Predictive performance of plant species distribution models depends on species traits
Publikation: Beiträge in Zeitschriften › Zeitschriftenaufsätze › Forschung
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in: Perspectives in Plant Ecology, Evolution and Systematics, Jahrgang 12, Nr. 3, 01.08.2010, S. 219-225.
Publikation: Beiträge in Zeitschriften › Zeitschriftenaufsätze › Forschung
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TY - JOUR
T1 - Predictive performance of plant species distribution models depends on species traits
AU - Hanspach, Jan
AU - Kühn, Ingolf
AU - Pompe, Sven
AU - Klotz, Stefan
N1 - Copyright 2010 Elsevier B.V., All rights reserved.
PY - 2010/8/1
Y1 - 2010/8/1
N2 - Predictive species distribution models are standard tools in ecological research and are used to address a variety of applied and conservation related issues. When making temporal or spatial predictions, uncertainty is inevitable and prediction errors may depend not only on data quality and the modelling algorithm used, but on species characteristics. Here, we applied a standard distribution modelling technique (generalized linear models) using European plant species distribution data and climatic parameters. Predictive performance was calculated using AUC, (Cohen's) Kappa and true skill statistic (TSS), that were subsequently correlated with biological and life-history traits. After accounting for phylogenetic dependence among species, model performance was poorest for species having a short life span and occurring in human disturbed habitats. Our results clearly indicate that the performance of distribution models can be dependent on functional traits and provide further evidence that a species' ecology is likely to affect the ability of models to predict its distribution. Biased and less reliable predictions could misguide policy decisions and the management and conservation of our natural heritage.
AB - Predictive species distribution models are standard tools in ecological research and are used to address a variety of applied and conservation related issues. When making temporal or spatial predictions, uncertainty is inevitable and prediction errors may depend not only on data quality and the modelling algorithm used, but on species characteristics. Here, we applied a standard distribution modelling technique (generalized linear models) using European plant species distribution data and climatic parameters. Predictive performance was calculated using AUC, (Cohen's) Kappa and true skill statistic (TSS), that were subsequently correlated with biological and life-history traits. After accounting for phylogenetic dependence among species, model performance was poorest for species having a short life span and occurring in human disturbed habitats. Our results clearly indicate that the performance of distribution models can be dependent on functional traits and provide further evidence that a species' ecology is likely to affect the ability of models to predict its distribution. Biased and less reliable predictions could misguide policy decisions and the management and conservation of our natural heritage.
KW - Environmental planning
UR - http://www.scopus.com/inward/record.url?scp=77955518388&partnerID=8YFLogxK
U2 - 10.1016/j.ppees.2010.04.002
DO - 10.1016/j.ppees.2010.04.002
M3 - Journal articles
AN - SCOPUS:77955518388
VL - 12
SP - 219
EP - 225
JO - Perspectives in Plant Ecology, Evolution and Systematics
JF - Perspectives in Plant Ecology, Evolution and Systematics
SN - 1619-0437
IS - 3
ER -