SEARCH

SEARCH BY CITATION

References

  • Akaike, H. (1974) A new look at statistical model identification. IEEE Transactions on Automatic Control, AU-19, 716722.
  • Austin, M.P. (2002) Spatial prediction of species distribution: an interface between ecological theory and statistical modelling. Ecological Modelling, 157, 101118.
  • Barry, S.C. & Elith, J. (2006) Error and uncertainty in habitat models. Journal of Applied Ecology, 43, 413423.
  • Carnaval, A.C. & Moritz, C. (2008) Historical climate modelling predicts patterns of current biodiversity in the Brazilian Atlantic forest. Journal of Biogeography, 35, 11871201.
  • Chefaoui, R.M. & Lobo, J.M. (2007) Assessing the effects of pseudo-absences on predictive distribution model performance. Ecological Modelling, 210, 478486.
  • Cordellier, M. & Pfenninger, M. (2009) Inferring the past to predict the future: climate modelling predictions and phylogeography for the freshwater gastropod Radix balthica (Pulmonata, Basommatophora). Molecular Ecology, 18, 534544.
  • Della Pietra, S., Della Pietra, V. & Lafferty, J. (1997) Inducing features of random fields. IEEE Transactions on Pattern Analysis and Machine Intelligence, 19, 113.
  • Dormann, C.F. (2007) Promising the future? Global change projections of species distributions Basic and Applied Ecology, 8, 387397.
  • Dudík, M., Schapire, R.E. & Phillips, S.J. (2006) Correcting sample selection bias in maximum entropy density estimation. Advances in neural information processing systems 18: proceedings of the 2005 conference, pp. 323330. MIT Press, Cambridge, MA.
  • Elith, J. & Leathwick, J.R. (2009a) Species distribution models: ecological explanation and prediction across space and time. Annual Review of Ecology, Evolution and Systematics, 40, 677697.
  • Elith, J. & Leathwick, J.R. (2009b) The contribution of species distribution modelling to conservation prioritization. Spatial Conservation Prioritization: Quantitative Methods & Computational Tools (ed. by A.Moilanen, K.A.Wilson and H.P.Possingham), pp. 7093, Oxford University Press, Oxford, UK.
  • Elith, J., Graham, C.H., Anderson, R.P. et al. (2006) Novel methods improve prediction of species’ distributions from occurrence data. Ecography, 29, 129151.
  • Elith, J., Kearney, M. & Phillips, S.J. (2010) The art of modelling range-shifting species. Methods in Ecology and Evolution, 1, 330342.
  • Franklin, J. (2009) Mapping species distributions: spatial inference and prediction. Cambridge University Press, Cambridge, UK.
  • Graham, C.H. & Hijmans, R.J. (2006) A comparison of methods for mapping species ranges and species richness. Global Ecology & Biogeography, 15, 578.
  • Hastie, T., Tibshirani, R. & Friedman, J.H. (2009) The elements of statistical learning: data mining, inference, and prediction, 2nd edn. Springer-Verlag, New York.
  • Hirzel, A.H. & Le Lay, G. (2008) Habitat suitability modelling and niche theory. Journal of Applied Ecology, 45, 13721381.
  • Jiménez-Valverde, A., Lobo, J.M. & Hortal, J. (2008) Not as good as they seem: the importance of concepts in species distribution modelling. Diversity and Distributions, 14, 885890.
  • Keating, K.A. & Cherry, S. (2004) Use and interpretation of logistic regression in habitat selection studies. Journal of Wildlife Management, 68, 774789.
  • Kharouba, H.M., Algar, A.C. & Kerr, J.T. (2009) Historically calibrated predictions of butterfly species’ range shift using global change as a pseudo-experiment. Ecology, 90, 22132222.
  • Lamb, J.M., Ralph, T.M.C., Goodman, S.M., Bogdanowicz, W., Fahr, J., Gajewska, M., Bates, P.J.J., Eger, J., Benda, P. & Taylor, P.J. (2008) Phylogeography and predicted distribution of African-Arabian and Malagasy populations of giant mastiff bats, Otomops spp. (Chiroptera : Molossidae). Acta Chiropterologica, 10, 2140.
