what factors influence the reliability of predictions?, Global Ecology and Biogeography, 26, 3, (371-384), (2016).
- Brett. R. Scheffers, Luke Shoo, Ben Phillips, Stewart L. Macdonald, Alex Anderson, Jeremy VanDerWal, Collin Storlie, Arnaud Gourret, Stephen E. Williams and Adam Algar, Vertical (arboreality) and horizontal (dispersal) movement increase the resilience of vertebrates to climatic instability, Global Ecology and Biogeography, 26, 7, (787-798), (2017).
- Robert A. Boria, Link E. Olson, Steven M. Goodman and Robert P. Anderson, A single‐algorithm ensemble approach to estimating suitability and uncertainty: cross‐time projections for four Malagasy tenrecs, Diversity and Distributions, 23, 2, (196-208), (2016).
- Frank T. Breiner, Antoine Guisan, Michael P. Nobis and Ariel Bergamini, Including environmental niche information to improve IUCN Red List assessments, Diversity and Distributions, 23, 5, (484-495), (2017).
- Gurutzeta Guillera‐Arroita, Modelling of species distributions, range dynamics and communities under imperfect detection: advances, challenges and opportunities, Ecography, 40, 2, (281-295), (2016).
- Marcelo Leandro Bueno, R. Toby Pennington, Kyle G. Dexter, Luciana H. Yoshino Kamino, Vanessa Pontara, Danilo Mesquita Neves, James Alexander Ratter and Ary Teixeira Oliveira‐Filho, Effects of Quaternary climatic fluctuations on the distribution of Neotropical savanna tree species, Ecography, 40, 3, (403-414), (2016).
- Martin Leipold, Simone Tausch, Peter Poschlod and Christoph Reisch, Species distribution modeling and molecular markers suggest longitudinal range shifts and cryptic northern refugia of the typical calcareous grassland species Hippocrepis comosa (horseshoe vetch), Ecology and Evolution, 7, 6, (1919-1935), (2017).
- Hatice Yilmaz, Osman Yalçın Yilmaz and Yaşar Feyza Akyüz, Determining the factors affecting the distribution of Muscari latifolium, an endemic plant of Turkey, and a mapping species distribution model, Ecology and Evolution, 7, 4, (1112-1124), (2017).
- Luke T. Kelly, Angie Haslem, Greg J. Holland, Steven W. J. Leonard, Josephine MacHunter, Michelle Bassett, Andrew F. Bennett, Matthew J. Bruce, Evelyn K. Chia, Fiona J. Christie, Michael F. Clarke, Julian Di Stefano, Richard Loyn, Michael A. McCarthy, Alina Pung, Natasha Robinson, Holly Sitters, Matthew Swan and Alan York, Fire regimes and environmental gradients shape vertebrate and plant distributions in temperate eucalypt forests, Ecosphere, 8, 4, (2017).
- Courtney A. Tye, Robert A. McCleery, Robert J. Fletcher, Daniel U. Greene and Ryan S. Butryn, Evaluating citizen vs. professional data for modelling distributions of a rare squirrel, Journal of Applied Ecology, 54, 2, (628-637), (2016).
- Cassandra S. James, April E. Reside, Jeremy VanDerWal, Richard G. Pearson, Damien Burrows, Samantha J. Capon, Thomas D. Harwood, Lauren Hodgson and Nathan J. Waltham, Sink or swim? Potential for high faunal turnover in Australian rivers under climate change, Journal of Biogeography, 44, 3, (489-501), (2017).
- Johanna Bradie and Brian Leung, A quantitative synthesis of the importance of variables used in MaxEnt species distribution models, Journal of Biogeography, 44, 6, (1344-1361), (2016).
- Yadéeh E. Sawyer, Melanie J. Flamme, Thomas S. Jung, Stephen O. MacDonald and Joseph A. Cook, Diversification of deermice (Rodentia: genus Peromyscus) at their north‐western range limit: genetic consequences of refugial and island isolation, Journal of Biogeography, 44, 7, (1572-1585), (2017).
- Y. Q. Wang, J. F. Ma, X. Q. Li, Y. F. Wang, S. Cao, A. T. Xie, S. F. Ye, B. X. Dong, W. X. Zhao, Y. X. Qin, F. Xia, Z. Y. Zheng, X. M. Zhu, J. Y. Jiang and Z. P. Dong, The distribution of Athetis lepigone and prediction of its potential distribution based on GARP and MaxEnt, Journal of Applied Entomology, 141, 6, (431-440), (2016).
- Guillaume Latombe, Cang Hui and Melodie A. McGeoch, Multi‐site generalised dissimilarity modelling: using zeta diversity to differentiate drivers of turnover in rare and widespread species, Methods in Ecology and Evolution, 8, 4, (431-442), (2017).
- Grant A. Duffy, Bernard W. T. Coetzee, Guillaume Latombe, Alexander H. Akerman, Melodie A. McGeoch and Steven L. Chown, Barriers to globally invasive species are weakening across the Antarctic, Diversity and Distributions, 23, 9, (982-996), (2017).
- Aryanne G. Amaral, Cássia B.R. Munhoz, Bruno M.T. Walter, Jesús Aguirre‐Gutiérrez and Niels Raes, Richness pattern and phytogeography of the Cerrado herb–shrub flora and implications for conservation, Journal of Vegetation Science, 28, 4, (848-858), (2017).
- Wladimir Moya, Gabriel Jacome and ChangKyoo Yoo, Past, current, and future trends of red spiny lobster based on PCA with MaxEnt model in Galapagos Islands, Ecuador, Ecology and Evolution, 7, 13, (4881-4890), (2017).
- Jiban C. Deb, Stuart Phinn, Nathalie Butt and Clive A. McAlpine, The impact of climate change on the distribution of two threatened Dipterocarp trees, Ecology and Evolution, 7, 7, (2238-2248), (2017).
- Anouschka R. Hof, Genoveva Rodríguez‐Castañeda, Andrew M. Allen, Roland Jansson and Christer Nilsson, Vulnerability of Subarctic and Arctic breeding birds, Ecological Applications, 27, 1, (219-234), (2017).
- Jennifer A. Border, Ian G. Henderson, John W. Redhead and Ian R. Hartley, Habitat selection by breeding Whinchats Saxicola rubetra at territory and landscape scales, Ibis, 159, 1, (139-151), (2016).
- Chris R. Pavey, Jane Addison, Rob Brandle, Chris R. Dickman, Peter J. McDonald, Katherine E. Moseby and Lauren I. Young, The role of refuges in the persistence of Australian dryland mammals, Biological Reviews, 92, 2, (647-664), (2015).
- Bezeng S. Bezeng, Ignacio Morales‐Castilla, Michelle Bank, Kowiyou Yessoufou, Barnabas H. Daru and T. Jonathan Davies, Climate change may reduce the spread of non‐native species, Ecosphere, 8, 3, (2017).
- James E. Whitney, Joanna B. Whittier and Craig P. Paukert, Environmental niche models for riverine desert fishes and their similarity according to phylogeny and functionality, Ecosphere, 8, 1, (2017).
- Marianna Giannoulaki, Evangelia Markoglou, Vasilis D. Valavanis, Paraskevi Alexiadou, Anna Cucknell and Alexandros Frantzis, Linking small pelagic fish and cetacean distribution to model suitable habitat for coastal dolphin species, Delphinus delphis and Tursiops truncatus, in the Greek Seas (Eastern Mediterranean), Aquatic Conservation: Marine and Freshwater Ecosystems, 27, 2, (436-451), (2016).
- Florent Noulèkoun, Stella Chude, Amanuel Zenebe and Emiru Birhane, Climate Change Impacts on Faidherbia albida (Delile) A. Chev. Distribution in Dry Lands of Ethiopia, African Journal of Ecology, 55, 2, (233-243), (2016).
- RAMIRO MORALES‐HOJAS, Molecular ecology of insect pests of agricultural importance: the case of aphids, Ecological Entomology, 42, S1, (18-27), (2017).
- Jorge L. Renteria, Mathieu Rouget and Vernon Visser, Rapid prioritization of alien plants for eradication based on climatic suitability and eradication feasibility, Austral Ecology, 42, 8, (995-1005), (2017).
- Tiago Silveira Vasconcelos, Caio Pastana Antonelli and Marcelo Felgueiras Napoli, Mutualism influences species distribution predictions for a bromeliad‐breeding anuran under climate change, Austral Ecology, 42, 7, (869-877), (2017).
- Huijie Qiao, Andrew Townsend Peterson, Liqiang Ji and Junhua Hu, Using data from related species to overcome spatial sampling bias and associated limitations in ecological niche modelling, Methods in Ecology and Evolution, 8, 12, (1804-1812), (2017).
- Anna M. Csergő, Roberto Salguero‐Gómez, Olivier Broennimann, Shaun R. Coutts, Antoine Guisan, Amy L. Angert, Erik Welk, Iain Stott, Brian J. Enquist, Brian McGill, Jens‐Christian Svenning, Cyrille Violle and Yvonne M. Buckley, Less favourable climates constrain demographic strategies in plants, Ecology Letters, 20, 8, (969-980), (2017).
- Jiří Šmíd, Jiří Moravec, Václav Gvoždík, Jan Štundl, Daniel Frynta, Petros Lymberakis, Paschalia Kapli, Thomas Wilms, Andreas Schmitz, Mohammed Shobrak, Saeed Hosseinian Yousefkhani, Eskandar Rastegar‐Pouyani, Aurora M. Castilla, Johannes Els and Werner Mayer, Cutting the Gordian Knot: Phylogenetic and ecological diversification of the Mesalina brevirostris species complex (Squamata, Lacertidae), Zoologica Scripta, 46, 6, (649-664), (2017).
- Weiwei Zhou, Jieqiong Jin, Jun Wu, Hongman Chen, Junxiao Yang, Robert W. Murphy and Jing Che, Mountains too high and valleys too deep drive population structuring and demographics in a Qinghai–Tibetan Plateau frog Nanorana pleskei (Dicroglossidae), Ecology and Evolution, 7, 1, (240-252), (2016).
- Mohsen Ahmadi, Bagher Nezami Balouchi, Houman Jowkar, Mahmoud‐Reza Hemami, Davoud Fadakar, Shima Malakouti‐Khah and Stéphane Ostrowski, Combining landscape suitability and habitat connectivity to conserve the last surviving population of cheetah in Asia, Diversity and Distributions, 23, 6, (592-603), (2017).
- Elizabeth P. Flesch and Jami J. Belt, Comparing citizen science and professional data to evaluate extrapolated mountain goat distribution models, Ecosphere, 8, 2, (2017).
- Auriel M. V. Fournier, Alexis R. Sullivan, Joseph K. Bump, Marie Perkins, Mark C. Shieldcastle and Sammy L. King, Combining citizen science species distribution models and stable isotopes reveals migratory connectivity in the secretive Virginia rail, Journal of Applied Ecology, 54, 2, (618-627), (2016).
- D. P. Silva, S. V. C. Groom, C. R. B. Silva, M. I. Stevens and M. P. Schwarz, Potential pollination maintenance by an exotic allodapine bee under climate change scenarios in the Indo‐Pacific region, Journal of Applied Entomology, 141, 1-2, (122-132), (2016).
- Linda J. Beaumont, Daisy Duursma, Darrell J. Kemp, Peter D. Wilson and Jason P. Evans, Potential impacts of a future persistent El Niño or La Niña on three subspecies of Australian butterflies, Biotropica, 49, 1, (110-116), (2016).
- Henry Ndaimani, Amon Murwira, Mhosisi Masocha, Tawanda W. Gara and Fadzai M. Zengeya, Evaluating performance of aerial survey data in elephant habitat modelling, African Journal of Ecology, 55, 3, (270-281), (2016).
- Brian Leung and Johanna Bradie, Estimating non‐indigenous species establishment and their impact on biodiversity, using the Relative Suitability Richness model, Journal of Applied Ecology, 54, 6, (1978-1988), (2017).
- Miguel A. Ortega‐Huerta and Jorge H. Vega‐Rivera, Validating distribution models for twelve endemic bird species of tropical dry forest in western Mexico, Ecology and Evolution, 7, 19, (7672-7686), (2017).
- Georgy Shenbrot, Anna Bannikova, Patrick Giraudoux, Jean‐Pierre Quéré, Francis Raoul and Vladimir Lebedev, A new recent genus and species of three‐toed jerboas (Rodentia: Dipodinae) from China: A living fossil?, Journal of Zoological Systematics and Evolutionary Research, 55, 4, (356-368), (2017).
- Bryony Townhill, John Pinnegar, Jonathan Tinker, Miranda Jones, Stephen Simpson, Paul Stebbing and Stephen Dye, Non‐native marine species in north‐west Europe: Developing an approach to assess future spread using regional downscaled climate projections, Aquatic Conservation: Marine and Freshwater Ecosystems, 27, 5, (1035-1050), (2017).
- D. Dagnino, L. Minuto and G. Casazza, Divergence is not enough: the use of ecological niche models for the validation of taxon boundaries, Plant Biology, 19, 6, (1003-1011), (2017).
- Paula Iturralde‐Pólit, Olivier Dangles, Santiago F. Burneo and Christine N. Meynard, The effects of climate change on a mega‐diverse country: predicted shifts in mammalian species richness and turnover in continental Ecuador, Biotropica, 49, 6, (821-831), (2017).
- Ashley D. Walters, David Ford, En Tze Chong, Marsha G. Williams, Neil B. Ford, Lance R. Williams and Joshua A. Banta, High‐resolution ecological niche modelling of threatened freshwater mussels in east Texas, USA, Aquatic Conservation: Marine and Freshwater Ecosystems, 27, 6, (1251-1260), (2017).
- Dennis Rödder, Flora Ihlow, Julien Courant, Jean Secondi, Anthony Herrel, Rui Rebelo, G. J. Measey, Francesco Lillo, F. A. De Villiers, Charlotte De Busschere and Thierry Backeljau, Global realized niche divergence in the African clawed frog Xenopus laevis, Ecology and Evolution, 7, 11, (4044-4058), (2017).
- Kerrie Mengersen, Erin E. Peterson, Samuel Clifford, Nan Ye, June Kim, Tomasz Bednarz, Ross Brown, Allan James, Julie Vercelloni, Alan R. Pearse, Jacqueline Davis and Vanessa Hunter, Modelling imperfect presence data obtained by citizen science, Environmetrics, 28, 5, (2017).
- A. M. Waterson, K. M. Edgar, D. N. Schmidt and P. J. Valdes, Quantifying the stability of planktic foraminiferal physical niches between the Holocene and Last Glacial Maximum, Paleoceanography, 32, 1, (74-89), (2017).
- T. A. Brichieri‐Colombi, J. M. McPherson, D. J. Sheppard and A. Moehrenschlager, In aid of (re)discovered species: maximizing conservation insights from minimal data, Animal Conservation, 20, 2, (205-212), (2016).
- Imelda Somodi, Zsolt Molnár, Bálint Czúcz, Ákos Bede‐Fazekas, János Bölöni, László Pásztor, Annamária Laborczi and Niklaus E. Zimmermann, Implementation and application of multiple potential natural vegetation models – a case study of Hungary, Journal of Vegetation Science, 28, 6, (1260-1269), (2017).
- Viviane F. Monteiro, Paulo C. Paiva and Pedro R. Peres‐Neto, A quantitative framework to estimate the relative importance of environment, spatial variation and patch connectivity in driving community composition, Journal of Animal Ecology, 86, 2, (316-326), (2017).
- Heather M. Williams, Mikkel Willemoes and Kasper Thorup, A temporally explicit species distribution model for a long distance avian migrant, the common cuckoo, Journal of Avian Biology, 48, 12, (1624-1636), (2017).
- Michelangelo Morganti, Damiano Preatoni and Maurizio Sarà, Climate determinants of breeding and wintering ranges of lesser kestrels in Italy and predicted impacts of climate change, Journal of Avian Biology, 48, 12, (1595-1607), (2017).
- Joel Methorst, Katrin Böhning‐Gaese, Imran Khaliq and Christian Hof, A framework integrating physiology, dispersal and land‐use to project species ranges under climate change, Journal of Avian Biology, 48, 12, (1532-1548), (2017).
- Shijie Zhou, André E Punt, Yimin Ye, Nick Ellis, Cathy M Dichmont, Malcolm Haddon, David C Smith and Anthony DM Smith, Estimating stock depletion level from patterns of catch history, Fish and Fisheries, 18, 4, (742-751), (2017).
- Laura A. Nunes and Richard G. Pearson, A null biogeographical test for assessing ecological niche evolution, Journal of Biogeography, 44, 6, (1331-1343), (2016).
- Farrah Zaidi, Syeda Hira Fatima, Tehmina Jan, Mehreen Fatima, Asad Ali, Muhammad Khisroon, Muhammad Adnan and Syed Basit Rasheed, Environmental risk modelling and potential sand fly vectors of cutaneous leishmaniasis in Chitral district: a leishmanial focal point of mount Tirich Mir, Pakistan, Tropical Medicine & International Health, 22, 9, (1130-1140), (2017).
- Juan Diego Rus, Rubén Ramírez-Rodríguez, Francisco Amich and Manuel Melendo-Luque, Habitat distribution modelling, under the present climatic scenario, of the threatened endemic Iberian Delphinium fissum subsp. sordidum (Ranunculaceae) and implications for its conservation, Plant Biosystems - An International Journal Dealing with all Aspects of Plant Biology, (1), (2017).
- Elizabeth Campos-Sánchez, Mario González-Espinosa, Neptalí Ramírez-Marcial, Darío Alejandro Navarrete-Gutiérrez and Miguel Ángel Pérez-Farrera, Riqueza de especies arbóreas en bosques de montaña de Chiapas: estimaciones a partir de datos de herbarios e inventarios florísticos, Revista Mexicana de Biodiversidad, 88, 4, (832), (2017).
- Juan José Vidal-Macua, Miquel Ninyerola, Alaitz Zabala, Cristina Domingo-Marimon and Xavier Pons, Factors affecting forest dynamics in the Iberian Peninsula from 1987 to 2012. The role of topography and drought, Forest Ecology and Management, 10.1016/j.foreco.2017.10.011, 406, (290-306), (2017).
- Natalia Trujillo-Arias, Gisele P.M. Dantas, Enrique Arbeláez-Cortés, Kazuya Naoki, Maria I. Gómez, Fabricio R. Santos, Cristina Y. Miyaki, Alexandre Aleixo, Pablo L. Tubaro and Gustavo S. Cabanne, The niche and phylogeography of a passerine reveal the history of biological diversification between the Andean and the Atlantic forests, Molecular Phylogenetics and Evolution, 10.1016/j.ympev.2017.03.025, 112, (107-121), (2017).
- Pablo C. Hernández-Romero, Carla Gutiérrez-Rodríguez, Carolina Valdespino and David A. Prieto-Torres, The Role of Geographical and Ecological Factors on Population Divergence of the Neotropical otter Lontra longicaudis (Carnivora, Mustelidae), Evolutionary Biology, (2017).
- Yue Liu, Kefa Zhou, Nannan Zhang and Jinlin Wang, Maximum entropy modeling for orogenic gold prospectivity mapping in the Tangbale-Hatu belt, western Junggar, China, Ore Geology Reviews, 10.1016/j.oregeorev.2017.04.029, (2017).
- Renqiang Li, Ming Xu, Ryan Powers, Fen Zhao, Walter Jetz, Hui Wen and Qingkai Sheng, Quantifying the evidence for co-benefits between species conservation and climate change mitigation in giant panda habitats, Scientific Reports, 7, 1, (2017).
- Luciano Bosso, Nicola Luchi, Giorgio Maresi, Gennaro Cristinzio, Sonia Smeraldo and Danilo Russo, Predicting current and future disease outbreaks of Diplodia sapinea shoot blight in Italy: species distribution models as a tool for forest management planning, Forest Ecology and Management, 10.1016/j.foreco.2017.06.044, 400, (655-664), (2017).
- Andrew W. Gichira, Zhi-Zhong Li, Josphat K. Saina, Guang-Wan Hu, Robert W. Gituru, Qing-Feng Wang and Jin-Ming Chen, Demographic history and population genetic structure of Hagenia abyssinica (Rosaceae), a tropical tree endemic to the Ethiopian highlands and eastern African mountains, Tree Genetics & Genomes, 13, 4, (2017).
- Malay Pramanik, Uttam Paudel, Biswajit Mondal, Suman Chakraborti and Pratik Deb, Predicting climate change impacts on the distribution of the threatened Garcinia indica in the Western Ghats, India, Climate Risk Management, 10.1016/j.crm.2017.11.002, (2017).
- J. Angus Webb, Angela H. Arthington and Julian D. Olden, Models of Ecological Responses to Flow Regime Change to Inform Environmental Flows Assessments, Water for the Environment, 10.1016/B978-0-12-803907-6.00014-0, (287-316), (2017).
- Katja Kalan, Vladimir Ivović, Peter Glasnović and Elena Buzan, Presence and Potential Distribution of Aedes albopictus and Aedes japonicus japonicus (Diptera: Culicidae) in Slovenia, Journal of Medical Entomology, 54, 6, (1510), (2017).
- Michel P. Laforge, Nicole L. Michel and Ryan K. Brook, Spatio-temporal trends in crop damage inform recent climate-mediated expansion of a large boreal herbivore into an agro-ecosystem, Scientific Reports, 7, 1, (2017).
- Christina Kassara, Laura Gangoso, Ugo Mellone, Gvido Piasevoli, Thomas G. Hadjikyriakou, Nikos Tsiopelas, Sinos Giokas, Pascual López-López, Vicente Urios, Jordi Figuerola, Rafa Silva, Willem Bouten, Alexander N. G. Kirschel, Munir Z. Virani, Wolfgang Fiedler, Peter Berthold and Marion Gschweng, Current and future suitability of wintering grounds for a long-distance migratory raptor, Scientific Reports, 10.1038/s41598-017-08753-w, 7, 1, (2017).
- Paulo A. Barros, Cátia Ribeiro and João A. CAbral, Winter Activity of Bats in Mediterranean Peri-Urban Deciduous Forests, Acta Chiropterologica, 19, 2, (367), (2017).
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- Martin Godefroid, Jean‐Yves Rasplus and Jean‐Pierre Rossi, Is phylogeography helpful for invasive species risk assessment? The case study of the bark beetle genus Dendroctonus, Ecography, 39, 12, (1197-1209), (2016).
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- Rachel Schwallier, Niels Raes, Hugo J. Boer, Rutger A. Vos, Rogier R. Vugt and Barbara Gravendeel, Phylogenetic analysis of niche divergence reveals distinct evolutionary histories and climate change implications for tropical carnivorous pitcher plants, Diversity and Distributions, 22, 1, (97-110), (2015).
- Fernando Martínez‐Freiría, Pedro Tarroso, Hugo Rebelo and José C. Brito, Contemporary niche contraction affects climate change predictions for elephants and giraffes, Diversity and Distributions, 22, 4, (432-444), (2015).
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- Samuel Veloz, Leonardo Salas, Bob Altman, John Alexander, Dennis Jongsomjit, Nathan Elliott and Grant Ballard, Improving effectiveness of systematic conservation planning with density data, Conservation Biology, 29, 4, (1217-1227), (2015).
- Nicholas A. Mason and Scott A. Taylor, Differentially expressed genes match bill morphology and plumage despite largely undifferentiated genomes in a Holarctic songbird, Molecular Ecology, 24, 12, (3009-3025), (2015).
- Sasha Pekarsky, Alon Angert, Barbara Haese, Martin Werner, Keith A. Hobson and Ran Nathan, Enriching the isotopic toolbox for migratory connectivity analysis: a new approach for migratory species breeding in remote or unexplored areas, Diversity and Distributions, 21, 4, (416-427), (2015).
- Nan Lyu, Martin Päckert, Dieter Thomas Tietze and Yue‐Hua Sun, Uncommon paleodistribution patterns of Chrysolophus pheasants in east Asia: explanations and implications, Journal of Avian Biology, 46, 5, (528-537), (2015).
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- Shaun C. Cunningham, Timothy R. Cavagnaro, Ralph Mac Nally, Keryn I. Paul, Patrick J. Baker, Jason Beringer, James R. Thomson and Ross M. Thompson, Reforestation with native mixed‐species plantings in a temperate continental climate effectively sequesters and stabilizes carbon within decades, Global Change Biology, 21, 4, (1552-1566), (2014).
- Gerardo J. de la Vega, Paula Medone, Soledad Ceccarelli, Jorge Rabinovich and Pablo E. Schilman, Geographical distribution, climatic variability and thermo‐tolerance of Chagas disease vectors, Ecography, 38, 8, (851-860), (2014).
- J. D. Anadón, E. Graciá, F. Botella, A. Giménez, S. Fahd and U. Fritz, Individualistic response to past climate changes: niche differentiation promotes diverging Quaternary range dynamics in the subspecies of Testudo graeca, Ecography, 38, 9, (956-966), (2015).
- Divya Vasudev, Robert J. Fletcher, Varun R. Goswami and Meghna Krishnadas, From dispersal constraints to landscape connectivity: lessons from species distribution modeling, Ecography, 38, 10, (967-978), (2015).
- Sophie Monsarrat, Maria G. Pennino, Tim D. Smith, Randall R. Reeves, Christine N. Meynard, David M. Kaplan and Ana S. L. Rodrigues, Historical summer distribution of the endangered North Atlantic right whale (Eubalaena glacialis): a hypothesis based on environmental preferences of a congeneric species, Diversity and Distributions, 21, 8, (925-937), (2015).
- Stephanie Brodie, Alistair J. Hobday, James A. Smith, Jason D. Everett, Matt D. Taylor, Charles A. Gray and Iain M. Suthers, Modelling the oceanic habitats of two pelagic species using recreational fisheries data, Fisheries Oceanography, 24, 5, (463-477), (2015).
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- Jantrararuk Tovaranonte, Anne Blach‐Overgaard, Ratchada Pongsattayapipat, Jens‐Christian Svenning and Anders S. Barfod, Distribution and diversity of palms in a tropical biodiversity hotspot (Thailand) assessed by species distribution modeling, Nordic Journal of Botany, 33, 2, (214-224), (2013).
- Ian W. Renner, Jane Elith, Adrian Baddeley, William Fithian, Trevor Hastie, Steven J. Phillips, Gordana Popovic and David I. Warton, Point process models for presence‐only analysis, Methods in Ecology and Evolution, 6, 4, (366-379), (2015).
- Nicola K. Abram, Erik Meijaard, Jessie A. Wells, Marc Ancrenaz, Anne‐Sophie Pellier, Rebecca K. Runting, David Gaveau, Serge Wich, Nardiyono, Albertus Tjiu, Anton Nurcahyo and Kerrie Mengersen, Mapping perceptions of species' threats and population trends to inform conservation efforts: the Bornean orangutan case study, Diversity and Distributions, 21, 5, (487-499), (2015).
- Jürgen Kusch, Interacting influences of climate factors and land cover types on the distribution of caddisflies (Trichoptera) in streams of a central European low mountain range, Insect Conservation and Diversity, 8, 1, (92-101), (2014).
- Kumar P. Mainali, Dan L. Warren, Kunjithapatham Dhileepan, Andrew McConnachie, Lorraine Strathie, Gul Hassan, Debendra Karki, Bharat B. Shrestha and Camille Parmesan, Projecting future expansion of invasive species: comparing and improving methodologies for species distribution modeling, Global Change Biology, 21, 12, (4464-4480), (2015).
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- Fábio de Almeida Vieira, Renan Milagres Lage Novaes, Cristiane Gouvêa Fajardo, Rubens Manoel dos Santos, Hisaias de Souza Almeida, Dulcinéia de Carvalho and Maria Bernadete Lovato, Holocene southward expansion in seasonally dry tropical forests in South America: phylogeography of icus bonijesulapensis (Moraceae), Botanical Journal of the Linnean Society, 177, 2, (189-201), (2015).
- Pedro Jiménez‐Mejías, Mario Fernández‐Mazuecos, María Elena Amat and Pablo Vargas, Narrow endemics in European mountains: high genetic diversity within the monospecific genus Pseudomisopates (Plantaginaceae) despite isolation since the late Pleistocene, Journal of Biogeography, 42, 8, (1455-1468), (2015).
- Junbin YE, Zhenlong XIAO, Chuanhai LI, Fusheng WANG, Jicheng LIAO, Jinzhong FU and Zhibin ZHANG, Past climate change and recent anthropogenic activities affect genetic structure and population demography of the greater long‐tailed hamster in northern China, Integrative Zoology, 10, 5, (482-496), (2015).
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- Mathieu Denoël and Gentile Francesco Ficetola, Using kernels and ecological niche modeling to delineate conservation areas in an endangered patch‐breeding phenotype, Ecological Applications, 25, 7, (1922-1931), (2015).
- Marcin Jan Kamiński, Phylogenetic reassessment and biogeography of the ctateus generic group (Coleoptera: Tenebrionidae: Platynotina), Zoological Journal of the Linnean Society, 175, 1, (73-106), (2015).
- Alexander V. Alexiades and William L. Fisher, Broad‐scale habitat classification variables predict maximum local abundance for native but not non‐native trout in New York streams, Aquatic Conservation: Marine and Freshwater Ecosystems, 25, 1, (31-40), (2014).
- Sara I. Montemayor, Pablo M. Dellapé and María C. Melo, Geographical distribution modelling of the bronze bug: a worldwide invasion, Agricultural and Forest Entomology, 17, 2, (129-137), (2014).
- Beth Crase, Peter A. Vesk, Adam Liedloff and Brendan A. Wintle, Modelling both dominance and species distribution provides a more complete picture of changes to mangrove ecosystems under climate change, Global Change Biology, 21, 8, (3005-3020), (2015).
- Eric Meineri, Anne‐Sophie Deville, David Grémillet, Michel Gauthier‐Clerc and Arnaud Béchet, Combining correlative and mechanistic habitat suitability models to improve ecological compensation, Biological Reviews, 90, 1, (314-329), (2014).
- Diane R. Menuz, Karin M. Kettenring, Charles P. Hawkins and D. Richard Cutler, Non‐equilibrium in plant distribution models – only an issue for introduced or dispersal limited species?, Ecography, 38, 3, (231-240), (2014).
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- Gary D. Powney and Nick J. B. Isaac, Beyond maps: a review of the applications of biological records, Biological Journal of the Linnean Society, 115, 3, (532-542), (2015).
- Xiao Feng and Monica Papeş, Ecological niche modelling confirms potential north‐east range expansion of the nine‐banded armadillo (Dasypus novemcinctus) in the USA, Journal of Biogeography, 42, 4, (803-807), (2014).
- Monica Papeş, Fabrice Cuzin and Philippe Gaubert, Niche dynamics in the European ranges of two African carnivores reflect their dispersal and demographic histories, Biological Journal of the Linnean Society, 114, 4, (737-751), (2015).
- Francisco J. Prevosti, Mariano A. Ramírez, Mauro Schiaffini, Fabiana Martin, Daniel E. Udrizar Sauthier, Marcelo Carrera, Claudio Sillero‐Zubiri and Ulyses F. J. Pardiñas, Extinctions in near time: new radiocarbon dates point to a very recent disappearance of the South American fox Dusicyon avus (Carnivora: Canidae), Biological Journal of the Linnean Society, 116, 3, (704-720), (2015).
- Bruno A. Walther and Adriaan Niekerk, Effects of climate change on species turnover and body mass frequency distributions of South African bird communities, African Journal of Ecology, 53, 1, (25-35), (2014).
- Russell G. Death, Fiona Death, Rachel Stubbington, Michael K. Joy and Marjan Belt, How good are Bayesian belief networks for environmental management? A test with data from an agricultural river catchment, Freshwater Biology, 60, 11, (2297-2309), (2015).
- Patrice Descombes, Mary S. Wisz, Fabien Leprieur, Valerianio Parravicini, Christian Heine, Steffen M. Olsen, Didier Swingedouw, Michel Kulbicki, David Mouillot and Loïc Pellissier, Forecasted coral reef decline in marine biodiversity hotspots under climate change, Global Change Biology, 21, 7, (2479-2487), (2015).
- A. M. JAMES, C. BURDETT, M. J. MCCOOL, A. FOX and P. RIGGS, The geographic distribution and ecological preferences of the American dog tick, ermacentor variabilis (Say), in the U.S.A., Medical and Veterinary Entomology, 29, 2, (178-188), (2015).
- Andrea Paz, Roberto Ibáñez, Karen R. Lips and Andrew J. Crawford, Testing the role of ecology and life history in structuring genetic variation across a landscape: a trait‐based phylogeographic approach, Molecular Ecology, 24, 14, (3723-3737), (2015).
- Steven J. Micheletti and Andrew Storfer, A test of the central–marginal hypothesis using population genetics and ecological niche modelling in an endemic salamander (Ambystoma barbouri), Molecular Ecology, 24, 5, (967-979), (2015).
- Kentaro Inoue, Brian K. Lang and David J. Berg, Past climate change drives current genetic structure of an endangered freshwater mussel species, Molecular Ecology, 24, 8, (1910-1926), (2015).
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- Jason J. Hamer, Erik J. Veneklaas, Pieter Poot, Karel Mokany and Michael Renton, Shallow environmental gradients put inland species at risk: Insights and implications from predicting future distributions of ucalyptus species in South Western Australia, Austral Ecology, 40, 8, (923-932), (2015).
- Gurutzeta Guillera‐Arroita, José J. Lahoz‐Monfort, Jane Elith, Ascelin Gordon, Heini Kujala, Pia E. Lentini, Michael A. McCarthy, Reid Tingley and Brendan A. Wintle, Is my species distribution model fit for purpose? Matching data and models to applications, Global Ecology and Biogeography, 24, 3, (276-292), (2015).
- Nienke Hartemink, Sophie O. Vanwambeke, Bethan V. Purse, Marius Gilbert and Hans Van Dyck, Towards a resource‐based habitat approach for spatial modelling of vector‐borne disease risks, Biological Reviews, 90, 4, (1151-1162), (2014).
- R. Alexander Pyron, Gabriel C. Costa, Michael A. Patten and Frank T. Burbrink, Phylogenetic niche conservatism and the evolutionary basis of ecological speciation, Biological Reviews, 90, 4, (1248-1262), (2014).
- D. Russo, M. Di Febbraro, L. Cistrone, G. Jones, S. Smeraldo, A. P. Garonna and L. Bosso, Protecting one, protecting both? Scale‐dependent ecological differences in two species using dead trees, the rosalia longicorn beetle and the barbastelle bat, Journal of Zoology, 297, 3, (165-175), (2015).
- L. M. Casey, H. Rebelo, E. Rotheray and D. Goulson, Evidence for habitat and climatic specializations driving the long‐term distribution trends of UK and Irish bumblebees, Diversity and Distributions, 21, 8, (864-875), (2015).
- Dominik Chłond and Agnieszka Bugaj‐Nawrocka, Assassin bugs of the subfamily Diaspidiinae (Heteroptera: Reduviidae): distribution and potential ecological niches, Entomological Science, 18, 3, (389-399), (2015).
- Pia E. Lentini and Brendan A. Wintle, Spatial conservation priorities are highly sensitive to choice of biodiversity surrogates and species distribution model type, Ecography, 38, 11, (1101-1111), (2015).
- G. Kozhoridze, N. Orlovsky, L. Orlovsky, Dan G. Blumberg and A. Golan‐Goldhirsh, Geographic distribution and migration pathways of Pistacia – present, past and future, Ecography, 38, 11, (1141-1154), (2015).
- Ryan Blanchard, Patrick J. O'Farrell and David M. Richardson, Anticipating potential biodiversity conflicts for future biofuel crops in South Africa: incorporating spatial filters with species distribution models, GCB Bioenergy, 7, 2, (273-287), (2014).
- A. Torre, J. Bosch, I. Iglesias, M. J. Muñoz, L. Mur, B. Martínez‐López, M. Martínez and J. M. Sánchez‐Vizcaíno, Assessing the Risk of African Swine Fever Introduction into the European Union by Wild Boar, Transboundary and Emerging Diseases, 62, 3, (272-279), (2013).
- Quresh S. Latif, Victoria A. Saab, Kim Mellen‐Mclean and Jonathan G. Dudley, Evaluating habitat suitability models for nesting white‐headed woodpeckers in unburned forest, The Journal of Wildlife Management, 79, 2, (263-273), (2015).
- Johannes Radinger and Christian Wolter, Disentangling the effects of habitat suitability, dispersal, and fragmentation on the distribution of river fishes, Ecological Applications, 25, 4, (914-927), (2015).
- Lélis A. Carlos‐Júnior, Danilo M. Neves, Newton P. U. Barbosa, Timothy P. Moulton and Joel C. Creed, Occurrence of an invasive coral in the southwest Atlantic and comparison with a congener suggest potential niche expansion, Ecology and Evolution, 5, 11, (2162-2171), (2015).
- Michael A. McQuillan and Amber M. Rice, Differential effects of climate and species interactions on range limits at a hybrid zone: potential direct and indirect impacts of climate change, Ecology and Evolution, 5, 21, (5120-5137), (2015).
- Steven P. Newman, Erik H. Meesters, Charlie S. Dryden, Stacey M. Williams, Cristina Sanchez, Peter J. Mumby and Nicholas V. C. Polunin, Reef flattening effects on total richness and species responses in the Caribbean, Journal of Animal Ecology, 84, 6, (1678-1689), (2015).
