Species distribution modelling and imperfect detection: comparing occupancy versus consensus methods. Issue 8 (26th March 2013)

• Record Type: Journal Article
• Authors: Comte, Lise; Grenouillet, Gaël; Robertson, Mark
• Is Part Of: Diversity & distributions. Volume 19:Issue 8(2013)
• Page Start: 996
• Page End: 1007
• Publication Date: 2013-03-26
• Subjects: Biodiversity -- Periodicals; Biodiversity conservation -- Periodicals; 577
• DOI: 10.1111/ddi.12078
• Languages: English
• ISSNs: 1366-9516

Abstract

<abstract abstract-type="main" id="ddi12078-abs-0001"> <title>Abstract</title> <sec id="ddi12078-sec-0001" sec-type="section"> <title>Aim</title> <p>We assessed the influence of species non‐detection in modelling species distributions with an ensemble consensus approach that did not account for imperfect detection, compared with an occupancy model that did.</p> </sec> <sec id="ddi12078-sec-0002" sec-type="section"> <title>Location</title> <p>The hydrographic network of France.</p> </sec> <sec id="ddi12078-sec-0003" sec-type="section"> <title>Methods</title> <p>We compared range maps of 35 stream fish species with differing degrees of detectability predicted using a consensus approach combining eight species distribution models (SDMs) to maps produced using an occupancy model. Using a spatially and temporally extensive monitoring database of fish populations (France), we modelled the occurrence of species as a function of several climatic and habitat variables and projected species distributions across the whole of the French hydrographic network. The benefits of occupancy models were then assessed from the differences in both predictive performance and species distribution.</p> </sec> <sec id="ddi12078-sec-0004" sec-type="section"> <title>Results</title> <p>We found that although the occupancy models enhanced the performance for difficult to detect species, consensus models outperformed occupancy models for highly detectable species. In contrast to the minor differences observed in performance measures, estimates of species distributions were severely affected by whether or not imperfect detection was accounted for and varied linearly according to species detectability.</p> </sec> <sec id="ddi12078-sec-0005" sec-type="section"> <title>Main conclusions</title> <p>This study demonstrated that false absences could have major consequences in estimating species distribution ranges. However, accounting for imperfect detection may not be enough to improve conventional SDMs. These findings could have important implications for conservation, notably in developing large‐scale distribution models and documenting species range shifts in the context of recent climate change.</p> </sec> </abstract>