  • Leathwick, J.R. (1998) Are New Zealand’s Nothofagus species in equilibrium with their environment? Journal of Vegetation Science, 9, 719732.
  • Lintermans, M.. (2000) The status of fish in the Australian capital territory: a review of current knowledge and management requirements. Technical Report No. 15, Environment ACT, Canberra.
  • Lobo, J.M., Jiménez-Valverde, A. & Hortal, J. (2010) The uncertain nature of absences and their importance in species distribution modelling. Ecography, 33, 103114.
  • MacKenzie, D.I. (2005) Was it there? Dealing with imperfect detection for species presence/absence data. Australia and New Zealand Journal of Statistics, 47, 6574.
  • MacKenzie, D.I. & Royle, J.A. (2005) Designing efficient occupancy studies: general advice and tips on allocation of survey effort. Journal of Applied Ecology, 42, 11051114.
  • Monterroso, P., Brito, J.C., Ferreras, P. & Alves, P.C. (2009) Spatial ecology of the European wildcat in a Mediterranean ecosystem: dealing with small radio-tracking datasets in species conservation. Journal of Zoology, 279, 2735.
  • Murray-Smith, C., Brummitt, N.A., Oliveira-Filho, A.T., Bachman, S., Moat, J., Lughadha, E.M.N. & Lucas, E.J. (2009) Plant diversity hotspots in the Atlantic coastal forests of Brazil. Conservation Biology, 23, 151163.
  • Newbold, T. (2010) Applications and limitations of museum data for conservation and ecology, with particular attention to species distribution models. Progress in Physical Geography, 34, 322.
  • Pearce, J.L. & Boyce, M.S. (2006) Modelling distribution and abundance with presence-only data. Journal of Applied Ecology, 43, 405412.
  • Pearson, R.G., Raxworthy, C.J., Nakamura, M. & Townsend Peterson, A. (2007) Predicting species distributions from small numbers of occurrence records: a test case using cryptic geckos in Madagascar. Journal of Biogeography, 34, 102117.
  • Phillips, S.J. & Dudík, M. (2008) Modeling of species distributions with Maxent: new extensions and a comprehensive evaluation. Ecography, 31, 161175.
  • Phillips, S.J., Anderson, R.P. & Schapire, R.E. (2006) Maximum entropy modeling of species geographic distributions. Ecological Modelling, 190, 231259.
  • Phillips, S.J., Dudík, M., Elith, J., Graham, C.H., Lehmann, A., Leathwick, J. & Ferrier, S. (2009) Sample selection bias and presence-only distribution models: implications for background and pseudo-absence data. Ecological Applications, 19, 181197.
  • Rabinowitz, D., Cairns, S. & Dillon, T. (1986) Seven forms of rarity and their frequency in the flora of the British Isles. Conservation biology: the science of scarcity and diversity (ed. by M.E.Soulé), pp. 182204, Sinauer Associates, Sunderland, Massachusetts, USA.
  • Real, R., Barbosa, A.M. & Vargas, J.M. (2006) Obtaining environmental favourability functions from logistic regression. Environmental and Ecological Statistics, 13, 237245.
  • Schulman, L., Toivonen, T. & Ruokolainen, K. (2007) Analysing botanical collecting effort in Amazonia and correcting for it in species range estimation. Journal of Biogeography, 34, 13881399.
  • Soberón, J. & Nakamura, M. (2009) Niches and distributional areas: concepts, methods, and assumptions. Proceedings of the National Academy of Sciences USA, 106, 1964419650.
  • Soberón, J.M. & Peterson, A.T. (2005) Interpretation of models of fundamental ecological niches and species’ distributional areas. Biodiversity Informatics, 2, 110.
  • Solomon, S., Qin, D., Manning, M., Chen, Z., Marquis, M., Averyt, K.D., Tignor, M. & Miller, H.L. (eds) (2007) Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change.