- Nawal SHRESTHA and Xian‐Chun ZHANG, Recircumscription of Huperzia serrata complex in China using morphological and climatic data, Journal of Systematics and Evolution, 53, 1, (88-103), (2014).
- Eric J. Ward, Jason E. Jannot, Yong-Woo Lee, Kotaro Ono, Andrew O. Shelton and James T. Thorson, Using spatiotemporal species distribution models to identify temporally evolving hotspots of species co‐occurrence, Ecological Applications, 25, 8, (2198-2209), (2015).
- David J. Harris, Generating realistic assemblages with a joint species distribution model, Methods in Ecology and Evolution, 6, 4, (465-473), (2015).
- Helena Hespanhol, Katia Cezón, Ángel M. Felicísimo, Jesús Muñoz and Rubén G. Mateo, How to describe species richness patterns for bryophyte conservation?, Ecology and Evolution, 5, 23, (5443-5455), (2015).
- P. J. Bouchet and J. J. Meeuwig, Drifting baited stereo‐videography: a novel sampling tool for surveying pelagic wildlife in offshore marine reserves, Ecosphere, 6, 8, (1-29), (2015).
- Daniel S. Park and Daniel Potter, Why close relatives make bad neighbours: phylogenetic conservatism in niche preferences and dispersal disproves Darwin's naturalization hypothesis in the thistle tribe, Molecular Ecology, 24, 12, (3181-3193), (2015).
- Hazel Jackson, Diederik Strubbe, Simon Tollington, Robert Prys‐Jones, Erik Matthysen and Jim J. Groombridge, Ancestral origins and invasion pathways in a globally invasive bird correlate with climate and influences from bird trade, Molecular Ecology, 24, 16, (4269-4285), (2015).
- M. J. Serra‐Varela, D. Grivet, L. Vincenot, O. Broennimann, J. Gonzalo‐Jiménez and N. E. Zimmermann, Does phylogeographical structure relate to climatic niche divergence? A test using maritime pine (inus pinaster Ait.), Global Ecology and Biogeography, 24, 11, (1302-1313), (2015).
- Jose Manuel Alvarez‐Martínez, Susana Suárez‐Seoane, Carlos Palacín, Julia Sanz and Juan C. Alonso, Can Eltonian processes explain species distributions at large scale? A case study with Great Bustard (Otis tarda), Diversity and Distributions, 21, 2, (123-138), (2014).
- Amber N. Wright, Robert J. Hijmans, Mark W. Schwartz and H. Bradley Shaffer, Multiple sources of uncertainty affect metrics for ranking conservation risk under climate change, Diversity and Distributions, 21, 1, (111-122), (2014).
- Motoki Higa, Yuichi Yamaura, Itsuro Koizumi, Yuki Yabuhara, Masayuki Senzaki and Satoru Ono, Mapping large‐scale bird distributions using occupancy models and citizen data with spatially biased sampling effort, Diversity and Distributions, 21, 1, (46-54), (2014).
- Jessica Stolar and Scott E. Nielsen, Accounting for spatially biased sampling effort in presence‐only species distribution modelling, Diversity and Distributions, 21, 5, (595-608), (2014).
- Stephen J. Tulowiecki and Chris P. S. Larsen, Native American impact on past forest composition inferred from species distribution models, Chautauqua County, New York, Ecological Monographs, 85, 4, (557-581), (2015).
- Guinevere O. U. Wogan and Jonathan Q. Richmond, Niche divergence builds the case for ecological speciation in skinks of the lestiodon skiltonianus species complex, Ecology and Evolution, 5, 20, (4683-4695), (2015).
- Kristine Engemann, Brian J. Enquist, Brody Sandel, Brad Boyle, Peter M. Jørgensen, Naia Morueta‐Holme, Robert K. Peet, Cyrille Violle and Jens‐Christian Svenning, Limited sampling hampers “big data” estimation of species richness in a tropical biodiversity hotspot, Ecology and Evolution, 5, 3, (807-820), (2015).
- Per Bergström, Susanne Lindegarth and Mats Lindegarth, Modeling and predicting the growth of the mussel, Mytilus edulis: implications for planning of aquaculture and eutrophication mitigation, Ecology and Evolution, 5, 24, (5920-5933), (2015).
- Emma Fuller, Eleanor Brush and Malin L. Pinsky, The persistence of populations facing climate shifts and harvest, Ecosphere, 6, 9, (1-16), (2015).
- E. Alfaro-Saiz, M.E. García-González, S. del Río, Á. Penas, A. Rodríguez and R. Alonso-Redondo, Incorporating bioclimatic and biogeographic data in the construction of species distribution models in order to prioritize searches for new populations of threatened flora, Plant Biosystems - An International Journal Dealing with all Aspects of Plant Biology, 149, 5, (827), (2015).
- Craig M. Costion, Lalita Simpson, Petina L. Pert, Monica M. Carlsen, W. John Kress and Darren Crayn, Will tropical mountaintop plant species survive climate change? Identifying key knowledge gaps using species distribution modelling in Australia, Biological Conservation, 10.1016/j.biocon.2015.07.022, 191, (322-330), (2015).
- Marcelo F. Bonino, Débora L. Moreno Azócar, James A. Schulte and Félix B. Cruz, Climate change and lizards: changing species' geographic ranges in Patagonia, Regional Environmental Change, 10.1007/s10113-014-0693-x, 15, 6, (1121-1132), (2014).
- Valerio Amici, Britta Eggers, Francesco Geri and Corrado Battisti, Habitat Suitability and Landscape Structure: A Maximum Entropy Approach in a Mediterranean Area, Landscape Research, 40, 2, (208), (2015).
- Alex O. Onojeghuo, Alan G. Blackburn, Francis Okeke and Ajoke R. Onojeghuo, Habitat Suitability Modeling of Endangered Primates in Nigeria: Integrating Satellite Remote Sensing and Spatial Modeling Techniques, Journal of Geoscience and Environment Protection, 03, 08, (23), (2015).
- Daniel P. Silva, Ana C. B. A. Macêdo, John S. Ascher and Paulo De Marco, Range increase of a Neotropical orchid bee under future scenarios of climate change, Journal of Insect Conservation, 19, 5, (901), (2015).
- Renan Maestri, Rodrigo Fornel, Daniel Galiano, Thales R. O. de Freitas and Diego Fontaneto, Niche Suitability Affects Development: Skull Asymmetry Increases in Less Suitable Areas, PLOS ONE, 10, 4, (e0122412), (2015).
- Juliana Hipólito, Érica Hasui and Blandina F. Viana, Solving problems involving the distribution of a species of unknown distribution via ecological niche modeling, Natureza & Conservação, 13, 1, (15), (2015).
- J.N. Goetz, A. Brenning, H. Petschko and P. Leopold, Evaluating machine learning and statistical prediction techniques for landslide susceptibility modeling, Computers & Geosciences, 81, (1), (2015).
- Yoonjung Ahn, Dong-Kun Lee, Ho Gul Kim, Chan Park, Jiyeon Kim and Jae-uk Kim, Estimating Korean Pine(Pinus koraiensis) Habitat Distribution Considering Climate Change Uncertainty - Using Species Distribution Models and RCP Scenarios -, Journal of the Korea Society of Environmental Restoration Technology, 18, 3, (51), (2015).
- Philipp Brun, Meike Vogt, Mark R. Payne, Nicolas Gruber, Colleen J. O'Brien, Erik T. Buitenhuis, Corinne Le Quéré, Karine Leblanc and Ya‐Wei Luo, Ecological niches of open ocean phytoplankton taxa, Limnology and Oceanography, 60, 3, (1020-1038), (2015).
- Renmin Yang, David G. Rossiter, Feng Liu, Yuanyuan Lu, Fan Yang, Fei Yang, Yuguo Zhao, Decheng Li, Ganlin Zhang and Xiujun Wang, Predictive Mapping of Topsoil Organic Carbon in an Alpine Environment Aided by Landsat TM, PLOS ONE, 10, 10, (e0139042), (2015).
- Duccio Rocchini, Veronica Andreo, Michael Förster, Carol Ximena Garzon-Lopez, Andrew Paul Gutierrez, Thomas W. Gillespie, Heidi C. Hauffe, Kate S. He, Birgit Kleinschmit, Paola Mairota, Matteo Marcantonio, Markus Metz, Harini Nagendra, Sajid Pareeth, Luigi Ponti, Carlo Ricotta, Annapaola Rizzoli, Gertrud Schaab, Marc Zebisch, Roberto Zorer and Markus Neteler, Potential of remote sensing to predict species invasions, Progress in Physical Geography, 10.1177/0309133315574659, 39, 3, (283-309), (2015).
- Hefin Wyn Williams, Dónall Eoin Cross, Heather Louise Crump, Cornelis Jan Drost and Christopher James Thomas, Climate suitability for European ticks: assessing species distribution models against null models and projection under AR5 climate, Parasites & Vectors, 8, 1, (2015).
- J. Angel Soto-Centeno and David W. Steadman, Fossils reject climate change as the cause of extinction of Caribbean bats, Scientific Reports, 10.1038/srep07971, 5, 1, (2015).
- Belinda Gallardo, Alexandra Zieritz, David C. Aldridge and Erik Sotka, The Importance of the Human Footprint in Shaping the Global Distribution of Terrestrial, Freshwater and Marine Invaders, PLOS ONE, 10, 5, (e0125801), (2015).
- V. Tytar and N. Makarova, Distribution Of The Freshwater Snail Species Fagotia (Gastropoda, Melanopsidae) In Ukraine According To Climatic Factors. I. Fagotia Esperi, Vestnik Zoologii, 49, 4, (2015).
- Milan Kilibarda, Melita Perčec Tadić, Tomislav Hengl, Jelena Luković and Branislav Bajat, Global geographic and feature space coverage of temperature data in the context of spatio-temporal interpolation, Spatial Statistics, 10.1016/j.spasta.2015.04.005, 14, (22-38), (2015).
- Aleksandra M. Naczk, Marta Kolanowska and Tzen-Yuh Chiang, Glacial Refugia and Future Habitat Coverage of Selected Dactylorhiza Representatives (Orchidaceae), PLOS ONE, 10, 11, (e0143478), (2015).
- Zhong Qin, Jia-en Zhang, Antonio DiTommaso, Rui-long Wang and Rui-shan Wu, Predicting invasions of Wedelia trilobata (L.) Hitchc. with Maxent and GARP models, Journal of Plant Research, 128, 5, (763), (2015).
- Paul R Sesink Clee, Ekwoge E Abwe, Ruffin D Ambahe, Nicola M Anthony, Roger Fotso, Sabrina Locatelli, Fiona Maisels, Matthew W Mitchell, Bethan J Morgan, Amy A Pokempner and Mary Gonder, Chimpanzee population structure in Cameroon and Nigeria is associated with habitat variation that may be lost under climate change, BMC Evolutionary Biology, 10.1186/s12862-014-0275-z, 15, 1, (2), (2015).
- Florencia Sangermano, Leslie Bol, Pedro Galvis, Raymond E. Gullison, Jared Hardner and Gail S. Ross, Habitat suitability and protection status of four species of amphibians in the Dominican Republic, Applied Geography, 10.1016/j.apgeog.2015.06.002, 63, (55-65), (2015).
- Steven D. Collins and Nancy E. McIntyre, Modeling the distribution of odonates: a review, Freshwater Science, 10.1086/682688, 34, 3, (1144-1158), (2015).
- Katie Leach, Ruth Kelly, Alison Cameron, W. Ian Montgomery, Neil Reid and Michael Hofreiter, Expertly Validated Models and Phylogenetically-Controlled Analysis Suggests Responses to Climate Change Are Related to Species Traits in the Order Lagomorpha, PLOS ONE, 10, 4, (e0122267), (2015).
- Stuart E. Newson, Hazel E. Evans and Simon Gillings, A novel citizen science approach for large-scale standardised monitoring of bat activity and distribution, evaluated in eastern England, Biological Conservation, 10.1016/j.biocon.2015.06.009, 191, (38-49), (2015).
- Stefano Mammola, Marco Isaia and Miquel A. Arnedo, Alpine endemic spiders shed light on the origin and evolution of subterranean species, PeerJ, 3, (e1384), (2015).
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- Crystal M. Krause, Neil S. Cobb and Deana D. Pennington, Range Shifts Under Future Scenarios of Climate Change: Dispersal Ability Matters for Colorado Plateau Endemic Plants, Natural Areas Journal, 10.3375/043.035.0306, 35, 3, (428-438), (2015).
- Mona Nazeri, Nima Madani, Lalit Kumar, Abdolrassoul Salman Mahiny and Bahram H. Kiabi, A geo-statistical approach to model Asiatic cheetah, onager, gazelle and wild sheep shared niche and distribution in Turan biosphere reserve-Iran, Ecological Informatics, 29, (25), (2015).
- Jocelyn Aycrigg, Gary Beauvais, Tracey Gotthardt, Falk Huettmann, Sanjay Pyare, Mark Andersen, Doug Keinath, Jeff Lonneker, Miles Spathelf and Kelly Walton, Novel Approaches to Modeling and Mapping Terrestrial Vertebrate Occurrence in the Northwest and Alaska: An Evaluation, Northwest Science, 89, 4, (355), (2015).
- Esteban Botero-Delgadillo, Nicholas J. Bayly, Sandra Escudero-Páez and María Isabel Moreno, Understanding the distribution of a threatened bird at multiple levels: A hierarchical analysis of the ecological niche of the Santa Marta Bush-Tyrant (Myiotheretes pernix), The Condor, 117, 4, (629), (2015).
- Ilaria Germishuizen and Robin AW Gardner, A tool for identifying potentialEucalyptus nitensseed orchard sites based on climate and topography, Southern Forests: a Journal of Forest Science, 77, 2, (123), (2015).
- Natalie G. Koncki and Myla F. J. Aronson, Invasion Risk in a Warmer World: Modeling Range Expansion and Habitat Preferences of Three Nonnative Aquatic Invasive Plants, Invasive Plant Science and Management, 8, 04, (436), (2015).
- Diana López‐Alvarez, Antonio J. Manzaneda, Pedro J. Rey, Patricia Giraldo, Elena Benavente, Joël Allainguillaume, Luis Mur, Ana L. Caicedo, Samuel P. Hazen, Adina Breiman, Smadar Ezrati and Pilar Catalán, Environmental niche variation and evolutionary diversification of the Brachypodium distachyon grass complex species in their native circum‐Mediterranean range, American Journal of Botany, 102, 7, (1073-1088), (2015).
- Sachiko Moriguchi, Maki N. Inoue, Toshio Kishimoto, Takeshi Kameyama, Fuminori Ito and Koichi Goka, Estimating colonization and invasion risk maps for Linepithema humile, in Japan, Journal of Asia-Pacific Entomology, 18, 2, (343), (2015).
- Christopher J. Ellis, Ancient woodland indicators signal the climate change risk for dispersal-limited species, Ecological Indicators, 53, (106), (2015).
- Sarah Cunze and Oliver Tackenberg, Decomposition of the maximum entropy niche function – A step beyond modelling species distribution, Environmental Modelling & Software, 72, (250), (2015).
- Julyan Arbel, Catherine K. King, Ben Raymond, Tristrom Winsley and Kerrie L. Mengersen, Application of a Bayesian nonparametric model to derive toxicity estimates based on the response of Antarctic microbial communities to fuel‐contaminated soil, Ecology and Evolution, 5, 13, (2633-2645), (2015).
- Chyi-Rong Chiou, Tung-Yu Hsieh and Chang-Chi Chien, Plant bioclimatic models in climate change research, Botanical Studies, 10.1186/s40529-015-0104-8, 56, 1, (2015).
- Song Chuangye, Ren Hongxu and Huang Chong, Test the relative importance of biotic and abiotic factors on species distribution – A case study in the Yellow River Delta, Acta Ecologica Sinica, 35, 3, (59), (2015).
- Joel K. Nohner and James S. Diana, Muskellunge Spawning Site Selection in Northern Wisconsin Lakes and a GIS‐Based Predictive Habitat Model, North American Journal of Fisheries Management, 35, 1, (141-157), (2015).
- M. Corrie Schoeman, Steven M. Goodman, Beza Ramasindrazana and Darina Koubínová, Species interactions during diversification and community assembly in Malagasy Miniopterus bats, Evolutionary Ecology, 29, 1, (17), (2015).
- Kate S.G. Gormley, Angela D. Hull, Joanne S. Porter, Michael C. Bell and William G. Sanderson, Adaptive management, international co-operation and planning for marine conservation hotspots in a changing climate, Marine Policy, 53, (54), (2015).
- M. Florencia Breitman, Marcelo F. Bonino, Jack W. Sites, Luciano J. Avila and Mariana Morando, Morphological Variation, Niche Divergence, and Phylogeography of Lizards of theLiolaemus lineomaculatusSection (Liolaemini) from Southern Patagonia, Herpetological Monographs, 29, 1, (65), (2015).
- Jian Huang, Emmanuel A. Frimpong and Robert Britton, Using Historical Atlas Data to Develop High-Resolution Distribution Models of Freshwater Fishes, PLOS ONE, 10, 6, (e0129995), (2015).
- Yoshinori Nakazawa, Matthew Mauldin, Ginny Emerson, Mary Reynolds, R. Lash, Jinxin Gao, Hui Zhao, Yu Li, Jean-Jacques Muyembe, Placide Kingebeni, Okito Wemakoy, Jean Malekani, Kevin Karem, Inger Damon and Darin Carroll, A Phylogeographic Investigation of African Monkeypox, Viruses, 7, 12, (2168), (2015).
- Dominik Chłond, Agnieszka Bugaj-Nawrocka and Łukasz Junkiert, Current and potential geographical distribution of Platymeris biguttatus (Linnaeus, 1767) with description of nymphs, Zoological Studies, 54, 1, (2015).
- Maialen Iturbide, Joaquín Bedia, Sixto Herrera, Oscar del Hierro, Miriam Pinto and Jose Manuel Gutiérrez, A framework for species distribution modelling with improved pseudo-absence generation, Ecological Modelling, 312, (166), (2015).
- P. Medone, S. Ceccarelli, P. E. Parham, A. Figuera and J. E. Rabinovich, The impact of climate change on the geographical distribution of two vectors of Chagas disease: implications for the force of infection, Philosophical Transactions of the Royal Society B: Biological Sciences, 370, 1665, (20130560), (2015).
- Ingrid Holzmann, Ilaria Agostini, Karen DeMatteo, Juan Ignacio Areta, Mariano L. Merino and Mario S. Di Bitetti, Using Species Distribution Modeling to Assess Factors that Determine the Distribution of Two Parapatric Howlers (Alouatta spp.) in South America, International Journal of Primatology, 36, 1, (18), (2015).
- Daniel R. Uden, Craig R. Allen, David G. Angeler, Lucía Corral and Kent A. Fricke, Adaptive invasive species distribution models: a framework for modeling incipient invasions, Biological Invasions, 17, 10, (2831), (2015).
- Narkis S. Morales, Ignacio C. Fernández, Basilio Carrasco and Cristina Orchard, Combining Niche Modelling, Land-Use Change, and Genetic Information to Assess the Conservation Status of Pouteria splendens Populations in Central Chile , International Journal of Ecology, 10.1155/2015/612194, 2015, (1-12), (2015).
- Matthew G. Betts, Lenore Fahrig, Adam S. Hadley, Katherine E. Halstead, Jeff Bowman, W. Douglas Robinson, John A. Wiens and David B. Lindenmayer, A species‐centered approach for uncovering generalities in organism responses to habitat loss and fragmentation, Ecography, 37, 6, (517-527), (2014).
- Babak Naimi, Nicholas A. S. Hamm, Thomas A. Groen, Andrew K. Skidmore and Albertus G. Toxopeus, Where is positional uncertainty a problem for species distribution modelling?, Ecography, 37, 2, (191-203), (2013).
- William Godsoe, Inferring the similarity of species distributions using Species’ Distribution Models, Ecography, 37, 2, (130-136), (2013).
- DAVID A. KEITH, MICHAEL MAHONY, HARRY HINES, JANE ELITH, TRACEY J. REGAN, JOHN B. BAUMGARTNER, DAVID HUNTER, GEOFFREY W. HEARD, NICOLA J. MITCHELL, KIRSTEN M. PARRIS, TRENT PENMAN, BEN SCHEELE, CHRISTOPHER C. SIMPSON, REID TINGLEY, CHRISTOPHER R. TRACY, MATT WEST and H. RESIT AKÇAKAYA, Detecting Extinction Risk from Climate Change by IUCN Red List Criteria, Conservation Biology, 28, 3, (810-819), (2014).
- Geiziane Tessarolo, Thiago F. Rangel, Miguel B. Araújo and Joaquín Hortal, Uncertainty associated with survey design in Species Distribution Models, Diversity and Distributions, 20, 11, (1258-1269), (2014).
- Rafael Barrientos, Laura Kvist, Andrés Barbosa, Francisco Valera, Fares Khoury, Sara Varela and Eulalia Moreno, Refugia, colonization and diversification of an arid‐adapted bird: coincident patterns between genetic data and ecological niche modelling, Molecular Ecology, 23, 2, (390-407), (2013).
- Isabel M. D. Rosa, Sadia E. Ahmed and Robert M. Ewers, The transparency, reliability and utility of tropical rainforest land‐use and land‐cover change models, Global Change Biology, 20, 6, (1707-1722), (2014).
- Jeroen Everaars, Karin Frank and Andreas Huth, Species ecology and the impacts of bioenergy crops: an assessment approach with four example farmland bird species, GCB Bioenergy, 6, 3, (252-264), (2014).
- Thibaud Rigot, Inge van Halder and Hervé Jactel, Landscape diversity slows the spread of an invasive forest pest species, Ecography, 37, 7, (648-658), (2014).
- Oluwatobi A. Oke, Stephen B. Heard and Jeremy T. Lundholm, Integrating phylogenetic community structure with species distribution models: an example with plants of rock barrens, Ecography, 37, 7, (614-625), (2013).
- Anett Schibalski, Aleksi Lehtonen and Boris Schröder, Climate change shifts environmental space and limits transferability of treeline models, Ecography, 37, 4, (321-335), (2013).
- Lionel R. Hertzog, Aurélien Besnard and Pierre Jay‐Robert, Field validation shows bias‐corrected pseudo‐absence selection is the best method for predictive species‐distribution modelling, Diversity and Distributions, 20, 12, (1403-1413), (2014).
- Fanuel Kebede, Patricia D. Moehlman, Afework Bekele and Paul H. Evangelista, Predicting seasonal habitat suitability for the critically endangered African wild ass in the Danakil, Ethiopia, African Journal of Ecology, 52, 4, (533-542), (2014).
- Robert Muscarella, Peter J. Galante, Mariano Soley‐Guardia, Robert A. Boria, Jamie M. Kass, María Uriarte and Robert P. Anderson, ENMeval: An R package for conducting spatially independent evaluations and estimating optimal model complexity for Maxent ecological niche models, Methods in Ecology and Evolution, 5, 11, (1198-1205), (2014).
- Emeric Thibaud, Blaise Petitpierre, Olivier Broennimann, Anthony C. Davison and Antoine Guisan, Measuring the relative effect of factors affecting species distribution model predictions, Methods in Ecology and Evolution, 5, 9, (947-955), (2014).
- Jin‐Won Lee, Hee‐Jin Noh, Yunkyoung Lee, Young‐Soo Kwon, Chang‐Hoe Kim and Jeong‐Chil Yoo, Spatial patterns, ecological niches, and interspecific competition of avian brood parasites: inferring from a case study of Korea, Ecology and Evolution, 4, 18, (3689-3702), (2014).
- Marta Kolanowska and Kamil Konowalik, Niche Conservatism and Future Changes in the Potential Area Coverage of Arundina graminifolia, an Invasive Orchid Species from Southeast Asia, Biotropica, 46, 2, (157-165), (2014).
- Eliécer E. Gutiérrez, Robert A. Boria and Robert P. Anderson, Can biotic interactions cause allopatry? Niche models, competition, and distributions of South American mouse opossums, Ecography, 37, 8, (741-753), (2014).
- Giovanni Rapacciuolo, David B. Roy, Simon Gillings and Andy Purvis, Temporal validation plots: quantifying how well correlative species distribution models predict species' range changes over time, Methods in Ecology and Evolution, 5, 5, (407-420), (2014).
- Susan F. Gould, Nicholas J. Beeton, Rebecca M. B. Harris, Michael F. Hutchinson, Alex M. Lechner, Luciana L. Porfirio and Brendan G. Mackey, A tool for simulating and communicating uncertainty when modelling species distributions under future climates, Ecology and Evolution, 4, 24, (4798-4811), (2014).
- Micah B. Hahn, Jonathan H. Epstein, Emily S. Gurley, Mohammad S. Islam, Stephen P. Luby, Peter Daszak and Jonathan A. Patz, Roosting behaviour and habitat selection of Pteropus giganteus reveal potential links to Nipah virus epidemiology, Journal of Applied Ecology, 51, 2, (376-387), (2014).
- Susana Suárez‐Seoane, Emilio Virgós, Olga Terroba, Xosé Pardavila and Jose M. Barea‐Azcón, Scaling of species distribution models across spatial resolutions and extents along a biogeographic gradient. The case of the Iberian mole Talpa occidentalis, Ecography, 37, 3, (279-292), (2013).
- Maarten Zonneveld, Nora Castañeda, Xavier Scheldeman, Jacob Etten and Patrick Van Damme, Application of consensus theory to formalize expert evaluations of plant species distribution models, Applied Vegetation Science, 17, 3, (528-542), (2013).
- Justin M. Calabrese, Grégoire Certain, Casper Kraan and Carsten F. Dormann, Stacking species distribution models and adjusting bias by linking them to macroecological models, Global Ecology and Biogeography, 23, 1, (99-112), (2013).
- Diego F. Alvarado‐Serrano and L. Lacey Knowles, Ecological niche models in phylogeographic studies: applications, advances and precautions, Molecular Ecology Resources, 14, 2, (233-248), (2013).
- Mariano Soley‐Guardia, Aleksandar Radosavljevic, Jhanine L. Rivera and Robert P. Anderson, The effect of spatially marginal localities in modelling species niches and distributions, Journal of Biogeography, 41, 7, (1390-1401), (2014).
- Anas Altartouri, Leena Nurminen and Ari Jolma, Modeling the role of the close‐range effect and environmental variables in the occurrence and spread of hragmites australis in four sites on the Finnish coast of the Gulf of Finland and the Archipelago Sea, Ecology and Evolution, 4, 7, (987-1005), (2014).
- Joaquín Ortego, Paul F. Gugger, Erin C. Riordan and Victoria L. Sork, Influence of climatic niche suitability and geographical overlap on hybridization patterns among southern Californian oaks, Journal of Biogeography, 41, 10, (1895-1908), (2014).
- Seema N. Sheth, Iván Jiménez and Amy L. Angert, Identifying the paths leading to variation in geographical range size in western North American monkeyflowers, Journal of Biogeography, 41, 12, (2344-2356), (2014).
- Laura Meller, Mar Cabeza, Samuel Pironon, Morgane Barbet‐Massin, Luigi Maiorano, Damien Georges and Wilfried Thuiller, Ensemble distribution models in conservation prioritization: from consensus predictions to consensus reserve networks, Diversity and Distributions, 20, 3, (309-321), (2013).
- Karina Wieczorek and Agnieszka Bugaj‐Nawrocka, Invasive aphids of the tribe Siphini: a model of potentially suitable ecological niches, Agricultural and Forest Entomology, 16, 4, (434-443), (2014).
- William C. Dunn and Bruce T. Milne, Implications of climatic heterogeneity for conservation of the Lesser Prairie‐Chicken (Tympanuchus pallidicinctus), Ecosphere, 5, 5, (1-17), (2014).
- Mohsen B. Mesgaran, Roger D. Cousens and Bruce L. Webber, Here be dragons: a tool for quantifying novelty due to covariate range and correlation change when projecting species distribution models, Diversity and Distributions, 20, 10, (1147-1159), (2014).
- Trevor H. Booth, Henry A. Nix, John R. Busby and Michael F. Hutchinson, bioclim: the first species distribution modelling package, its early applications and relevance to most current MaxEnt studies, Diversity and Distributions, 20, 1, (1-9), (2013).
- Rebecca Leaper, Piers K. Dunstan, Scott D. Foster, Neville S. Barrett and Graham J. Edgar, Do communities exist? Complex patterns of overlapping marine species distributions, Ecology, 95, 7, (2016-2025), (2014).
- Wilfried Thuiller, Tamara Münkemüller, Katja H. Schiffers, Damien Georges, Stefan Dullinger, Vincent M. Eckhart, Thomas C. Edwards, Dominique Gravel, Georges Kunstler, Cory Merow, Kara Moore, Christian Piedallu, Steve Vissault, Niklaus E. Zimmermann, Damaris Zurell and Frank M. Schurr, Does probability of occurrence relate to population dynamics?, Ecography, 37, 12, (1155-1166), (2014).
- Alex Bush, Virgilio Hermoso, Simon Linke, David Nipperess, Eren Turak and Lesley Hughes, Freshwater conservation planning under climate change: demonstrating proactive approaches for Australian Odonata, Journal of Applied Ecology, 51, 5, (1273-1281), (2014).
- Niza Gámez, Tania Escalante, David Espinosa, Luis E. Eguiarte and Juan. J. Morrone, Temporal dynamics of areas of endemism under climate change: a case study of Mexican Bursera (Burseraceae), Journal of Biogeography, 41, 5, (871-881), (2013).
- Hao‐Chih Kuo, Shiang‐Fan Chen, Yin‐Ping Fang, Jon Flanders and Stephen J. Rossiter, Comparative rangewide phylogeography of four endemic Taiwanese bat species, Molecular Ecology, 23, 14, (3566-3586), (2014).
- Samaneh Solhjouy‐Fard and Alimorad Sarafrazi, Potential impacts of climate change on distribution range of abis pseudoferus and . palifer (Hemiptera: Nabidae) in Iran, Entomological Science, 17, 3, (283-292), (2013).
- J.O. Cerdeira, T. Monteiro‐Henriques, M.J. Martins, P.C. Silva, D. Alagador and A.M.A. Franco, Mathematical contributions to link biota with environment, Journal of Vegetation Science, 25, 5, (1148-1153), (2014).
- Nicola Stevens, Anthony M. Swemmer, Leanne Ezzy and Barend F.N. Erasmus, Investigating potential determinants of the distribution limits of a savanna woody plant: olophospermum mopane, Journal of Vegetation Science, 25, 2, (363-373), (2013).
- Matthew R. Graham, Robert W. Bryson and Brett R. Riddle, Late Pleistocene to Holocene distributional stasis in scorpions along the Baja California peninsula, Biological Journal of the Linnean Society, 111, 2, (450-461), (2014).
- Andreas L.S. Meyer, Marcio R. Pie and Fernando C. Passos, Assessing the exposure of lion tamarins (Leontopithecus spp.) to future climate change, American Journal of Primatology, 76, 6, (551-562), (2013).
- Hiroto Enari and Haruka Sakamaki‐Enari, Impact assessment of dam construction and forest management for Japanese macaque habitats in snowy areas, American Journal of Primatology, 76, 3, (271-280), (2013).
- Alex Quinn, Belinda Gallardo and David C. Aldridge, Quantifying the ecological niche overlap between two interacting invasive species: the zebra mussel (Dreissena polymorpha) and the quagga mussel (Dreissena rostriformis bugensis), Aquatic Conservation: Marine and Freshwater Ecosystems, 24, 3, (324-337), (2013).
- Ryan J. Harrigan, Henri A. Thomassen, Wolfgang Buermann and Thomas B. Smith, A continental risk assessment of West Nile virus under climate change, Global Change Biology, 20, 8, (2417-2425), (2014).
- Carlos B. Araújo, Luiz Octavio Marcondes‐Machado and Gabriel C. Costa, The importance of biotic interactions in species distribution models: a test of the Eltonian noise hypothesis using parrots, Journal of Biogeography, 41, 3, (513-523), (2013).
- Janne Soininen and Miska Luoto, Predictability in species distributions: a global analysis across organisms and ecosystems, Global Ecology and Biogeography, 23, 11, (1264-1274), (2014).
- Benjamin Blonder, Christine Lamanna, Cyrille Violle and Brian J. Enquist, The n‐dimensional hypervolume, Global Ecology and Biogeography, 23, 5, (595-609), (2014).
- José J. Lahoz‐Monfort, Gurutzeta Guillera‐Arroita and Brendan A. Wintle, Imperfect detection impacts the performance of species distribution models, Global Ecology and Biogeography, 23, 4, (504-515), (2013).
- Nicole K. S. Barker, Stuart M. Slattery, Marcel Darveau and Steve G. Cumming, Modeling distribution and abundance of multiple species: Different pooling strategies produce similar results, Ecosphere, 5, 12, (1-24), (2014).
- Cândida G. Vale, Pedro Tarroso and José C. Brito, Predicting species distribution at range margins: testing the effects of study area extent, resolution and threshold selection in the Sahara–Sahel transition zone, Diversity and Distributions, 20, 1, (20-33), (2013).
- Philip J. Platts, Raquel A. Garcia, Christian Hof, Wendy Foden, Louis A. Hansen, Carsten Rahbek and Neil D. Burgess, Conservation implications of omitting narrow‐ranging taxa from species distribution models, now and in the future, Diversity and Distributions, 20, 11, (1307-1320), (2014).
- Eric R. Larson, Rachael V. Gallagher, Linda J. Beaumont and Julian D. Olden, Generalized “avatar” niche shifts improve distribution models for invasive species, Diversity and Distributions, 20, 11, (1296-1306), (2014).
- Ram C. Poudel, Michael Möller, Jie Liu, Lian‐Ming Gao, Sushim R. Baral and De‐Zhu Li, Low genetic diversity and high inbreeding of the endangered yews in Central Himalaya: implications for conservation of their highly fragmented populations, Diversity and Distributions, 20, 11, (1270-1284), (2014).
- Morgane Barbet‐Massin and Walter Jetz, A 40‐year, continent‐wide, multispecies assessment of relevant climate predictors for species distribution modelling, Diversity and Distributions, 20, 11, (1285-1295), (2014).
- Catherine S. Jarnevich, Wayne E. Esaias, Peter L. A. Ma, Jeffery T. Morisette, Jaime E. Nickeson, Thomas J. Stohlgren, Tracy R. Holcombe, Joanne M. Nightingale, Robert E. Wolfe and Bin Tan, Regional distribution models with lack of proximate predictors: Africanized honeybees expanding north, Diversity and Distributions, 20, 2, (193-201), (2013).
- David A. Keith, Jane Elith and Christopher C. Simpson, Predicting distribution changes of a mire ecosystem under future climates, Diversity and Distributions, 20, 4, (440-454), (2014).
- Linda J. Beaumont, Rachael V. Gallagher, Michelle R. Leishman, Lesley Hughes and Paul O. Downey, How can knowledge of the climate niche inform the weed risk assessment process? A case study of hrysanthemoides monilifera in Australia, Diversity and Distributions, 20, 6, (613-625), (2014).
- Alex Bush, David A. Nipperess, Gunther Theischinger, Eren Turak and Lesley Hughes, Testing for taxonomic bias in the future diversity of Australian Odonata, Diversity and Distributions, 20, 9, (1016-1028), (2014).
- A. Michelle Lawing and Nicholas J. Matzke, Conservation paleobiology needs phylogenetic methods, Ecography, 37, 11, (1109-1122), (2014).
- Thomas J. Duff, Tina L. Bell and Alan York, Recognising fuzzy vegetation pattern: the spatial prediction of floristically defined fuzzy communities using species distribution modelling methods, Journal of Vegetation Science, 25, 2, (323-337), (2013).
- E. Castellanos‐Frías, D. García de León, A. Pujadas‐Salva, J. Dorado and J.L. Gonzalez‐Andujar, Potential distribution of Avena sterilis L. in Europe under climate change, Annals of Applied Biology, 165, 1, (53-61), (2014).
- David A. Steen, James C. Godwin, Christopher J. W. Mcclure and Michael Barbour, Informing management of endemic habitat specialists: Multiscale habitat selection by the Red Hills salamander, The Journal of Wildlife Management, 78, 3, (463-470), (2014).
- Anne M. Trainor, Oswald J. Schmitz, Jacob S. Ivan and Tanya M. Shenk, Enhancing species distribution modeling by characterizing predator–prey interactions, Ecological Applications, 24, 1, (204-216), (2014).
- Shawn M. Crimmins, Solomon Z. Dobrowski, Alison R. Mynsberge and Hugh D. Safford, Can fire atlas data improve species distribution model projections?, Ecological Applications, 24, 5, (1057-1069), (2014).
- James S. Clark, Alan E. Gelfand, Christopher W. Woodall and Kai Zhu, More than the sum of the parts: forest climate response from joint species distribution models, Ecological Applications, 24, 5, (990-999), (2014).
- Yueyun Zhang, Chongtao Chen, Li Li, Chengjian Zhao, Weicai Chen and Yong Huang, Insights from ecological niche modeling on the taxonomic distinction and niche differentiation between the black‐spotted and red‐spotted tokay geckoes (ekko gecko), Ecology and Evolution, 4, 17, (3383-3394), (2014).
