- Top of page
- Materials and methods
- Supporting Information
Habitat suitability models (HSM) are usually produced using species presence or habitat selection to infer habitat quality (Guisan & Thuiller 2005). However, this approach does not consider demographic performance at the population level, leading to erroneous conclusions if species occurrence does not correspond to positive reproductive and survival rates (Van Horne 1983; Garshelis 2000). High quality habitats identified using species occurrence alone might actually be located in ecological sinks, areas where reproductive and/or survival rates are too low to sustain a viable population (Pulliam 1988). ‘Attractive sinks’ represent a particular case of ecological sink, with individual animals perceiving an area as good habitat even when human-related habitat conditions will ultimately reduce demographic performance (Delibes, Gaona & Ferreras 2001).
Naves et al. (2003) originally proposed the identification of attractive sink-like habitats (areas of high habitat suitability and high human-caused mortality) and of source-like habitats (areas of high habitat suitability and low human-caused mortality) using a two-dimensional habitat model. Following Naves et al. (2003), sources and sinks are hereby referred to as sink-like and source-like habitats to indicate that these categories are based on habitat models without explicit consideration of demographic features. This framework can be used to develop two complementary strategies: conservation of source-like habitats, and management of attractive sink-like habitats to mitigate mortality risks (e.g. to control accessibility to humans) or to make these areas less attractive (i.e. to decrease habitat quality). The issue is particularly relevant for species with low reproductive rates and high susceptibility to low levels of mortality, especially in human-modified landscapes (Delibes et al. 2001). The Italian endemic Apennine brown bear Ursus arctos marsicanus Altobello, 1921, clearly represents such an example.
Figure 1. Study area and location of the main protected areas: (a) subdivision of the study area in core area (Apennine brown bear core range) and marginal area; the Aterno valley and the Fucino area were excluded from the analyses; (b) location of the study area in Italy.
Download figure to PowerPoint
The Apennine brown bear is protected by law and considered critically endangered by the International Union for the Conservation of Nature (IUCN 2007). The core of the subspecies’ distribution range covers 1500–2500 km2 across the Abruzzo–Lazio–Molise National Park (PNALM) and surrounding areas (Fig. 1; Bologna & Vigna-Taglianti 1992; Posillico et al. 2004). Few indirect signs of bear presence or rare direct observations are recorded in other parts of the central Apennines (Terminillo mountains, Sirente–Velino Regional Park, Sibillini National Park, Fig. 1), most probably from dispersing individuals.
Recent HSMs suggest some 150–240 bears could theoretically live in the central Apennines (Posillico et al. 2004; Falcucci 2007). Moreover, Falcucci et al. (2008) projected that availability of suitable land-cover on a landscape scale should not be a relevant issue for bear conservation, at least up to 2020. These indications clearly support the idea that the subspecies can potentially recover in the future and occupy an area larger than the current range. However, the practical implications of these analyses for conservation planning are limited because no consideration of human-related mortality has been included.
The importance of human-related mortality is indicated by 74 bears (L. Gentile and L. Sammarone, unpublished data) killed by humans in the last 30 years in areas considered to be good habitat inside the PNALM and its buffer zone. In this context, traditional HSMs cannot provide useful indications and habitat preservation does not represent per se a sufficient solution. Proactive conservation actions aimed at reducing human-caused mortality in the core population appear to be critical and extremely urgent in order to facilitate the natural expansion of the bear population in the long term (Ciucci & Boitani 2008).
Using both occurrence data and records of human-induced mortalities, we developed a habitat-based model for distinguishing attractive sink-like and source-like habitats for the bear in the central Apennines based on Ecological Niche Factor Analysis (ENFA; Hirzel et al. 2002), providing a tool that can effectively guide conservation planning and assist management intervention on a large scale.
- Top of page
- Materials and methods
- Supporting Information
Any evaluation of habitat quality should be explicitly linked with demographic features or vital statistics (Thomas & Kunin 1999), especially for slow-reproducing species living in human-dominated landscapes (Naves et al. 2003). Since survival can vary among habitats and landscapes, relying on animal occurrence alone for the assessment of habitat quality is questionable (Van Horne 1983; Battin 2004), with the risk that attractive sinks remain undetected. From a practical conservation perspective, therefore, traditional HSMs can produce incomplete or misleading indications when the model output is integrated into conservation and management planning. Notwithstanding habitat suitability (but see Mitchell & Powell 2003), survival and long-term population dynamics of a species can be substantially affected by human-caused mortality (Treves & Karanth 2003), which may eventually drive small populations to extinction (Swenson et al. 1995). This is particularly true in the case of large carnivores living in human-dominated landscape where factors determining survival and reproduction are often unrelated or even negatively correlated (Naves et al. 2003).