  • Svenning, J.C. & Skov, F. (2004) Limited filling of the potential range in European tree species. Ecology Letters, 7, 565573.
  • Taylor, A. & Hopper, S.D. (1988) The Banksia atlas. AGPS, Canberra, ACT.
  • Tibshirani, R. (1996) Regression shrinkage and selection via the lasso. Journal of the Royal Statistical Society Series B, 58, 267288.
  • Tinoco, B.A., Astudillo, P.X., Latta, S.C. & Graham, C.H. (2009) Distribution, ecology and conservation of an endangered Andean hummingbird: the Violet-throated Metaltail (Metallura baroni). Bird Conservation International, 19, 6376.
  • Tittensor, D.P., Baco, A.R., Brewin, P.E., Clark, M.R., Consalvey, M., Hall-Spencer, J., Rowden, A.A., Schlacher, T., Stocks, K.I. & Rogers, A.D. (2009) Predicting global habitat suitability for stony corals on seamounts. Journal of Biogeography, 36, 11111128.
  • Tognelli, M.F., Roig-Junent, S.A., Marvaldi, A.E., Flores, G.E. & Lobo, J.M. (2009) An evaluation of methods for modelling distribution of Patagonian insects. Revista Chilena De Historia Natural, 82, 347360.
  • VanDerWal, J., Shoo, L.P., Graham, C. & Williams, S.E. (2009) Selecting pseudo-absence data for presence-only distribution modeling: how far should you stray from what you know? Ecological Modelling, 220, 589594.
  • Verbruggen, H., Tyberghein, L., Pauly, K., Vlaeminck, C., Van Nieuwenhuyze, K., Kooistra, W., Leliaert, F. & De Clerck, O. (2009) Macroecology meets macroevolution: evolutionary niche dynamics in the seaweed Halimeda. Global Ecology and Biogeography, 18, 393405.
  • Wang, Y., Xie, B., Wan, F., Xiao, Q. & Dai, L. (2007) The potential geographic distribution of Radopholus similis in China. Agricultural Sciences in China, 6, 14441449.
  • Ward, D. (2007a) Modelling the potential geographic distribution of invasive ant species in New Zealand. Biological Invasions, 9, 723735.
  • Ward, G. (2007b) Statistics in ecological modeling; presence-only data and boosted mars. Stanford University, Palo Alto.
  • Ward, G., Hastie, T., Barry, S.C., Elith, J. & Leathwick, J.R. (2009) Presence-only data and the EM algorithm. Biometrics, 65, 554563.
  • Williams, J.N., Seo, C.W., Thorne, J., Nelson, J.K., Erwin, S., O’Brien, J.M. & Schwartz, M.W. (2009) Using species distribution models to predict new occurrences for rare plants. Diversity and Distributions, 15, 565576.
  • Wintle, B.A., McCarthy, M.A., Parris, K.M. & Burgman, M.A. (2004) Precision and bias of methods for estimating point survey detection probabilities. Ecological Applications, 14, 703712.
  • Wollan, A.K., Bakkestuen, V., Kauserud, H., Gulden, G. & Halvorsen, R. (2008) Modelling and predicting fungal distribution patterns using herbarium data. Journal of Biogeography, 35, 22982310.
  • Yates, C., McNeill, A., Elith, J. & Midgley, G. (2010) Assessing the impacts of climate change and land transformation on Banksia in the South West Australian Floristic Region. Diversity and Distributions, 16, 187201.
  • Yesson, C. & Culham, A. (2006) A phyloclimatic study of Cyclamen. BMC Evolutionary Biology, 6, 7295.
  • Young, B.F., Franke, I., Hernandez, P.A., Herzog, S.K., Paniagua, L., Tovar, C. & Valqui, T. (2009) Using spatial models to predict areas of endemism and gaps in the protection of Andean slope birds. Auk, 126, 554565.
  • Zadrozny, B. (2004) Learning and evaluating classifiers under sample selection bias. In Proceedings of the Twenty-First International Conference on Machine Learning, pp. 903–910. Association for Computing Machinery, New York, USA.