- Thomas A. Worthington, Shannon K. Brewer, Timothy B. Grabowski and Julia Mueller, Backcasting the decline of a vulnerable Great Plains reproductive ecotype: identifying threats and conservation priorities, Global Change Biology, 20, 1, (89-102), (2013).
- Javier Gutiérrez Illán, Chris D. Thomas, Julia A. Jones, Weng‐Keen Wong, Susan M. Shirley and Matthew G. Betts, Precipitation and winter temperature predict long‐term range‐scale abundance changes in Western North American birds, Global Change Biology, 20, 11, (3351-3364), (2014).
- Dorothea V. Pio, Robin Engler, H. Peter Linder, Ara Monadjem, Fenton P.D. Cotterill, Peter J. Taylor, M. Corrie Schoeman, Benjamin W. Price, Martin H. Villet, Geeta Eick, Nicolas Salamin and Antoine Guisan, Climate change effects on animal and plant phylogenetic diversity in southern Africa, Global Change Biology, 20, 5, (1538-1549), (2014).
- Chia‐Ying Ko, Oswald J. Schmitz, Morgane Barbet‐Massin and Walter Jetz, Dietary guild composition and disaggregation of avian assemblages under climate change, Global Change Biology, 20, 3, (790-802), (2014).
- Emily A. Berzitis, Jordan N. Minigan, Rebecca H. Hallett and Jonathan A. Newman, Climate and host plant availability impact the future distribution of the bean leaf beetle (Cerotoma trifurcata), Global Change Biology, 20, 9, (2778-2792), (2014).
- Andrew J. Plumptre, Richard A. Fuller, Aggrey Rwetsiba, Fredrick Wanyama, Deo Kujirakwinja, Margaret Driciru, Grace Nangendo, James E. M. Watson and Hugh P. Possingham, Efficiently targeting resources to deter illegal activities in protected areas, Journal of Applied Ecology, 51, 3, (714-725), (2014).
- William T. Bean, Laura R. Prugh, Robert Stafford, H. Scott Butterfield, Michael Westphal and Justin S. Brashares, Species distribution models of an endangered rodent offer conflicting measures of habitat quality at multiple scales, Journal of Applied Ecology, 51, 4, (1116-1125), (2014).
- Renee A. Catullo, Robert Lanfear, Paul Doughty and J. Scott Keogh, The biogeographical boundaries of northern Australia: evidence from ecological niche models and a multi‐locus phylogeny of Uperoleia toadlets (Anura: Myobatrachidae), Journal of Biogeography, 41, 4, (659-672), (2013).
- David Eme, Florian Malard, Céline Colson‐Proch, Pauline Jean, Sébastien Calvignac, Lara Konecny‐Dupré, Frédéric Hervant and Christophe J. Douady, Integrating phylogeography, physiology and habitat modelling to explore species range determinants, Journal of Biogeography, 41, 4, (687-699), (2013).
- HERMAN DE JONG and PASQUALE CILIBERTI, How cold‐adapted flightless flies dispersed over the northern hemisphere: phylogeny and biogeography of the snow fly genus Chionea Dalman (Diptera: Limoniidae), Systematic Entomology, 39, 3, (563-589), (2014).
- Z Qin, A DiTommaso, R S Wu and H Y Huang, Potential distribution of two mbrosia species in China under projected climate change, Weed Research, 54, 5, (520-531), (2014).
- N. Sillero, M. Reis, C. P. Vieira, J. Vieira and R. Morales‐Hojas, Niche evolution and thermal adaptation in the temperate species Drosophila americana, Journal of Evolutionary Biology, 27, 8, (1549-1561), (2014).
- Anna McConville, Bradley Law, Trent Penman and Michael Mahony, Contrasting habitat use of morphologically similar bat species with differing conservation status in south‐eastern Australia, Austral Ecology, 39, 1, (83-94), (2013).
- Robert M. Dorazio, Accounting for imperfect detection and survey bias in statistical analysis of presence‐only data, Global Ecology and Biogeography, 23, 12, (1472-1484), (2014).
- Yu Zhang, Han Y. H. Chen and Anthony Taylor, Multiple drivers of plant diversity in forest ecosystems, Global Ecology and Biogeography, 23, 8, (885-893), (2014).
- Jacquomo Monk, How long should we ignore imperfect detection of species in the marine environment when modelling their distribution?, Fish and Fisheries, 15, 2, (352-358), (2013).
- Sunil Kumar, Lisa G. Neven and Wee L. Yee, Evaluating correlative and mechanistic niche models for assessing the risk of pest establishment, Ecosphere, 5, 7, (1-23), (2014).
- B. C. Mclaughlin, C. N. Morozumi, J. MacKenzie, A. Cole and S. Gennet, Demography linked to climate change projections in an ecoregional case study: integrating forecasts and field data, Ecosphere, 5, 7, (1-16), (2014).
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- Weihua Xu, Andrés Viña, Zengxiang Qi, Zhiyun Ouyang, Jianguo Liu, Wei Liu and Hui Wan, Evaluating conservation effectiveness of nature reserves established for surrogate species: Case of a giant panda nature reserve in Qinling Mountains, China, Chinese Geographical Science, 24, 1, (60), (2014).
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- Javier Fajardo, Janeth Lessmann, Elisa Bonaccorso, Christian Devenish, Jesús Muñoz and Stephanie S. Romanach, Combined Use of Systematic Conservation Planning, Species Distribution Modelling, and Connectivity Analysis Reveals Severe Conservation Gaps in a Megadiverse Country (Peru), PLoS ONE, 9, 12, (e114367), (2014).
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- Danilo Russo, Mirko Di Febbraro, Hugo Rebelo, Mauro Mucedda, Luca Cistrone, Paolo Agnelli, Pier Paolo De Pasquale, Adriano Martinoli, Dino Scaravelli, Cristiano Spilinga, Luciano Bosso and R. Mark Brigham, What Story Does Geographic Separation of Insular Bats Tell? A Case Study on Sardinian Rhinolophids, PLoS ONE, 9, 10, (e110894), (2014).
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- Francisco T. Peña-Gómez, Pablo C. Guerrero, Gustavo Bizama, Milén Duarte, Ramiro O. Bustamante and Harald Auge, Climatic Niche Conservatism and Biogeographical Non-Equilibrium in Eschscholzia californica (Papaveraceae), an Invasive Plant in the Chilean Mediterranean Region, PLoS ONE, 9, 8, (e105025), (2014).
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- Zhenshan Xue, Zhongsheng Zhang, Xianguo Lu, Yuanchun Zou, Yonglei Lu, Ming Jiang, Shouzheng Tong and Kun Zhang, Predicted areas of potential distributions of alpine wetlands under different scenarios in the Qinghai-Tibetan Plateau, China, Global and Planetary Change, 123, (77), (2014).
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- Burcu Tarıkahya-Hacıoğlu, Çağaşan Karacaoğlu and Barış Özüdoğru, The speciation history and systematics of Carthamus (Asteraceae) with special emphasis on Turkish species by integrating phylogenetic and Ecological Niche Modelling data, Plant Systematics and Evolution, 300, 6, (1349), (2014).
- Hitendra Padalia, Vivek Srivastava and S.P.S. Kushwaha, Modeling potential invasion range of alien invasive species, Hyptis suaveolens (L.) Poit. in India: Comparison of MaxEnt and GARP, Ecological Informatics, 10.1016/j.ecoinf.2014.04.002, 22, (36-43), (2014).
- Koustubh Sharma, Raghunandan Singh Chundawat, Joanna Van Gruisen and Asad Rafi Rahmani, Understanding the patchy distribution of four-horned antelope Tetracerus quadricornis in a tropical dry deciduous forest in Central India, Journal of Tropical Ecology, 30, 01, (45), (2014).
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- Jairo Patiño, Rafael Medina, Alain Vanderpoorten, Juana M. González‐Mancebo, Olaf Werner, Nicolas Devos, Rubén G. Mateo, Francisco Lara and Rosa M. Ros, Origin and fate of the single‐island endemic moss Orthotrichum handiense, Journal of Biogeography, 40, 5, (857-868), (2012).
- Weiwei Zhou, Fang Yan, Jinzhong Fu, Shifang Wu, Robert W. Murphy, Jing Che and Yaping Zhang, River islands, refugia and genetic structuring in the endemic brown frog ana kukunoris (Anura, Ranidae) of the Qinghai‐Tibetan Plateau, Molecular Ecology, 22, 1, (130-142), (2012).
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- Rocio Ponce‐Reyes, Emily Nicholson, Peter W. J. Baxter, Richard A. Fuller and Hugh Possingham, Extinction risk in cloud forest fragments under climate change and habitat loss, Diversity and Distributions, 19, 5-6, (518-529), (2013).
- Mark A. Burgman, Michael A. McCarthy, Andrew Robinson, Susan M. Hester, Marissa F. McBride, Jane Elith and F. Dane Panetta, Improving decisions for invasive species management: reformulation and extensions of the Panetta–Lawes eradication graph, Diversity and Distributions, 19, 5-6, (603-607), (2013).
- Belinda Gallardo and David C. Aldridge, Priority setting for invasive species management: risk assessment of Ponto‐Caspian invasive species into Great Britain, Ecological Applications, 23, 2, (352-364), (2013).
- Steven T. Knick, Steven E. Hanser and Kristine L. Preston, Modeling ecological minimum requirements for distribution of greater sage‐grouse leks: implications for population connectivity across their western range, U.S.A, Ecology and Evolution, 3, 6, (1539-1551), (2013).
- Rado H. Andriamasimanana and Alison Cameron, Predicting the impacts of climate change on the distribution of threatened forest‐restricted birds in Madagascar, Ecology and Evolution, 3, 4, (763-769), (2013).
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- Kota Funayama, Ellen Hines, Jerry Davis and Sarah Allen, Effects of sea‐level rise on northern elephant seal breeding habitat at Point Reyes Peninsula, California, Aquatic Conservation: Marine and Freshwater Ecosystems, 23, 2, (233-245), (2012).
- Giancarlo Sadoti, Benjamin Zuckerberg, Marta A. Jarzyna and William F. Porter, Applying occupancy estimation and modelling to the analysis of atlas data, Diversity and Distributions, 19, 7, (804-814), (2013).
- Robert Bagchi, Mike Crosby, Brian Huntley, David G. Hole, Stuart H. M. Butchart, Yvonne Collingham, Mohit Kalra, Jagadish Rajkumar, Asad Rahmani, Mitra Pandey, Hum Gurung, Le Trong Trai, Nguyen Quang and Stephen G. Willis, Evaluating the effectiveness of conservation site networks under climate change: accounting for uncertainty, Global Change Biology, 19, 4, (1236-1248), (2013).
- Franz Gassert, Ulrich Schulte, Martin Husemann, Werner Ulrich, Dennis Rödder, Axel Hochkirch, Edmée Engel, Jobst Meyer and Jan Christian Habel, From southern refugia to the northern range margin: genetic population structure of the common wall lizard, Podarcis muralis, Journal of Biogeography, 40, 8, (1475-1489), (2013).
- Jason L. Malaney and Joseph A. Cook, Using biogeographical history to inform conservation: the case of Preble's meadow jumping mouse, Molecular Ecology, 22, 24, (6000-6017), (2013).
- Matthew R. Graham, Jef R. Jaeger, Lorenzo Prendini and Brett R. Riddle, Phylogeography of the Arizona hairy scorpion (adrurus arizonensis) supports a model of biotic assembly in the Mojave Desert and adds a new Pleistocene refugium, Journal of Biogeography, 40, 7, (1298-1312), (2013).
- Ulf Bergström, Göran Sundblad, Anna‐Leena Downie, Martin Snickars, Christoffer Boström and Mats Lindegarth, Evaluating eutrophication management scenarios in the Baltic Sea using species distribution modelling, Journal of Applied Ecology, 50, 3, (680-690), (2013).
- L. H. Swanepoel, P. Lindsey, M. J. Somers, W. Hoven and F. Dalerum, Extent and fragmentation of suitable leopard habitat in South Africa, Animal Conservation, 16, 1, (41-50), (2012).
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- GREG R. GUERIN and ANDREW J. LOWE, Multi‐species distribution modelling highlights the Adelaide Geosyncline, South Australia, as an important continental‐scale arid‐zone refugium, Austral Ecology, 38, 4, (427-435), (2012).
- Leigh G. Torres, Tim D. Smith, Phil Sutton, Alison MacDiarmid, John Bannister and Tomio Miyashita, From exploitation to conservation: habitat models using whaling data predict distribution patterns and threat exposure of an endangered whale, Diversity and Distributions, 19, 9, (1138-1152), (2013).
- C. J. Storlie, B. L. Phillips, J. J. VanDerWal and S. E. Williams, Improved spatial estimates of climate predict patchier species distributions, Diversity and Distributions, 19, 9, (1106-1113), (2013).
- Steven Delean, C. Michael Bull, Barry W. Brook, Lee M. B. Heard and Damien A. Fordham, Using plant distributions to predict the current and future range of a rare lizard, Diversity and Distributions, 19, 9, (1125-1137), (2013).
- Anne Dubuis, Sara Giovanettina, Loïc Pellissier, Julien Pottier, Pascal Vittoz and Antoine Guisan, Improving the prediction of plant species distribution and community composition by adding edaphic to topo‐climatic variables, Journal of Vegetation Science, 24, 4, (593-606), (2012).
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- Trent L. McDonald, The point process use‐availability or presence‐only likelihood and comments on analysis, Journal of Animal Ecology, 82, 6, (1174-1182), (2013).
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- Tiago Jordão Porto, Ana Carolina Carnaval and Pedro Luís Bernardo da Rocha, Evaluating forest refugial models using species distribution models, model filling and inclusion: a case study with 14 Brazilian species, Diversity and Distributions, 19, 3, (330-340), (2012).
- L. D. Estes, B. A. Bradley, H. Beukes, D. G. Hole, M. Lau, M. G. Oppenheimer, R. Schulze, M. A. Tadross and W. R. Turner, Comparing mechanistic and empirical model projections of crop suitability and productivity: implications for ecological forecasting, Global Ecology and Biogeography, 22, 8, (1007-1018), (2013).
- Janne Soininen, Jenni J. Korhonen and Miska Luoto, Stochastic species distributions are driven by organism size, Ecology, 94, 3, (660-670), (2013).
- Peter C. le Roux, Jonathan Lenoir, Loïc Pellissier, Mary S. Wisz and Miska Luoto, Horizontal, but not vertical, biotic interactions affect fine‐scale plant distribution patterns in a low‐energy system, Ecology, 94, 3, (671-682), (2013).
- Eli S. Bridge, Jeffrey F. Kelly, Andrea Contina, Richard M. Gabrielson, Robert B. MacCurdy and David W. Winkler, Advances in tracking small migratory birds: a technical review of light‐level geolocation, Journal of Field Ornithology, 84, 2, (121-137), (2013).
- Antonin Machac, David Storch and John J. Wiens, ECOLOGICAL CAUSES OF DECELERATING DIVERSIFICATION IN CARNIVORAN MAMMALS, Evolution, 67, 8, (2423-2433), (2013).
- Kathrin Schidelko, Nicole Wüstenhagen, Darius Stiels, Renate van den Elzen and Dennis Rödder, Continental shelf as potential retreat areas for Austral‐Asian estrildid finches (Passeriformes: Estrildidae) during the Pleistocene, Journal of Avian Biology, 44, 2, (121-132), (2012).
- Richard Schuster and Peter Arcese, Using bird species community occurrence to prioritize forests for old growth restoration, Ecography, 36, 4, (499-507), (2012).
- Bénédicte Madon, David I. Warton and Miguel B. Araújo, Community‐level vs species‐specific approaches to model selection, Ecography, 36, 12, (1291-1298), (2013).
- Pablo A. Menéndez‐Guerrero and Catherine H. Graham, Evaluating multiple causes of amphibian declines of Ecuador using geographical quantitative analyses, Ecography, 36, 7, (756-769), (2013).
- Heather M. Kharouba, Jenny L. McCune, Wilfried Thuiller and Brian Huntley, Do ecological differences between taxonomic groups influence the relationship between species’ distributions and climate? A global meta‐analysis using species distribution models, Ecography, 36, 6, (657-664), (2012).
- Peter C. le Roux, Risto Virtanen and Miska Luoto, Geomorphological disturbance is necessary for predicting fine‐scale species distributions, Ecography, 36, 7, (800-808), (2013).
- Rafael D. Zenni and Martin A. Nuñez, The elephant in the room: the role of failed invasions in understanding invasion biology, Oikos, 122, 6, (801-815), (2013).
- Pablo A. Martinez, Dardo A. Marti, Wagner F. Molina and Claudio J. Bidau, Bergmann's rule across the equator: a case study in erdocyon thous (Canidae), Journal of Animal Ecology, 82, 5, (997-1008), (2013).
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- Irina Levinsky, Miguel B. Araújo, David Nogués‐Bravo, Alan M. Haywood, Paul J. Valdes and Carsten Rahbek, Climate envelope models suggest spatio‐temporal co‐occurrence of refugia of African birds and mammals, Global Ecology and Biogeography, 22, 3, (351-363), (2013).
- John W. Williams, Heather M. Kharouba, Sam Veloz, Mark Vellend, Jason McLachlan, Zhengyu Liu, Bette Otto‐Bliesner and Feng He, The ice age ecologist: testing methods for reserve prioritization during the last global warming, Global Ecology and Biogeography, 22, 3, (289-301), (2012).
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- Rohan Mellick, Andrew Lowe, Chris Allen, Robert S. Hill and Maurizio Rossetto, Palaeodistribution modelling and genetic evidence highlight differential post‐glacial range shifts of a rain forest conifer distributed across a latitudinal gradient, Journal of Biogeography, 39, 12, (2292-2302), (2012).
- M. Brambilla, R. Falco and I. Negri, A spatially explicit assessment of within‐season changes in environmental suitability for farmland birds along an altitudinal gradient, Animal Conservation, 15, 6, (638-647), (2012).
- Craig Loehle, Relative frequency function models for species distribution modeling, Ecography, 35, 6, (487-498), (2012).
- Brooke L. Bateman, Jeremy VanDerWal and Christopher N. Johnson, Nice weather for bettongs: using weather events, not climate means, in species distribution models, Ecography, 35, 4, (306-314), (2012).
- Carsten F. Dormann, Stanislaus J. Schymanski, Juliano Cabral, Isabelle Chuine, Catherine Graham, Florian Hartig, Michael Kearney, Xavier Morin, Christine Römermann, Boris Schröder and Alexander Singer, Correlation and process in species distribution models: bridging a dichotomy, Journal of Biogeography, 39, 12, (2119-2131), (2012).
- Geert Aarts, John Fieberg and Jason Matthiopoulos, Comparative interpretation of count, presence–absence and point methods for species distribution models, Methods in Ecology and Evolution, 3, 1, (177-187), (2011).
- Mattia Brambilla and Gentile F. Ficetola, Species distribution models as a tool to estimate reproductive parameters: a case study with a passerine bird species, Journal of Animal Ecology, 81, 4, (781-787), (2012).
- Alberto Jiménez‐Valverde, Insights into the area under the receiver operating characteristic curve (AUC) as a discrimination measure in species distribution modelling, Global Ecology and Biogeography, 21, 4, (498-507), (2011).
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- HUGO REBELO, ELSA FROUFE, JOSÉ C. BRITO, DANILO RUSSO, LUCA CISTRONE, NUNO FERRAND and GARETH JONES, Postglacial colonization of Europe by the barbastelle bat: agreement between molecular data and past predictive modelling, Molecular Ecology, 21, 11, (2761-2774), (2012).
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- Jessica O'Donnell, Rachael V. Gallagher, Peter D. Wilson, Paul O. Downey, Lesley Hughes and Michelle R. Leishman, Invasion hotspots for non‐native plants in Australia under current and future climates, Global Change Biology, 18, 2, (617-629), (2011).
- François Brischoux, Reid Tingley, Richard Shine and Harvey B. Lillywhite, Salinity influences the distribution of marine snakes: implications for evolutionary transitions to marine life, Ecography, 35, 11, (994-1003), (2012).
- Nora Pérez and Xavier Font, Predicting vascular plant richness patterns in Catalonia (NE Spain) using species distribution models, Applied Vegetation Science, 15, 3, (390-400), (2012).
- Colin R. Maycock, Chris J. Kettle, Eyen Khoo, Joan T. Pereira, John B. Sugau, Reuben Nilus, Robert C. Ong, Nazahatul A. Amaludin, Mark F. Newman and David F.R.P. Burslem, A Revised Conservation Assessment of Dipterocarps in Sabah, Biotropica, 44, 5, (649-657), (2012).
- Jessica C. Stanton, Richard G. Pearson, Ned Horning, Peter Ersts and H. Reşit Akçakaya, Combining static and dynamic variables in species distribution models under climate change, Methods in Ecology and Evolution, 3, 2, (349-357), (2011).
- Morgane Barbet‐Massin, Frédéric Jiguet, Cécile Hélène Albert and Wilfried Thuiller, Selecting pseudo‐absences for species distribution models: how, where and how many?, Methods in Ecology and Evolution, 3, 2, (327-338), (2012).
- Frank M. Fontanella, Natalia Feltrin, Luciano J. Avila, Jack W. Sites and Mariana Morando, Early stages of divergence: phylogeography, climate modeling, and morphological differentiation in the South American lizard Liolaemus petrophilus (Squamata: Liolaemidae), Ecology and Evolution, 2, 4, (792-808), (2012).
- April E. Reside, Jeremy VanDerWal and Alex S. Kutt, Projected changes in distributions of Australian tropical savanna birds under climate change using three dispersal scenarios, Ecology and Evolution, 2, 4, (705-718), (2012).
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- Raquel A. Garcia, Neil D. Burgess, Mar Cabeza, Carsten Rahbek and Miguel B. Araújo, Exploring consensus in 21st century projections of climatically suitable areas for African vertebrates, Global Change Biology, 18, 4, (1253-1269), (2011).
- Damien A. Fordham, H. Resit Akçakaya, Miguel B. Araújo, Jane Elith, David A. Keith, Richard Pearson, Tony D. Auld, Camille Mellin, John W. Morgan, Tracey J. Regan, Mark Tozer, Michael J. Watts, Matthew White, Brendan A. Wintle, Colin Yates and Barry W. Brook, Plant extinction risk under climate change: are forecast range shifts alone a good indicator of species vulnerability to global warming?, Global Change Biology, 18, 4, (1357-1371), (2012).
- Hoi‐Fei Mok, Stefan K. Arndt and Craig R. Nitschke, Modelling the potential impact of climate variability and change on species regeneration potential in the temperate forests of South‐Eastern Australia, Global Change Biology, 18, 3, (1053-1072), (2011).
- HELEN M. REGAN, ALEXANDRA D. SYPHARD, JANET FRANKLIN, REBECCA M. SWAB, LISA MARKOVCHICK, ALAN L. FLINT, LORRAINE E. FLINT and PAUL H. ZEDLER, Evaluation of assisted colonization strategies under global change for a rare, fire‐dependent plant, Global Change Biology, 18, 3, (936-947), (2011).
- Elena Couce, Andy Ridgwell and Erica J. Hendy, Environmental controls on the global distribution of shallow‐water coral reefs, Journal of Biogeography, 39, 8, (1508-1523), (2012).
- M. Papeş, A. T. Peterson and G. V. N. Powell, Vegetation dynamics and avian seasonal migration: clues from remotely sensed vegetation indices and ecological niche modelling, Journal of Biogeography, 39, 4, (652-664), (2011).
- W. D. Kissling, Carsten F. Dormann, Jürgen Groeneveld, Thomas Hickler, Ingolf Kühn, Greg J. McInerny, José M. Montoya, Christine Römermann, Katja Schiffers, Frank M. Schurr, Alexander Singer, Jens‐Christian Svenning, Niklaus E. Zimmermann and Robert B. O’Hara, Towards novel approaches to modelling biotic interactions in multispecies assemblages at large spatial extents, Journal of Biogeography, 39, 12, (2163-2178), (2011).
- Camille Mellin, Bayden D. Russell, Sean D. Connell, Barry W. Brook and Damien A. Fordham, Geographic range determinants of two commercially important marine molluscs, Diversity and Distributions, 18, 2, (133-146), (2011).
- Steven I. Higgins, Robert B. O’Hara, Olga Bykova, Michael D. Cramer, Isabelle Chuine, Eva‐Maria Gerstner, Thomas Hickler, Xavier Morin, Michael R. Kearney, Guy F. Midgley and Simon Scheiter, A physiological analogy of the niche for projecting the potential distribution of plants, Journal of Biogeography, 39, 12, (2132-2145), (2012).
- Arnald Marcer, Joan Pino, Xavier Pons and Lluís Brotons, Modelling invasive alien species distributions from digital biodiversity atlases. Model upscaling as a means of reconciling data at different scales, Diversity and Distributions, 18, 12, (1177-1189), (2012).
- Anouschka R. Hof, Roland Jansson and Christer Nilsson, How biotic interactions may alter future predictions of species distributions: future threats to the persistence of the arctic fox in Fennoscandia, Diversity and Distributions, 18, 6, (554-562), (2012).
- April E. Reside, Jeremy VanDerWal, Alex Kutt, Ian Watson and Stephen Williams, Fire regime shifts affect bird species distributions, Diversity and Distributions, 18, 3, (213-225), (2011).
- Michael Kuhlmann, Danni Guo, Ruan Veldtman and John Donaldson, Consequences of warming up a hotspot: species range shifts within a centre of bee diversity, Diversity and Distributions, 18, 9, (885-897), (2012).
- NICOLA J. VAN WILGEN and DAVID M. RICHARDSON, The Roles of Climate, Phylogenetic Relatedness, Introduction Effort, and Reproductive Traits in the Establishment of Non‐Native Reptiles and Amphibians, Conservation Biology, 26, 2, (267-277), (2012).
- KYLE P. MCCARTHY, ROBERT J. FLETCHER JR, CHRISTOPHER T. ROTA and RICHARD L. HUTTO, Predicting Species Distributions from Samples Collected along Roadsides, Conservation Biology, 26, 1, (68-77), (2011).
- Daniel R. Schlaepfer, William K. Lauenroth and John B. Bradford, Ecohydrological niche of sagebrush ecosystems, Ecohydrology, 5, 4, (453-466), (2011).
- Jaymi J. LeBrun, Wayne E. Thogmartin and James R. Miller, Evaluating the ability of regional models to predict local avian abundance, The Journal of Wildlife Management, 76, 6, (1177-1187), (2012).
- Robert M. Dorazio, Predicting the Geographic Distribution of a Species from Presence‐Only Data Subject to Detection Errors, Biometrics, 68, 4, (1303-1312), (2012).
- Na Zhao, Chuanyin Dai, Wenjuan Wang, Ruiying Zhang, Yanhua Qu, Gang Song, Kai Chen, Xiaojun Yang, Fasheng Zou and Fumin Lei, Pleistocene climate changes shaped the divergence and demography of Asian populations of the great tit Parus major: evidence from phylogeographic analysis and ecological niche models, Journal of Avian Biology, 43, 4, (297-310), (2012).
- Håkon M. Kalkvik, I. Jack Stout, Terry J. Doonan and Christopher L. Parkinson, Investigating niche and lineage diversification in widely distributed taxa: phylogeography and ecological niche modeling of the Peromyscus maniculatus species group, Ecography, 35, 1, (54-64), (2012).
- Albert Cama, Rosa Abellana, Isadora Christel, Xavier Ferrer and David R. Vieites, Living on predictability: modelling the density distribution of efficient foraging seabirds, Ecography, 35, 10, (912-921), (2012).
- Beth Crase, Adam C. Liedloff and Brendan A. Wintle, A new method for dealing with residual spatial autocorrelation in species distribution models, Ecography, 35, 10, (879-888), (2012).
- Christine N. Meynard and David M. Kaplan, The effect of a gradual response to the environment on species distribution modeling performance, Ecography, 35, 6, (499-509), (2011).
- Giovanni Strona and Kevin D. Lafferty, How to catch a parasite: Parasite Niche Modeler (PaNic) meets Fishbase, Ecography, 35, 6, (481-486), (2012).
- Maria Mbatudde, Majaliwa Mwanjololo, Esezah Kyomugisha Kakudidi and Helmut Dalitz, Modelling the potential distribution of endangered runus africana (Hook.f.) Kalkm. in East Africa, African Journal of Ecology, 50, 4, (393-403), (2012).
- Ulrich Schulte, Axel Hochkirch, Stefan Lötters, Dennis Rödder, Silke Schweiger, Thomas Weimann and Michael Veith, Cryptic niche conservatism among evolutionary lineages of an invasive lizard, Global Ecology and Biogeography, 21, 2, (198-211), (2011).
- Lennert Tyberghein, Heroen Verbruggen, Klaas Pauly, Charles Troupin, Frederic Mineur and Olivier De Clerck, Bio‐ORACLE: a global environmental dataset for marine species distribution modelling, Global Ecology and Biogeography, 21, 2, (272-281), (2011).
- Jan Engel, Andreas Huth and Karin Frank, Bioenergy production and Skylark (lauda arvensis) population abundance – a modelling approach for the analysis of land‐use change impacts and conservation options, GCB Bioenergy, 4, 6, (713-727), (2012).
- Max A. Moritz, Marc-André Parisien, Enric Batllori, Meg A. Krawchuk, Jeff Van Dorn, David J. Ganz and Katharine Hayhoe, Climate change and disruptions to global fire activity, Ecosphere, 3, 6, (1-22), (2012).
- GUILLERMO DEBANDI, VALERIA CORBALÁN, JOSÉ ALEJANDRO SCOLARO and SERGIO ALBERTO ROIG‐JUÑENT, Predicting the environmental niche of the genus Phymaturus: Are palluma and patagonicus groups ecologically differentiated?, Austral Ecology, 37, 3, (392-400), (2011).
- Elise F. Zipkin, Evan H. Campbell Grant and William F. Fagan, Evaluating the predictive abilities of community occupancy models using AUC while accounting for imperfect detection, Ecological Applications, 22, 7, (1962-1972), (2012).
- Genoveva Gonzalez-Mirelis and Mats Lindegarth, Predicting the distribution of out‐of‐reach biotopes with decision trees in a Swedish marine protected area, Ecological Applications, 22, 8, (2248-2264), (2012).
- Michelle M. Jackson, Monica G. Turner, Scott M. Pearson and Anthony R. Ives, Seeing the forest and the trees: multilevel models reveal both species and community patterns, Ecosphere, 3, 9, (1-16), (2012).
- Christine N. Meynard, Neville Pillay, Manon Perrigault, Pierre Caminade and Guila Ganem, Evidence of environmental niche differentiation in the striped mouse (Rhabdomys sp.): inference from its current distribution in southern Africa, Ecology and Evolution, 2, 5, (1008-1023), (2012).
- Kevin M. Johnston, Kathryn A. Freund and Oswald J. Schmitz, Projected range shifting by montane mammals under climate change: implications for Cascadia's National Parks, Ecosphere, 3, 11, (1-51), (2012).
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- Steven Phillips, Inferring prevalence from presence‐only data: a response to ‘Can we model the probability of presence of species without absence data?’, Ecography, 35, 5, (385-387), (2012).
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- William Godsoe, Are comparisons of species distribution models biased? Are they biologically meaningful?, Ecography, 35, 9, (769-779), (2012).
- Michael T. Calkins, Erik A. Beever, Kenneth G. Boykin, Jennifer K. Frey and Mark C. Andersen, Not‐so‐splendid isolation: modeling climate‐mediated range collapse of a montane mammal Ochotona princeps across numerous ecoregions, Ecography, 35, 9, (780-791), (2012).
- David R. Roberts and Andreas Hamann, Method selection for species distribution modelling: are temporally or spatially independent evaluations necessary?, Ecography, 35, 9, (792-802), (2011).
- Loïc Pellissier, Jean‐Nicolas Pradervand, Julien Pottier, Anne Dubuis, Luigi Maiorano and Antoine Guisan, Climate‐based empirical models show biased predictions of butterfly communities along environmental gradients, Ecography, 35, 8, (684-692), (2011).
- Laura J. Pollock, William K. Morris and Peter A. Vesk, The role of functional traits in species distributions revealed through a hierarchical model, Ecography, 35, 8, (716-725), (2011).
- Carlos Yañez‐Arenas, Enrique Martínez‐Meyer, Salvador Mandujano and Octavio Rojas‐Soto, Modelling geographic patterns of population density of the white‐tailed deer in central Mexico by implementing ecological niche theory, Oikos, 121, 12, (2081-2089), (2012).
- JENNIFER M. LAMB, THESHNIE NAIDOO, PETER J. TAYLOR, MELANIE NAPIER, FANJA RATRIMOMANARIVO and STEVEN M. GOODMAN, Genetically and geographically isolated lineages of a tropical bat (Chiroptera: Molossidae) show demographic stability over the late Pleistocene, Biological Journal of the Linnean Society, 106, 1, (18-40), (2012).
- Michael L. Morrison, Bret A. Collier, Heather A. Mathewson, Julie E. Groce and R. Neal Wilkins, The prevailing paradigm as a hindrance to conservation, Wildlife Society Bulletin, 36, 3, (408-414), (2012).
- Alex S. Anderson, April E. Reside, Jeremy J. VanDerWal, Luke P. Shoo, Richard G. Pearson and Stephen E. Williams, Immigrants and refugees: the importance of dispersal in mediating biotic attrition under climate change, Global Change Biology, 18, 7, (2126-2134), (2012).
- Robert J. Hijmans, Cross‐validation of species distribution models: removing spatial sorting bias and calibration with a null model, Ecology, 93, 3, (679-688), (2012).
- Gopalasamy Reuben CLEMENTS, D. Mark RAYAN, Sheema Abdul AZIZ, Kae KAWANISHI, Carl TRAEHOLT, David MAGINTAN, Muhammad Fadlli Abdul YAZI and Reid TINGLEY, Predicting the distribution of the Asian tapir in Peninsular Malaysia using maximum entropy modeling, Integrative Zoology, 7, 4, (400-406), (2012).
- GONZALO GIRIBET, PRASHANT P. SHARMA, LIGIA R. BENAVIDES, SARAH L. BOYER, RONALD M. CLOUSE, BENJAMIN L. DE BIVORT, DIMITAR DIMITROV, GISELE Y. KAWAUCHI, JEROME MURIENNE and PETER J. SCHWENDINGER, Evolutionary and biogeographical history of an ancient and global group of arachnids (Arachnida: Opiliones: Cyphophthalmi) with a new taxonomic arrangement, Biological Journal of the Linnean Society, 105, 1, (92-130), (2011).
- MAFALDA BARATA, ANA PERERA, FERNANDO MARTÍNEZ‐FREIRÍA and D. JAMES HARRIS, Cryptic diversity within the Moroccan endemic day geckos Quedenfeldtia (Squamata: Gekkonidae): a multidisciplinary approach using genetic, morphological and ecological data, Biological Journal of the Linnean Society, 106, 4, (828-850), (2012).
- Damaris Zurell, Jane Elith and Boris Schröder, Predicting to new environments: tools for visualizing model behaviour and impacts on mapped distributions, Diversity and Distributions, 18, 6, (628-634), (2012).
- Tiago S. Vasconcelos, Miguel Á Rodríguez and Bradford A. Hawkins, Species distribution modelling as a macroecological tool: a case study using New World amphibians, Ecography, 35, 6, (539-548), (2011).
- Michael Notaro, Adrien Mauss and John W. Williams, Projected vegetation changes for the American Southwest: combined dynamic modeling and bioclimatic‐envelope approach, Ecological Applications, 22, 4, (1365-1388), (2012).
- David M. Summers, Brett A. Bryan, Neville D. Crossman and Wayne S. Meyer, Species vulnerability to climate change: impacts on spatial conservation priorities and species representation, Global Change Biology, 18, 7, (2335-2348), (2012).
- Kirsty F. McGregor, Michael S. Watt, Philip E. Hulme and Richard P. Duncan, What determines pine naturalization: species traits, climate suitability or forestry use?, Diversity and Distributions, 18, 10, (1013-1023), (2012).
- Brian Leung, Nuria Roura‐Pascual, Sven Bacher, Jaakko Heikkilä, Lluis Brotons, Mark A. Burgman, Katharina Dehnen‐Schmutz, Franz Essl, Philip E. Hulme, David M. Richardson, Daniel Sol and Montserrat Vilà, TEASIng apart alien species risk assessments: a framework for best practices, Ecology Letters, 15, 12, (1475-1493), (2012).
- Laure Gallien, Rolland Douzet, Steve Pratte, Niklaus E. Zimmermann and Wilfried Thuiller, Invasive species distribution models – how violating the equilibrium assumption can create new insights, Global Ecology and Biogeography, 21, 11, (1126-1136), (2012).
- Alain Smith, Bruce Page, Kevin Duffy and Rob Slotow, Using Maximum Entropy modeling to predict the potential distributions of large trees for conservation planning, Ecosphere, 3, 6, (1-21), (2012).
- Adrián García‐Rodríguez, Gerardo Chaves, Catalina Benavides‐Varela and Robert Puschendorf, Where are the survivors? Tracking relictual populations of endangered frogs in Costa Rica, Diversity and Distributions, 18, 2, (204-212), (2011).
