Accès libre

How much is enough? Influence of number of presence observations on the performance of species distribution models

À propos de cet article

Citez

Austin, M. 2007. Species distribution models and ecological theory, a critical assessment and some possible new approaches. Ecological Modelling 200,1–19.10.1016/j.ecolmodel.2006.07.005Search in Google Scholar

Bakkestuen, V., Erikstad, L., Halvorsen, R. 2008. Step-less models for regional environmental variation in Norway. Journal of Biogeography 35,1906–1922.10.1111/j.1365-2699.2008.01941.xSearch in Google Scholar

Chapman, A. D. 2009. Numbers of living species in Australia and the world. Department of the Environment, Water, Heritage and the Arts, Canberra, Australia.Search in Google Scholar

Chefaoui, R. M., J. Hortal, and J. M. Lobo. 2005. Potential distribution modelling, niche characterization and conservation status assessment using GIS tools, a case study of Iberian Copris species. Biological conservation 122,327–338.10.1016/j.biocon.2004.08.005Search in Google Scholar

Crawley, M. J. 2013. The R book. Second edition. Wiley, Chichester, UK.Search in Google Scholar

Cumming, G. S. 2000. Using between-model comparisons to fine-tune linear models of species ranges. Journal of Biogeography 27,441–455.10.1046/j.1365-2699.2000.00408.xSearch in Google Scholar

Dupin, M., P. Reynaud, V. Jarošík, R. Baker, S. Brunel, D. Eyre, J. Pergl, and D. Makowski. 2011. Effects of the Training Dataset Characteristics on the Performance of Nine Species Distribution Models, Application to Diabrotica virgifera virgifera. PLoS ONE 6,e20957.10.1371/journal.pone.0020957Search in Google Scholar

Edvardsen, A., V. Bakkestuen, and R. Halvorsen. 2011. A fine-grained spatial prediction model for the red-listed vascular plant Scorzonera humilis. Nordic Journal of Botany 29,495–504.10.1111/j.1756-1051.2010.00984.xSearch in Google Scholar

Elith, J., C. H. Graham, R. P. Anderson, M. Dudik, S. Ferrier, A. Guisan, R. J. Hijmans, F. Huettmann, J. R. Leathwick, A. Lehmann, J. Li, L. G. Lohmann, B. A. Loiselle, G. Manion, C. Moritz, M. Nakamura, Y. Nakazawa, J. M. Overton, A. T. Peterson, S. J. Phillips, K. Richardson, R. Scachetti-Pereira, R. E. Schapire, J. Soberon, S. Williams, M. S. Wisz, and N. E. Zimmermann. 2006. Novel methods improve prediction of species’ distributions from occurrence data. Ecography 29,129–151.10.1111/j.2006.0906-7590.04596.xSearch in Google Scholar

Elith, J., S. J. Phillips, T. Hastie, M. Dudík, Y. E. Chee, and C. J. Yates. 2011. A statistical explanation of MaxEnt for ecologists. Diversity and Distributions 17,43–57.10.1111/j.1472-4642.2010.00725.xSearch in Google Scholar

Engler, R., A. Guisan, and L. Rechsteiner. 2004. An improved approach for predicting the distribution of rare and endangered species from occurrence and pseudo-absence data. Journal of Applied Ecology 41,263–274.10.1111/j.0021-8901.2004.00881.xSearch in Google Scholar

Feeley, K. J., and M. R. Silman. 2011a. The data void in modeling current and future distributions of tropical species. Global Change Biology 17,626–630.10.1111/j.1365-2486.2010.02239.xSearch in Google Scholar

Feeley, K. J., and M. R. Silman. 2011b. Keep collecting, accurate species distribution modelling requires more collections than previously thought. Diversity and Distributions 17,1132–1140.10.1111/j.1472-4642.2011.00813.xSearch in Google Scholar

Fielding, A. H., and J. F. Bell. 1997. A review of methods for the assessment of prediction errors in conservation presence/absence models. Environmental Conservation 24,38–49.10.1017/S0376892997000088Search in Google Scholar

