Using virtual species to study species distributions and model performance

Journal of Biogeography

Volumn 40, Issue 1, 2013, Pages 1-8

  Meynard, Christine N ^a   Kaplan, David M ^a  

^a INSTITUT DE RECHERCHE POUR LE DÉVELOPPEMENT   (France)

Author keywords

AUC; Predictive ecology; Presence absence; Prevalence; Sensitivity; Simulations; Specificity; Threshold; Virtual species

Indexed keywords

EID: 84871289035     PISSN: 03050270     EISSN: 13652699     Source Type: Journal    
DOI: 10.1111/jbi.12006     Document Type: Editorial

References (26)

1. Albert, C.H. & Thuiller, W. (2008) Favourability functions versus probability of presence: advantages and misuses. Ecography, 31, 417-422.
2. Barbet-Massin, M., Jiguet, F., Albert, C.H. & Thuiller, W. (2012) Selecting pseudo-absences for species distribution models: how, where and how many? Methods in Ecology and Evolution, 3, 327-338.
3. Bombi, P. & D'Amen, M. (2012) Scaling down distribution maps from atlas data: a test of different approaches with virtual species. Journal of Biogeography, 39, 640-651.
4. Elith, J. & Graham, C.H. (2009) Do they? How do they? WHY do they differ? On finding reasons for differing performances of species distribution models. Ecography, 32, 66-77.
5. Elith, J. & Leathwick, J.R. (2009) Species distribution models: ecological explanation and prediction across space and time. Annual Review of Ecology, Evolution, and Systematics, 40, 677-697.
6. Franklin, J. (2009) Mapping species distributions: spatial inference and prediction. Cambridge University Press, Cambridge, UK.
7. Guisan, A. & Thuiller, W. (2005) Predicting species distribution: offering more than simple habitat models. Ecology Letters, 8, 993-1009.
8. Hanski, I. (1999) Metapopulation ecology. Oxford University Press, New York.
9. Hirzel, A.H., Helfer, V. & Metral, F. (2001) Assessing habitat-suitability models with a virtual species. Ecological Modelling, 145, 111-121.
10. Holyoak, M., Leibold, M.A., Mouquet, N.M., Holt, R.D. & Hoopes, M.F. (2005) Metacommunities: a framework for large-scale community ecology. Metacommunities: spatial dynamics and ecological communities (ed. by M. Holyoak, M.A. Leibold and R.D. Holt), pp. 1-31. University of Chicago Press, Chicago.
11. Jiménez-Valverde, A. & Lobo, J.M. (2007) Threshold criteria for conversion of probability of species presence to either-or presence-absence. Acta Oecologica - International Journal of Ecology, 31, 361-369.
12. Jiménez-Valverde, A., Lobo, J.M. & Hortal, J. (2009) The effect of prevalence and its interaction with sample size on the reliability of species distribution models. Community Ecology, 10, 196-205.
13. Li, W., Guo, Q. & Elkan, C. (2011) Can we model the probability of presence of species without absence data? Ecography, 34, 1096-1105.
14. Liu, C.R., Berry, P.M., Dawson, T.P. & Pearson, R.G. (2005) Selecting thresholds of occurrence in the prediction of species distributions. Ecography, 28, 385-393.
15. Lobo, J.M. & Tognelli, M.F. (2011) Exploring the effects of quantity and location of pseudo-absences and sampling biases on the performance of distribution models with limited point occurrence data. Journal for Nature Conservation, 19, 1-7.
16. Meynard, C.N. & Kaplan, D.M. (2012) The effect of a gradual response to the environment on species distribution modeling performance. Ecography, 35, 468-480.
17. Meynard, C.N. & Quinn, J.F. (2007) Predicting species distributions: a critical comparison of the most common statistical models using artificial species. Journal of Biogeography, 34, 1455-1469.
18. Peterson, A.T. (2011) Ecological niche conservatism: a time-structured review of evidence. Journal of Biogeography, 38, 817-827.
19. R Development Core Team (2011) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria.
20. Real, R., Barbosa, A.M. & Vargas, J.M. (2006) Obtaining environmental favourability functions from logistic regression. Environmental and Ecological Statistics, 13, 237-245.
21. Santika, T. (2011) Assessing the effect of prevalence on the predictive performance of species distribution models using simulated data. Global Ecology and Biogeography, 20, 181-192.
22. Santika, T. & Hutchinson, M.F. (2009) The effect of species response form on species distribution model prediction and inference. Ecological Modelling, 220, 2365-2379.
23. Venables, W.N. & Ripley, B.D. (2002) Modern applied statistics with S, 4th edn. Springer-Verlag, New York.
24. Ward, G., Hastie, T., Barry, S., Elith, J. & Leathwick, J.R. (2009) Presence-only data and the EM algorithm. Biometrics, 65, 554-563.
25. Warren, D.L., Glor, R.E. & Turelli, M. (2008) Environmental niche equivalency versus conservatism: quantitative approaches to niche evolution. Evolution, 62, 2868-2883.
26. Zurell, D., Berger, U., Cabral, J.S., Jeltsch, F., Meynard, C.N., Munkemuller, T., Nehrbass, N., Pagel, J., Reineking, B., Schroder, B. & Grimm, V. (2010) The virtual ecologist approach: simulating data and observers. Oikos, 119, 622-635.