- JUDITH D. TOMS, JOHN FAABORG and WAYNE J. ARENDT, Climate change and birds in the forgotten tropics: the importance of tropical dry forests, Ibis, 154, 3, (632-634), (2012).
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- Simon W. Doxford and Robert P. Freckleton, Changes in the large‐scale distribution of plants: extinction, colonisation and the effects of climate, Journal of Ecology, 100, 2, (519-529), (2011).
- Zen Faulkes, Teresa Feria and Jesús Muñoz, Do Marmorkrebs, Procambarus fallax f. virginalis, threaten freshwater Japanese ecosystems?, Aquatic Biosystems, 8, 1, (13), (2012).
- Sali Bourou, Colm Bowe, Macoumba Diouf and Patrick Van Damme, Ecological and human impacts on stand density and distribution of tamarind (amarindus indica L.) in Senegal, African Journal of Ecology, 50, 3, (253-265), (2012).
- Rikke Anker Jensen, Peter Sunde and Gösta Nachman, Predicting the distribution of Tawny Owl (Strix aluco) at the scale of individual territories in Denmark, Journal of Ornithology, 153, 3, (677), (2012).
- Martha Anahí Güizado-Rodríguez, Claudia Ballesteros-Barrera, Gustavo Casas-Andreu, Victor Luis Barradas-Miranda, Oswaldo Téllez-Valdés and Isaías Hazarmabeth Salgado-Ugarte, The Impact of Global Warming on the Range Distribution of Different Climatic Groups ofAspidoscelis costata costata, Zoological Science, 29, 12, (834), (2012).
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- Lukas J. Rinnhofer, Núria Roura-Pascual, Wolfgang Arthofer, Thomas Dejaco, Barbara Thaler-Knoflach, Gregor A. Wachter, Erhard Christian, Florian M. Steiner and Birgit C. Schlick-Steiner, Iterative species distribution modelling and ground validation in endemism research: an Alpine jumping bristletail example, Biodiversity and Conservation, 10.1007/s10531-012-0341-z, 21, 11, (2845-2863), (2012).
- Alexandra D. Syphard, Jon E. Keeley, Avi Bar Massada, Teresa J. Brennan, Volker C. Radeloff and Guy J-P. Schumann, Housing Arrangement and Location Determine the Likelihood of Housing Loss Due to Wildfire, PLoS ONE, 7, 3, (e33954), (2012).
- Erin E. Poor, Colby Loucks, Andrew Jakes, Dean L. Urban and Marco Festa-Bianchet, Comparing Habitat Suitability and Connectivity Modeling Methods for Conserving Pronghorn Migrations, PLoS ONE, 7, 11, (e49390), (2012).
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- Wesley Dáttilo, Jéssica C. F. Falcão and Marcos C. Teixeira, Predictive model of distribution ofAtta robustaBorgmeier 1939 (Hymenoptera: Formicidae): subsidies for conservation of a Brazilian leaf-cutting ant endangered species, Studies on Neotropical Fauna and Environment, 47, 3, (193), (2012).
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- Catherine S. Millar and Gabriel Blouin-Demers, Habitat suitability modelling for species at risk is sensitive to algorithm and scale: A case study of Blanding's turtle, Emydoidea blandingii, in Ontario, Canada, Journal for Nature Conservation, 20, 1, (18), (2012).
- Christina Kassara, Anastasios Dimalexis, Jakob Fric, Georgios Karris, Christos Barboutis and Spyros Sfenthourakis, Nest-site preferences of Eleonora’s Falcon (Falco eleonorae) on uninhabited islets of the Aegean Sea using GIS and species distribution models, Journal of Ornithology, 153, 3, (663), (2012).
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- Mona Nazeri, Kamaruzaman Jusoff, Nima Madani, Ahmad Rodzi Mahmud, Abdul Rani Bahman, Lalit Kumar and Sean Walker, Predictive Modeling and Mapping of Malayan Sun Bear (Helarctos malayanus) Distribution Using Maximum Entropy, PLoS ONE, 7, 10, (e48104), (2012).
- Jan Hjort and Miska Luoto, Can geodiversity be predicted from space?, Geomorphology, 153-154, (74), (2012).
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- Kathleen A. Alexander, Bryan L. Lewis, Madhav Marathe, Stephen Eubank and Jason K. Blackburn, Modeling of Wildlife-Associated Zoonoses: Applications and Caveats, Vector-Borne and Zoonotic Diseases, 12, 12, (1005), (2012).
- Esther Julia Olaya-Marín, Francisco Martínez-Capel, Rui Manuel Soares Costa and Juan Diego Alcaraz-Hernández, Modelling native fish richness to evaluate the effects of hydromorphological changes and river restoration (Júcar River Basin, Spain), Science of The Total Environment, 10.1016/j.scitotenv.2012.07.093, 440, (95-105), (2012).
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- Anouschka R. Hof, Roland Jansson and Christer Nilsson, The usefulness of elevation as a predictor variable in species distribution modelling, Ecological Modelling, 246, (86), (2012).
- Irene Pérez, Eva Graciá, Rachid Rouag, Soumia Fahd, Said Larbes, Mohammed Znari, Marcos Ferrández, Andrés Giménez, Mohsen Kalboussi, Tahar Slimani, José Daniel Anadón, Hassan El Mouden, Uwe Fritz and Tarek Jdeidi, Distribution of Testudo graeca in the western Mediterranean according to climatic factors, Amphibia-Reptilia, 33, 2, (285), (2012).
- Hannah Slater, Edwin Michael and Matthew Baylis, Predicting the Current and Future Potential Distributions of Lymphatic Filariasis in Africa Using Maximum Entropy Ecological Niche Modelling, PLoS ONE, 7, 2, (e32202), (2012).
- Felipe Sodré Mendes Barros, Marinez Ferreira de Siqueira and Denise Pinheiro da Costa, Modeling the potential geographic distribution of five species of Metzgeria Raddi in Brazil, aiming at their conservation, The Bryologist, 115, 2, (341), (2012).
- Thomas P. Van Boeckel, Weerapong Thanapongtharm, Timothy Robinson, Chandrashekhar M. Biradar, Xiangming Xiao, Marius Gilbert and Matthew Baylis, Improving Risk Models for Avian Influenza: The Role of Intensive Poultry Farming and Flooded Land during the 2004 Thailand Epidemic, PLoS ONE, 7, 11, (e49528), (2012).
- K. L. Glennon, L. J. Rissler and S. A. Church, Ecogeographic isolation: a reproductive barrier between species and between cytotypes in Houstonia (Rubiaceae), Evolutionary Ecology, 26, 4, (909), (2012).
- Stefan Heinänen, Johnny Erola and Mikael von Numers, High resolution species distribution models of two nesting water bird species: a study of transferability and predictive performance, Landscape Ecology, 27, 4, (545), (2012).
- Rasmus Revermann, Hans Schmid, Niklaus Zbinden, Reto Spaar and Boris Schröder, Habitat at the mountain tops: how long can Rock Ptarmigan (Lagopus muta helvetica) survive rapid climate change in the Swiss Alps? A multi-scale approach, Journal of Ornithology, 10.1007/s10336-012-0819-1, 153, 3, (891-905), (2012).
- A. T. Peterson and J. Soberón, Integrating fundamental concepts of ecology, biogeography, and sampling into effective ecological niche modeling and species distribution modeling, Plant Biosystems - An International Journal Dealing with all Aspects of Plant Biology, 146, 4, (789), (2012).
- Octavio R. Rojas-Soto, Victoria Sosa and Juan Francisco Ornelas, Forecasting cloud forest in eastern and southern Mexico: conservation insights under future climate change scenarios, Biodiversity and Conservation, 21, 10, (2671), (2012).
- D. Adhikari, S.K. Barik and K. Upadhaya, Habitat distribution modelling for reintroduction of Ilex khasiana Purk., a critically endangered tree species of northeastern India, Ecological Engineering, 40, (37), (2012).
- Michael B. Ashcroft, John R. Gollan and Michael Batley, Combining citizen science, bioclimatic envelope models and observed habitat preferences to determine the distribution of an inconspicuous, recently detected introduced bee (Halictus smaragdulus Vachal Hymenoptera: Halictidae) in Australia, Biological Invasions, 14, 3, (515), (2012).
- Rolando O. Santos, Diego Lirman and Bernard Sainte-Marie, Using habitat suitability models to predict changes in seagrass distribution caused by water management practices1This article is derived from a special session entitled “A New Hydrology: Inflow Effects on Ecosystem Form and Functioning” that took place at the February 2011 ASLO Aquatic Sciences conference in San Juan, Puerto Rico., Canadian Journal of Fisheries and Aquatic Sciences, 69, 8, (1380), (2012).
- Elizabeth A. Hunter, Patrick A. Raney, James P. Gibbs and Donald J. Leopold, Improving Wetland Mitigation Site Identification Through Community Distribution Modeling and a Patch-Based Ranking Scheme, Wetlands, 10.1007/s13157-012-0315-7, 32, 5, (841-850), (2012).
- Grant R. W. Humphries, Clara J. Deal, Scott Elliott and Falk Huettmann, Spatial predictions of sea surface dimethylsulfide concentrations in the high arctic, Biogeochemistry, 10.1007/s10533-011-9683-y, 110, 1-3, (287-301), (2012).
- Zafar A. Reshi and Anzar A. Khuroo, Alien Plant Invasions in India: Current Status and Management Challenges, Proceedings of the National Academy of Sciences, India Section B: Biological Sciences, (2012).
- Eduardo Pineda and Jorge M. Lobo, The performance of range maps and species distribution models representing the geographic variation of species richness at different resolutions, Global Ecology and Biogeography, 21, 9, (935), (2012).
- Rubén G. Mateo, Ángel M. Felicísimo, Julien Pottier, Antoine Guisan, Jesús Muñoz and Abdisalan Mohamed Noor, Do Stacked Species Distribution Models Reflect Altitudinal Diversity Patterns?, PLoS ONE, 7, 3, (e32586), (2012).
- B. Petitpierre, C. Kueffer, O. Broennimann, C. Randin, C. Daehler and A. Guisan, Climatic Niche Shifts Are Rare Among Terrestrial Plant Invaders, Science, 335, 6074, (1344), (2012).
- Duncan Golicher, Andrew Ford, Luis Cayuela and Adrian Newton, Pseudo-absences, pseudo-models and pseudo-niches: pitfalls of model selection based on the area under the curve, International Journal of Geographical Information Science, 26, 11, (2049), (2012).
- Francesc Sardà-Palomera, Lluís Brotons, Dani Villero, Henk Sierdsema, Stuart E. Newson and Frédéric Jiguet, Mapping from heterogeneous biodiversity monitoring data sources, Biodiversity and Conservation, 21, 11, (2927), (2012).
- Esteban Botero-Delgadillo, Carlos Andrés Páez and Jeyson Sanabria-Mejía, Discovery of Two New Localities for Todd's ParakeetPyrrhura picta caeruleicepsUsing Distribution Models: Enhancing Knowledge of a Little Known Neotropical Bird, Ardeola, 59, 2, (237), (2012).
- Joshua T. Clark, Songlin Fei, Liang Liang and Lynne K. Rieske, Mapping eastern hemlock: Comparing classification techniques to evaluate susceptibility of a fragmented and valued resource to an exotic invader, the hemlock woolly adelgid, Forest Ecology and Management, 266, (216), (2012).
- Mayra P.M. Amboni and Shawn W. Laffan, The effect of species geographical distribution estimation methods on richness and phylogenetic diversity estimates, International Journal of Geographical Information Science, 26, 11, (2097), (2012).
- G. R. W. Humphries, F. Huettmann, G. A. Nevitt, C. Deal and D. Atkinson, Species distribution modeling of storm-petrels (Oceanodroma furcata and O. leucorhoa) in the North Pacific and the role of dimethyl sulfide, Polar Biology, 10.1007/s00300-012-1207-2, 35, 11, (1669-1680), (2012).
- A. Townsend Peterson and Bruce S. Lieberman, Species’ Geographic Distributions Through Time: Playing Catch-up with Changing Climates, Evolution: Education and Outreach, 5, 4, (569), (2012).
- S.A. Wich, G.M. Fredriksson, G. Usher, H.H. Peters, D. Priatna, F. Basalamah, W. Susanto and H. Kühl, Hunting of Sumatran orang-utans and its importance in determining distribution and density, Biological Conservation, 146, 1, (163), (2012).
- Mostafa Tarkesh and Gottfried Jetschke, Comparison of six correlative models in predictive vegetation mapping on a local scale, Environmental and Ecological Statistics, 19, 3, (437), (2012).
- Margaret E. Andrew, Michael A. Wulder and Nicholas C. Coops, Identification of de facto protected areas in boreal Canada, Biological Conservation, 10.1016/j.biocon.2011.11.029, 146, 1, (97-107), (2012).
- Naomi J. Fox, Glenn Marion, Ross S. Davidson, Piran C. L. White and Michael R. Hutchings, Livestock Helminths in a Changing Climate: Approaches and Restrictions to Meaningful Predictions, Animals, 2, 4, (93), (2012).
- Anni Arponen, Prioritizing species for conservation planning, Biodiversity and Conservation, 21, 4, (875), (2012).
- Alycia W. Crall, Mark Renz, Brendon J. Panke, Gregory J. Newman, Carmen Chapin, Jim Graham and Chuck Bargeron, Developing cost-effective early detection networks for regional invasions, Biological Invasions, 14, 12, (2461), (2012).
- Thomas Litt, Christian Ohlwein, Frank H. Neumann, Andreas Hense and Mordechai Stein, Holocene climate variability in the Levant from the Dead Sea pollen record, Quaternary Science Reviews, 49, (95), (2012).
- Elia Axinia Machado-Machado, Empirical mapping of suitability to dengue fever in Mexico using species distribution modeling, Applied Geography, 33, (82), (2012).
- Betty J. Kreakie and Timothy H. Keitt, Integration of distance, direction and habitat into a predictive migratory movement model for blue-winged teal (Anas discors), Ecological Modelling, 224, 1, (25), (2012).
- Patricia Illoldi-Rangel, Chissa-Louise Rivaldi, Blake Sissel, Rebecca Trout Fryxell, Guadalupe Gordillo-Pérez, Angel Rodríguez-Moreno, Phillip Williamson, Griselda Montiel-Parra, Víctor Sánchez-Cordero and Sahotra Sarkar, Species Distribution Models and Ecological Suitability Analysis for Potential Tick Vectors of Lyme Disease in Mexico, Journal of Tropical Medicine, 2012, (1), (2012).
- Chloe J. Hardman, Sophie Williams, Bryan Naqqi Manco and Martin A. Hamilton, Predicting the potential threat of Casuarina equisetifolia to three endemic plant species on the Turks and Caicos Islands, Oryx, 46, 02, (204), (2012).
- A.R. Sofy, A.A. Mousa, A.M. Soliman and Kh.A. El- Dougdoug, The Limiting of Climatic Factors and Predicting of Suitable Habitat for Citrus Gummy Bark Disease Occurrence using GIS, International Journal of Virology, 8, 2, (165), (2012).
- Michael B. Ashcroft, Kristine O. French and Laurie A. Chisholm, A simple post-hoc method to add spatial context to predictive species distribution models, Ecological Modelling, 228, (17), (2012).
- Eduardo Ruiz-Sanchez, Flor Rodriguez-Gomez and Victoria Sosa, Refugia and geographic barriers of populations of the desert poppy, Hunnemannia fumariifolia (Papaveraceae), Organisms Diversity & Evolution, 12, 2, (133), (2012).
- Guoqing Li, Changcheng Liu, Yuguo Liu, Jun Yang, Xinshi Zhang and Ke Guo, Effects of climate, disturbance and soil factors on the potential distribution of Liaotung oak (Quercus wutaishanica Mayr) in China, Ecological Research, 27, 2, (427-436), (2012).
- Junhua Hu and Zhigang Jiang, Detecting the potential sympatric range and niche divergence between Asian endemic ungulates of Procapra, Naturwissenschaften, 10.1007/s00114-012-0933-1, 99, 7, (553-565), (2012).
- Franz Essl, Stefan Dullinger, Dietmar Moser, Wolfgang Rabitsch and Ingrid Kleinbauer, Vulnerability of mires under climate change: implications for nature conservation and climate change adaptation, Biodiversity and Conservation, 10.1007/s10531-011-0206-x, 21, 3, (655-669), (2011).
- L. La Manna, S. D. Matteucci and T. Kitzberger, Modelling Phytophthora disease risk in Austrocedrus chilensis forests of Patagonia, European Journal of Forest Research, 131, 2, (323), (2012).
- Werner Rolf, Roman Lenz and David Peters, Development of a quantitative ‘bioassay’ approach for ecosystem mapping, International Journal of Biodiversity Science, Ecosystem Services & Management, 10.1080/21513732.2012.686121, 8, 1-2, (71-79), (2012).
- Iván F. Rodil, Tanya J. Compton, Mariano Lastra and Brian R. MacKenzie, Exploring Macroinvertebrate Species Distributions at Regional and Local Scales across a Sandy Beach Geographic Continuum, PLoS ONE, 7, 6, (e39609), (2012).
- JA McKinney, ER Hoffmayer, W Wu, R Fulford and J Hendon, Feeding habitat of the whale shark Rhincodon typus in the northern Gulf of Mexico determined using species distribution modelling, Marine Ecology Progress Series, 10.3354/meps09777, 458, (199-211), (2012).
- Hyuk Soo Kwon, Chang Wan Seo and Chong Hwa Park, Development of Species Distribution Models and Evaluation of Species Richness in Jirisan region, Journal of Korean Society for Geospatial Information System, 20, 3, (11), (2012).
- C. Caminade, J. M. Medlock, E. Ducheyne, K. M. McIntyre, S. Leach, M. Baylis and A. P. Morse, Suitability of European climate for the Asian tiger mosquito Aedes albopictus: recent trends and future scenarios, Journal of The Royal Society Interface, 9, 75, (2708), (2012).
- Valerie Obsomer, Pierre Defourny, Marc Coosemans and João Pinto, Predicted Distribution of Major Malaria Vectors Belonging to the Anopheles dirus Complex in Asia: Ecological Niche and Environmental Influences, PLoS ONE, 7, 11, (e50475), (2012).
- Rodrigo Gurgel-Gonçalves, Cléber Galvão, Jane Costa and A. Townsend Peterson, Geographic Distribution of Chagas Disease Vectors in Brazil Based on Ecological Niche Modeling, Journal of Tropical Medicine, 2012, (1), (2012).
- Maarten van Zonneveld, Xavier Scheldeman, Pilar Escribano, María A. Viruel, Patrick Van Damme, Willman Garcia, César Tapia, José Romero, Manuel Sigueñas, José I. Hormaza and Pär K. Ingvarsson, Mapping Genetic Diversity of Cherimoya (Annona cherimola Mill.): Application of Spatial Analysis for Conservation and Use of Plant Genetic Resources, PLoS ONE, 7, 1, (e29845), (2012).
- T.O. Adeyemi, O.T. Ogundipe and J.D. Olowokudej, Species Distribution Modelling of Family Sapindaceae in West Africa, International Journal of Botany, 8, 1, (45), (2012).
- Lior Blank and Leon Blaustein, Using ecological niche modeling to predict the distributions of two endangered amphibian species in aquatic breeding sites, Hydrobiologia, 693, 1, (157), (2012).
- Hugo I. Martínez‐Cabrera, Carl D. Schlichting, John A. Silander and Cynthia S. Jones, Low levels of climate niche conservatism may explain clade diversity patterns in the South African genus Pelargonium (Geraniaceae), American Journal of Botany, 99, 5, (954-960), (2012).
- Pu Huang and Barbara A. Schaal, Association between the geographic distribution during the last glacial maximum of Asian wild rice, Oryza rufipogon (Poaceae), and its current genetic variation, American Journal of Botany, 99, 11, (1866-1874), (2012).
- C.S. Martin, S. Vaz, J.R. Ellis, V. Lauria, F. Coppin and A. Carpentier, Modelled distributions of ten demersal elasmobranchs of the eastern English Channel in relation to the environment, Journal of Experimental Marine Biology and Ecology, 10.1016/j.jembe.2012.03.010, 418-419, (91-103), (2012).
- Tara Forbis de Queiroz, Carson Baughman, Owen Baughman, Maria Gara and Nancy Williams, Species Distribution Modeling for Conservation of Rare, Edaphic Endemic Plants in White River Valley, Nevada, Natural Areas Journal, 32, 2, (149), (2012).
- Juliano Ricardo Fabricante, Kelianne Carolina Targino de Araújo, Leonaldo Alves de Andrade and Jéssica Viviane Amorim Ferreira, Invasão biológica de Artocarpus heterophyllus Lam. (Moraceae) em um fragmento de Mata Atlântica no Nordeste do Brasil: impactos sobre a fitodiversidade e os solos dos sítios invadidos, Acta Botanica Brasilica, 26, 2, (399), (2012).
- Eric Meineri, Olav Skarpaas and Vigdis Vandvik, Modeling alpine plant distributions at the landscape scale: Do biotic interactions matter?, Ecological Modelling, 10.1016/j.ecolmodel.2012.01.021, 231, (1-10), (2012).
- SHINJI FUKUDA and BERNARD DE BAETS, DO ABSENCE DATA MATTER WHEN MODELLING FISH HABITAT PREFERENCE USING A GENETIC TAKAGI-SUGENO FUZZY MODEL?, International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 20, supp02, (233), (2012).
- Hyuksoo Kwon, Jieun Ryu, Changwan Seo, Jiyeon Kim, Jaehwa Tho, Minhwan Suh and Chonghwa Park, Climatic and Environmental Effects on Distribution of Narrow Range Plants, Journal of the Korea Society of Environmental Restoration Technology, 15, 6, (17), (2012).
- Rita Bastos, Mário Santos, Jaime Albino Ramos, Joana Vicente, Carlos Guerra, Joaquim Alonso, João Honrado, Ricardo Santos Ceia, Sérgio Timóteo and João Alexandre Cabral, Testing a novel spatially-explicit dynamic modelling approach in the scope of the laurel forest management for the endangered Azores bullfinch (Pyrrhula murina) conservation, Biological Conservation, 147, 1, (243), (2012).
- Matteo Convertino, Paul Welle, Rafael Muñoz-Carpena, Gregory A. Kiker, Ma.L. Chu-Agor, Richard A. Fischer and Igor Linkov, Epistemic uncertainty in predicting shorebird biogeography affected by sea-level rise, Ecological Modelling, 10.1016/j.ecolmodel.2012.04.012, 240, (1-15), (2012).
- César Capinha, Brian Leung and Pedro Anastácio, Predicting worldwide invasiveness for four major problematic decapods: an evaluation of using different calibration sets, Ecography, 34, 3, (448-459), (2010).
- Matthew C. Fitzpatrick, Nathan J. Sanders, Simon Ferrier, John T. Longino, Michael D. Weiser and Rob Dunn, Forecasting the future of biodiversity: a test of single‐ and multi‐species models for ants in North America, Ecography, 34, 5, (836-847), (2011).
- Robert W. Bryson, Robert W. Murphy, Matthew R. Graham, Amy Lathrop and David Lazcano, Ephemeral Pleistocene woodlands connect the dots for highland rattlesnakes of the Crotalus intermedius group, Journal of Biogeography, 38, 12, (2299-2310), (2011).
- PETER C. ESSELMAN and J. D. ALLAN, Application of species distribution models and conservation planning software to the design of a reserve network for the riverine fishes of northeastern Mesoamerica, Freshwater Biology, 56, 1, (71-88), (2010).
- Brian F. Jacobs, Spatial patterns and ecological drivers of historic piñon–juniper woodland expansion in the American southwest, Ecography, 34, 6, (1085-1095), (2011).
- Lesley A. Gibson, The importance of incorporating imperfect detection in biodiversity assessments: a case study of small mammals in an Australian region, Diversity and Distributions, 17, 4, (613-623), (2011).
- Pierluigi Bombi, Luca Luiselli and Manuela D’Amen, When the method for mapping species matters: defining priority areas for conservation of African freshwater turtles, Diversity and Distributions, 17, 4, (581-592), (2011).
- Aida Cuni Sanchez, Patrick E. Osborne and Nazmul Haq, Climate change and the African baobab (Adansonia digitata L.): the need for better conservation strategies, African Journal of Ecology, 49, 2, (234-245), (2011).
- Peter M. Buston and Jane Elith, Determinants of reproductive success in dominant pairs of clownfish: a boosted regression tree analysis, Journal of Animal Ecology, 80, 3, (528-538), (2011).
- BENJAMIN PLANQUE, CHRISTOPHE LOOTS, PIERRE PETITGAS, ULF LINDSTRøM and SANDRINE VAZ, Understanding what controls the spatial distribution of fish populations using a multi‐model approach, Fisheries Oceanography, 20, 1, (1-17), (2010).
- Kris A. Murray, Richard W. R. Retallick, Robert Puschendorf, Lee F. Skerratt, Dan Rosauer, Hamish I. McCallum, Lee Berger, Rick Speare and Jeremy VanDerWal, Assessing spatial patterns of disease risk to biodiversity: implications for the management of the amphibian pathogen, Batrachochytrium dendrobatidis, Journal of Applied Ecology, 48, 1, (163-173), (2010).
- A. Townsend Peterson, Ecological niche conservatism: a time‐structured review of evidence, Journal of Biogeography, 38, 5, (817-827), (2011).
- Marc Kéry, Towards the modelling of true species distributions, Journal of Biogeography, 38, 4, (617-618), (2011).
- Tereza Jezkova, Viktoria Olah‐Hemmings and Brett R. Riddle, Niche shifting in response to warming climate after the last glacial maximum: inference from genetic data and niche assessments in the chisel‐toothed kangaroo rat (ipodomys microps), Global Change Biology, 17, 11, (3486-3502), (2011).
- Kris A. Murray, Richard W. R. Retallick, Robert Puschendorf, Lee F. Skerratt, Dan Rosauer, Hamish I. McCallum, Lee Berger, Rick Speare and Jeremy VanDerWal, Issues with modelling the current and future distribution of invasive pathogens, Journal of Applied Ecology, 48, 1, (177-180), (2010).
- Babak Naimi, Andrew K. Skidmore, Thomas A. Groen and Nicholas A. S. Hamm, Spatial autocorrelation in predictors reduces the impact of positional uncertainty in occurrence data on species distribution modelling, Journal of Biogeography, 38, 8, (1497-1509), (2011).
- Daniel S. Chapman and Bethan V. Purse, Community versus single‐species distribution models for British plants, Journal of Biogeography, 38, 8, (1524-1535), (2011).
- Marcelo H. Cassini, Ecological principles of species distribution models: the habitat matching rule, Journal of Biogeography, 38, 11, (2057-2065), (2011).
- Juan L. Hernández‐Roldán, Cesc Múrria, Helena Romo, Gerard Talavera, Evgeny Zakharov, Paul D. N. Hebert and Roger Vila, Tracing the origin of disjunct distributions: a case of biogeographical convergence in Pyrgus butterflies, Journal of Biogeography, 38, 10, (2006-2020), (2011).
- Jon Flanders, Li Wei, Stephen J. Rossiter and Shuyi Zhang, Identifying the effects of the Pleistocene on the greater horseshoe bat, Rhinolophus ferrumequinum, in East Asia using ecological niche modelling and phylogenetic analyses, Journal of Biogeography, 38, 3, (439-452), (2010).
- Avishek Chakraborty, Alan E. Gelfand, Adam M. Wilson, Andrew M. Latimer and John A. Silander, Point pattern modelling for degraded presence‐only data over large regions, Journal of the Royal Statistical Society: Series C (Applied Statistics), 60, 5, (757-776), (2011).
- Ilya M. D. Maclean, Robert J. Wilson and Mark Hassall, Predicting changes in the abundance of African wetland birds by incorporating abundance–occupancy relationships into habitat association models, Diversity and Distributions, 17, 3, (480-490), (2011).
- Martin A. Nuñez and Kim A. Medley, Pine invasions: climate predicts invasion success; something else predicts failure, Diversity and Distributions, 17, 4, (703-713), (2011).
- Chris D. Thomas, Jane K. Hill, Barbara J. Anderson, Sallie Bailey, Colin M. Beale, Richard B. Bradbury, Caroline R. Bulman, Humphrey Q. P. Crick, Felix Eigenbrod, Hannah M. Griffiths, William E. Kunin, Tom H. Oliver, Clive A. Walmsley, Kevin Watts, Nicholas T. Worsfold and Tim Yardley, A framework for assessing threats and benefits to species responding to climate change, Methods in Ecology and Evolution, 2, 2, (125-142), (2010).
- Peter D. Wilson, Distance‐based methods for the analysis of maps produced by species distribution models, Methods in Ecology and Evolution, 2, 6, (623-633), (2011).
- Canran Liu, Matt White and Graeme Newell, Measuring and comparing the accuracy of species distribution models with presence–absence data, Ecography, 34, 2, (232-243), (2010).
- Andrew J. Suggitt, Phillipa K. Gillingham, Jane K. Hill, Brian Huntley, William E. Kunin, David B. Roy and Chris D. Thomas, Habitat microclimates drive fine‐scale variation in extreme temperatures, Oikos, 120, 1, (1-8), (2010).
- Hazuki Arakida, Hiromune Mitsuhashi, Mahito Kamada and Kazuo Koyama, Mapping the potential distribution of shorebirds in Japan: the importance of landscape‐level coastal geomorphology, Aquatic Conservation: Marine and Freshwater Ecosystems, 21, 6, (553-563), (2011).
- Antoine Guisan and Carsten Rahbek, SESAM – a new framework integrating macroecological and species distribution models for predicting spatio‐temporal patterns of species assemblages, Journal of Biogeography, 38, 8, (1433-1444), (2011).
- Aston L Arthur, Andrew R Weeks, Matthew P Hill and Ary A Hoffmann, The distribution, abundance and life cycle of the pest mites Balaustium medicagoense (Prostigmata: Erythraeidae) and Bryobia spp. (Prostigmata: Tetranychidae) in Australia, Australian Journal of Entomology, 50, 1, (22-36), (2010).
- VALERIA DI COLA and MARGARITA CHIARAVIGLIO, Establishing species' environmental requirements to understand how the southernmost species of South American pitvipers (Bothrops, Viperidae) are distributed: A niche‐based modelling approach, Austral Ecology, 36, 1, (90-98), (2011).
- J. Bedia, J. Busqué and J.M. Gutiérrez, Predicting plant species distribution across an alpine rangeland in northern Spain. A comparison of probabilistic methods, Applied Vegetation Science, 14, 3, (415-432), (2011).
- Jonathan Heubes, Ingolf Kühn, Konstantin König, Rüdiger Wittig, Georg Zizka and Karen Hahn, Modelling biome shifts and tree cover change for 2050 in West Africa, Journal of Biogeography, 38, 12, (2248-2258), (2011).
- Gustavo Rocha Leite, Claudiney Biral dos Santos and Aloísio Falqueto, Influence of the landscape on dispersal of sylvatic triatomines to anthropic habitats in the Atlantic Forest, Journal of Biogeography, 38, 4, (651-663), (2010).
- Reuben P. Keller, Dragi Kocev and Sašo Džeroski, Trait‐based risk assessment for invasive species: high performance across diverse taxonomic groups, geographic ranges and machine learning/statistical tools, Diversity and Distributions, 17, 3, (451-461), (2011).
- Caroline C. Nóbrega and Paulo De Marco, Unprotecting the rare species: a niche‐based gap analysis for odonates in a core Cerrado area, Diversity and Distributions, 17, 3, (491-505), (2011).
- Sílvia B. Carvalho, José C. Brito, Eduardo J. Crespo and Hugh P. Possingham, Incorporating evolutionary processes into conservation planning using species distribution data: a case study with the western Mediterranean herpetofauna, Diversity and Distributions, 17, 3, (408-421), (2011).
- César Capinha and Pedro Anastácio, Assessing the environmental requirements of invaders using ensembles of distribution models, Diversity and Distributions, 17, 1, (13-24), (2010).
- Clarita Rodríguez‐Soto, Octavio Monroy‐Vilchis, Luigi Maiorano, Luigi Boitani, Juan Carlos Faller, Miguel Á. Briones, Rodrigo Núñez, Octavio Rosas‐Rosas, Gerardo Ceballos and Alessandra Falcucci, Predicting potential distribution of the jaguar (Panthera onca) in Mexico: identification of priority areas for conservation, Diversity and Distributions, 17, 2, (350-361), (2011).
- Jorgelina Marino, Magdalena Bennett, Daniel Cossios, Agustin Iriarte, Mauro Lucherini, Patricio Pliscoff, Claudio Sillero‐Zubiri, Lilian Villalba and Susan Walker, Bioclimatic constraints to Andean cat distribution: a modelling application for rare species, Diversity and Distributions, 17, 2, (311-322), (2011).
- Jane Elith, Steven J. Phillips, Trevor Hastie, Miroslav Dudík, Yung En Chee and Colin J. Yates, A statistical explanation of MaxEnt for ecologists, Diversity and Distributions, 17, 1, (43-57), (2010).
- Antje Ahrends, Neil D. Burgess, Roy E. Gereau, Rob Marchant, Mark T. Bulling, Jon C. Lovett, Philip J. Platts, Victoria Wilkins Kindemba, Nisha Owen, Eibleis Fanning and Carsten Rahbek, Funding begets biodiversity, Diversity and Distributions, 17, 2, (191-200), (2011).
- Alvar Carranza, Omar Defeo and Matías Arim, Taxonomic relatedness and spatial structure of a shelf benthic gastropod assemblage, Diversity and Distributions, 17, 1, (25-34), (2010).
- Kenneth J. Feeley and Miles R. Silman, Keep collecting: accurate species distribution modelling requires more collections than previously thought, Diversity and Distributions, 17, 6, (1132-1140), (2011).
- Jane A. Catford, Peter A. Vesk, Matt D. White and Brendan A. Wintle, Hotspots of plant invasion predicted by propagule pressure and ecosystem characteristics, Diversity and Distributions, 17, 6, (1099-1110), (2011).
- Aidin Niamir, Andrew K. Skidmore, Albertus G. Toxopeus, Antonio R. Muñoz and Raimundo Real, Finessing atlas data for species distribution models, Diversity and Distributions, 17, 6, (1173-1185), (2011).
- Bruce L. Webber, Colin J. Yates, David C. Le Maitre, John K. Scott, Darren J. Kriticos, Noboru Ota, Asha McNeill, Johannes J. Le Roux and Guy F. Midgley, Modelling horses for novel climate courses: insights from projecting potential distributions of native and alien Australian acacias with correlative and mechanistic models, Diversity and Distributions, 17, 5, (978-1000), (2011).
- OLAV SKARPAAS, OLA H. DISERUD, ANNE SVERDRUP‐THYGESON and FRODE ØDEGAARD, Predicting hotspots for red‐listed species: multivariate regression models for oak‐associated beetles, Insect Conservation and Diversity, 4, 1, (53-59), (2010).
- Anette Edvardsen, Vegar Bakkestuen and Rune Halvorsen, A fine‐grained spatial prediction model for the red‐listed vascular plant Scorzonera humilis, Nordic Journal of Botany, 29, 4, (495-504), (2011).
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- WOLFGANG BUERMANN, JAIME A. CHAVES, ROBERT DUDLEY, JIMMY A. McGUIRE, THOMAS B. SMITH and DOUGLAS L. ALTSHULER, Projected changes in elevational distribution and flight performance of montane Neotropical hummingbirds in response to climate change, Global Change Biology, 17, 4, (1671-1680), (2010).
- David G. Jenkins, Ranked species occupancy curves reveal common patterns among diverse metacommunities, Global Ecology and Biogeography, 20, 3, (486-497), (2010).
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- Leonel López‐Toledo, Constantino Gonzalez‐Salazar, David F.R.P. Burslem and Miguel Martinez‐Ramos, Conservation Assessment of Guaiacum sanctum and Guaiacum coulteri: Historic Distribution and Future Trends in Mexico, Biotropica, 43, 2, (246-255), (2010).
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- Angela L. Strecker, Julian D. Olden, Joanna B. Whittier and Craig P. Paukert, Defining conservation priorities for freshwater fishes according to taxonomic, functional, and phylogenetic diversity, Ecological Applications, 21, 8, (3002-3013), (2011).
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- James E. Bromberg, Sunil Kumar, Cynthia S. Brown and Thomas J. Stohlgren, Distributional Changes and Range Predictions of Downy Brome (Bromus tectorum) in Rocky Mountain National Park, Invasive Plant Science and Management, 4, 02, (173), (2011).
- Michael D. Martin and Kevin E. Omland, Environmental Niche Modeling Reveals Climatic Differences among Breeding Ranges of Orchard Oriole Subspecies, The American Midland Naturalist, 166, 2, (404), (2011).
- Zhi Huang, Brendan Brooke and Jin Li, Performance of predictive models in marine benthic environments based on predictions of sponge distribution on the Australian continental shelf, Ecological Informatics, 6, 3-4, (205), (2011).