Fitzpatrick, M. C., J. F. Weltzin, N. J. Sanders, and R. R. Dunn. 2007. The biogeography of prediction error, why does the introduced range of the fire ant over-predict its native range? Global Ecology and Biogeography 16,24–33.10.1111/j.1466-8238.2006.00258.xSearch in Google Scholar

Franklin, J. 2009. Mapping species distributions, spatial inference and prediction. Cambridge University Press, Cambridge.10.1017/CBO9780511810602Search in Google Scholar

Guisan, A., O. Broennimann, R. Engler, M. Vust, N. G. Yoccoz, A. Lehmann, and N. E. Zimmermann. 2006. Using niche-based models to improve the sampling of rare species. Conservation Biology 20,501–511.10.1111/j.1523-1739.2006.00354.xSearch in Google Scholar

Guisan, A., and W. Thuiller. 2005. Predicting species distribution, offering more than simple habitat models. Ecology letters 8,993–1009.10.1111/j.1461-0248.2005.00792.xSearch in Google Scholar

Guisan, A., and N. E. Zimmermann. 2000. Predictive habitat distribution models in ecology. Ecological Modelling 135,147–186.10.1016/S0304-3800(00)00354-9Search in Google Scholar

Guisan, A., N. E. Zimmermann, J. Elith, C. H. Graham, S. Phillips, and A. T. Peterson. 2007. What matters for predicting the occurrences of trees, Techniques, data, or species’ characteristics? Ecological Monographs 77,615–630.10.1890/06-1060.1Search in Google Scholar

Halvorsen, R. 2012. A gradient analytic perspective on distribution modelling. Sommerfeltia 35,1–165.10.2478/v10208-011-0015-3Search in Google Scholar

Halvorsen, R. 2013. A maximum likelihood explanation of MaxEnt, and some implications for distribution modelling. Sommerfeltia 36,1–165.10.2478/v10208-011-0016-2Search in Google Scholar

Hanberry, B. B., H. S. He, and D. C. Dey. 2012. Sample sizes and model comparison metrics for species distribution models. Ecological Modelling 227,29–33.10.1016/j.ecolmodel.2011.12.001Search in Google Scholar

Hastie, T., R. Tibshirani, and J. Friedman. 2009. The elements of statistical learning. Data mining, inference, and prediction. Second Edition. Springer, New York.10.1007/978-0-387-84858-7Search in Google Scholar

Hernandez, P. A., C. H. Graham, L. L. Master, and D. L. Albert. 2006. The effect of sample size and species characteristics on performance of different species distribution modeling methods. Ecography 29,773–785.10.1111/j.0906-7590.2006.04700.xSearch in Google Scholar

IUCN. 2001. IUCN Red List categories and criteria, version 3.1. IUCN (International Union for Conservation of Nature, Gland, Switzerland.Search in Google Scholar

Jaynes, E. T. 1957a. Information theory and statistical mechanics. Physical Review 106,620–630.10.1103/PhysRev.106.620Search in Google Scholar

Jaynes, E. T. 1957b. Information theory and statistical mechanics 2. Physical Review 108,171–190.10.1103/PhysRev.108.171Search in Google Scholar

Kadmon, R., O. Farber, and A. Danin. 2003. A systematic analysis of factors affecting the performance of climatic envelope models. Ecological Applications 13,853–867.10.1890/1051-0761(2003)013[0853:ASAOFA]2.0.CO;2Search in Google Scholar

Kamino, L. H. Y., J. R. Stehmann, S. Amaral, P. De Marco, T. F. Rangel, M. F. de Siqueira, R. De Giovanni, and J. Hortal. 2012. Challenges and perspectives for species distribution modelling in the neotropics. Biology Letters 8,324–326.10.1098/rsbl.2011.0942Search in Google Scholar

Kålås, J. A., Å. Viken, S. Henriksen, S. Skjelseth, and (Eds.). 2010. The 2010 Norwegian Red List for Species. Norwegian Biodiversity Information Centre, Trondheim, Norway.Search in Google Scholar

Le Lay, G., R. Engler, E. Franc, and A. Guisan. 2010. Prospective sampling based on model ensembles improves the detection of rare species. Ecography 33,1015–1027.10.1111/j.1600-0587.2010.06338.xSearch in Google Scholar

