Evaluating the ability of habitat suitability models to predict species presences.

Details

Serval ID
serval:BIB_24DB4B5866C2
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Evaluating the ability of habitat suitability models to predict species presences.
Journal
Ecological Modelling.
Author(s)
Hirzel A.H., Le Lay G., Helfer V., Randin C., Guisan A.
ISSN
0304-3800
Publication state
Published
Issued date
2006
Peer-reviewed
Oui
Volume
199
Number
1
Pages
142-152
Language
english
Notes
2nd Workshop on Advances in Predictive Species Distribution Models Riederalp, SWITZERLAND, 2004
Abstract
Models predicting species spatial distribution are increasingly applied to wildlife management issues, emphasising the need for reliable methods to evaluate the accuracy of their predictions. As many available datasets (e.g. museums, herbariums, atlas) do not provide reliable information about species absences, several presence-only based analyses have been developed. However, methods to evaluate the accuracy of their predictions are few and have never been validated. The aim of this paper is to compare existing and new presenceonly evaluators to usual presence/absence measures.
We use a reliable, diverse, presence/absence dataset of 114 plant species to test how common presence/absence indices (Kappa, MaxKappa, AUC, adjusted D-2) compare to presenceonly measures (AVI, CVI, Boyce index) for evaluating generalised linear models (GLM). Moreover we propose a new, threshold-independent evaluator, which we call "continuous Boyce index". All indices were implemented in the B10MAPPER software.
We show that the presence-only evaluators are fairly correlated (p > 0.7) to the presence/absence ones. The Boyce indices are closer to AUC than to MaxKappa and are fairly insensitive to species prevalence. In addition, the Boyce indices provide predicted-toexpected ratio curves that offer further insights into the model quality: robustness, habitat suitability resolution and deviation from randomness. This information helps reclassifying predicted maps into meaningful habitat suitability classes. The continuous Boyce index is thus both a complement to usual evaluation of presence/absence models and a reliable measure of presence-only based predictions.
Keywords
niche-based modelling, model evaluation, cross-validation, generalised linear models (GLM), alpine plants, Swiss Alps
Web of science
Create date
19/11/2007 9:50
Last modification date
20/08/2019 13:03
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