- Jens-Christian Svenning, Camilla Fløjgaard, Katharine A. Marske, David Nógues-Bravo and Signe Normand, Applications of species distribution modeling to paleobiology, Quaternary Science Reviews, 30, 21-22, (2930), (2011).
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- Sergio Ibáñez-Bernal, Ingeborg Becker-Fauser, Camila González, Enrique Martínez-Meyer, Víctor Sánchez-Cordero, Eduardo A. Rebollar-Téllez and A. Townsend Peterson, Current Knowledge of Leishmania Vectors in Mexico: How Geographic Distributions of Species Relate to Transmission Areas, The American Journal of Tropical Medicine and Hygiene, 85, 5, (839), (2011).
- Christine Adams-Hosking, Hedley S. Grantham, Jonathan R. Rhodes, Clive McAlpine and Patrick T. Moss, Modelling climate-change-induced shifts in the distribution of the koala, Wildlife Research, 38, 2, (122), (2011).
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- Pedro Cardoso, Terry L. Erwin, Paulo A.V. Borges and Tim R. New, The seven impediments in invertebrate conservation and how to overcome them, Biological Conservation, 144, 11, (2647), (2011).
- Gonzalo D. Rubio and Luis E. Acosta, Geographical Distribution of the Space-Weaving Spider,Chibchea salta, from Northwestern Argentina: New Records and Bioclimatic Modeling, Journal of Insect Science, 11, 54, (1), (2011).
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- Pedro Corrêa, Mariana Carvalhaes, Antonio Saraiva, Fabrício Rodrigues, Elisângela Rodrigues and Ricardo Luis de Azevedo da Rocha, Computational Techniques for Biologic Species Distribution Modeling, Computational Methods for Agricultural Research, 10.4018/978-1-61692-871-1.ch015, (308-325), (2011).
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- Sílvia B. Carvalho, José C. Brito, Eduardo G. Crespo, Matthew E. Watts and Hugh P. Possingham, Conservation planning under climate change: Toward accounting for uncertainty in predicted species distributions to increase confidence in conservation investments in space and time, Biological Conservation, 144, 7, (2020), (2011).
- Hugo Fernando López-Arévalo, Sonia Gallina, Rosario Landgrave, Enrique Martínez-Meyer and Lyssette E. Muñoz-Villers, Local knowledge and species distribution models’ contribution towards mammalian conservation, Biological Conservation, 10.1016/j.biocon.2011.01.014, 144, 5, (1451-1463), (2011).
- M. V. Cardo, D. Vezzani and A. E. Carbajo, Environmental Predictors of the Occurrence of Ground Water Mosquito Immatures in the Paraná Lower Delta, Argentina, Journal of Medical Entomology, 48, 5, (991), (2011).
- James P. Strange, Jonathan B. Koch, Victor H. Gonzalez, Lindsay Nemelka and Terry Griswold, Global invasion by Anthidium manicatum (Linnaeus) (Hymenoptera: Megachilidae): assessing potential distribution in North America and beyond, Biological Invasions, 13, 9, (2115), (2011).
- Patrick A. Reeves and Christopher M. Richards, Species Delimitation under the General Lineage Concept: An Empirical Example Using Wild North American Hops (Cannabaceae: Humulus lupulus), Systematic Biology, 10.1093/sysbio/syq056, 60, 1, (45-59), (2010).
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- Raoul H. Bain and Martha M. Hurley, A Biogeographic Synthesis of the Amphibians and Reptiles of Indochina, Bulletin of the American Museum of Natural History, 10.1206/360.1, 360, (1-138), (2011).
- Theodore C. Weber, Maximum entropy modeling of mature hardwood forest distribution in four U.S. states, Forest Ecology and Management, 261, 3, (779), (2011).
- David P. Logan, M. Garry Hill, Patrick G. Connolly, Bridget J. Maher and Shirley J. Dobson, Influence of landscape structure on endemic cicadas in New Zealand kiwifruit orchards, Agricultural and Forest Entomology, 13, 3, (259-271), (2010).
- Bradley J. Walls and Alycia L. Stigall, Analyzing niche stability and biogeography of Late Ordovician brachiopod species using ecological niche modeling, Palaeogeography, Palaeoclimatology, Palaeoecology, 299, 1-2, (15), (2011).
- Hongjuan Liu, Rencang Bu, Jintong Liu, Wenfang Leng, Yuanman Hu, Libing Yang and Huitao Liu, Predicting the wetland distributions under climate warming in the Great Xing'an Mountains, northeastern China, Ecological Research, 26, 3, (605-613), (2011).
- Kerry L. Howell, Rebecca Holt, Inés Pulido Endrino and Heather Stewart, When the species is also a habitat: Comparing the predictively modelled distributions of Lophelia pertusa and the reef habitat it forms, Biological Conservation, 144, 11, (2656), (2011).
- Branislav Bajat, Tomislav Hengl, Milan Kilibarda and Nikola Krunić, Mapping population change index in Southern Serbia (1961–2027) as a function of environmental factors, Computers, Environment and Urban Systems, 35, 1, (35), (2011).
- Malcolm P. Francis, Mark A. Morrison, John Leathwick and Cameron Walsh, Predicting patterns of richness, occurrence and abundance of small fish in New Zealand estuaries, Marine and Freshwater Research, 10.1071/MF11067, 62, 11, (1327), (2011).
- Marcus Hedblom and Ulla Mörtberg, Characterizing Biodiversity in Urban Areas Using Remote Sensing, Urban Remote Sensing, (287-304), (2011).
- Nicholas C. Coops and Richard H. Waring, A process-based approach to estimate lodgepole pine (Pinus contorta Dougl.) distribution in the Pacific Northwest under climate change, Climatic Change, 105, 1-2, (313), (2011).
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- Verónica Andreo, Gregory Glass, Timothy Shields, Cecilia Provensal and Jaime Polop, Modeling Potential Distribution of Oligoryzomys longicaudatus, the Andes Virus (Genus: Hantavirus) Reservoir, in Argentina, EcoHealth, 8, 3, (332), (2011).
- Ricardo Moratelli, Cecilia S. de Andreazzi, João A. de Oliveira and José Luís P. Cordeiro, Current and potential distribution of Myotis simus (Chiroptera, Vespertilionidae), mammalia, 75, 3, (2011).
- A. Palialexis, S. Georgakarakos, I. Karakassis, K. Lika and V. D. Valavanis, Prediction of marine species distribution from presence–absence acoustic data: comparing the fitting efficiency and the predictive capacity of conventional and novel distribution models, Hydrobiologia, 670, 1, (241), (2011).
- Javier Nori, J. Nicolás Urbina-Cardona, Rafael D. Loyola, Julián N. Lescano, Gerardo C. Leynaud and Adam Stow, Climate Change and American Bullfrog Invasion: What Could We Expect in South America?, PLoS ONE, 6, 10, (e25718), (2011).
- Craig R. Jackson and Mark P. Robertson, Predicting the potential distribution of an endangered cryptic subterranean mammal from few occurrence records, Journal for Nature Conservation, 19, 2, (87), (2011).
- Klaas Pauly, Barry P. Jupp and Olivier De Clerck, Modelling the distribution and ecology of Trichosolen blooms on coral reefs worldwide, Marine Biology, 10.1007/s00227-011-1729-0, 158, 10, (2239-2246), (2011).
- Robert P. Anderson and Israel Gonzalez, Species-specific tuning increases robustness to sampling bias in models of species distributions: An implementation with Maxent, Ecological Modelling, 222, 15, (2796), (2011).
- A. Palialexis, S. Georgakarakos, I. Karakassis, K. Lika and V. D. Valavanis, Fish distribution predictions from different points of view: comparing associative neural networks, geostatistics and regression models, Hydrobiologia, 670, 1, (165), (2011).
- Dominik Fischer, Philipp Moeller, Stephanie M. Thomas, Torsten J. Naucke, Carl Beierkuhnlein and Ricardo E. Gürtler, Combining Climatic Projections and Dispersal Ability: A Method for Estimating the Responses of Sandfly Vector Species to Climate Change, PLoS Neglected Tropical Diseases, 5, 11, (e1407), (2011).
- Xiaojun Kou, Qin Li, Shirong Liu and Mike B. Gravenor, Quantifying Species' Range Shifts in Relation to Climate Change: A Case Study of Abies spp. in China, PLoS ONE, 6, 8, (e23115), (2011).
- A. Jiménez-Valverde, A. T. Peterson, J. Soberón, J. M. Overton, P. Aragón and J. M. Lobo, Use of niche models in invasive species risk assessments, Biological Invasions, 10.1007/s10530-011-9963-4, 13, 12, (2785-2797), (2011).
- Javier Sunyer, Josiah H. Townsend, David B. Wake, Scott L. Travers, Sergio C. Gonzalez, Lenin A. Obando and Ardiel Z. Quintana, A New Cryptic Species of Salamander, Genus Oedipina (Caudata: Plethodontidae), from Premontane Elevations in Northern Nicaragua, with Comments on the Systematic Status of the Nicaraguan Paratypes of O. pseudouniformis Brame, 1968, Breviora, 526, (1), (2011).
- Sarah J. Dolman, Peter G.H. Evans, Giuseppe Notarbartolo-di-Sciara and Heidrun Frisch, Active sonar, beaked whales and European regional policy, Marine Pollution Bulletin, 63, 1-4, (27), (2011).
- Richard W. Malizia and Alycia L. Stigall, Niche stability in Late Ordovician articulated brachiopod species before, during, and after the Richmondian Invasion, Palaeogeography, Palaeoclimatology, Palaeoecology, 311, 3-4, (154), (2011).
- Cor J. Vink, José G. B. Derraik, Craig B. Phillips and Phil J. Sirvid, The invasive Australian redback spider, Latrodectus hasseltii Thorell 1870 (Araneae: Theridiidae): current and potential distributions, and likely impacts, Biological Invasions, 13, 4, (1003), (2011).
- Xiangming Xiao, Pavel Dorovskoy, Chandrashekhar Biradar and Eli Bridge, A library of georeferenced photos from the field, Eos, Transactions American Geophysical Union, 92, 49, (453-454), (2011).
- Ramón-Alberto Díaz-Varela, Pedro Álvarez-Álvarez, Emilio Diaz-Varela and Silvia Calvo-Iglesias, Prediction of stand quality characteristics in sweet chestnut forests in NW Spain by combining terrain attributes, spectral textural features and landscape metrics, Forest Ecology and Management, 261, 11, (1962), (2011).
- M. Convertino, J.F. Donoghue, M.L. Chu-Agor, G.A. Kiker, R. Muñoz-Carpena, R.A. Fischer and I. Linkov, Anthropogenic renourishment feedback on shorebirds: A multispecies Bayesian perspective, Ecological Engineering, 37, 8, (1184), (2011).
- Sarah E. May, Kim A. Medley, Steve A. Johnson and Eric A. Hoffman, Combining genetic structure and ecological niche modeling to establish units of conservation: A case study of an imperiled salamander, Biological Conservation, 10.1016/j.biocon.2011.01.013, 144, 5, (1441-1450), (2011).
- Claudia Raedig and Holger Kreft, Influence of different species range types on the perception of macroecological patterns, Systematics and Biodiversity, 9, 2, (159), (2011).
- B. Planque, E. Bellier and C. Loots, Uncertainties in projecting spatial distributions of marine populations, ICES Journal of Marine Science, 68, 6, (1045), (2011).
- Aida Cuni Sanchez, The baobab tree in Malawi, Fruits, 66, 6, (405), (2011).
- JORGE H. VEGA RIVERA, MIGUEL A. ORTEGA-HUERTA, SAHOTRA SARKAR and JOHN H. RAPPOLE, Modelling the potential winter distribution of the endangered Black-capped Vireo ( Vireo atricapilla), Bird Conservation International, 21, 01, (92), (2011).
- Andrew K. Skidmore, Janet Franklin, Terry P. Dawson and Petter Pilesjö, Geospatial tools address emerging issues in spatial ecology: a review and commentary on the Special Issue, International Journal of Geographical Information Science, 10.1080/13658816.2011.554296, 25, 3, (337-365), (2011).
- Philippe Koubbi, Masato Moteki, Guy Duhamel, Anne Goarant, Percy-Alexander Hulley, Richard O’Driscoll, Takashi Ishimaru, Patrice Pruvost, Eric Tavernier and Graham Hosie, Ecoregionalization of myctophid fish in the Indian sector of the Southern Ocean: Results from generalized dissimilarity models, Deep Sea Research Part II: Topical Studies in Oceanography, 10.1016/j.dsr2.2010.09.007, 58, 1-2, (170-180), (2011).
- Beatriz Vanessa Herrera Campo, Glenn Hyman and Anthony Bellotti, Threats to cassava production: known and potential geographic distribution of four key biotic constraints, Food Security, 3, 3, (329), (2011).
- Pedro J. Leitão, Francisco Moreira and Patrick E. Osborne, Effects of geographical data sampling bias on habitat models of species distributions: a case study with steppe birds in southern Portugal, International Journal of Geographical Information Science, 25, 3, (439), (2011).
- Luc De Meester, Peter van Tienderen, Marinus Werger, Andrew Hector, Gert Wörheide, Jari Niemelä, Alex Aguilar, Erik Smets, Charles Godfray, William Sutherland, Jürgen Bauhus, Franck Courchamp, Gustavo Gandini, Marcus Koch, Yvon Le Maho, Michaël Manuel, Jan Pawlowski, Eric Quéinnec, Ian Owens and Laura Keustermans, Challenges for biodiversity research in Europe, Procedia - Social and Behavioral Sciences, 13, (83), (2011).
- Juan José Martínez and Valeria Di Cola, Geographic distribution and phenetic skull variation in two close species of Graomys (Rodentia, Cricetidae, Sigmodontinae), Zoologischer Anzeiger - A Journal of Comparative Zoology, 250, 3, (175), (2011).
- Michael J. Watts, Yuxiao Li, Bayden D. Russell, Camille Mellin, Sean D. Connell and Damien A. Fordham, A novel method for mapping reefs and subtidal rocky habitats using artificial neural networks, Ecological Modelling, 222, 15, (2606), (2011).
- Valeria Corbalán, Marcelo F. Tognelli, José A. Scolaro and Sergio A. Roig-Juñent, Lizards as conservation targets in Argentinean Patagonia, Journal for Nature Conservation, 19, 1, (60), (2011).
- Maxime Dupin, Philippe Reynaud, Vojtěch Jarošík, Richard Baker, Sarah Brunel, Dominic Eyre, Jan Pergl, David Makowski and Simon Thrush, Effects of the Training Dataset Characteristics on the Performance of Nine Species Distribution Models: Application to Diabrotica virgifera virgifera, PLoS ONE, 6, 6, (e20957), (2011).
- Kim B. Stevens and Dirk U. Pfeiffer, Spatial modelling of disease using data- and knowledge-driven approaches, Spatial and Spatio-temporal Epidemiology, 2, 3, (125), (2011).
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- Nicholas K. Ukrainetz, Gregory A. O’Neill and Barry Jaquish, Comparison of fixed and focal point seed transfer systems for reforestation and assisted migration: a case study for interior spruce in British Columbia, Canadian Journal of Forest Research, 41, 7, (1452), (2011).
- Blas Benito, Juan Lorite and Julio Peñas, Simulating potential effects of climatic warming on altitudinal patterns of key species in Mediterranean-alpine ecosystems, Climatic Change, 10.1007/s10584-010-0015-3, 108, 3, (471-483), (2011).
- JAN CHRISTIAN HABEL, DENNIS RÖDDER, THOMAS SCHMITT and GABRIEL NÈVE, Global warming will affect the genetic diversity and uniqueness of Lycaena helle populations, Global Change Biology, 17, 1, (194-205), (2010).
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- Jiping Zhang, Yili Zhang, Linshan Liu and Yong Nie, Predicting potential distribution of Tibetan spruce (Picea smithiana) in Qomolangma (Mount Everest) National Nature Preserve using maximum entropy niche-based model, Chinese Geographical Science, 21, 4, (417), (2011).
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- EJ Gregr, Insights into North Pacific right whale Eubalaena japonica habitat from historic whaling records, Endangered Species Research, 10.3354/esr00381, 15, 3, (223-239), (2011).
- Dominik Fischer, Stephanie Margarete Thomas, Franziska Niemitz, Björn Reineking and Carl Beierkuhnlein, Projection of climatic suitability for Aedes albopictus Skuse (Culicidae) in Europe under climate change conditions, Global and Planetary Change, 78, 1-2, (54), (2011).
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- John Coll, David Bourke, Micheline Sheehy Skeffington, John Sweeney and Michael Gormally, Developing a predictive modelling capacity for a climate change-vulnerable blanket bog habitat: Assessing 1961–1990 baseline relationships, Irish Geography, 44, 1, (27), (2011).
- John Klicka, Garth M. Spellman, Kevin Winker, Vivien Chua and Brian T. Smith, A Phylogeographic and Population Genetic Analysis of a Widespread, Sedentary North American Bird: the Hairy Woodpecker (Picoides Villosus), The Auk, 128, 2, (346), (2011).
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- Andrew P. Jennings and Geraldine Veron, Predicted distributions and ecological niches of 8 civet and mongoose species in Southeast Asia, Journal of Mammalogy, 92, 2, (316), (2011).
- Falk Huettmann, Yuri Artukhin, Olivier Gilg and Grant Humphries, Predictions of 27 Arctic pelagic seabird distributions using public environmental variables, assessed with colony data: a first digital IPY and GBIF open access synthesis platform, Marine Biodiversity, 41, 1, (141), (2011).
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- Erin E. Saupe, Monica Papes, Paul A. Selden, Richard S. Vetter and Corrie Moreau, Tracking a Medically Important Spider: Climate Change, Ecological Niche Modeling, and the Brown Recluse (Loxosceles reclusa), PLoS ONE, 6, 3, (e17731), (2011).
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- Philip de Pous, Wouter Beukema, Martijn Weterings, Ignas Dümmer and Philippe Geniez, Area prioritization and performance evaluation of the conservation area network for the Moroccan herpetofauna: a preliminary assessment, Biodiversity and Conservation, 20, 1, (89), (2011).
- Junhua Hu, Zhigang Jiang and Brian Gratwicke, Climate Change Hastens the Conservation Urgency of an Endangered Ungulate, PLoS ONE, 6, 8, (e22873), (2011).
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- Neftalí Sillero, What does ecological modelling model? A proposed classification of ecological niche models based on their underlying methods, Ecological Modelling, 222, 8, (1343), (2011).
- Jim R. Muirhead and Hugh J. MacIsaac, Evaluation of stochastic gravity model selection for use in estimating non-indigenous species dispersal and establishment, Biological Invasions, 13, 11, (2445), (2011).
- Wen-Yi Zhang, Lan Wei, Xian-Jun Wang, Hong Yang, Zhi-Qiang Wang, Wu-Chun Cao, Quan Qian, Li-Qun Fang, Shao-Xia Song, Xiu-Jun Li and Gregory E. Glass, Using Geographic Information System-based Ecologic Niche Models to Forecast the Risk of Hantavirus Infection in Shandong Province, China, The American Journal of Tropical Medicine and Hygiene, 84, 3, (497), (2011).
- Elias J. Martinson, Zachary B. Eddy, Julie L. Commerford, Emilie Blevins, Susan J. Rolfsmeier and Kendra K. McLauchlan, Biogeographic Distributions of Selected North American Grassland Plant Species, Physical Geography, 32, 6, (583), (2011).
- Stephanie Januchowski-Hartley, Jeremy VanDerWal and Damon Sydes, Effective Control of Aquatic Invasive Species in Tropical Australia, Environmental Management, 48, 3, (568), (2011).
- TREVOR KEENAN, JOSEP MARIA SERRA, FRANCISCO LLORET, MIQUEL NINYEROLA and SANTIAGO SABATE, Predicting the future of forests in the Mediterranean under climate change, with niche‐ and process‐based models: CO2 matters!, Global Change Biology, 17, 1, (565-579), (2010).
- Maria R. Donalisio and A. Townsend Peterson, Environmental factors affecting transmission risk for hantaviruses in forested portions of southern Brazil, Acta Tropica, 119, 2-3, (125), (2011).
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- Orly Razgour, Julia Hanmer and Gareth Jones, Using multi-scale modelling to predict habitat suitability for species of conservation concern: The grey long-eared bat as a case study, Biological Conservation, 10.1016/j.biocon.2011.08.010, 144, 12, (2922-2930), (2011).
- Jan Hjort, Juuso Suomi and Jukka Käyhkö, Spatial prediction of urban–rural temperatures using statistical methods, Theoretical and Applied Climatology, 10.1007/s00704-011-0425-9, 106, 1-2, (139-152), (2011).
- Franziska Rupprecht, Jens Oldeland and Manfred Finckh, Modelling potential distribution of the threatened tree species Juniperus oxycedrus: how to evaluate the predictions of different modelling approaches?, Journal of Vegetation Science, 22, 4, (647-659), (2011).
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- Brooke L. Bateman, Sandra E. Abell-Davis and Christopher N. Johnson, Climate-driven variation in food availability between the core and range edge of the endangered northern bettong (Bettongia tropica), Australian Journal of Zoology, 59, 3, (177), (2011).
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- Yongyut Trisurat and Prateep Duengkae, Consequences of land use change on bird distribution at Sakaerat Environmental Research Station, Journal of Ecology and Environment, 34, 2, (203), (2011).
- Vincent Martin, Dirk U. Pfeiffer, Xiaoyan Zhou, Xiangming Xiao, Diann J. Prosser, Fusheng Guo, Marius Gilbert and Neil M. Ferguson, Spatial Distribution and Risk Factors of Highly Pathogenic Avian Influenza (HPAI) H5N1 in China, PLoS Pathogens, 7, 3, (e1001308), (2011).
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- Claire Villemant, Morgane Barbet-Massin, Adrien Perrard, Franck Muller, Olivier Gargominy, Frédéric Jiguet and Quentin Rome, Predicting the invasion risk by the alien bee-hawking Yellow-legged hornet Vespa velutina nigrithorax across Europe and other continents with niche models, Biological Conservation, 144, 9, (2142), (2011).
- Christian Pitra, Susana Suárez-Seoane, Carlos A. Martín, Wolf-Jürgen Streich and Juan C. Alonso, Linking habitat quality with genetic diversity: a lesson from great bustards in Spain, European Journal of Wildlife Research, 57, 3, (411), (2011).
- Trevon Fuller, Henri A. Thomassen, Prime M. Mulembakani, Sara C. Johnston, James O. Lloyd-Smith, Neville K. Kisalu, Timothee K. Lutete, Seth Blumberg, Joseph N. Fair, Nathan D. Wolfe, Robert L. Shongo, Pierre Formenty, Hermann Meyer, Linda L. Wright, Jean-Jacques Muyembe, Wolfgang Buermann, Sassan S. Saatchi, Emile Okitolonda, Lisa Hensley, Thomas B. Smith and Anne W. Rimoin, Using Remote Sensing to Map the Risk of Human Monkeypox Virus in the Congo Basin, EcoHealth, 8, 1, (14), (2011).
- Mauro Enrique de Souza Muñoz, Renato De Giovanni, Marinez Ferreira de Siqueira, Tim Sutton, Peter Brewer, Ricardo Scachetti Pereira, Dora Ann Lange Canhos and Vanderlei Perez Canhos, openModeller: a generic approach to species’ potential distribution modelling, GeoInformatica, 15, 1, (111), (2011).
- Peter Zeilhofer and Suzy Mara Klemp, Spatial modelling of sprinkler irrigation suitability in a Central Brazilian Cerrado region, Geocarto International, 26, 3, (227), (2011).
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- Katherine M. Giljohann, Cindy E. Hauser, Nicholas S. G. Williams and Joslin L. Moore, Optimizing invasive species control across space: willow invasion management in the Australian Alps, Journal of Applied Ecology, 48, 5, (1286-1294), (2011).
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- Armanda D Bastos, Deenadayalan Nair, Peter J Taylor, Helene Brettschneider, Frikkie Kirsten, Elmarie Mostert, Emil von Maltitz, Jennifer M Lamb, Pim van Hooft, Steven R Belmain, Giancarlo Contrafatto, Sarah Downs and Christian T Chimimba, Genetic monitoring detects an overlooked cryptic species and reveals the diversity and distribution of three invasive Rattus congeners in south Africa, BMC Genetics, 10.1186/1471-2156-12-26, 12, 1, (26), (2011).
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- Yongyut Trisurat, Rajendra P. Shrestha and Roger Kjelgren, Plant species vulnerability to climate change in Peninsular Thailand, Applied Geography, 31, 3, (1106), (2011).
- John Giles, A. Townsend Peterson, Alzira Almeida and Giovanna Raso, Ecology and Geography of Plague Transmission Areas in Northeastern Brazil, PLoS Neglected Tropical Diseases, 5, 1, (e925), (2011).
- Joana Vicente, Christophe F. Randin, João Gonçalves, Marc J. Metzger, Ângela Lomba, João Honrado and Antoine Guisan, Where will conflicts between alien and rare species occur after climate and land-use change? A test with a novel combined modelling approach, Biological Invasions, 13, 5, (1209), (2011).
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- Peter B. Pearman, Antoine Guisan and Niklaus E. Zimmermann, Impacts of climate change on Swiss biodiversity: An indicator taxa approach, Biological Conservation, 144, 2, (866), (2011).
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- Sara Varela, Jorge M. Lobo and Joaquín Hortal, Using species distribution models in paleobiogeography: A matter of data, predictors and concepts, Palaeogeography, Palaeoclimatology, Palaeoecology, 310, 3-4, (451), (2011).
- Jeffrey D. Lozier and Nicholas J. Mills, Predicting the potential invasive range of light brown apple moth (Epiphyas postvittana) using biologically informed and correlative species distribution models, Biological Invasions, 13, 10, (2409), (2011).
- Darren Norris, Fabiana Rocha-Mendes, Renato Marques, Rodrigo de Almeida Nobre and Mauro Galetti, Density and Spatial Distribution of Buffy-tufted-ear Marmosets (Callithrix aurita) in a Continuous Atlantic Forest, International Journal of Primatology, 32, 4, (811), (2011).
- Shinji Fukuda, Assessing the applicability of fuzzy neural networks for habitat preference evaluation of Japanese medaka (Oryzias latipes), Ecological Informatics, 6, 5, (286), (2011).
- Tomoko Doko, Hiromichi Fukui, Andre Kooiman, A.G. Toxopeus, Tomohiro Ichinose, Wenbo Chen and A.K. Skidmore, Identifying habitat patches and potential ecological corridors for remnant Asiatic black bear (Ursus thibetanus japonicus) populations in Japan, Ecological Modelling, 222, 3, (748), (2011).
- S. Normand, R. E. Ricklefs, F. Skov, J. Bladt, O. Tackenberg and J.-C. Svenning, Postglacial migration supplements climate in determining plant species ranges in Europe, Proceedings of the Royal Society B: Biological Sciences, 278, 1725, (3644), (2011).
- Robert W. Sutherst, Fiona Constable, Kyla J. Finlay, Richard Harrington, Jo Luck and Myron P. Zalucki, Adapting to crop pest and pathogen risks under a changing climate, Wiley Interdisciplinary Reviews: Climate Change, 2, 2, (220-237), (2011).
- Valerio Amici, Dealing with vagueness in complex forest landscapes: A soft classification approach through a niche-based distribution model, Ecological Informatics, 6, 6, (371), (2011).
- Christelle Robinet, Nico Van Opstal, Richard Baker and Alain Roques, Applying a spread model to identify the entry points from which the pine wood nematode, the vector of pine wilt disease, would spread most rapidly across Europe, Biological Invasions, 10.1007/s10530-011-9983-0, 13, 12, (2981-2995), (2011).
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- Hannah Rose and Richard Wall, Modelling the impact of climate change on spatial patterns of disease risk: Sheep blowfly strike by Lucilia sericata in Great Britain, International Journal for Parasitology, 41, 7, (739), (2011).
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- Paula C. Rivera, Valeria Di Cola, Juan J. Martínez, Cristina N. Gardenal, Margarita Chiaraviglio and Anna Stepanova, Species Delimitation in the Continental Forms of the Genus Epicrates (Serpentes, Boidae) Integrating Phylogenetics and Environmental Niche Models, PLoS ONE, 6, 9, (e22199), (2011).
- Catherine S. Jarnevich, Paul Evangelista, Thomas J. Stohlgren and Jeffery Morisette, Improving National-Scale Invasion Maps: Tamarisk in the Western United States, Western North American Naturalist, 71, 2, (164), (2011).
- Dennis Rödder, Stefan Lötters, Mehmed Öz, Sergé Bogaerts, Karolos Eleftherakos and Michael Veith, A novel method to calculate climatic niche similarity among species with restricted ranges—the case of terrestrial Lycian salamanders, Organisms Diversity & Evolution, 11, 5, (409), (2011).
- Andrew J. Davies, John M. Guinotte and Richard K. F. Unsworth, Global Habitat Suitability for Framework-Forming Cold-Water Corals, PLoS ONE, 6, 4, (e18483), (2011).
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- Oliver Hawlitschek, Nick Porch, Lars Hendrich, Michael Balke and David Nogues-Bravo, Ecological Niche Modelling and nDNA Sequencing Support a New, Morphologically Cryptic Beetle Species Unveiled by DNA Barcoding, PLoS ONE, 6, 2, (e16662), (2011).
- T.M. Wilms, P. Wagner, M. Shobrak, D. Rödder and W. Böhme, Living on the edge? – On the thermobiology and activity pattern of the large herbivorous desert lizard Uromastyx aegyptia microlepis Blanford, 1875 at Mahazat as-Sayd Protected Area, Saudi Arabia, Journal of Arid Environments, 75, 7, (636), (2011).
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- Lars Eisen and Rebecca J. Eisen, Using Geographic Information Systems and Decision Support Systems for the Prediction, Prevention, and Control of Vector-Borne Diseases, Annual Review of Entomology, 56, 1, (41), (2011).
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- Rafael Alonso Ponce, Beatriz Águeda, Teresa Ágreda, María Pilar Modrego, Jorge Aldea, Luz Marina Fernández-toirán and Fernando MartÍnez-peña, Rockroses and Boletus edulis ectomycorrhizal association: realized niche and climatic suitability in Spain, Fungal Ecology, 4, 3, (224), (2011).
- Rosane G. Collevatti, João Carlos Nabout and Jose Alexandre F. Diniz-Filho, Range shift and loss of genetic diversity under climate change in Caryocar brasiliense, a Neotropical tree species, Tree Genetics & Genomes, 7, 6, (1237), (2011).
- Duccio Rocchini, Joaquín Hortal, Szabolcs Lengyel, Jorge M. Lobo, Alberto Jiménez-Valverde, Carlo Ricotta, Giovanni Bacaro and Alessandro Chiarucci, Accounting for uncertainty when mapping species distributions: The need for maps of ignorance, Progress in Physical Geography: Earth and Environment, 10.1177/0309133311399491, 35, 2, (211-226), (2011).
- Melanie Gogol-Prokurat, Predicting habitat suitability for rare plants at local spatial scales using a species distribution model, Ecological Applications, 21, 1, (33), (2011).
- Eli S. Bridge, Kasper Thorup, Melissa S. Bowlin, Phillip B. Chilson, Robert H. Diehl, René W. Fléron, Phillip Hartl, Roland Kays, Jeffrey F. Kelly, W. Douglas Robinson and Martin Wikelski, Technology on the Move: Recent and Forthcoming Innovations for Tracking Migratory Birds, BioScience, 61, 9, (689), (2011).
- S. R. Januchowski-Hartley, P. Visconti and R. L. Pressey, A systematic approach for prioritizing multiple management actions for invasive species, Biological Invasions, 13, 5, (1241), (2011).
- April E. Reside, Ian Watson, Jeremy VanDerWal and Alex S. Kutt, Incorporating low-resolution historic species location data decreases performance of distribution models, Ecological Modelling, 222, 18, (3444), (2011).
- Rohan Mellick, Andrew Lowe and Maurizio Rossetto, Consequences of long- and short-term fragmentation on the genetic diversity and differentiation of a late successional rainforest conifer, Australian Journal of Botany, 10.1071/BT10291, 59, 4, (351), (2011).
- M. W. Sears, E. Raskin and M. J. Angilletta, The World Is not Flat: Defining Relevant Thermal Landscapes in the Context of Climate Change, Integrative and Comparative Biology, 51, 5, (666), (2011).
- Marcelo F. Tognelli, Agustín M. Abba, J. Benjamín Bender and Viviana P. Seitz, Assessing conservation priorities of xenarthrans in Argentina, Biodiversity and Conservation, 20, 1, (141), (2011).
- Sarah Bodbyl-Roels, A Townsend Peterson and Xiangming Xiao, Comparative analysis of remotely-sensed data products via ecological niche modeling of avian influenza case occurrences in Middle Eastern poultry, International Journal of Health Geographics, 10, 1, (21), (2011).
- Brooke L. Bateman and Christopher N. Johnson, The influences of climate, habitat and fire on the distribution of cockatoo grass (Alloteropsis semialata) (Poaceae) in the Wet Tropics of northern Australia, Australian Journal of Botany, 10.1071/BT10266, 59, 4, (315), (2011).
- Jennifer R. Seavey, Ben Gilmer and Kevin M. McGarigal, Effect of sea-level rise on piping plover (Charadrius melodus) breeding habitat, Biological Conservation, 10.1016/j.biocon.2010.09.017, 144, 1, (393-401), (2011).
- Jane Elith, Michael Kearney and Steven Phillips, The art of modelling range‐shifting species, Methods in Ecology and Evolution, 1, 4, (330-342), (2010).
- JASON T. BRIED and CELESTE A. MAZZACANO, National review of state wildlife action plans for Odonata species of greatest conservation need, Insect Conservation and Diversity, 3, 2, (61-71), (2010).
- MIRIAN C. DE ALMEIDA, LARA G. CÔRTES and PAULO DE MARCO JÚNIOR, New records and a niche model for the distribution of two Neotropical damselflies: Schistolobos boliviensis and Tuberculobasis inversa (Odonata: Coenagrionidae), Insect Conservation and Diversity, 3, 4, (252-256), (2010).
- JOSE ALEXANDRE F. DINIZ‐FILHO, JOÃO CARLOS NABOUT, LUIS MAURICIO BINI, RAFAEL DIAS LOYOLA, THIAGO FERNANDO RANGEL, DAVID NOGUES‐BRAVO and MIGUEL B. ARAÚJO, Ensemble forecasting shifts in climatically suitable areas for Tropidacris cristata (Orthoptera: Acridoidea: Romaleidae), Insect Conservation and Diversity, 3, 3, (213-221), (2010).
- M. P. Robertson, G. S. Cumming and B. F. N. Erasmus, Getting the most out of atlas data, Diversity and Distributions, 16, 3, (363-375), (2010).
- Benjamin E. Wolfe, Franck Richard, Hugh B. Cross and Anne Pringle, Distribution and abundance of the introduced ectomycorrhizal fungus Amanita phalloides in North America, New Phytologist, 185, 3, (803-816), (2009).
- Diederik Strubbe, Erik Matthysen and Catherine H. Graham, Assessing the potential impact of invasive ring‐necked parakeets Psittacula krameri on native nuthatches Sitta europeae in Belgium, Journal of Applied Ecology, 47, 3, (549-557), (2010).
- Rubén G. Mateo, Thomas B. Croat, Ángel M. Felicísimo and Jesús Muñoz, Profile or group discriminative techniques? Generating reliable species distribution models using pseudo‐absences and target‐group absences from natural history collections, Diversity and Distributions, 16, 1, (84-94), (2009).
- Trent D. Penman, David A. Pike, Jonathan K. Webb and Richard Shine, Predicting the impact of climate change on Australia’s most endangered snake, Hoplocephalus bungaroides, Diversity and Distributions, 16, 1, (109-118), (2009).
- John E. McCormack, Amanda J. Zellmer and L. Lacey Knowles, DOES NICHE DIVERGENCE ACCOMPANY ALLOPATRIC DIVERGENCE IN APHELOCOMA JAYS AS PREDICTED UNDER ECOLOGICAL SPECIATION?: INSIGHTS FROM TESTS WITH NICHE MODELS, Evolution, 64, 5, (1231-1244), (2009).
- Anne Blach‐Overgaard, Jens‐Christian Svenning, John Dransfield, Michelle Greve and Henrik Balslev, Determinants of palm species distributions across Africa: the relative roles of climate, non‐climatic environmental factors, and spatial constraints, Ecography, 33, 2, (380-391), (2010).
- Dan L. Warren, Richard E. Glor and Michael Turelli, ENMTools: a toolbox for comparative studies of environmental niche models, Ecography, 33, 3, (607-611), (2010).
- Colin J. Yates, Asha McNeill, Jane Elith and Guy F. Midgley, Assessing the impacts of climate change and land transformation on Banksia in the South West Australian Floristic Region, Diversity and Distributions, 16, 1, (187-201), (2009).
- Colin M. Beale, Jack J. Lennon, Jon M. Yearsley, Mark J. Brewer and David A. Elston, Regression analysis of spatial data, Ecology Letters, 13, 2, (246-264), (2010).
- Ente Rood, Abdullah A. Ganie and Vincent Nijman, Using presence‐only modelling to predict Asian elephant habitat use in a tropical forest landscape: implications for conservation, Diversity and Distributions, 16, 6, (975-984), (2010).