Lim, B. K., A. T. Peterson, and M. D. Engstrom. 2002. Robustness of ecological niche modeling algorithms for mammals in Guyana. Biodiversity and Conservation 11,1237–1246.10.1023/A:1016038501986Search in Google Scholar

Lobo, J. M., A. Jiménez-Valverde, and J. Hortal. 2010. The uncertain nature of absences and their importance in species distribution modelling. Ecography 33,103–114.10.1111/j.1600-0587.2009.06039.xSearch in Google Scholar

Loe, L. E., C. Bonenfant, E. L. Meisingset, and A. Mysterud. 2012. Effects of spatial scale and sample size in GPS-based species distribution models, are the best models trivial for red deer management? European Journal of Wildlife Research 58,195–203.10.1007/s10344-011-0563-5Search in Google Scholar

Lomba, A., L. Pellissier, C. Randin, J. Vicente, F. Moreira, J. Honrado, and A. Guisan. 2010. Overcoming the rare species modelling paradox, a novel hierarchical framework applied to an Iberian endemic plant. Biological conservation 143,2647–2657.10.1016/j.biocon.2010.07.007Search in Google Scholar

López-Cárdenas, J., F. E. G. Bravo, P. M. S. Schettino, J. C. G. Solorzano, E. R. Barba, J. M. Mendez, V. Sánchez-Cordero, A. T. Peterson, and J. Ramsey. 2005. Fine-scale predictions of distributions of Chagas disease vectors in the state of Guanajuato, Mexico. Journal of medical entomology 42,1068–1081.10.1603/0022-2585(2005)042[1068:FPODOC]2.0.CO;2Search in Google Scholar

Marini, M., M. Barbet-Massin, L. Lopes, and F. Jiguet. 2010. Predicting the occurrence of rare Brazilian birds with species distribution models. Journal of Ornithology 151,857–866.10.1007/s10336-010-0523-ySearch in Google Scholar

Mateo, R. G., A. M. Felicísimo, and J. Muñoz. 2010. 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 21,908–922.10.1111/j.1654-1103.2010.01198.xSearch in Google Scholar

Meggs, J. M., S. A. Munks, R. Corkrey, and K. Richards. 2004. Development and evaluation of predictive habitat models to assist the conservation planning of a threatened lucanid beetle, Hoplogonus simsoni, in north-east Tasmania. Biological conservation 118,501–511.10.1016/j.biocon.2003.10.001Search in Google Scholar

Moen, A. 1999. National atlas of Norway, Vegetation. Norwegian Mapping Authority, Hønefoss.Search in Google Scholar

New, T. R. 2009. Insect species conservation. Cambridge University Press, Cambridge, UK.Search in Google Scholar

Papeş, M., and P. Gaubert. 2007. 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 13,890–902.10.1111/j.1472-4642.2007.00392.xSearch in Google Scholar

Pearce, J., and S. Ferrier. 2000. Evaluating the predictive performance of habitat models developed using logistic regression. Ecological Modelling 133,225–245.10.1016/S0304-3800(00)00322-7Search in Google Scholar

Pearson, R. G., C. J. Raxworthy, M. Nakamura, and A. T. Peterson. 2007. Predicting species distributions from small numbers of occurrence records, a test case using cryptic geckos in Madagascar. Journal of Biogeography 34,102–117.10.1111/j.1365-2699.2006.01594.xSearch in Google Scholar

Peterson, A. T., C. Martínez-Campos, Y. Nakazawa, and E. Martínez-Meyer. 2005. Time-specific ecological niche modeling predicts spatial dynamics of vector insects and human dengue cases. Transactions of the Royal Society of Tropical Medicine and Hygiene 99,647–655.10.1016/j.trstmh.2005.02.004Search in Google Scholar

Peterson, A. T., J. Soberón, R. G. Pearson, R. P. Anderson, E. Martínez-Meyer, M. Nakamura, and M. B. Araújo. 2011. Ecological niches and geographic distributions. Princeton University Press, Princeton and Oxford.10.23943/princeton/9780691136868.003.0003Search in Google Scholar

Phillips, S. J., R. P. Anderson, and R. E. Schapire. 2006. Maximum entropy modeling of species geographic distributions. Ecological Modelling 190,231–259.10.1016/j.ecolmodel.2005.03.026Search in Google Scholar