Although habitat loss has often been indicated as one of the main factors potentially affecting the Apennine brown bear population (Boscagli 1999; Lorenzini et al. 2004), bear habitat availability at the landscape scale does not seems to represent a limiting factor (Posillico et al. 2004; Falcucci et al. 2008), and the same indication is given by our BO model. However, comparing our final two-dimensional model with those already available (Posillico et al. 2004; Falcucci et al. 2008; our BO model), it is clear that most of what is usually identified as suitable habitat for the bear the Apennines is actually composed of attractive sink-like habitats (43% of all the suitable in our BO model). Thus, effective control of human-related mortality should be regarded as high priority for the conservation of the bear population (Posillico et al. 2004; Ciucci & Boitani 2008). From this perspective, a habitat quality model based on demographic performance would represent a useful tool for the conservation and management of the Apennine brown bear population.
We used bear presence and mortality as a proxy of demographic performance in the absence of more detailed demographic data, assuming that human-caused bear mortalities can be used to model the effect of habitat and anthropogenic features on bear survival, and that bear presences can be used to model occurrence. The same approach, based on logistic regression functions, has already been used to identify attractive sink-like and source-like habitats for brown bears in Spain and Canada (Naves et al. 2003; Nielsen, Stenhouse & Boyce 2006). For the Apennine brown bear population, we preferred ENFA because Generalized Linear Models can be negatively affected if the modelled population has yet to reach its equilibrium density in the study area, or if its extent of occurrence is still limited compared to the available habitat (Hirzel et al. 2001). It is important to recognize, however, that a distribution model considering an area only marginally used by a species has a number of potential ecological and theoretical problems (Guisan & Thuiller 2005). In our case, no data sets on presence or mortality were available outside the core area due to the occasional and inconsistent presence of bears in the marginal area. Nevertheless, since we deemed it important to produce a model applicable to the entire bear range in the central Apennines, we performed our ENFA tests over the entire study area and we compared the BO and BM models with those developed for the core area only. In both cases, the relative importance of the predictor variables was the same, the suitability scores were highly correlated, and the values of global marginality and tolerance were very similar, clearly indicating that our core-area only models can be safely expanded to the entire study area.
Naves et al. (2003) built their two-dimensional model considering only variables related to natural resources for the model of habitat suitability and human-related variables for the mortality model. They argued that an occurrence model including both natural and human variables can potentially obscure the separation of effects on reproduction and survival. However, we followed the approach suggested by Nielsen, Stenhouse & Boyce (2006), considering both types of variables in both models. In central Italy, the interspersion of resources among artificial and natural habitats is particularly widespread and well-established (Falcucci, Maiorano & Boitani 2007), and it would be misleading to distinguish ‘pure’ human-related effects from natural ones on survival and/or habitat suitability.
Evaluation of both models was positive, even if there was weaker evidence in support of the BM model due to the low power of our test. However, the BM model was extremely stable in its predictions for increasingly smaller sample sizes, further supporting our confidence in the model itself. As no data set on demographic statistics is yet available for this bear population, no formal evaluation was possible for the two-dimensional habitat model. We therefore adopted the simplest possible approach by selecting the suitability/mortality risk threshold values, with no direct indication that this is the optimal solution for the system we analysed (Liu et al. 2005; Jiménez-Valverde & Lobo 2007). As a consequence, the classification adopted for our two-dimensional model may be susceptible to some degree of arbitrariness and, although it does provide useful management indications, we cannot claim that it is representative of the unknown underlying demographic patterns. However, indirect support for the model comes from the Velino–Sirente Regional Park (Fig. 1), the only protected area outside PNALM that has hosted at least one reproducing female and other bears over the past 10 years (P. Morini, personal communication): this area has the highest share of first-level source-like and the lowest share of first-level attractive sink-like habitat.