- Henri A. Thomassen, Wolfgang Buermann, Borja Milá, Catherine H. Graham, Susan E. Cameron, Christopher J. Schneider, John P. Pollinger, Sassan Saatchi, Robert K. Wayne and Thomas B. Smith, Modeling environmentally associated morphological and genetic variation in a rainforest bird, and its application to conservation prioritization, Evolutionary Applications, 3, 1, (1-16), (2009).
- René Wolmarans, Mark P. Robertson and Berndt J. van Rensburg, Predicting invasive alien plant distributions: how geographical bias in occurrence records influences model performance, Journal of Biogeography, 37, 9, (1797-1810), (2010).
- Ashley B. Morris, Catherine H. Graham, Douglas E. Soltis and Pamela S. Soltis, Reassessment of phylogeographical structure in an eastern North American tree using Monmonier’s algorithm and ecological niche modelling, Journal of Biogeography, 37, 9, (1657-1667), (2010).
- Robert P. Anderson and Ali Raza, The effect of the extent of the study region on GIS models of species geographic distributions and estimates of niche evolution: preliminary tests with montane rodents (genus Nephelomys) in Venezuela, Journal of Biogeography, 37, 7, (1378-1393), (2010).
- Catherine H. Graham, Natalia Silva and Jorge Velásquez‐Tibatá, Evaluating the potential causes of range limits of birds of the Colombian Andes, Journal of Biogeography, 37, 10, (1863-1875), (2010).
- Brenton S. Chatfield, Kimberly P. Van Niel, Gary A. Kendrick and Euan S. Harvey, Combining environmental gradients to explain and predict the structure of demersal fish distributions, Journal of Biogeography, 37, 4, (593-605), (2010).
- LUCINDA P. LAWSON, The discordance of diversification: evolution in the tropical‐montane frogs of the Eastern Arc Mountains of Tanzania, Molecular Ecology, 19, 18, (4046-4060), (2010).
- JAVIER A. RODRÍGUEZ‐ROBLES, TEREZA JEZKOVA and MANUEL LEAL, Climatic stability and genetic divergence in the tropical insular lizard Anolis krugi, the Puerto Rican ‘Lagartijo Jardinero de la Montaña’, Molecular Ecology, 19, 9, (1860-1876), (2010).
- Lauren B. Buckley, Mark C. Urban, Michael J. Angilletta, Lisa G. Crozier, Leslie J. Rissler and Michael W. Sears, Can mechanism inform species’ distribution models?, Ecology Letters, 13, 8, (1041-1054), (2010).
- Thiago F. Rangel, Jose Alexandre F. Diniz‐Filho and Luis Mauricio Bini, SAM: a comprehensive application for Spatial Analysis in Macroecology, Ecography, 33, 1, (46-50), (2010).
- Darren J. Kriticos and Agathe Leriche, The effects of climate data precision on fitting and projecting species niche models, Ecography, 33, 1, (115-127), (2010).
- Stephen Hartley, Paul D. Krushelnycky and Philip J. Lester, Integrating physiology, population dynamics and climate to make multi‐scale predictions for the spread of an invasive insect: the Argentine ant at Haleakala National Park, Hawaii, Ecography, 33, 1, (83-94), (2010).
- Jorge M. Lobo, Alberto Jiménez‐Valverde and Joaquín Hortal, The uncertain nature of absences and their importance in species distribution modelling, Ecography, 33, 1, (103-114), (2010).
- Robert J. Wilson, Zoe G. Davies and Chris D. Thomas, Linking habitat use to range expansion rates in fragmented landscapes: a metapopulation approach, Ecography, 33, 1, (73-82), (2010).
- Jorge M. Soberón, Niche and area of distribution modeling: a population ecology perspective, Ecography, 33, 1, (159-167), (2010).
- Janet Franklin, Moving beyond static species distribution models in support of conservation biogeography, Diversity and Distributions, 16, 3, (321-330), (2010).
- T. J. Compton, J. R. Leathwick and G. J. Inglis, Thermogeography predicts the potential global range of the invasive European green crab (Carcinus maenas), Diversity and Distributions, 16, 2, (243-255), (2010).
- Francisca Alba‐Sánchez, José A. López‐Sáez, Blas Benito‐de Pando, Juan C. Linares, Diego Nieto‐Lugilde and Lourdes López‐Merino, Past and present potential distribution of the Iberian Abies species: a phytogeographic approach using fossil pollen data and species distribution models, Diversity and Distributions, 16, 2, (214-228), (2010).
- Miguel Angel Martínez‐Morales, Iriana Zuria, Leonardo Chapa‐Vargas, Ian MacGregor‐Fors, Rubén Ortega‐Álvarez, Edgar Romero‐Águila and Pilar Carbó, BIODIVERSITY RESEARCH: Current distribution and predicted geographic expansion of the Rufous‐backed Robin in Mexico: a fading endemism?, Diversity and Distributions, 16, 5, (786-797), (2010).
- Agustín Estrada‐Peña, Santiago Nava, Ivan G. Horak and Alberto A. Guglielmone, Using ground‐derived data to assess the environmental niche of the spinose ear tick, Otobius megnini, Entomologia Experimentalis et Applicata, 137, 2, (132-142), (2010).
- FRANZISKA TANNEBERGER, MARTIN FLADE, ZYDRUNAS PREIKSA and BORIS SCHRÖDER, Habitat selection of the globally threatened Aquatic Warbler Acrocephalus paludicola at the western margin of its breeding range and implications for management, Ibis, 152, 2, (347-358), (2010).
- X. Y. Wang, X. L. Huang, L. Y. Jiang and G. X. Qiao, Predicting potential distribution of chestnut phylloxerid (Hemiptera: Phylloxeridae) based on GARP and Maxent ecological niche models, Journal of Applied Entomology, 134, 1, (45-54), (2009).
- José J. Lahoz‐Monfort, Gurutzeta Guillera‐Arroita, E. J. Milner‐Gulland, Richard P. Young and Emily Nicholson, Satellite imagery as a single source of predictor variables for habitat suitability modelling: how Landsat can inform the conservation of a critically endangered lemur, Journal of Applied Ecology, 47, 5, (1094-1102), (2010).
- Hugo Rebelo and Gareth Jones, Ground validation of presence‐only modelling with rare species: a case study on barbastelles Barbastella barbastellus (Chiroptera: Vespertilionidae), Journal of Applied Ecology, 47, 2, (410-420), (2010).
- Bette A. Loiselle, Catherine H. Graham, Jaqueline M. Goerck and Milton Cezar Ribeiro, Assessing the impact of deforestation and climate change on the range size and environmental niche of bird species in the Atlantic forests, Brazil, Journal of Biogeography, 37, 7, (1288-1301), (2010).
- Andrés Baselga and Miguel B. Araújo, Do community‐level models describe community variation effectively?, Journal of Biogeography, 37, 10, (1842-1850), (2010).
- Marc Kéry, Beth Gardner and Christian Monnerat, Predicting species distributions from checklist data using site‐occupancy models, Journal of Biogeography, 37, 10, (1851-1862), (2010).
- M.G. Smolik, S. Dullinger, F. Essl, I. Kleinbauer, M. Leitner, J. Peterseil, L.‐M. Stadler and G. Vogl, Integrating species distribution models and interacting particle systems to predict the spread of an invasive alien plant, Journal of Biogeography, 37, 3, (411-422), (2009).
- Kenneth J. Feeley and Miles R. Silman, Modelling the responses of Andean and Amazonian plant species to climate change: the effects of georeferencing errors and the importance of data filtering, Journal of Biogeography, 37, 4, (733-740), (2009).
- ADAM H. FREEDMAN, HENRI A. THOMASSEN, WOLFGANG BUERMANN and THOMAS B. SMITH, Genomic signals of diversification along ecological gradients in a tropical lizard, Molecular Ecology, 19, 17, (3773-3788), (2010).
- L. LACEY KNOWLES and DIEGO F. ALVARADO‐SERRANO, Exploring the population genetic consequences of the colonization process with spatio‐temporally explicit models: insights from coupled ecological, demographic and genetic models in montane grasshoppers, Molecular Ecology, 19, 17, (3727-3745), (2010).
- S. MANEL, B. N. PONCET, P. LEGENDRE, F. GUGERLI and R. HOLDEREGGER, Common factors drive adaptive genetic variation at different spatial scales in Arabis alpina, Molecular Ecology, 19, 17, (3824-3835), (2010).
- VICTORIA L. SORK, FRANK W. DAVIS, ROBERT WESTFALL, ALAN FLINT, MAKIHIKO IKEGAMI, HONGFANG WANG and DELPHINE GRIVET, Gene movement and genetic association with regional climate gradients in California valley oak (Quercus lobata Née) in the face of climate change, Molecular Ecology, 19, 17, (3806-3823), (2010).
- ALICE B. DENNIS and MICHAEL E. HELLBERG, Ecological partitioning among parapatric cryptic species, Molecular Ecology, 19, 15, (3206-3225), (2010).
- JARED G. UNDERWOOD, CATERINA D’AGROSA and LEAH R. GERBER, Identifying Conservation Areas on the Basis of Alternative Distribution Data Sets, Conservation Biology, 24, 1, (162-170), (2009).
- MARC KÉRY, J. ANDREW ROYLE, HANS SCHMID, MICHAEL SCHAUB, BERNARD VOLET, GUIDO HÄFLIGER and NIKLAUS ZBINDEN, Site‐Occupancy Distribution Modeling to Correct Population‐Trend Estimates Derived from Opportunistic Observations, Conservation Biology, 24, 5, (1388-1397), (2010).
- Eric R. Larson, Julian D. Olden and Nisikawa Usio, Decoupled conservatism of Grinnellian and Eltonian niches in an invasive arthropod, Ecosphere, 1, 6, (1-13), (2010).
- Fränzi Korner‐Nievergelt, Annette Sauter, Philip W. Atkinson, Jérôme Guélat, Wojciech Kania, Marc Kéry, Ulrich Köppen, Robert A. Robinson, Michael Schaub, Kasper Thorup, Henk Van Der Jeugd and Arie J. Van Noordwijk, Improving the analysis of movement data from marked individuals through explicit estimation of observer heterogeneity, Journal of Avian Biology, 41, 1, (8-17), (2010).
- M. Arthur Munson, Rich Caruana, Daniel Fink, Wesley M. Hochachka, Marshall Iliff, Kenneth V. Rosenberg, Daniel Sheldon, Brian L. Sullivan, Christopher Wood and Steve Kelling, A method for measuring the relative information content of data from different monitoring protocols, Methods in Ecology and Evolution, 1, 3, (263-273), (2010).
- Denys Yemshanov, Frank H. Koch, Yakov Ben‐Haim and William D. Smith, Robustness of Risk Maps and Survey Networks to Knowledge Gaps About a New Invasive Pest, Risk Analysis, 30, 2, (261-276), (2009).
- J. NICOLÁS URBINA‐CARDONA and OSCAR FLORES‐VILLELA, Ecological‐Niche Modeling and Prioritization of Conservation‐Area Networks for Mexican Herpetofauna, Conservation Biology, 24, 4, (1031-1041), (2010).
- LJILJANA TOMOVIĆ, JELKA CRNOBRNJA‐ISAILOVIĆ and JOSÉ CARLOS BRITO, The use of geostatistics and GIS for evolutionary history studies: the case of the nose‐horned viper (Vipera ammodytes) in the Balkan Peninsula, Biological Journal of the Linnean Society, 101, 3, (651-666), (2010).
- PAUL GIOIA, Managing biodiversity data within the context of climate change: towards best practice, Austral Ecology, 35, 4, (392-405), (2009).
- JASON M. EVANS, ROBERT J. FLETCHER and JANAKI ALAVALAPATI, Using species distribution models to identify suitable areas for biofuel feedstock production, GCB Bioenergy, 2, 2, (63-78), (2010).
- Gabriel C. Costa and Ingo Schlupp, Biogeography of the Amazon molly: ecological niche and range limits of an asexual hybrid species, Global Ecology and Biogeography, 19, 4, (442-451), (2010).
- Alexandra D. Syphard and Janet Franklin, Species traits affect the performance of species distribution models for plants in southern California, Journal of Vegetation Science, 21, 1, (177-189), (2009).
- Lauren B. Buckley, The range implications of lizard traits in changing environments, Global Ecology and Biogeography, 19, 4, (452-464), (2010).
- Qinghua Guo and Yu Liu, ModEco: an integrated software package for ecological niche modeling, Ecography, 33, 4, (637-642), (2010).
- Rodrigo Vega, Camilla Fløjgaard, Andrés Lira‐Noriega, Yoshinori Nakazawa, Jens‐Christian Svenning and Jeremy B. Searle, Northern glacial refugia for the pygmy shrew Sorex minutus in Europe revealed by phylogeographic analyses and species distribution modelling, Ecography, 33, 2, (260-271), (2010).
- Isabel Marques, Gonzalo Nieto Feliner, David Draper Munt, Maria Amélia Martins‐Loução and Javier Fuertes Aguilar, UNRAVELING CRYPTIC RETICULATE RELATIONSHIPS AND THE ORIGIN OF ORPHAN HYBRID DISJUNCT POPULATIONS IN NARCISSUS, Evolution, 64, 8, (2353-2368), (2010).
- CARLOS DANIEL CADENA and ANDRÉS M. CUERVO, Molecules, ecology, morphology, and songs in concert: how many species is Arremon torquatus (Aves: Emberizidae)?, Biological Journal of the Linnean Society, 99, 1, (152-176), (2009).
- Kim A. Medley, Niche shifts during the global invasion of the Asian tiger mosquito, Aedes albopictus Skuse (Culicidae), revealed by reciprocal distribution models, Global Ecology and Biogeography, 19, 1, (122-133), (2009).
- Daniel S. Chapman, Weak climatic associations among British plant distributions, Global Ecology and Biogeography, 19, 6, (831-841), (2010).
- José Alexandre Felizola Diniz‐Filho, Levi Carina Terribile, Mary Joice Ribeiro da Cruz and Ludgero Cardoso G. Vieira, Hidden patterns of phylogenetic non‐stationarity overwhelm comparative analyses of niche conservatism and divergence, Global Ecology and Biogeography, 19, 6, (916-926), (2010).
- Peter B. Pearman, Manuela D'Amen, Catherine H. Graham, Wilfried Thuiller and Niklaus E. Zimmermann, Within‐taxon niche structure: niche conservatism, divergence and predicted effects of climate change, Ecography, 33, 6, (990-1003), (2010).
- Niklaus E. Zimmermann, Thomas C. Edwards, Catherine H. Graham, Peter B. Pearman and Jens‐Christian Svenning, New trends in species distribution modelling, Ecography, 33, 6, (985-989), (2010).
- LAËTITIA BUISSON, WILFRIED THUILLER, NICOLAS CASAJUS, SOVAN LEK and GAËL GRENOUILLET, Uncertainty in ensemble forecasting of species distribution, Global Change Biology, 16, 4, (1145-1157), (2009).
- CARLOS CARROLL, JEFFREY R. DUNK and ATTE MOILANEN, Optimizing resiliency of reserve networks to climate change: multispecies conservation planning in the Pacific Northwest, USA, Global Change Biology, 16, 3, (891-904), (2009).
- Graham H. Pyke and Paul R. Ehrlich, Biological collections and ecological/environmental research: a review, some observations and a look to the future, Biological Reviews, 85, 2, (247-266), (2009).
- Tim Newbold, Tom Reader, Ahmed El‐Gabbas, Wiebke Berg, Wael M. Shohdi, Samy Zalat, Sherif Baha El Din and Francis Gilbert, Testing the accuracy of species distribution models using species records from a new field survey, Oikos, 119, 8, (1326-1334), (2010).
- Eliane S. Meier, Felix Kienast, Peter B. Pearman, Jens‐Christian Svenning, Wilfried Thuiller, Miguel B. Araújo, Antoine Guisan and Niklaus E. Zimmermann, Biotic and abiotic variables show little redundancy in explaining tree species distributions, Ecography, 33, 6, (1038-1048), (2010).
- Gwenaëlle Le Lay, Robin Engler, Erika Franc and Antoine Guisan, Prospective sampling based on model ensembles improves the detection of rare species, Ecography, 33, 6, (1015-1027), (2010).
- Jens‐Christian Svenning, Matthew C. Fitzpatrick, Signe Normand, Catherine H. Graham, Peter B. Pearman, Louis R. Iverson and Flemming Skov, Geography, topography, and history affect realized‐to‐potential tree species richness patterns in Europe, Ecography, 33, 6, (1070-1080), (2010).
- Veronika Braunisch and Rudi Suchant, Predicting species distributions based on incomplete survey data: the trade‐off between precision and scale, Ecography, 33, 5, (826-840), (2010).
- ANTONIO TRABUCCO, WOUTER M. J. ACHTEN, COLM BOWE, RAF AERTS, JOS VAN ORSHOVEN, LINDSEY NORGROVE and BART MUYS, Global mapping of Jatropha curcas yield based on response of fitness to present and future climate, GCB Bioenergy, 2, 3, (139-151), (2010).
- Susi M. C. Edrén, Mary S. Wisz, Jonas Teilmann, Rune Dietz and Johan Söderkvist, Modelling spatial patterns in harbour porpoise satellite telemetry data using maximum entropy, Ecography, 33, 4, (698-708), (2010).
- Justin D. Hoffman, Naikoa Aguilar‐Amuchastegui and Andrew J. Tyre, Use of simulated data from a process‐based habitat model to evaluate methods for predicting species occurrence, Ecography, 33, 4, (656-666), (2010).
- WOUTER BEUKEMA, PHILIP DE POUS, DAVID DONAIRE, DANIEL ESCORIZA, SERGE BOGAERTS, ALBERTUS G. TOXOPEUS, CORNELIS A. J. M. DE BIE, JOSEP ROCA and SALVADOR CARRANZA, Biogeography and contemporary climatic differentiation among Moroccan Salamandra algira, Biological Journal of the Linnean Society, 101, 3, (626-641), (2010).
- JAN CHRISTIAN HABEL, DENNIS RÖDDER, SCALERCIO STEFANO, MARC MEYER and THOMAS SCHMITT, Strong genetic cohesiveness between Italy and North Africa in four butterfly species, Biological Journal of the Linnean Society, 99, 4, (818-830), (2010).
- GENTILE FRANCESCO FICETOLA, LUIGI MAIORANO, ALESSANDRA FALCUCCI, NICOLAS DENDONCKER, LUIGI BOITANI, EMILIO PADOA‐SCHIOPPA, CLAUDE MIAUD and WILFRIED THUILLER, Knowing the past to predict the future: land‐use change and the distribution of invasive bullfrogs, Global Change Biology, 16, 2, (528-537), (2009).
- HUGO REBELO, PEDRO TARROSO and GARETH JONES, Predicted impact of climate change on European bats in relation to their biogeographic patterns, Global Change Biology, 16, 2, (561-576), (2009).
- SÍLVIA B. CARVALHO, JOSÉ C. BRITO, EDUARDO J. CRESPO and HUGH P. POSSINGHAM, From climate change predictions to actions – conserving vulnerable animal groups in hotspots at a regional scale, Global Change Biology, 16, 12, (3257-3270), (2010).
- CARLOS CARROLL, DEVIN S. JOHNSON, JEFFREY R. DUNK and WILLIAM J. ZIELINSKI, Hierarchical Bayesian Spatial Models for Multispecies Conservation Planning and Monitoring, Conservation Biology, 24, 6, (1538-1548), (2010).
- J. Hu and Z. Jiang, Predicting the potential distribution of the endangered Przewalski's gazelle, Journal of Zoology, 282, 1, (54-63), (2010).
- Rubén G. Mateo, Ángel M. Felicísimo and Jesús Muñoz, Effects of the number of presences on reliability and stability of MARS species distribution models: the importance of regional niche variation and ecological heterogeneity, Journal of Vegetation Science, 21, 5, (908-922), (2010).
- A. Lomba, L. Pellissier, C. Randin, J. Vicente, F. Moreira, J. Honrado and A. Guisan, Overcoming the rare species modelling paradox: A novel hierarchical framework applied to an Iberian endemic plant, Biological Conservation, 10.1016/j.biocon.2010.07.007, 143, 11, (2647-2657), (2010).
- Gemma Siles, Julio M. Alcántara, Pedro J. Rey and Jesús M. Bastida, Defining a Target Map of Native Species Assemblages for Restoration, Restoration Ecology, 18, 4, (439-448), (2008).
- Simon M. Smart, W. Andrew Scott, Jeanette Whitaker, Mark O. Hill, David B. Roy, C. Nigel Critchley, Lorenzo Marini, Christopher Evans, Bridget A. Emmett, Edwin C. Rowe, Andrew Crowe, Mike Le Duc and Robert H. Marrs, Empirical realised niche models for British higher and lower plants – development and preliminary testing, Journal of Vegetation Science, 21, 4, (643-656), (2010).
- COLIN J. YATES, JANE ELITH, ANDREW M. LATIMER, DAVID LE MAITRE, GUY F. MIDGLEY, FRANK M. SCHURR and ADAM G. WEST, Projecting climate change impacts on species distributions in megadiverse South African Cape and Southwest Australian Floristic Regions: Opportunities and challenges, Austral Ecology, 35, 4, (374-391), (2009).
- M. De Meyer, M.P. Robertson, M.W. Mansell, S. Ekesi, K. Tsuruta, W. Mwaiko, J-F Vayssières and A.T. Peterson, Ecological niche and potential geographic distribution of the invasive fruit fly Bactrocera invadens (Diptera, Tephritidae), Bulletin of Entomological Research, 100, 01, (35), (2010).
- Takuya Iwamura, Kerrie A. Wilson, Oscar Venter, Hugh P. Possingham and Brian Gratwicke, A Climatic Stability Approach to Prioritizing Global Conservation Investments, PLoS ONE, 5, 11, (e15103), (2010).
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- Alexander Gavashelishvili and Zura Javakhishvili, Combining radio-telemetry and random observations to model the habitat of Near Threatened Caucasian grouse Tetrao mlokosiewiczi, Oryx, 44, 04, (491), (2010).
- Catherine S. Jarnevich, Tracy R. Holcombe, David T. Barnett, Thomas J. Stohlgren and John T. Kartesz, Forecasting Weed Distributions using Climate Data: A GIS Early Warning Tool, Invasive Plant Science and Management, 3, 04, (365), (2010).
- Sarah E. Randolph and David J. Rogers, The arrival, establishment and spread of exotic diseases: patterns and predictions, Nature Reviews Microbiology, 10.1038/nrmicro2336, 8, 5, (361-371), (2010).
- Katia Maria Paschoaletto Micchi de Barros Ferraz, Marinez Ferreira de Siqueira, Paula Sanches Martin, Carolina Franco Esteves and Hilton Thadeu Zarate do Couto, Assessment of Cerdocyon thous distribution in an agricultural mosaic, southeastern Brazil, mammalia, 74, 3, (2010).
- Jonathan Ready, Kristin Kaschner, Andy B. South, Paul D. Eastwood, Tony Rees, Josephine Rius, Eli Agbayani, Sven Kullander and Rainer Froese, Predicting the distributions of marine organisms at the global scale, Ecological Modelling, 221, 3, (467), (2010).
- Alistair J. Hobday, Ensemble analysis of the future distribution of large pelagic fishes off Australia, Progress in Oceanography, 86, 1-2, (291), (2010).
- F. Thomas Ledig, Gerald E. Rehfeldt, Cuauhtémoc Sáenz‐Romero and Celestino Flores‐López, Projections of suitable habitat for rare species under global warming scenarios, American Journal of Botany, 97, 6, (970-987), (2010).
- K. G. Ross, D. Gotzek, M. S. Ascunce and D. D. Shoemaker, Species Delimitation: A Case Study in a Problematic Ant Taxon, Systematic Biology, 59, 2, (162), (2010).
- Wenkai Li and Qinghua Guo, A maximum entropy approach to one-class classification of remote sensing imagery, International Journal of Remote Sensing, 10.1080/01431161003702245, 31, 8, (2227-2235), (2010).
- Heather M. Kharouba and Jeremy T. Kerr, Just passing through: Global change and the conservation of biodiversity in protected areas, Biological Conservation, 143, 5, (1094), (2010).
- W. Godsoe, Regional Variation Exaggerates Ecological Divergence in Niche Models, Systematic Biology, 59, 3, (298), (2010).
- S. A. Schaefer and J. Arroyave, Rivers as islands: determinants of the distribution of Andean astroblepid catfishes, Journal of Fish Biology, 77, 10, (2373-2390), (2010).
- Mauro F. Carrasco and Pedro J. Barón, Analysis of the potential geographic range of the Pacific oyster Crassostrea gigas (Thunberg, 1793) based on surface seawater temperature satellite data and climate charts: the coast of South America as a study case, Biological Invasions, 10.1007/s10530-009-9668-0, 12, 8, (2597-2607), (2009).
- David Ainley, Joellen Russell, Stephanie Jenouvrier, Eric Woehler, Philip O'B. Lyver, William R. Fraser and Gerald L. Kooyman, Antarctic penguin response to habitat change as Earth's troposphere reaches 2°C above preindustrial levels, Ecological Monographs, 80, 1, (49-66), (2010).
- J. Bielby, M. Cardillo, N. Cooper and A. Purvis, Modelling extinction risk in multispecies data sets: phylogenetically independent contrasts versus decision trees, Biodiversity and Conservation, 10.1007/s10531-009-9709-0, 19, 1, (113-127), (2009).
- Andrés Viña, Mao-Ning Tuanmu, Weihua Xu, Yu Li, Zhiyun Ouyang, Ruth DeFries and Jianguo Liu, Range-wide analysis of wildlife habitat: Implications for conservation, Biological Conservation, 10.1016/j.biocon.2010.04.046, 143, 9, (1960-1969), (2010).
- Rodrigo W. Soria-Auza, Michael Kessler, Kerstin Bach, Paola M. Barajas-Barbosa, Marcus Lehnert, Sebastian K. Herzog and Jürgen Böhner, Impact of the quality of climate models for modelling species occurrences in countries with poor climatic documentation: a case study from Bolivia, Ecological Modelling, 10.1016/j.ecolmodel.2010.01.004, 221, 8, (1221-1229), (2010).
- K. E. Parks and M. Mulligan, On the relationship between a resource based measure of geodiversity and broad scale biodiversity patterns, Biodiversity and Conservation, 10.1007/s10531-010-9876-z, 19, 9, (2751-2766), (2010).
- Klaas Pauly and Olivier De Clerck, GIS-Based Environmental Analysis, Remote Sensing, and Niche Modeling of Seaweed Communities, Seaweeds and their Role in Globally Changing Environments, 10.1007/978-90-481-8569-6_6, (93-114), (2010).
- Jan C. Habel, Bettina Augenstein, Marc Meyer, Gabriel Nève, Dennis Rödder and Thorsten Assmann, Population Genetics and Ecological Niche Modelling Reveal High Fragmentation and Potential Future Extinction of the Endangered Relict Butterfly Lycaena helle, Relict Species, 10.1007/978-3-540-92160-8_25, (417-439), (2009).
- Oriol Grau, Pasi Rautio, Juliana Heikkinen, Karita Saravesi, Mikhail V. Kozlov and Annamari Markkola, An ericoid shrub plays a dual role in recruiting both pines and their fungal symbionts along primary succession gradients, Oikos, 119, 11, (1727-1734), (2010).
- Cristina Sazima, Paulo R. Guimarães, Sérgio F. Dos Reis and Ivan Sazima, What makes a species central in a cleaning mutualism network?, Oikos, 119, 8, (1319-1325), (2010).
- Masahiro Nakamura, Miho Asanuma and Tsutom Hiura, Differential effects of host plant hybridization on herbivore community structure and grazing pressure on forest canopies, Oikos, 119, 9, (1445-1452), (2010).
- Attila Hettyey, Szilvia Zsarnóczai, Krisztina Vincze, Herbert Hoi and Anssi Laurila, Interactions between the information content of different chemical cues affect induced defences in tadpoles, Oikos, 119, 11, (1814-1822), (2010).
- Carolina Cavalieri Gomes, Alessandra Pires Duarte, Marina Gonçalves Diniz and Ricardo Santiago Gomez, REVIEW ARTICLE: Current concepts of ameloblastoma pathogenesis, Journal of Oral Pathology & Medicine, 39, 8, (585-591), (2010).
- Vivyan Lisewski and Christopher J. Ellis, Epiphyte sensitivity to a cross-scale interaction between habitat quality and macroclimate: an opportunity for range-edge conservation, Biodiversity and Conservation, 10.1007/s10531-010-9938-2, 19, 14, (3935-3949), (2010).
- Troy M. Hegel, Samuel A. Cushman, Jeffrey Evans and Falk Huettmann, Current State of the Art for Statistical Modelling of Species Distributions, Spatial Complexity, Informatics, and Wildlife Conservation, 10.1007/978-4-431-87771-4_16, (273-311), (2010).
- Dawn Robin Magness, John M. Morton and Falk Huettmann, How Spatial Information Contributes to the Conservation and Management of Biodiversity, Spatial Complexity, Informatics, and Wildlife Conservation, 10.1007/978-4-431-87771-4_23, (429-444), (2010).
- Steffen Oppel and Falk Huettmann, Using a Random Forest Model and Public Data to Predict the Distribution of Prey for Marine Wildlife Management, Spatial Complexity, Informatics, and Wildlife Conservation, 10.1007/978-4-431-87771-4_8, (151-163), (2010).
- Jennifer A. Miller and Janet Franklin, Incorporating Spatial Autocorrelation in Species Distribution Models, Handbook of Applied Spatial Analysis, 10.1007/978-3-642-03647-7_32, (685-702), (2009).
- Michael P. Nobis, Jochen A. G. Jaeger and Niklaus E. Zimmermann, Neophyte species richness at the landscape scale under urban sprawl and climate warming, Diversity and Distributions, 15, 6, (928-939), (2009).
- John N. Williams, Changwan Seo, James Thorne, Julie K. Nelson, Susan Erwin, Joshua M. O’Brien and Mark W. Schwartz, Using species distribution models to predict new occurrences for rare plants, Diversity and Distributions, 15, 4, (565-576), (2009).
- Margaret E. Andrew and Susan L. Ustin, Habitat suitability modelling of an invasive plant with advanced remote sensing data, Diversity and Distributions, 15, 4, (627-640), (2009).
- Patrick E. Osborne and Pedro J. Leitão, Effects of species and habitat positional errors on the performance and interpretation of species distribution models, Diversity and Distributions, 15, 4, (671-681), (2009).
- William Godsoe, Eva Strand, Christopher Irwin Smith, Jeremy B. Yoder, Todd C. Esque and Olle Pellmyr, Divergence in an obligate mutualism is not explained by divergent climatic factors, New Phytologist, 183, 3, (589-599), (2009).
- David G. Hole, Stephen G. Willis, Deborah J. Pain, Lincoln D. Fishpool, Stuart H. M. Butchart, Yvonne C. Collingham, Carsten Rahbek and Brian Huntley, Projected impacts of climate change on a continent‐wide protected area network, Ecology Letters, 12, 5, (420-431), (2009).
- Janet Franklin, Katherine E. Wejnert, Stacie A. Hathaway, Carlton J. Rochester and Robert N. Fisher, Effect of species rarity on the accuracy of species distribution models for reptiles and amphibians in southern California, Diversity and Distributions, 15, 1, (167-177), (2008).
- Mathieu Marmion, Miia Parviainen, Miska Luoto, Risto K. Heikkinen and Wilfried Thuiller, Evaluation of consensus methods in predictive species distribution modelling, Diversity and Distributions, 15, 1, (59-69), (2008).
- Llewellyn C. Foxcroft, David M. Richardson, Mathieu Rouget and Sandra MacFadyen, Patterns of alien plant distribution at multiple spatial scales in a large national park: implications for ecology, management and monitoring, Diversity and Distributions, 15, 3, (367-378), (2008).
- Ismael A. Hinojosa‐Díaz, Teresa P. Feria‐Arroyo and Michael S. Engel, Potential distribution of orchid bees outside their native range: The cases of Eulaema polychroma (Mocsáry) and Euglossa viridissima Friese in the USA (Hymenoptera: Apidae), Diversity and Distributions, 15, 3, (421-428), (2008).
- Robert Puschendorf, Ana C. Carnaval, Jeremy VanDerWal, Héctor Zumbado‐Ulate, Gerardo Chaves, Federico Bolaños and Ross A. Alford, Distribution models for the amphibian chytrid Batrachochytrium dendrobatidis in Costa Rica: proposing climatic refuges as a conservation tool, Diversity and Distributions, 15, 3, (401-408), (2009).
- BARBARA J. ANDERSON, YIXUAN BAI, CHRIS D. THOMAS and GEOFF S. OXFORD, Predicting range overlap in two closely related species of spiders, Insect Conservation and Diversity, 2, 2, (135-141), (2009).
- S. B. Menke, D. A. Holway, R. N. Fisher and W. Jetz, Characterizing and predicting species distributions across environments and scales: Argentine ant occurrences in the eye of the beholder, Global Ecology and Biogeography, 18, 1, (50-63), (2008).
- Aaron D. Gove, Matthew C. Fitzpatrick, Jonathan D. Majer and Robert R. Dunn, Dispersal traits linked to range size through range location, not dispersal ability, in Western Australian angiosperms, Global Ecology and Biogeography, 18, 5, (596-606), (2009).
- ADNAN MOUSSALLI, CRAIG MORITZ, STEPHEN E. WILLIAMS and ANA C. CARNAVAL, Variable responses of skinks to a common history of rainforest fluctuation: concordance between phylogeography and palaeo‐distribution models, Molecular Ecology, 18, 3, (483-499), (2009).
- M. CORDELLIER and M. PFENNINGER, Inferring the past to predict the future: climate modelling predictions and phylogeography for the freshwater gastropod Radix balthica (Pulmonata, Basommatophora), Molecular Ecology, 18, 3, (534-544), (2009).
- Erin C. Riordan and Philip W. Rundel, Modelling the distribution of a threatened habitat: the California sage scrub, Journal of Biogeography, 36, 11, (2176-2188), (2009).
- Tim Newbold, Francis Gilbert, Samy Zalat, Ahmed El‐Gabbas and Tom Reader, Climate‐based models of spatial patterns of species richness in Egypt’s butterfly and mammal fauna, Journal of Biogeography, 36, 11, (2085-2095), (2009).
- Michael Kearney and Warren Porter, Mechanistic niche modelling: combining physiological and spatial data to predict species’ ranges, Ecology Letters, 12, 4, (334-350), (2009).
- Nicholas J. Gotelli, Marti J. Anderson, Hector T. Arita, Anne Chao, Robert K. Colwell, Sean R. Connolly, David J. Currie, Robert R. Dunn, Gary R. Graves, Jessica L. Green, John‐Arvid Grytnes, Yi‐Huei Jiang, Walter Jetz, S. Kathleen Lyons, Christy M. McCain, Anne E. Magurran, Carsten Rahbek, Thiago F.L.V.B. Rangel, Jorge Soberón, Campbell O. Webb and Michael R. Willig, Patterns and causes of species richness: a general simulation model for macroecology, Ecology Letters, 12, 9, (873-886), (2009).
- Thomas Hickler, Stefan Fronzek, Miguel B. Araújo, Oliver Schweiger, Wilfried Thuiller and Martin T. Sykes, An ecosystem model‐based estimate of changes in water availability differs from water proxies that are commonly used in species distribution models, Global Ecology and Biogeography, 18, 3, (304-313), (2009).
- Heroen Verbruggen, Lennert Tyberghein, Klaas Pauly, Caroline Vlaeminck, Katrien Van Nieuwenhuyze, Wiebe H.C.F. Kooistra, Frederik Leliaert and Olivier De Clerck, Macroecology meets macroevolution: evolutionary niche dynamics in the seaweed Halimeda, Global Ecology and Biogeography, 18, 4, (393-405), (2009).
- Leif‐Matthias Herborg, Patrick O’Hara and Thomas W. Therriault, Forecasting the potential distribution of the invasive tunicate Didemnum vexillum, Journal of Applied Ecology, 46, 1, (64-72), (2008).
- Rebecca A. Bartel and Joseph O. Sexton, Monitoring habitat dynamics for rare and endangered species using satellite images and niche‐based models, Ecography, 32, 5, (888-896), (2009).
- Linda J. Beaumont, Rachael V. Gallagher, Paul O. Downey, Wilfried Thuiller, Michelle R. Leishman and Lesley Hughes, Modelling the impact of Hieracium spp. on protected areas in Australia under future climates, Ecography, 32, 5, (757-764), (2009).
- Jane Elith and Catherine H. Graham, Do they? How do they? WHY do they differ? On finding reasons for differing performances of species distribution models, Ecography, 32, 1, (66-77), (2009).
- Heather R. Cunningham, Leslie J. Rissler and Joseph J. Apodaca, Competition at the range boundary in the slimy salamander: using reciprocal transplants for studies on the role of biotic interactions in spatial distributions, Journal of Animal Ecology, 78, 1, (52-62), (2008).
- Stefan Heinänen and Mikael Von Numers, Modelling species distribution in complex environments: an evaluation of predictive ability and reliability in five shorebird species, Diversity and Distributions, 15, 2, (266-279), (2008).
