Modeling the potential area of occupancy at fine resolution may reduce uncertainty in species range estimates

• Published in: Biological Conservation
• Main Authors: Jiménez-Alfaro, Borja, Draper, David, Nogues, David Bravo
• Format: Article in Journal/Newspaper
• Language: English
• Published: 2012
• Subjects: Empetrum nigrum
• Online Access: https://curis.ku.dk/portal/da/publications/modeling-the-potential-area-of-occupancy-at-fine-resolution-may-reduce-uncertainty-in-species-range-estimates(263e9eab-b9ab-45a8-93af-df73b6a38a0c).html; https://doi.org/10.1016/j.biocon.2011.12.030; http://www.sciencedirect.com/science/article/pii/S0006320711004939

Area of Occupancy (AOO), is a measure of species geographical ranges commonly used for species red listing. In most cases, AOO is estimated using reported localities of species distributions at coarse grain resolution, providing measures subjected to uncertainties of data quality and spatial resolution. To illustrate the ability of fine-resolution species distribution models for obtaining new measures of species ranges and their impact in conservation planning, we estimate the potential AOO of an endangered species in alpine environments. We use field occurrences of relict Empetrum nigrum and maximum entropy modeling to assess whether different sampling (expert versus systematic surveys) may affect AOO estimates based on habitat suitability maps, and the differences between such measurements and traditional coarse-grid methods. Fine-scale models performed robustly and were not influenced by survey protocols, providing similar habitat suitability outputs with high spatial agreement. Model-based estimates of potential AOO were significantly smaller than AOO measures obtained from coarse-scale grids, even if the first were obtained from conservative thresholds based on the Minimal Predicted Area (MPA). As defined here, the potential AOO provides spatially-explicit measures of species ranges which are permanent in the time and scarcely affected by sampling bias. The overestimation of these measures may be reduced using higher thresholds of habitat suitability, but standard rules as the MPA permit comparable measures among species. We conclude that estimates of AOO based on fine-resolution distribution models are more robust tools for risk assessment than traditional systems, allowing a better understanding of species ranges at habitat level.