Phillips, S. J., and M. Dudík. 2008. Modeling of species distributions with Maxent, new extensions and a comprehensive evaluation. Ecography 31,161–175.10.1111/j.0906-7590.2008.5203.xSearch in Google Scholar

Phillips, S. J., M. Dudík, and R. E. Schapire. 2004. A maximum entropy approach to species distribution modeling.in Proceedings of the twenty-first international conference on machine learning. ACM, New York.10.1145/1015330.1015412Search in Google Scholar

Raes, N., and H. ter Steege. 2007. A null-model for significance testing of presence-only species distribution models. Ecography 30,727–736.10.1111/j.2007.0906-7590.05041.xSearch in Google Scholar

Rebelo, H., and G. Jones. 2010. Ground validation of presence-only modelling with rare species, a case study on barbastelles Barbastella barbastellus (Chiroptera, Vespertilionidae). Journal of Applied Ecology 47,410–420.10.1111/j.1365-2664.2009.01765.xSearch in Google Scholar

Reese, G. C., K. R. Wilson, J. A. Hoeting, and C. H. Flather. 2005. Factors affecting species distribution predictions, A simulation modeling experiment. Ecological Applications 15,554–564.10.1890/03-5374Search in Google Scholar

Renner, I. W., and D. I. Warton. 2013. Equivalence of MAXENT and Poisson point process models for species distribution modeling in ecology. Biometrics 69,274–281.10.1111/j.1541-0420.2012.01824.xSearch in Google Scholar

Roura-Pascual, N., A. V. Suarez, C. Gómez, P. Pons, Y. Touyama, A. L. Wild, and A. T. Peterson. 2004. Geographical potential of Argentine ants (Linepithema humile Mayr) in the face of global climate change. Proceedings of the Royal Society of London. Series B, Biological Sciences 271,2527–253510.1098/rspb.2004.2898169189915615677Search in Google Scholar

SPWG. 2006. Guidelines for Using the IUCN Red List Categories and Criteria. Version 6.2. IUCN Gland, Switzerland; Cambridge, UK.Search in Google Scholar

Stockwell, D. R. B., and A. T. Peterson. 2002. Effects of sample size on accuracy of species distribution models. Ecological Modelling 148,1–13.10.1016/S0304-3800(01)00388-XSearch in Google Scholar

Stokland, J. N., R. Halvorsen, and B. Støa. 2011. Species distribution modelling—Effect of design and sample size of pseudo-absence observations. Ecological Modelling 222,1800–1809.10.1016/j.ecolmodel.2011.02.025Search in Google Scholar

Tibshirani, R. 1996. Regression shrinkage and selection via the lasso. Journal of the Royal Statistical Society. Series B (Methodological),267–288.10.1111/j.2517-6161.1996.tb02080.xSearch in Google Scholar

Van der Vaart, A. W. 1998. Asymptotic statistics. Cambridge University Press, Cambridge, UK.10.1017/CBO9780511802256Search in Google Scholar

Veloz, S. 2009. Spatially autocorrelated sampling falsely inflates measures of accuracy for presence-only niche models. Journal of Biogeography 36,2290–2299.10.1111/j.1365-2699.2009.02174.xSearch in Google Scholar

Whittaker, R. H. 1956. Vegetation of the great smoky mountains. Ecological Monographs 26,1–80.10.2307/1943577Search in Google Scholar

Wisz, M. S., R. J. Hijmans, J. Li, A. T. Peterson, C. H. Graham, and A. Guisan. 2008. Effects of sample size on the performance of species distribution models. Diversity and Distributions 14,763–773.10.1111/j.1472-4642.2008.00482.xSearch in Google Scholar

Wollan, A. K., V. Bakkestuen, H. Kauserud, G. Gulden, and R. Halvorsen. 2008. Modelling and predicting fungal distribution patterns using herbarium data. Journal of Biogeography 35,2298–2310.10.1111/j.1365-2699.2008.01965.xSearch in Google Scholar

eISSN:
2084-0098
Langue:
Anglais
Périodicité:
Volume Open
Sujets de la revue:
Life Sciences, Plant Science, Ecology, other