- J. S. Thorn, V. Nijman, D. Smith and K. A. I. Nekaris, Ecological niche modelling as a technique for assessing threats and setting conservation priorities for Asian slow lorises (Primates: Nycticebus), Diversity and Distributions, 15, 2, (289-298), (2008).
- Linda J. Beaumont, Rachael V. Gallagher, Wilfried Thuiller, Paul O. Downey, Michelle R. Leishman and Lesley Hughes, Different climatic envelopes among invasive populations may lead to underestimations of current and future biological invasions, Diversity and Distributions, 15, 3, (409-420), (2009).
- Gentile Francesco Ficetola, Wilfried Thuiller and Emilio Padoa‐Schioppa, From introduction to the establishment of alien species: bioclimatic differences between presence and reproduction localities in the slider turtle, Diversity and Distributions, 15, 1, (108-116), (2008).
- R. ALEXANDER PYRON and FRANK T. BURBRINK, Lineage diversification in a widespread species: roles for niche divergence and conservatism in the common kingsnake, Lampropeltis getula, Molecular Ecology, 18, 16, (3443-3457), (2009).
- Andrés Baselga and Miguel B. Araújo, Individualistic vs community modelling of species distributions under climate change, Ecography, 32, 1, (55-65), (2009).
- Adam C. Algar, Heather M. Kharouba, Eric R. Young and Jeremy T. Kerr, Predicting the future of species diversity: macroecological theory, climate change, and direct tests of alternative forecasting methods, Ecography, 32, 1, (22-33), (2009).
- Tom Oliver, Jane K. Hill, Chris D. Thomas, Tom Brereton and David B. Roy, Changes in habitat specificity of species at their climatic range boundaries, Ecology Letters, 12, 10, (1091-1102), (2009).
- Inger Greve Alsos, Torbjørn Alm, Signe Normand and Christian Brochmann, Past and future range shifts and loss of diversity in dwarf willow (Salix herbacea L.) inferred from genetics, fossils and modelling, Global Ecology and Biogeography, 18, 2, (223-239), (2008).
- MIGUEL ÂNGELO MARINI, MORGANE BARBET‐MASSIN, LEONARDO ESTEVES LOPES and FRÉDÉRIC JIGUET, Predicted Climate‐Driven Bird Distribution Changes and Forecasted Conservation Conflicts in a Neotropical Savanna, Conservation Biology, 23, 6, (1558-1567), (2009).
- Erik P. Willems and Russell A. Hill, A critical assessment of two species distribution models: a case study of the vervet monkey (Cercopithecus aethiops), Journal of Biogeography, 36, 12, (2300-2312), (2009).
- Samuel D. Veloz, Spatially autocorrelated sampling falsely inflates measures of accuracy for presence‐only niche models, Journal of Biogeography, 36, 12, (2290-2299), (2009).
- Camilla Fløjgaard, Signe Normand, Flemming Skov and Jens‐Christian Svenning, Ice age distributions of European small mammals: insights from species distribution modelling, Journal of Biogeography, 36, 6, (1152-1163), (2009).
- Derek P. Tittensor, Amy R. Baco, Paul E. Brewin, Malcolm R. Clark, Mireille Consalvey, Jason Hall‐Spencer, Ashley A. Rowden, Thomas Schlacher, Karen I. Stocks and Alex D. Rogers, Predicting global habitat suitability for stony corals on seamounts, Journal of Biogeography, 36, 6, (1111-1128), (2009).
- TERESA P. FERIA ARROYO, MARK E. OLSON, ABISAÍ GARCÍA‐MENDOZA and ELOY SOLANO, A GIS‐Based Comparison of the Mexican National and IUCN Methods for Determining Extinction Risk, Conservation Biology, 23, 5, (1156-1166), (2009).
- Jeremy VanDerWal, Luke P. Shoo and Stephen E. Williams, New approaches to understanding late Quaternary climate fluctuations and refugial dynamics in Australian wet tropical rain forests, Journal of Biogeography, 36, 2, (291-301), (2008).
- Hedley S. Grantham, Kerrie A. Wilson, Atte Moilanen, Tony Rebelo and Hugh P. Possingham, Delaying conservation actions for improved knowledge: how long should we wait?, Ecology Letters, 12, 4, (293-301), (2009).
- CHARLOTTE MURRAY‐SMITH, NEIL A. BRUMMITT, ARY T. OLIVEIRA‐FILHO, STEVEN BACHMAN, JUSTIN MOAT, EIMEAR M. NIC LUGHADHA and EVE J. LUCAS, Plant Diversity Hotspots in the Atlantic Coastal Forests of Brazil, Conservation Biology, 23, 1, (151-163), (2008).
- Niels Raes, Marco C. Roos, J. W. Ferry Slik, E. Emiel Van Loon and Hans ter Steege, Botanical richness and endemicity patterns of Borneo derived from species distribution models, Ecography, 32, 1, (180-192), (2009).
- BETHANY A. BRADLEY, Regional analysis of the impacts of climate change on cheatgrass invasion shows potential risk and opportunity, Global Change Biology, 15, 1, (196-208), (2008).
- Sunil Kumar, Sarah A Spaulding, Thomas J Stohlgren, Karl A Hermann, Travis S Schmidt and Loren L Bahls, Potential habitat distribution for the freshwater diatom Didymosphenia geminata in the continental US, Frontiers in Ecology and the Environment, 7, 8, (415-420), (2008).
- ESTHER S. RUBIN, CHRIS J. STERMER, WALTER M. BOYCE and STEVEN G. TORRES, Assessment of Predictive Habitat Models for Bighorn Sheep in California's Peninsular Ranges, The Journal of Wildlife Management, 73, 6, (859-869), (2010).
- G. H. Wilson, K. Mcdonald and M. J. O'Connell, Skeletal forelimb measurements and hoof spread in relation to asymmetry in the bilateral forelimb of horses, Equine Veterinary Journal, 41, 3, (238-241), (2010).
- Dennis Rödder and Stefan Lötters, Niche shift versus niche conservatism? Climatic characteristics of the native and invasive ranges of the Mediterranean house gecko (Hemidactylus turcicus), Global Ecology and Biogeography, 18, 6, (674-687), (2009).
- Bernard W. T. Coetzee, Mark P. Robertson, Barend F. N. Erasmus, Berndt J. Van Rensburg and Wilfried Thuiller, Ensemble models predict Important Bird Areas in southern Africa will become less effective for conserving endemic birds under climate change, Global Ecology and Biogeography, 18, 6, (701-710), (2009).
- STACEY I. JAREMA, JASON SAMSON, BRIAN J. MCGILL and MURRAY M. HUMPHRIES, Variation in abundance across a species' range predicts climate change responses in the range interior will exceed those at the edge: a case study with North American beaver, Global Change Biology, 15, 2, (508-522), (2008).
- M. A. Sepúlveda, J. L. Bartheld, C. Meynard, M. Benavides, C. Astorga, D. Parra and G. Medina‐Vogel, Landscape features and crustacean prey as predictors of the Southern river otter distribution in Chile., Animal Conservation, 12, 6, (522-530), (2009).
- MICHAEL J. JACOBS and HUGH J. MACISAAC, Modelling spread of the invasive macrophyte Cabomba caroliniana, Freshwater Biology, 54, 2, (296-305), (2008).
- Eduardo Pineda and Jorge M. Lobo, Assessing the accuracy of species distribution models to predict amphibian species richness patterns, Journal of Animal Ecology, 78, 1, (182-190), (2008).
- Gill Ward, Trevor Hastie, Simon Barry, Jane Elith and John R. Leathwick, Presence‐Only Data and the EM Algorithm, Biometrics, 65, 2, (554-563), (2008).
- José Alexandre F. Diniz‐Filho, Luis Mauricio Bini, Thiago Fernando Rangel, Rafael D. Loyola, Christian Hof, David Nogués‐Bravo and Miguel B. Araújo, Partitioning and mapping uncertainties in ensembles of forecasts of species turnover under climate change, Ecography, 32, 6, (897-906), (2009).
- Alexandra D. Syphard and Janet Franklin, Differences in spatial predictions among species distribution modeling methods vary with species traits and environmental predictors, Ecography, 32, 6, (907-918), (2009).
- ADAM H. FREEDMAN, WOLFGANG BUERMANN, MATTHEW LEBRETON, LAURENT CHIRIO and THOMAS B. SMITH, Modeling the Effects of Anthropogenic Habitat Change on Savanna Snake Invasions into African Rainforest, Conservation Biology, 23, 1, (81-92), (2008).
- Wilfried Thuiller, Bruno Lafourcade, Robin Engler and Miguel B. Araújo, BIOMOD – a platform for ensemble forecasting of species distributions, Ecography, 32, 3, (369-373), (2009).
- B. Gebremedhin, G. F. Ficetola, S. Naderi, H.‐R. Rezaei, C. Maudet, D. Rioux, G. Luikart, Ø. Flagstad, W. Thuiller and P. Taberlet, Combining genetic and ecological data to assess the conservation status of the endangered Ethiopian walia ibex, Animal Conservation, 12, 2, (89-100), (2009).
- J. MURIENNE, E. GUILBERT and P. GRANDCOLAS, Species' diversity in the New Caledonian endemic genera Cephalidiosus and Nobarnus (Insecta: Heteroptera: Tingidae), an approach using phylogeny and species' distribution modelling, Biological Journal of the Linnean Society, 97, 1, (177-184), (2009).
- Rieks D. Van Klinken, Ben E. Lawson and Myron P. Zalucki, Predicting invasions in Australia by a Neotropical shrub under climate change: the challenge of novel climates and parameter estimation, Global Ecology and Biogeography, 18, 6, (688-700), (2009).
- Michael P. Austin, Thomas M. Smith, Kimberley P. Van Niel and A. Bruce. Wellington, Physiological responses and statistical models of the environmental niche: a comparative study of two co‐occurring Eucalyptus species, Journal of Ecology, 97, 3, (496-507), (2009).
- L.E. Ritchie, M.G. Betts, G. Forbes and K. Vernes, Effects of landscape composition and configuration on northern flying squirrels in a forest mosaic, Forest Ecology and Management, 10.1016/j.foreco.2009.01.028, 257, 9, (1920-1929), (2009).
- Rut Sánchez de Dios, Marta Benito-Garzón and Helios Sainz-Ollero, Present and future extension of the Iberian submediterranean territories as determined from the distribution of marcescent oaks, Plant Ecology, 10.1007/s11258-009-9584-5, 204, 2, (189-205), (2009).
- Mathieu Marmion, Jan Hjort, Wilfried Thuiller and Miska Luoto, Statistical consensus methods for improving predictive geomorphology maps, Computers & Geosciences, 10.1016/j.cageo.2008.02.024, 35, 3, (615-625), (2009).
- Denys Yemshanov, Daniel W. McKenney, John H. Pedlar, Frank H. Koch and David Cook, Towards an integrated approach to modelling the risks and impacts of invasive forest species, Environmental Reviews, 17, NA, (163), (2009).
- Tomáš Václavík and Ross K. Meentemeyer, Invasive species distribution modeling (iSDM): Are absence data and dispersal constraints needed to predict actual distributions?, Ecological Modelling, 220, 23, (3248), (2009).
- Mathieu Marmion, Miska Luoto, Risto K. Heikkinen and Wilfried Thuiller, The performance of state-of-the-art modelling techniques depends on geographical distribution of species, Ecological Modelling, 220, 24, (3512), (2009).
- Luke P. Shoo, Alex Anderson and Stephen E. Williams, On the isolated population of Lewin's Honeyeater (Mel iphaga lewinii amphochlora) from the McIlwraith Range uplands, Cape York Peninsula, Australia: estimates of population size and distribution, Emu - Austral Ornithology, 109, 4, (288), (2009).
- Stefano Nativi, Paolo Mazzetti, Hannu Saarenmaa, Jeremy Kerr and Éamonn Ó Tuama, Biodiversity and climate change use scenarios framework for the GEOSS interoperability pilot process, Ecological Informatics, 4, 1, (23), (2009).
- Daniel Müller, Boris Schröder and Jörg Müller, Modelling habitat selection of the cryptic Hazel Grouse Bonasa bonasia in a montane forest, Journal of Ornithology, 10.1007/s10336-009-0390-6, 150, 4, (717-732), (2009).
- Margaret E. K. Evans, Stephen A. Smith, Rachel S. Flynn and Michael J. Donoghue, Climate, Niche Evolution, and Diversification of the “Bird‐Cage” Evening Primroses (Oenothera, SectionsAnograandKleinia), The American Naturalist, 173, 2, (225), (2009).
- J.R. Leathwick, J. Elith, D. Rowe and K. Julian, Robust planning for restoring diadromous fish species in New Zealand's lowland rivers and streams, New Zealand Journal of Marine and Freshwater Research, 10.1080/00288330909510032, 43, 3, (659-671), (2009).
- Matthew A. Etterson, Gerald J. Niemi and Nicholas P. Danz, Estimating the effects of detection heterogeneity and overdispersion on trends estimated from avian point counts, Ecological Applications, 19, 8, (2049), (2009).
- Miia Parviainen, Mathieu Marmion, Miska Luoto, Wilfried Thuiller and Risto K. Heikkinen, Using summed individual species models and state-of-the-art modelling techniques to identify threatened plant species hotspots, Biological Conservation, 142, 11, (2501), (2009).
- João Carlos Nabout, Paulo de Marco Júnior, Luis Maurício Bini and José Alexandre F. Diniz-Filho, Distribuição geográfica potencial de espécies americanas do caranguejo "violinista" (Uca spp.) (Crustacea, Decapoda) com base em modelagem de nicho ecológico, Iheringia. Série Zoologia, 99, 1, (92), (2009).
- John M. Drake and Jonathan M. Bossenbroek, Profiling ecosystem vulnerability to invasion by zebra mussels with support vector machines, Theoretical Ecology, 10.1007/s12080-009-0050-8, 2, 4, (189-198), (2009).
- Miguel Fernández, Daniel Cole, W. Ronald Heyer, Steffen Reichle and Rafael O. De Sá, PredictingLeptodactylus(Amphibia, Anura, Leptodactylidae) Distributions: Broad-Ranging Versus Patchily Distributed Species Using a Presence-Only Environmental Niche Modeling Technique, South American Journal of Herpetology, 4, 2, (103), (2009).
- T. Bekkby, E. Rinde, L. Erikstad and V. Bakkestuen, Spatial predictive distribution modelling of the kelp species Laminaria hyperborea, ICES Journal of Marine Science, 10.1093/icesjms/fsp195, 66, 10, (2106-2115), (2009).
- Elisabeth Fichet-Calvet, David John Rogers and Robert Tesh, Risk Maps of Lassa Fever in West Africa, PLoS Neglected Tropical Diseases, 3, 3, (e388), (2009).
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- Georgy Shenbrot, On the conspecifity of Allactaga hotsoni Thomas, 1920 and Allactaga firouzi Womochel, 1978 (Rodentia: Dipodoidea), mammalia, 73, 3, (2009).
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- James M. Mottonen, Minli Xu, Donald J. Jacobs and Dennis R. Livesay, Unifying mechanical and thermodynamic descriptions across the thioredoxin protein family, Proteins: Structure, Function, and Bioinformatics, 75, 3, (610-627), (2008).
- Menachem Fromer and Chen Yanover, Accurate prediction for atomic‐level protein design and its application in diversifying the near‐optimal sequence space, "Proteins: Structure, Function, and Bioinformatics", 75, 3, (682-705), (2008).
- Ahmed H. Ahmed, Qi Wang, Holger Sondermann and Robert E. Oswald, Structure of the S1S2 glutamate binding domain of GLuR3, "Proteins: Structure, Function, and Bioinformatics", 75, 3, (628-637), (2008).
- Na Zhang, Yongjun Jiang, Jianwei Zou, Qingsen Yu and Wenna Zhao, Structural basis for the complete loss of GSK3β catalytic activity due to R96 mutation investigated by molecular dynamics study, "Proteins: Structure, Function, and Bioinformatics", 75, 3, (671-681), (2008).
- Rong Shi, Ariane Proteau, John Wagner, Qizhi Cui, Enrico O. Purisima, Allan Matte and Miroslaw Cygler, Trapping open and closed forms of FitE—A group III periplasmic binding protein, "Proteins: Structure, Function, and Bioinformatics", 75, 3, (598-609), (2008).
- M.‐J. Hu, Y.‐P. Guo, Y.‐G. Shen, D.‐P. Guo and D.‐Y. Li, Midday depression of photosynthesis and effects of mist spray in citrus, Annals of Applied Biology, 154, 1, (143-155), (2008).
- Julie Deuquet, Laurence Abrami, Analisa Difeo, Maria Celeste M. Ramirez, John A. Martignetti and F. Gisou van der Goot, Systemic hyalinosis mutations in the CMG2 ectodomain leading to loss of function through retention in the endoplasmic reticulum, Human Mutation, 30, 4, (583-589), (2009).
- Carlo Nobile, Roberto Michelucci, Simonetta Andreazza, Elena Pasini, Silvio C.E. Tosatto and Pasquale Striano, LGI1 mutations in autosomal dominant and sporadic lateral temporal epilepsy, Human Mutation, 30, 4, (530-536), (2009).
- R. Scott Rector, Melissa A. Linden, John Q. Zhang, Shana O. Warner, Thomas S. Altena, Bryan K. Smith, George G. Ziogas, Ying Liu and Tom R. Thomas, Predicting Postprandial Lipemia in Healthy Adults and in At‐Risk Individuals With Components of the Cardiometabolic Syndrome, The Journal of Clinical Hypertension, 11, 11, (663-671), (2009).
- H. M. H. F. Sanders, G. J. Strijkers, W. J. M. Mulder, H. P. Huinink, S. J. F. Erich, O. C. G. Adan, N. A. J. M. Sommerdijk, M. Merkx and K. Nicolay, Morphology, binding behavior and MR‐properties of paramagnetic collagen‐binding liposomes, Contrast Media & Molecular Imaging, 4, 2, (81-88), (2009).
- Adam M. Kennedy, David C. Garen and Roy W. Koch, The association between climate teleconnection indices and Upper Klamath seasonal streamflow: Trans‐Niño Index, Hydrological Processes, 23, 7, (973-984), (2009).
- Marie-Jose´e Fortin and Stephanie J. Melles, Avian Spatial Responses to Forest Spatial Heterogeneity at the Landscape Level: Conceptual and Statistical Challenges, Real World Ecology, 10.1007/978-0-387-77942-3_6, (137-160), (2009).
- Daniel Fink and Wesley Hochachka, Gaussian Semiparametric Analysis Using Hierarchical Predictive Models, Modeling Demographic Processes In Marked Populations, 10.1007/978-0-387-78151-8_46, (1011-1035), (2009).
- Catherine S. Jarnevich and Thomas J. Stohlgren, Temporal Management of Invasive Species, Management of Invasive Weeds, 10.1007/978-1-4020-9202-2_6, (103-122), (2009).
- Baoqing Dong, Lei Chen and Yuefeng Zhou, Soa Based Integration Information Serviceplatform Strategy In Rural Informatization, Computer and Computing Technologies in Agriculture II, Volume 3, 10.1007/978-1-4419-0213-9_42, (1919-1927), (2009).
- Mary Wisz, Nicolas Dendoncker, Jesper Madsen, Mark Rounsevell, Martin Jespersen, Eckhart Kuijken, Wouter Courtens, Christine Verscheure and Fred Cottaar, Modelling pink‐footed goose (Anser brachyrhynchus) wintering distributions for the year 2050: potential effects of land‐use change in Europe, Diversity and Distributions, 14, 5, (721-731), (2008).
- M. S. Wisz, R. J. Hijmans, J. Li, A. T. Peterson, C. H. Graham and A. Guisan, Effects of sample size on the performance of species distribution models, Diversity and Distributions, 14, 5, (763-773), (2008).
- F. Martínez‐Freiría, N. Sillero, M. Lizana and J. C. Brito, GIS‐based niche models identify environmental correlates sustaining a contact zone between three species of European vipers, Diversity and Distributions, 14, 3, (452-461), (2008).
- Florian M. Steiner, Birgit C. Schlick‐Steiner, Jeremy VanDerWal, Keefe D. Reuther, Erhard Christian, Christian Stauffer, Andrew V. Suarez, Stephen E. Williams and Ross H. Crozier, Combined modelling of distribution and niche in invasion biology: a case study of two invasive Tetramorium ant species, Diversity and Distributions, 14, 3, (538-545), (2008).
- Peter B. Pearman, Christophe F. Randin, Olivier Broennimann, Pascal Vittoz, Willem O. van der Knaap, Robin Engler, Gwenaelle Le Lay, Niklaus E. Zimmermann and Antoine Guisan, Prediction of plant species distributions across six millennia, Ecology Letters, 11, 4, (357-369), (2008).
- Bette A. Loiselle, Peter M. Jørgensen, Trisha Consiglio, Iván Jiménez, John G. Blake, Lúcia G. Lohmann and Olga Martha Montiel, Predicting species distributions from herbarium collections: does climate bias in collection sampling influence model outcomes?, Journal of Biogeography, 35, 1, (105-116), (2007).
- Duncan J. Golicher, Luis Cayuela, J. Rob M. Alkemade, Mario González‐Espinosa and Neptalí Ramírez‐Marcial, Applying climatically associated species pools to the modelling of compositional change in tropical montane forests, Global Ecology and Biogeography, 17, 2, (262-273), (2007).
- Catherine H. Graham and Paul V. A. Fine, Phylogenetic beta diversity: linking ecological and evolutionary processes across space in time, Ecology Letters, 11, 12, (1265-1277), (2008).
- Patricia Illoldi‐Rangel, Trevon Fuller, Miguel Linaje, Christopher Pappas, Víctor Sánchez‐Cordero and Sahotra Sarkar, Solving the maximum representation problem to prioritize areas for the conservation of terrestrial mammals at risk in Oaxaca, Diversity and Distributions, 14, 3, (493-508), (2008).
- Mary S. Wisz, Mikkel P. Tamstorf, Jesper Madsen and Martin Jespersen, Where might the western Svalbard tundra be vulnerable to pink‐footed goose (Anser brachyrhynchus) population expansion? Clues from species distribution models, Diversity and Distributions, 14, 1, (26-37), (2007).
- Steven J. Phillips, Transferability, sample selection bias and background data in presence‐only modelling: a response to Peterson et al. (2007), Ecography, 31, 2, (272-278), (2008).
- Alberto Jiménez‐Valverde, Jorge M. Lobo and Joaquín Hortal, Not as good as they seem: the importance of concepts in species distribution modelling, Diversity and Distributions, 14, 6, (885-890), (2008).
- Steven J. Phillips and Miroslav Dudík, Modeling of species distributions with Maxent: new extensions and a comprehensive evaluation, Ecography, 31, 2, (161-175), (2008).
- David C. Le Maitre, Wilfried Thuiller and Lucille Schonegevel, Developing an approach to defining the potential distributions of invasive plant species: a case study of Hakea species in South Africa, Global Ecology and Biogeography, 17, 5, (569-584), (2008).
- Michael Kearney, Ben L. Phillips, Christopher R. Tracy, Keith A. Christian, Gregory Betts and Warren P. Porter, Modelling species distributions without using species distributions: the cane toad in Australia under current and future climates, Ecography, 31, 4, (423-434), (2008).
- EDWARD BYRD DAVIS, MICHELLE S. KOO, CHRIS CONROY, JAMES L. PATTON and CRAIG MORITZ, The California Hotspots Project: identifying regions of rapid diversification of mammals, Molecular Ecology, 17, 1, (120-138), (2007).
- W. Daniel Kissling and Gudrun Carl, Spatial autocorrelation and the selection of simultaneous autoregressive models, Global Ecology and Biogeography, 17, 1, (59-71), (2007).
- A. T. Peterson and Y. Nakazawa, Environmental data sets matter in ecological niche modelling: an example with Solenopsis invicta and Solenopsis richteri, Global Ecology and Biogeography, 17, 1, (135-144), (2007).
- Sally N. Aitken, Sam Yeaman, Jason A. Holliday, Tongli Wang and Sierra Curtis‐McLane, Adaptation, migration or extirpation: climate change outcomes for tree populations, Evolutionary Applications, 1, 1, (95-111), (2008).
- Francisco Rodríguez‐Sánchez and Juan Arroyo, Reconstructing the demise of Tethyan plants: climate‐driven range dynamics of since the Pliocene, Global Ecology and Biogeography, 17, 6, (685-695), (2008).
- Ralph Mac Nally, Erica Fleishman, James R. Thomson and David S. Dobkin, Use of guilds for modelling avian responses to vegetation in the Intermountain West (USA), Global Ecology and Biogeography, 17, 6, (758-769), (2008).
- Vincent Deblauwe, Nicolas Barbier, Pierre Couteron, Olivier Lejeune and Jan Bogaert, The global biogeography of semi‐arid periodic vegetation patterns, Global Ecology and Biogeography, 17, 6, (715-723), (2008).
- Anni Arponen, Atte Moilanen and Simon Ferrier, A successful community‐level strategy for conservation prioritization, Journal of Applied Ecology, 45, 5, (1436-1445), (2008).
- Gilberto Parolo, Graziano Rossi and Alessandro Ferrarini, Toward improved species niche modelling: Arnica montana in the Alps as a case study, Journal of Applied Ecology, 45, 5, (1410-1418), (2008).
- Astrid J. A. Van Teeffelen, Mar Cabeza, Juha Pöyry, Katja Raatikainen and Mikko Kuussaari, Maximizing conservation benefit for grassland species with contrasting management requirements, Journal of Applied Ecology, 45, 5, (1401-1409), (2008).
- Maaike Y. Bader and Johan J.A. Ruijten, A topography‐based model of forest cover at the alpine tree line in the tropical Andes, Journal of Biogeography, 35, 4, (711-723), (2007).
- J. R. Leathwick, J. Elith, W. L. Chadderton, D. Rowe and T. Hastie, Dispersal, disturbance and the contrasting biogeographies of New Zealand’s diadromous and non‐diadromous fish species, Journal of Biogeography, 35, 8, (1481-1497), (2008).
- DESMOND H. FOLEY, ANNA L. WEITZMAN, SCOTT E. MILLER, MICHAEL E. FARAN, LEOPOLDO M. RUEDA and RICHARD C. WILKERSON, The value of georeferenced collection records for predicting patterns of mosquito species richness and endemism in the Neotropics, Ecological Entomology, 33, 1, (12-23), (2007).
- J. Elith, J. R. Leathwick and T. Hastie, A working guide to boosted regression trees, Journal of Animal Ecology, 77, 4, (802-813), (2008).
- Mirkka M. Jones, Hanna Tuomisto and Paulo C. Olivas, Differences in the degree of environmental control on large and small tropical plants: just a sampling effect?, Journal of Ecology, 96, 2, (367-377), (2008).
- Jens‐Christian Svenning, Signe Normand and Masa Kageyama, Glacial refugia of temperate trees in Europe: insights from species distribution modelling, Journal of Ecology, 96, 6, (1117-1127), (2008).
- RIKKE A. JENSEN, JESPER MADSEN, MARK O'CONNELL, MARY S. WISZ, HANS TØMMERVIK and FRIDTJOF MEHLUM, Prediction of the distribution of Arctic‐nesting pink‐footed geese under a warmer climate scenario, Global Change Biology, 14, 1, (1-10), (2007).
- Wolfgang Buermann, Sassan Saatchi, Thomas B. Smith, Brian R. Zutta, Jaime A. Chaves, Borja Milá and Catherine H. Graham, Predicting species distributions across the Amazonian and Andean regions using remote sensing data, Journal of Biogeography, 35, 7, (1160-1176), (2008).
- Ana Carolina Carnaval and Craig Moritz, Historical climate modelling predicts patterns of current biodiversity in the Brazilian Atlantic forest, Journal of Biogeography, 35, 7, (1187-1201), (2008).
- ATTE MOILANEN, JOHN LEATHWICK and JANE ELITH, A method for spatial freshwater conservation prioritization, Freshwater Biology, 53, 3, (577-592), (2007).
- N. G. SWENSON, The past and future influence of geographic information systems on hybrid zone, phylogeographic and speciation research, Journal of Evolutionary Biology, 21, 2, (421-434), (2008).
- Lee Hannah, Protected Areas and Climate Change, Annals of the New York Academy of Sciences, 1134, 1, (201-212), (2008).
- Juha Pöyry, Miska Luoto, Risto K. Heikkinen and Kimmo Saarinen, Species traits are associated with the quality of bioclimatic models, Global Ecology and Biogeography, 17, 3, (403-414), (2008).
- Jorge M. Lobo, Alberto Jiménez‐Valverde and Raimundo Real, AUC: a misleading measure of the performance of predictive distribution models, Global Ecology and Biogeography, 17, 2, (145-151), (2007).
- Catherine H Graham, Jane Elith, Robert J Hijmans, Antoine Guisan, A Townsend Peterson and Bette A Loiselle, The influence of spatial errors in species occurrence data used in distribution models, Journal of Applied Ecology, 45, 1, (239-247), (2007).
- Gregory A. O’Neill, Andreas Hamann and Tongli Wang, Accounting for population variation improves estimates of the impact of climate change on species’ growth and distribution, Journal of Applied Ecology, 45, 4, (1040-1049), (2008).
- Miia Parviainen, Miska Luoto, Terhi Ryttäri and Risto K. Heikkinen, Modelling the occurrence of threatened plant species in taiga landscapes: methodological and ecological perspectives, Journal of Biogeography, 35, 10, (1888-1905), (2008).
- Vegar Bakkestuen, Lars Erikstad and Rune Halvorsen, Step‐less models for regional environmental variation in Norway, Journal of Biogeography, 35, 10, (1906-1922), (2008).
- Mariana Munguía, Andrew Townsend Peterson and Víctor Sánchez‐Cordero, Dispersal limitation and geographical distributions of mammal species, Journal of Biogeography, 35, 10, (1879-1887), (2008).
- Anders K. Wollan, Vegar Bakkestuen, Håvard Kauserud, Gro Gulden and Rune Halvorsen, Modelling and predicting fungal distribution patterns using herbarium data, Journal of Biogeography, 35, 12, (2298-2310), (2008).
- M. De Meyer, M. P. Robertson, A. T. Peterson and M. W. Mansell, Ecological niches and potential geographical distributions of Mediterranean fruit fly (Ceratitis capitata) and Natal fruit fly (Ceratitis rosa), Journal of Biogeography, 35, 2, (270-281), (2007).
- Matthias C. Wichmann, Matt J. Alexander, Rosie S. Hails and James M. Bullock, Historical distribution and regional dynamics of two Brassica species, Ecography, 31, 6, (673-684), (2008).
- Jonathan M. Jeschke and David L. Strayer, Usefulness of Bioclimatic Models for Studying Climate Change and Invasive Species, Annals of the New York Academy of Sciences, 1134, 1, (1-24), (2008).
- Joaquín Hortal, Alberto Jiménez‐Valverde, José F. Gómez, Jorge M. Lobo and Andrés Baselga, Historical bias in biodiversity inventories affects the observed environmental niche of the species, Oikos, 117, 6, (847-858), (2008).
- KRISTINE L. PRESTON, JOHN T. ROTENBERRY, RICHARD A. REDAK and MICHAEL F. ALLEN, Habitat shifts of endangered species under altered climate conditions: importance of biotic interactions, Global Change Biology, 14, 11, (2501-2515), (2008).
- , Editorial: launching Software Notes, Ecography, 31, 1, (3-3), (2008).
- C. Calenge, G. Darmon, M. Basille, A. Loison and J.-M. Jullien, THE FACTORIAL DECOMPOSITION OF THE MAHALANOBIS DISTANCES IN HABITAT SELECTION STUDIES, Ecology, 89, 2, (555-566), (2008).
- Octavio R. Rojas‐Soto, Enrique Martínez‐Meyer, Adolfo G. Navarro‐Sigüenza, Adán Oliveras de Ita, Héctor Gómez de Silva and A. Townsend Peterson, Modeling distributions of disjunct populations of the Sierra Madre Sparrow, Journal of Field Ornithology, 79, 3, (245-253), (2008).
- MATTHEW C. FITZPATRICK, AARON D. GOVE, NATHAN J. SANDERS and ROBERT R. DUNN, Climate change, plant migration, and range collapse in a global biodiversity hotspot: the Banksia (Proteaceae) of Western Australia, Global Change Biology, 14, 6, (1337-1352), (2008).
- MUIR D. EATON, JORGE SOBERÓN and A. TOWNSEND PETERSON, Phylogenetic perspective on ecological niche evolution in american blackbirds (Family Icteridae), Biological Journal of the Linnean Society, 94, 4, (869-878), (2008).
- JOSÉ C. BRITO, XAVIER SANTOS, JUAN M. PLEGUEZUELOS and NEFTALÍ SILLERO, Inferring evolutionary scenarios with geostatistics and geographical information systems for the viperid snakes Vipera latastei and Vipera monticola, Biological Journal of the Linnean Society, 95, 4, (790-806), (2008).
- Mathieu Marmion, Jan Hjort, Wilfried Thuiller and Miska Luoto, A comparison of predictive methods in modelling the distribution of periglacial landforms in Finnish Lapland, Earth Surface Processes and Landforms, 33, 14, (2241-2254), (2008).
- C. J. Raxworthy, R. G. Pearson, B. M. Zimkus, S. Reddy, A. J. Deo, R. A. Nussbaum and C. M. Ingram, Continental speciation in the tropics: contrasting biogeographic patterns of divergence in the Uroplatus leaf‐tailed gecko radiation of Madagascar, Journal of Zoology, 275, 4, (423-440), (2008).
- Dan L. Warren, Richard E. Glor and Michael Turelli, ENVIRONMENTAL NICHE EQUIVALENCY VERSUS CONSERVATISM: QUANTITATIVE APPROACHES TO NICHE EVOLUTION, Evolution, 62, 11, (2868-2883), (2008).
- Neville D. Crossman and David A. Bass, Application of common predictive habitat techniques for post‐border weed risk management, Diversity and Distributions, 14, 2, (213-224), (2007).
- John Leathwick, Atte Moilanen, Malcolm Francis, Jane Elith, Paul Taylor, Kathryn Julian, Trevor Hastie and Clinton Duffy, Novel methods for the design and evaluation of marine protected areas in offshore waters, Conservation Letters, 1, 2, (91-102), (2008).
- HENRY LEE II, DEBORAH A. REUSSER, JULIAN D. OLDEN, SCOTT S. SMITH, JIM GRAHAM, VIRGINIA BURKETT, JEFFREY S. DUKES, ROBERT J. PIORKOWSKI and JOHN MCPHEDRAN, Integrated Monitoring and Information Systems for Managing Aquatic Invasive Species in a Changing Climate, Conservation Biology, 22, 3, (575-584), (2008).
- SARAH C. ELMENDORF and KARA A. MOORE, Use of Community‐Composition Data to Predict the Fecundity and Abundance of Species, Conservation Biology, 22, 6, (1523-1532), (2008).
- Hedley S. Grantham, Atte Moilanen, Kerrie A. Wilson, Robert L. Pressey, Tony G. Rebelo and Hugh P. Possingham, Diminishing return on investment for biodiversity data in conservation planning, Conservation Letters, 1, 4, (190-198), (2008).
- LAËTITIA BUISSON, WILFRIED THUILLER, SOVAN LEK, PUY LIM and GAËL GRENOUILLET, Climate change hastens the turnover of stream fish assemblages, Global Change Biology, 14, 10, (2232-2248), (2008).
- MANDAR R. TRIVEDI, PAMELA M. BERRY, MICHAEL D. MORECROFT and TERENCE P. DAWSON, Spatial scale affects bioclimate model projections of climate change impacts on mountain plants, Global Change Biology, 14, 5, (1089-1103), (2008).
- Paul H. Evangelista, Sunil Kumar, Thomas J. Stohlgren, Catherine S. Jarnevich, Alycia W. Crall, John B. Norman III and David T. Barnett, Modelling invasion for a habitat generalist and a specialist plant species, Diversity and Distributions, 14, 5, (808-817), (2008).
- Blair C. Parsons, Jeff C. Short and J. Dale Roberts, Contraction in the range of Malleefowl (Leipoa ocellata) in Western Australia: a comparative assessment using presence-only and presence—absence datasets, Emu - Austral Ornithology, 108, 3, (221), (2008).
- Apostolos Siapatis, Marianna Giannoulaki, Vasilis D. Valavanis, Andreas Palialexis, Eudoxia Schismenou, Athanassios Machias and Stylianos Somarakis, Modelling potential habitat of the invasive ctenophore Mnemiopsis leidyi in Aegean Sea, Hydrobiologia, 10.1007/s10750-008-9497-7, 612, 1, (281-295), (2008).
- Michael J. Watts and S.P. Worner, Comparing ensemble and cascaded neural networks that combine biotic and abiotic variables to predict insect species distribution, Ecological Informatics, 3, 6, (354), (2008).
- Mia Rönkä, Harri Tolvanen, Esa Lehikoinen, Mikael von Numers and Mauri Rautkari, Breeding habitat preferences of 15 bird species on south-western Finnish archipelago coast: Applicability of digital spatial data archives to habitat assessment, Biological Conservation, 141, 2, (402), (2008).
