%0 Journal Article %1 Hirzel2006 %A Hirzel, Alexandre H. %A Le Lay, Gwenaëlle %A Helfer, Véronique %A Randin, Christophe %A Guisan, Antoine %B Predicting Species Distributions - Results from a Second Workshop on Advances in Predictive Species Distribution Models, held in Riederalp, Switzerland, 2004 %D 2006 %J Ecological Modelling %K methods Niche-basedmodelling Kappastatistics continuousBoyceindex AUC validation Modelevaluation SwissAlps Generalisedlinearmodels(GLM) Alpineplants Cross-validation %N 2 %P 142--152 %T Evaluating the ability of habitat suitability models to predict species presences %U http://www.sciencedirect.com/science/article/B6VBS-4KBVX0S-1/2/53fbe6932771351ec3fcdd56132314d8 %V 199 %X 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 presence-only 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 D2) compare to presence-only 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 BIOMAPPER software. We show that the presence-only evaluators are fairly correlated (rho > 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-to-expected 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.

@article{Hirzel2006, 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 presence-only 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 D2) compare to presence-only 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 BIOMAPPER software. We show that the presence-only evaluators are fairly correlated ([rho] > 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-to-expected 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.}, added-at = {2010-01-14T17:46:02.000+0100}, author = {Hirzel, Alexandre H. and Le Lay, Gwenaëlle and Helfer, Véronique and Randin, Christophe and Guisan, Antoine}, biburl = {https://www.bibsonomy.org/bibtex/2df965eaf124845abcaedcbb37649ce33/uvesco}, booktitle = {Predicting Species Distributions - Results from a Second Workshop on Advances in Predictive Species Distribution Models, held in Riederalp, Switzerland, 2004}, file = {:Hirzel2006.pdf:PDF}, interhash = {ae81cda0fd3965161e7273b62a4d8b78}, intrahash = {df965eaf124845abcaedcbb37649ce33}, issn = {0304-3800}, journal = {Ecological Modelling}, keywords = {methods Niche-basedmodelling Kappastatistics continuousBoyceindex AUC validation Modelevaluation SwissAlps Generalisedlinearmodels(GLM) Alpineplants Cross-validation}, month = {#nov#}, note = {2review}, number = 2, pages = {142--152}, timestamp = {2010-01-14T17:46:02.000+0100}, title = {Evaluating the ability of habitat suitability models to predict species presences}, url = {http://www.sciencedirect.com/science/article/B6VBS-4KBVX0S-1/2/53fbe6932771351ec3fcdd56132314d8}, volume = 199, year = 2006 }