Characterising a species’ geographical range extent is central to many conservation assessments, including those of the International Union for Conservation of Nature’s (IUCN) Red List of Threatened Species. The IUCN currently recommends that extent of occurrence (EOO) is quantified by drawing a minimum convex polygon around known or inferred species localities. Rarely do these assessments incorporate information from species distribution models (SDMs), despite major advances in the modelling techniques in recent years. A key impediment to this stems from uncertainty about how SDM predictions relate to EOO, especially when data are scarce. By comparing EOOs of Costa Rican and Panamanian plants derived from specimen localities with those generated by SDMs, we show that modelling provide useful information which could be used to complement the present process of IUCN Red List assessments1. We have also shown that MaxEnt, one of the most common approaches for modelling species distributions, performs much better if a sampling bias grid is included in the analyses2
- Syfert, M.M., Joppa, L., Smith,M.J., Coomes,D.A. Bachman, S.P., Brummitt, N.A. (in review) Applying species distribution models to help inform IUCN Red List assessments. Conservation Biology
- Syfert, M.M., Smith, M.J., Coomes, D.A. (2013) The effects of sampling bias and model complexity on the predictive performance of MaxEnt species distribution models. PLoS ONE 8(2): e55158. DOI link
We have used SDMs to understand niche differentiation of Tree ferns over evolutionary timescales.