- Justin D. Hoffman, Sunil Narumalani, Deepak R. Mishra, Paul Merani and Robert G. Wilson, Predicting Potential Occurrence and Spread of Invasive Plant Species along the North Platte River, Nebraska, Invasive Plant Science and Management, 1, 04, (359), (2008).
- Mathilde Cordellier and Markus Pfenninger, Climate-driven range dynamics of the freshwater limpet,Ancylus fluviatilis(Pulmonata, Basommatophora), Journal of Biogeography, 35, 9, (1580), (2008).
- David M. Cahill, James E. Rookes, Barbara A. Wilson, Lesley Gibson and Keith L. McDougall, Phytophthora cinnamomi and Australia's biodiversity: impacts, predictions and progress towards control, Australian Journal of Botany, 10.1071/BT07159, 56, 4, (279), (2008).
- F.S. Santana, M.F. de Siqueira, A.M. Saraiva and P.L.P. Correa, A reference business process for ecological niche modelling, Ecological Informatics, 3, 1, (75), (2008).
- JUAN L. PARRA and WILLIAM B. MONAHAN, Variability in 20th century climate change reconstructions and its consequences for predicting geographic responses of California mammals, Global Change Biology, 14, 10, (2215-2231), (2008).
- Steven L Chown and Kevin J Gaston, Macrophysiology for a changing world, Proceedings of the Royal Society B: Biological Sciences, 10.1098/rspb.2008.0137, 275, 1642, (1469-1478), (2008).
- Andy Jarvis, Annie Lane and Robert J. Hijmans, The effect of climate change on crop wild relatives, Agriculture, Ecosystems & Environment, 126, 1-2, (13), (2008).
- Andrew J. Davies, Max Wisshak, James C. Orr and J. Murray Roberts, Predicting suitable habitat for the cold-water coral Lophelia pertusa (Scleractinia), Deep Sea Research Part I: Oceanographic Research Papers, 10.1016/j.dsr.2008.04.010, 55, 8, (1048-1062), (2008).
- Boris Schröder, Challenges of species distribution modeling belowground, Journal of Plant Nutrition and Soil Science, 171, 3, (325-337), (2008).
- Raul Romero-Calcerrada, C. J. Novillo, J. D. A. Millington and I. Gomez-Jimenez, GIS analysis of spatial patterns of human-caused wildfire ignition risk in the SW of Madrid (Central Spain), Landscape Ecology, 10.1007/s10980-008-9190-2, 23, 3, (341-354), (2008).
- Kerry A. Brown, Sacha Spector and Wei Wu, Multi‐scale analysis of species introductions: combining landscape and demographic models to improve management decisions about non‐native species, Journal of Applied Ecology, 45, 6, (1639-1648), (2008).
- Benjamin L. Phillips, Joseph D. Chipperfield and Michael R. Kearney, The toad ahead: challenges of modelling the range and spread of an invasive species, Wildlife Research, 10.1071/WR07101, 35, 3, (222), (2008).
- A. Townsend Peterson, Aimee Stewart, Kamal I. Mohamed, Miguel B. Araújo and Jerome Chave, Shifting Global Invasive Potential of European Plants with Climate Change, PLoS ONE, 3, 6, (e2441), (2008).
- Seth J. Wenger and Mary C. Freeman, ESTIMATING SPECIES OCCURRENCE, ABUNDANCE, AND DETECTION PROBABILITY USING ZERO-INFLATED DISTRIBUTIONS, Ecology, 89, 10, (2953), (2008).
- Paulo De Marco, José Alexandre Felizola Diniz-Filho and Luis Mauricio Bini, Spatial analysis improves species distribution modelling during range expansion, Biology Letters, 10.1098/rsbl.2008.0210, 4, 5, (577-580), (2008).
- Surangi W. Punyasena, Estimating Neotropical palaeotemperature and palaeoprecipitation using plant family climatic optima, Palaeogeography, Palaeoclimatology, Palaeoecology, 265, 3-4, (226), (2008).
- Roberto Danovaro, Cristina Gambi, Nikolaos Lampadariou and Anastasios Tselepides, Deep‐sea nematode biodiversity in the Mediterranean basin: testing for longitudinal, bathymetric and energetic gradients, Ecography, 31, 2, (231-244), (2008).
- A. Townsend Peterson, Monica Papeş and Jorge Soberón, Rethinking receiver operating characteristic analysis applications in ecological niche modeling, Ecological Modelling, 213, 1, (63), (2008).
- Olivier Broennimann and Antoine Guisan, Predicting current and future biological invasions: both native and invaded ranges matter, Biology Letters, 10.1098/rsbl.2008.0254, 4, 5, (585-589), (2008).
- Desmond H. Foley, Leopoldo M. Rueda, A. Townsend Peterson and Richard C. Wilkerson, Potential Distribution of Two Species in the Medically Important Anopheles minimus Complex (Diptera: Culicidae) , Journal of Medical Entomology, 45, 5, (852), (2008).
- Steven J. Phillips, Transferability, sample selection bias and background data in presence-only modelling: a response to Peterson et al. (2007), Ecography, 0, 0, (080227084236895), (2008).
- Jens von dem Bussche, Reto Spaar, Hans Schmid and Boris Schröder, Modelling the recent and potential future spatial distribution of the Ring Ouzel (Turdus torquatus) and Blackbird (T. merula) in Switzerland, Journal of Ornithology, 10.1007/s10336-008-0295-9, 149, 4, (529-544), (2008).
- C. Kremen, A. Cameron, A. Moilanen, S. J. Phillips, C. D. Thomas, H. Beentje, J. Dransfield, B. L. Fisher, F. Glaw, T. C. Good, G. J. Harper, R. J. Hijmans, D. C. Lees, E. Louis, R. A. Nussbaum, C. J. Raxworthy, A. Razafimpahanana, G. E. Schatz, M. Vences, D. R. Vieites, P. C. Wright and M. L. Zjhra, Aligning Conservation Priorities Across Taxa in Madagascar with High-Resolution Planning Tools, Science, 320, 5873, (222), (2008).
- Heather M. Kharouba, Julie L. Nadeau, Eric Young and Jeremy T. Kerr, Using species distribution models to effectively conserve biodiversity into the future, Biodiversity, 9, 3-4, (39), (2008).
- A. Townsend Peterson, Biogeography of diseases: a framework for analysis, Naturwissenschaften, 10.1007/s00114-008-0352-5, 95, 6, (483-491), (2008).
- Scott E. Solomon, Mauricio Bacci, Joaquim Martins, Giovanna Gonçalves Vinha, Ulrich G. Mueller and Peter M. Bennett, Paleodistributions and Comparative Molecular Phylogeography of Leafcutter Ants (Atta spp.) Provide New Insight into the Origins of Amazonian Diversity, PLoS ONE, 3, 7, (e2738), (2008).
- Andrew C. Yost, Steven L. Petersen, Michael Gregg and Richard Miller, Predictive modeling and mapping sage grouse (Centrocercus urophasianus) nesting habitat using Maximum Entropy and a long-term dataset from Southern Oregon, Ecological Informatics, 3, 6, (375), (2008).
- Kurt D. Reed, Jennifer K. Meece, John R. Archer, A. Townsend Peterson and Dee A. Carter, Ecologic Niche Modeling of Blastomyces dermatitidis in Wisconsin, PLoS ONE, 3, 4, (e2034), (2008).
- Maarten J. M. Christenhusz and Tuuli K. Toivonen, Giants invading the tropics: the oriental vessel fern, Angiopteris evecta (Marattiaceae), Biological Invasions, 10.1007/s10530-007-9197-7, 10, 8, (1215-1228), (2007).
- J. Harte, T. Zillio, E. Conlisk and A. B. Smith, MAXIMUM ENTROPY AND THE STATE-VARIABLE APPROACH TO MACROECOLOGY, Ecology, 89, 10, (2700), (2008).
- Clément Calenge and Mathieu Basille, A general framework for the statistical exploration of the ecological niche, Journal of Theoretical Biology, 252, 4, (674), (2008).
- Mathieu Basille, Clément Calenge, Éric Marboutin, Reidar Andersen and Jean-Michel Gaillard, Assessing habitat selection using multivariate statistics: Some refinements of the ecological-niche factor analysis, Ecological Modelling, 211, 1-2, (233), (2008).
- David L. Lentz, Robert Bye and Victor Sánchez‐Cordero, Ecological Niche Modeling and Distribution of Wild Sunflower (Helianthus annuusL.) in Mexico, International Journal of Plant Sciences, 169, 4, (541), (2008).
- Christoph Zöckler, Lera Miles, Lucy Fish, Annett Wolf, Gareth Rees and Fiona Danks, Potential impact of climate change and reindeer density on tundra indicator species in the Barents Sea region, Climatic Change, 10.1007/s10584-007-9344-2, 87, 1-2, (119-130), (2007).
- Jan Hjort and Mathieu Marmion, Effects of sample size on the accuracy of geomorphological models, Geomorphology, 102, 3-4, (341), (2008).
- Jennifer M. Lamb, Taryn M. C. Ralph, Steven M. Goodman, Wiesław Bogdanowicz, Jakob Fahr, Marta Gajewska, Paul J. J. Bates, Judith Eger, Petr Benda and Peter J. Taylor, Phylogeography and predicted distribution of African-Arabian and Malagasy populations of giant mastiff bats, Otomops spp. (Chiroptera: Molossidae), Acta Chiropterologica, 10, 1, (21), (2008).
- Jason E. Bond and Amy K. Stockman, An Integrative Method for Delimiting Cohesion Species: Finding the Population-Species Interface in a Group of Californian Trapdoor Spiders with Extreme Genetic Divergence and Geographic Structuring, Systematic Biology, 57, 4, (628), (2008).
- João G. R. Giovanelli, Célio F. B. Haddad and João Alexandrino, Predicting the potential distribution of the alien invasive American bullfrog (Lithobates catesbeianus) in Brazil, Biological Invasions, 10.1007/s10530-007-9154-5, 10, 5, (585-590), (2007).
- Antonia Sandman, Martin Isaeus, Ulf Bergström and Hans Kautsky, Spatial predictions of Baltic phytobenthic communities: Measuring robustness of generalized additive models based on transect data, Journal of Marine Systems, 74, (S86), (2008).
- Karin Meißner, Alexander Darr and Eike Rachor, Development of habitat models for Nephtys species (Polychaeta: Nephtyidae) in the German Bight (North Sea), Journal of Sea Research, 60, 4, (276), (2008).
- Marianna Giannoulaki, Vasilis D. Valavanis, Andreas Palialexis, Konstantinos Tsagarakis, Athanassios Machias, Stylianos Somarakis and Costas Papaconstantinou, Modelling the presence of anchovy Engraulis encrasicolus in the Aegean Sea during early summer, based on satellite environmental data, Hydrobiologia, 10.1007/s10750-008-9498-6, 612, 1, (225-240), (2008).
- Trevon Fuller, David P. Morton and Sahotra Sarkar, Incorporating uncertainty about species’ potential distributions under climate change into the selection of conservation areas with a case study from the Arctic Coastal Plain of Alaska, Biological Conservation, 141, 6, (1547), (2008).
- J. Nicolás Urbina-Cardona and Rafael D. Loyola, Applying Niche-Based Models to Predict Endangered-Hylid Potential Distributions: Are Neotropical Protected Areas Effective Enough?, Tropical Conservation Science, 1, 4, (417), (2008).
- A. Kaliontzopoulou, J. C. Brito, M. A. Carretero, S. Larbes and D. J. Harris, Modelling the partially unknown distribution of wall lizards (Podarcis) in North Africa: ecological affinities, potential areas of occurrence, and methodological constraints, Canadian Journal of Zoology, 86, 9, (992), (2008).
- Arno Thomaes, Thierry Kervyn and Dirk Maes, Applying species distribution modelling for the conservation of the threatened saproxylic Stag Beetle (Lucanus cervus), Biological Conservation, 141, 5, (1400), (2008).
- Scott R. Loarie, Benjamin E. Carter, Katharine Hayhoe, Sean McMahon, Richard Moe, Charles A. Knight, David D. Ackerly and Craig R. McClain, Climate Change and the Future of California's Endemic Flora, PLoS ONE, 3, 6, (e2502), (2008).
- Konstantinos Tsagarakis, Athanassios Machias, Stylianos Somarakis, Marianna Giannoulaki, Andreas Palialexis and Vasilis D. Valavanis, Habitat discrimination of juvenile sardines in the Aegean Sea using remotely sensed environmental data, Hydrobiologia, 10.1007/s10750-008-9500-3, 612, 1, (215-223), (2008).
- C. M. Beale, J. J. Lennon and A. Gimona, Opening the climate envelope reveals no macroscale associations with climate in European birds, Proceedings of the National Academy of Sciences, 105, 39, (14908), (2008).
- Vasilis D. Valavanis, Graham J. Pierce, Alain F. Zuur, Andreas Palialexis, Anatoly Saveliev, Isidora Katara and Jianjun Wang, Modelling of essential fish habitat based on remote sensing, spatial analysis and GIS, Hydrobiologia, 10.1007/s10750-008-9493-y, 612, 1, (5-20), (2008).
- Roger Cousens, Risk Assessment of Potential Biofuel Species: An Application for Trait-Based Models for Predicting Weediness, Weed Science, 56, 6, (873), (2008).
- Shaily Menon, Zafar-Ul Islam, Jorge Soberón and A. Townsend Peterson, Preliminary analysis of the ecology and geography of the Asian nuthatches (Aves: Sittidae), The Wilson Journal of Ornithology, 120, 4, (692), (2008).
- Sassan Saatchi, Wolfgang Buermann, Hans ter Steege, Scott Mori and Thomas B. Smith, Modeling distribution of Amazonian tree species and diversity using remote sensing measurements, Remote Sensing of Environment, 112, 5, (2000), (2008).
- T. Bekkby, H.C. Nilsson, F. Olsgard, B. Rygg, P.E. Isachsen and M. Isæus, Identifying soft sediments at sea using GIS-modelled predictor variables and Sediment Profile Image (SPI) measured response variables, Estuarine, Coastal and Shelf Science, 79, 4, (631), (2008).
- P. A. Hernandez, I. Franke, S. K. Herzog, V. Pacheco, L. Paniagua, H. L. Quintana, A. Soto, J. J. Swenson, C. Tovar, T. H. Valqui, J. Vargas and B. E. Young, Predicting species distributions in poorly-studied landscapes, Biodiversity and Conservation, 10.1007/s10531-007-9314-z, 17, 6, (1353-1366), (2008).
- Thomas W. Gillespie, Giles M. Foody, Duccio Rocchini, Ana Paula Giorgi and Sassan Saatchi, Measuring and modelling biodiversity from space, Progress in Physical Geography: Earth and Environment, 10.1177/0309133308093606, 32, 2, (203-221), (2008).
- Carsten F. Dormann, Oliver Purschke, Jaime R. García Márquez, Sven Lautenbach and Boris Schröder, COMPONENTS OF UNCERTAINTY IN SPECIES DISTRIBUTION ANALYSIS: A CASE STUDY OF THE GREAT GREY SHRIKE, Ecology, 89, 12, (3371-3386), (2008).
- Eudoxia Schismenou, Marianna Giannoulaki, Vasilis D. Valavanis and Stylianos Somarakis, Modeling and predicting potential spawning habitat of anchovy (Engraulis encrasicolus) and round sardinella (Sardinella aurita) based on satellite environmental information, Hydrobiologia, 10.1007/s10750-008-9502-1, 612, 1, (201-214), (2008).
- Euan G. Ritchie and Elizabeth E. Bolitho, Australia’s Savanna Herbivores: Bioclimatic Distributions and an Assessment of the Potential Impact of Regional Climate Change, Physiological and Biochemical Zoology, 81, 6, (880), (2008).
- Richard A.J. Williams, Folorunso O. Fasina and A. Townsend Peterson, Predictable ecology and geography of avian influenza (H5N1) transmission in Nigeria and West Africa, Transactions of the Royal Society of Tropical Medicine and Hygiene, 102, 5, (471), (2008).
- Jin Li and David W. Hilbert, LIVES: a new habitat modelling technique for predicting the distribution of species’ occurrences using presence-only data based on limiting factor theory, Biodiversity and Conservation, 10.1007/s10531-007-9270-7, 17, 13, (3079-3095), (2008).
- Grant R Bigg, Clifford W Cunningham, Geir Ottersen, Grant H Pogson, Martin R Wadley and Phillip Williamson, Ice-age survival of Atlantic cod: agreement between palaeoecology models and genetics, Proceedings of the Royal Society B: Biological Sciences, 10.1098/rspb.2007.1153, 275, 1631, (163-173), (2008).
- Susana Suárez-Seoane, Eladio L. García de la Morena, Manuel B. Morales Prieto, Patrick E. Osborne and Eduardo de Juana, Maximum entropy niche-based modelling of seasonal changes in little bustard (Tetrax tetrax) distribution, Ecological Modelling, 219, 1-2, (17), (2008).
- Christian Piedallu and Jean-claude Gégout, Efficient assessment of topographic solar radiation to improve plant distribution models, Agricultural and Forest Meteorology, 148, 11, (1696), (2008).
- Desmond H. Foley, Leopoldo M. Rueda, A. Townsend Peterson and Richard C. Wilkerson, Potential Distribution of Two Species in the Medically Important Anopheles minimus Complex (Diptera: Culicidae), Journal of Medical Entomology, 45, 5, (852), (2008).
- R. Alexander Pyron, Frank T. Burbrink, Timothy J. Guiher and Andy Hector, Claims of Potential Expansion throughout the U.S. by Invasive Python Species Are Contradicted by Ecological Niche Models, PLoS ONE, 3, 8, (e2931), (2008).
- Eugenia Lefkaditou, Chrissi-Yianna Politou, Andreas Palialexis, John Dokos, Panayota Cosmopoulos and Vasilis D. Valavanis, Influences of environmental variability on the population structure and distribution patterns of the short-fin squid Illex coindetii (Cephalopoda: Ommastrephidae) in the Eastern Ionian Sea, Hydrobiologia, 10.1007/s10750-008-9490-1, 612, 1, (71-90), (2008).
- Rafael Dias Loyola, Carlos Guilherme Becker, Umberto Kubota, Célio Fernando Baptista Haddad, Carlos Roberto Fonseca, Thomas Michael Lewinsohn and Wayne M. Getz, Hung Out to Dry: Choice of Priority Ecoregions for Conserving Threatened Neotropical Anurans Depends on Life-History Traits, PLoS ONE, 3, 5, (e2120), (2008).
- Karen E. DeMatteo and Bette A. Loiselle, New data on the status and distribution of the bush dog (Speothos venaticus): Evaluating its quality of protection and directing research efforts, Biological Conservation, 141, 10, (2494), (2008).
- Gary N. Geller and Forrest Melton, Looking forward: Applying an ecological model web to assess impacts of climate change, Biodiversity, 9, 3-4, (79), (2008).
- Jim Graham, Annie Simpson, Alycia Crall, Catherine Jarnevich, Greg Newman and Thomas J. Stohlgren, Vision of a Cyberinfrastructure for Nonnative, Invasive Species Management, BioScience, 58, 3, (263), (2008).
- Mark Burgman, Jane Elith, Emma Gorrod and Bonnie Wintle, Tools for Conserving Managing Individual Plant Species in Dynamic Landscapes, Managing and Designing Landscapes for Conservation, (330-342), (2008).
- José Alexandre Felizola Diniz-Filho, Luis Mauricio Bini, Míriam Plaza Pinto, Levi Carina Terribile, Guilherme de Oliveira, Cleiber Marques Vieira, Daniel Blamires, Bruno de Souza Barreto, Priscilla Carvalho, Thiago Fernando L.V.B. Rangel, Natalia Mundin Tôrres and Rogério Pereira Bastos, Conservation planning: a macroecological approach using the endemic terrestrial vertebrates of the Brazilian Cerrado, Oryx, 10.1017/S0030605308001129, 42, 04, (567), (2008).
- Laura M. Bellis, Anna M. Pidgeon, Volker C. Radeloff, Véronique St-Louis, Joaquín L. Navarro and Mónica B. Martella, MODELING HABITAT SUITABILITY FOR GREATER RHEAS BASED ON SATELLITE IMAGE TEXTURE, Ecological Applications, 18, 8, (1956-1966), (2008).
- Kenneth H. Kozak, Catherine H. Graham and John J. Wiens, Integrating GIS-based environmental data into evolutionary biology, Trends in Ecology & Evolution, 23, 3, (141), (2008).
- Colby Loucks, Taylor H. Ricketts, Robin Naidoo, John Lamoreux and Jonathan Hoekstra, Explaining the global pattern of protected area coverage: relative importance of vertebrate biodiversity, human activities and agricultural suitability, Journal of Biogeography, 35, 8, (1337-1348), (2008).
- Miriam Dühnforth, Alexander L. Densmore, Susan Ivy‐Ochs and Philip A. Allen, Controls on sediment evacuation from glacially modified and unmodified catchments in the eastern Sierra Nevada, California, Earth Surface Processes and Landforms, 33, 10, (1602-1613), (2008).
- Philip C.J. Donoghue, Anthony Graham and Robert N. Kelsh, The origin and evolution of the neural crest, BioEssays, 30, 6, (530-541), (2008).
- Hiroshi Momiji, A consideration on the autostabilization mechanisms operational on a sand dune at equilibrium, Earth Surface Processes and Landforms, 33, 14, (2297-2299), (2008).
- Andrew M. Schurko and John M. Logsdon, Using a meiosis detection toolkit to investigate ancient asexual “scandals” and the evolution of sex, BioEssays, 30, 6, (579-589), (2008).
- Leonardo Esteves Lopes, The range of the curl‐crested jay: lessons for evaluating bird endemism in the South American Cerrado, Diversity and Distributions, 14, 4, (561-568), (2007).
- Carlo Ricotta, Sandrine Godefroid and Laura Celesti‐Grapow, Common species have lower taxonomic diversity Evidence from the urban floras of Brussels and Rome, Diversity and Distributions, 14, 3, (530-537), (2008).
- Hong Qian, A latitudinal gradient of beta diversity for exotic vascular plant species in North America, Diversity and Distributions, 14, 3, (556-560), (2008).
- Jonathan M. Waters, Marine biogeographical disjunction in temperate Australia: historical landbridge, contemporary currents, or both?, Diversity and Distributions, 14, 4, (692-700), (2008).
- Alison G. Boyer, Extinction patterns in the avifauna of the Hawaiian islands, Diversity and Distributions, 14, 3, (509-517), (2008).
- Alvaro Soutullo, Monica De Castro and Vicente Urios, Linking political and scientifically derived targets for global biodiversity conservation: implications for the expansion of the global network of protected areas, Diversity and Distributions, 14, 4, (604-613), (2007).
- Michel Saint‐Germain, Pierre Drapeau and Christopher M. Buddle, Persistence of pyrophilous insects in fire‐driven boreal forests: population dynamics in burned and unburned habitats, Diversity and Distributions, 14, 4, (713-720), (2007).
- Viviane Gianluppi Ferro and Ivone Rezende Diniz, Biological attributes affect the data of description of tiger moths (Arctiidae) in the Brazilian Cerrado, Diversity and Distributions, 14, 3, (472-482), (2008).
- V. Hutsemekers, C. Dopagne and A. Vanderpoorten, How far and how fast do bryophytes travel at the landscape scale?, Diversity and Distributions, 14, 3, (483-492), (2008).
- Ana C. Lorena, Marinez F. de Siqueira, Renato De Giovanni, André C. P. L. F. de Carvalho and Ronaldo C. Prati, Potential Distribution Modelling Using Machine Learning, New Frontiers in Applied Artificial Intelligence, 10.1007/978-3-540-69052-8_27, (255-264), (2008).
- B Pando de Benito and J Giles de Peñas, Greenhouses, land use change, and predictive models: MaxEnt and Geomod working together, Modelling Environmental Dynamics, 10.1007/978-3-540-68498-5_11, (297-317), (2008).
- Apostolos Siapatis, Marianna Giannoulaki, Vasilis D. Valavanis, Andreas Palialexis, Eudoxia Schismenou, Athanassios Machias and Stylianos Somarakis, Modelling potential habitat of the invasive ctenophore Mnemiopsis leidyi in Aegean Sea, Essential Fish Habitat Mapping in the Mediterranean, 10.1007/978-1-4020-9141-4_21, (281-295), (2008).
- Eudoxia Schismenou, Marianna Giannoulaki, Vasilis D. Valavanis and Stylianos Somarakis, Modeling and predicting potential spawning habitat of anchovy (Engraulis encrasicolus) and round sardinella (Sardinella aurita) based on satellite environmental information, Essential Fish Habitat Mapping in the Mediterranean, 10.1007/978-1-4020-9141-4_15, (201-214), (2008).
- Konstantinos Tsagarakis, Athanassios Machias, Stylianos Somarakis, Marianna Giannoulaki, Andreas Palialexis and Vasilis D. Valavanis, Habitat discrimination of juvenile sardines in the Aegean Sea using remotely sensed environmental data, Essential Fish Habitat Mapping in the Mediterranean, 10.1007/978-1-4020-9141-4_16, (215-223), (2008).
- Eugenia Lefkaditou, Chrissi-Yianna Politou, Andreas Palialexis, John Dokos, Panayota Cosmopoulos and Vasilis D. Valavanis, Influences of environmental variability on the population structure and distribution patterns of the short-fin squid Illex coindetii (Cephalopoda: Ommastrephidae) in the Eastern Ionian Sea, Essential Fish Habitat Mapping in the Mediterranean, 10.1007/978-1-4020-9141-4_6, (71-90), (2008).
- Marianna Giannoulaki, Vasilis D. Valavanis, Andreas Palialexis, Konstantinos Tsagarakis, Athanassios Machias, Stylianos Somarakis and Costas Papaconstantinou, Modelling the presence of anchovy Engraulis encrasicolus in the Aegean Sea during early summer, based on satellite environmental data, Essential Fish Habitat Mapping in the Mediterranean, 10.1007/978-1-4020-9141-4_17, (225-240), (2008).
- Vasilis D. Valavanis, Graham J. Pierce, Alain F. Zuur, Andreas Palialexis, Anatoly Saveliev, Isidora Katara and Jianjun Wang, Modelling of essential fish habitat based on remote sensing, spatial analysis and GIS, Essential Fish Habitat Mapping in the Mediterranean, 10.1007/978-1-4020-9141-4_2, (5-20), (2008).
- Dawn R. Magness, Falk Huettmann and John M. Morton, Using Random Forests to Provide Predicted Species Distribution Maps as a Metric for Ecological Inventory & Monitoring Programs, Applications of Computational Intelligence in Biology, 10.1007/978-3-540-78534-7_9, (209-229), (2008).
- V. B. Chaudhary, M. K. Lau and N. C. Johnson, Macroecology of Microbes – Biogeography of the Glomeromycota, Mycorrhiza, 10.1007/978-3-540-78826-3_26, (529-563), (2008).
- Asaf Tsoar, Omri Allouche, Ofer Steinitz, Dotan Rotem and Ronen Kadmon, A comparative evaluation of presence‐only methods for modelling species distribution, Diversity and Distributions, 13, 4, (397-405), (2007).
- Gentile Francesco Ficetola, Wilfried Thuiller and Claude Miaud, Prediction and validation of the potential global distribution of a problematic alien invasive species — the American bullfrog, Diversity and Distributions, 13, 4, (476-485), (2007).
- K. M. DLUGOSCH and I. M. PARKER, Molecular and quantitative trait variation across the native range of the invasive species Hypericum canariense: evidence for ancient patterns of colonization via pre‐adaptation?, Molecular Ecology, 16, 20, (4269-4283), (2007).
- Milena Holmgren and Lourens Poorter, Does a ruderal strategy dominate the endemic flora of the West African forests?, Journal of Biogeography, 34, 6, (1100-1111), (2007).
- Christine N. Meynard and James F. Quinn, Predicting species distributions: a critical comparison of the most common statistical models using artificial species, Journal of Biogeography, 34, 8, (1455-1469), (2007).
- N. E. ZIMMERMANN, T. C. EDWARDS, G. G. MOISEN, T. S. FRESCINO and J. A. BLACKARD, Remote sensing‐based predictors improve distribution models of rare, early successional and broadleaf tree species in Utah, Journal of Applied Ecology, 44, 5, (1057-1067), (2007).
- Christelle Robinet, Peter Baier, Josef Pennerstorfer, Axel Schopf and Alain Roques, Modelling the effects of climate change on the potential feeding activity of Thaumetopoea pityocampa (Den. & Schiff.) (Lep., Notodontidae) in France, Global Ecology and Biogeography, 16, 4, (460-471), (2007).
- Corinne L. Richards, Bryan C. Carstens and L. Lacey Knowles, Distribution modelling and statistical phylogeography: an integrative framework for generating and testing alternative biogeographical hypotheses, Journal of Biogeography, 34, 11, (1833-1845), (2007).
- KAREN L. BELL, CRAIG MORITZ, ADNAN MOUSSALLI and DAVID K. YEATES, Comparative phylogeography and speciation of dung beetles from the Australian Wet Tropics rainforest, Molecular Ecology, 16, 23, (4984-4998), (2007).
- M. Papeş and P. Gaubert, Modelling ecological niches from low numbers of occurrences: assessment of the conservation status of poorly known viverrids (Mammalia, Carnivora) across two continents, Diversity and Distributions, 13, 6, (890-902), (2007).
- A. Townsend Peterson, Monica Papeş and Muir Eaton, Transferability and model evaluation in ecological niche modeling: a comparison of GARP and Maxent, Ecography, 30, 4, (550-560), (2007).
- Niels Raes and Hans ter Steege, A null‐model for significance testing of presence‐only species distribution models, Ecography, 30, 5, (727-736), (2007).
- Carsten F. Dormann, Jana M. McPherson, Miguel B. Araújo, Roger Bivand, Janine Bolliger, Gudrun Carl, Richard G. Davies, Alexandre Hirzel, Walter Jetz, W. Daniel Kissling, Ingolf Kühn, Ralf Ohlemüller, Pedro R. Peres‐Neto, Björn Reineking, Boris Schröder, Frank M. Schurr and Robert Wilson, Methods to account for spatial autocorrelation in the analysis of species distributional data: a review, Ecography, 30, 5, (609-628), (2007).
- Gabriel C. Costa, Cristiano Nogueira, Ricardo B. Machado and Guarino R. Colli, Squamate richness in the Brazilian Cerrado and its environmental–climatic associations, Diversity and Distributions, 13, 6, (714-724), (2007).
- Hugh P. Possingham, Hedley Grantham and Carlo Rondinini, How can you conserve species that haven't been found?, Journal of Biogeography, 34, 5, (758-759), (2007).
- M. S. Wisz, B. A. Walther and C. Rahbek, Using potential distributions to explore determinants of Western Palaearctic migratory songbird species richness in sub‐Saharan Africa, Journal of Biogeography, 34, 5, (828-841), (2007).
- JOHAN SPENS, GÖRAN ENGLUND and HANS LUNDQVIST, Network connectivity and dispersal barriers: using geographical information system (GIS) tools to predict landscape scale distribution of a key predator (Esox lucius) among lakes, Journal of Applied Ecology, 44, 6, (1127-1137), (2007).
- Carsten F. Dormann, Effects of incorporating spatial autocorrelation into the analysis of species distribution data, Global Ecology and Biogeography, 16, 2, (129-138), (2006).
- AMY K. STOCKMAN and JASON E. BOND, Delimiting cohesion species: extreme population structuring and the role of ecological interchangeability, Molecular Ecology, 16, 16, (3374-3392), (2007).
- Richard G. Pearson, Christopher J. Raxworthy, Miguel Nakamura and A. Townsend Peterson, ORIGINAL ARTICLE: Predicting species distributions from small numbers of occurrence records: a test case using cryptic geckos in Madagascar, Journal of Biogeography, 34, 1, (102-117), (2006).
- Peter J.T. White and Jeremy T. Kerr, Human impacts on environment–diversity relationships: evidence for biotic homogenization from butterfly species richness patterns, Global Ecology and Biogeography, 16, 3, (290-299), (2007).
- Volker Bahn and Brian J. McGill, Can niche‐based distribution models outperform spatial interpolation?, Global Ecology and Biogeography, 16, 6, (733-742), (2007).
- Risto K. Heikkinen, Miska Luoto, Raimo Virkkala, Richard G. Pearson and Jan‐Hendrik Körber, Biotic interactions improve prediction of boreal bird distributions at macro‐scales, Global Ecology and Biogeography, 16, 6, (754-763), (2007).
- Simon Ferrier, Glenn Manion, Jane Elith and Karen Richardson, Using generalized dissimilarity modelling to analyse and predict patterns of beta diversity in regional biodiversity assessment, Diversity and Distributions, 13, 3, (252-264), (2007).
- Jane Elith and John Leathwick, Predicting species distributions from museum and herbarium records using multiresponse models fitted with multivariate adaptive regression splines, Diversity and Distributions, 13, 3, (265-275), (2007).
- Jorge M. Lobo, Andrés Baselga, Joaquín Hortal, Alberto Jiménez‐Valverde and Jose F. Gómez, How does the knowledge about the spatial distribution of Iberian dung beetle species accumulate over time?, Diversity and Distributions, 13, 6, (772-780), (2007).
- Lesley Gibson, Brent Barrett and Allan Burbidge, Dealing with uncertain absences in habitat modelling: a case study of a rare ground‐dwelling parrot, Diversity and Distributions, 13, 6, (704-713), (2007).
- BRUNO A. WALTHER, NORBERT SCHÄFFER, ADRIAAN VAN NIEKERK, WILFRIED THUILLER, CARSTEN RAHBEK and STEVEN L. CHOWN, Modelling the winter distribution of a rare and endangered migrant, the Aquatic Warbler Acrocephalus paludicola, Ibis, 149, 4, (701-714), (2007).
- D. A. Kluza, D. A. Vieglais, J. K. Andreasen and A. T. Peterson, Sudden oak death: geographic risk estimates and predictions of origins, Plant Pathology, 56, 4, (580-587), (2007).
- WESLEY M. HOCHACHKA, RICH CARUANA, DANIEL FINK, ART MUNSON, MIREK RIEDEWALD, DARIA SOROKINA and STEVE KELLING, Data‐Mining Discovery of Pattern and Process in Ecological Systems, The Journal of Wildlife Management, 71, 7, (2427-2437), (2010).
- O. Broennimann, U. A. Treier, H. Müller‐Schärer, W. Thuiller, A. T. Peterson and A. Guisan, Evidence of climatic niche shift during biological invasion, Ecology Letters, 10, 8, (701-709), (2007).
- Carlos Daniel Cadena and Bette A. Loiselle, Limits to elevational distributions in two species of emberizine finches: disentangling the role of interspecific competition, autoecology, and geographic variation in the environment, Ecography, 30, 4, (491-504), (2007).
- Jana M. McPherson and Walter Jetz, Effects of species’ ecology on the accuracy of distribution models, Ecography, 30, 1, (135-151), (2007).
- J. Andrew Royle, Marc Kéry, Roland Gautier and Hans Schmid, HIERARCHICAL SPATIAL MODELS OF ABUNDANCE AND OCCURRENCE FROM IMPERFECT SURVEY DATA, Ecological Monographs, 77, 3, (465-481), (2007).
- JASON S. McLACHLAN, JESSICA J. HELLMANN and MARK W. SCHWARTZ, A Framework for Debate of Assisted Migration in an Era of Climate Change, Conservation Biology, 21, 2, (297-302), (2007).
- ATTE MOILANEN and BRENDAN A. WINTLE, The Boundary‐Quality Penalty: a Quantitative Method for Approximating Species Responses to Fragmentation in Reserve Selection, Conservation Biology, 21, 2, (355-364), (2007).
- Frank W. Davis, Changwan Seo and William J. Zielinski, REGIONAL VARIATION IN HOME‐RANGE‐SCALE HABITAT MODELS FOR FISHER (MARTES PENNANTI) IN CALIFORNIA, Ecological Applications, 17, 8, (2195-2213), (2007).
- Ricardo Rodríguez‐Estrella, Land use changes affect distributional patterns of desert birds in the Baja California peninsula, Mexico, Diversity and Distributions, 13, 6, (877-889), (2007).
- LEIF‐MATTHIAS HERBORG, DEBORAH A. RUDNICK, YANG SILIANG, DAVID M. LODGE and HUGH J. MacISAAC, Predicting the Range of Chinese Mitten Crabs in Europe, Conservation Biology, 21, 5, (1316-1323), (2007).
- Patrick E. Osborne, Susana Suárez‐Seoane and Juan Carlos Alonso, Behavioural mechanisms that undermine species envelope models: the causes of patchiness in the distribution of great bustards Otis tarda in Spain, Ecography, 30, 6, (819-829), (2007).
- Jimmy A. McGuire, Charles W. Linkem, Michelle S. Koo, Delbert W. Hutchison, A. Kristopher Lappin, David I. Orange, Julio Lemos‐Espinal, Brett R. Riddle and Jef R. Jaeger, MITOCHONDRIAL INTROGRESSION AND INCOMPLETE LINEAGE SORTING THROUGH SPACE AND TIME: PHYLOGENETICS OF CROTAPHYTID LIZARDS, Evolution, 61, 12, (2879-2897), (2007).
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