One limitation of our approach is that the BM model may be affected by different sources of bias. In particular, we do not expect that our sample included all human-caused bear mortalities, but we do believe that most of the bears killed in these past three decades were reported. Accordingly, we assume that the spatial pattern of mortality events is representative of the true distribution of human-induced mortality risk for the Apennine bear population. In fact, given the estimated population size of 40–50 bears (Gervasi et al. 2008), we expect the unreported proportion of human-caused bear mortality to be limited and to reflect patterns similar to the known sample. In addition, given the high social appeal of the bear among local populations, and the high human activity within the bear range (park patrolling, livestock grazing, tourism, timber harvesting, hunting, etc.), it is unlikely that killed bears go unreported for long. Moreover, our simulations to test the BM model performance showed that the model was consistent and stable over increasingly smaller sample sizes, yielding confidence in its spatial predictions. As our main aim was to provide a tool to encourage a reduction in human-caused bear mortality, the effect of potential sources of bias in our bear mortality data should be minimal and, most importantly, should not affect the habitat-specific ranking in mortality risk.
Given the limited sample size of our bear mortality data, we could not distinguish among different human-related mortality causes within attractive sink-like habitats. Moreover, we pooled all bear mortalities reported from 1980 onwards for sample size requirements, thereby equating patterns of mortality risk throughout the last 27 years. Although human-caused bear mortalities have fluctuated significantly over the past 20 years, management or control reactions to illegal mortality have not changed or intensified (Ciucci & Boitani 2008), and it can be reasonably assumed that today Apennine brown bears face similar mortality risks to those in the 1980s.
A similar problem was potentially introduced in our BO model (pooling fallacy: Schooley 1994), for which we used bear presence data collected from March to December, and for different age and sex classes. A higher resolution in our BO model could have been achieved by focusing on the most sensitive demographic vector (reproducing females) during the most critical biological season (late hyperphagia), but unfortunately no such data are yet available for our bear population. However, we are confident that the habitat quality description we achieved through the integrated BO/BM model is adequate enough to provide a meaningful improvement over previous habitat quality models.
In terms of overall habitat quality, our integrated model indicated that the core area still hosts important habitat for the Apennine brown bear, and that the marginal area comprises several unoccupied and potentially suitable areas where the population can be expected to expand in the future. However, areas of medium to high mortality risk are widespread throughout the study area (Fig. 3b), with attractive sink-like habitats being common inside and outside protected areas (Fig. 4).
We found that many areas characterized by high habitat suitability, as identified through traditional modelling (Posillico et al. 2004; Falcucci 2007; Falcucci et al. 2008; Fig. 3a), were highly interspersed with attractive sink-like habitats (Fig. 4), confirming that human-caused mortality should be regarded as the most important threat to the Apennine brown bear population (Ciucci & Boitani 2008). We consider the identification of first-level source-like and attractive sink-like habitats as an essential element of a renewed Apennine brown bear conservation strategy. Our model identifies first-level attractive sink-like habitats in the core area and along potential travel routes used by bears dispersing from the PNALM, and provides a first description of their environmental characteristics. Area-specific management interventions (patrolling, road closure, human-conflict management, threat monitoring, etc.) should be quickly implemented to prevent human-caused mortality. In this perspective, the authorities in charge will benefit from knowing the distribution of attractive sink-like habitats within their jurisdiction and the potential role they might play in maintaining large-scale habitat connectivity for the bear. On the other hand, management interventions aimed at increasing habitat attractiveness and suitability for bears (e.g. the long time feeding campaigns implemented in the PNALM; Ciucci & Boitani 2008), could obtain the opposite, unexpected result and increase susceptibility of bears to human-caused mortality if these interventions are not planned according to the distribution of mortality risk. If risk factors are not adequately mitigated, management actions focused on a specific land-cover category should not be considered as priorities for conservation given that, based on our results, first-level sink-like and source-like habitats share similar environmental characteristics. In addition, landscape patterns should be explicitly considered when targeting restoration or management areas to avoid isolation of sites within a high mortality risk matrix.
Nielsen, Stenhouse & Boyce (2006) recognized that two-dimensional modelling allows different conservation and management goals. For instance, the ‘no net loss’ of source-like habitats: if a given land-use activity ends up turning a bear habitat area into an attractive sink-like habitat, an equivalent amount of attractive sink-like area should be restored towards source-like bear habitats (e.g. deactivation and re-vegetation of roads). However, given the current situation of the Apennine brown bear population and its range (Ciucci & Boitani 2008), we believe any efforts should rather be devoted at this stage to significantly reduce the extension of attractive sink-like habitats. Especially within established protected areas like the PNALM, a management goal of ‘net loss’ in first-level attractive sink-like habitats should be promoted through proactive management intervention and effective direct control of human access and activity.