2005Global Ecology and BiogeographyRequires access

Uncertainty of bioclimate envelope models based on the geographical distribution of species

Miska Luoto, Juha Pöyry, Risto K. Heikkinen, K. Saarinen

Open publisher page 211 citations

Abstract

ABSTRACT Aim We explored the effects of prevalence, latitudinal range and spatial autocorrelation of species distribution patterns on the accuracy of bioclimate envelope models of butterflies. Location Finland, northern Europe. Methods The data of a national butterfly atlas survey (NAFI) carried out in 1991–2003 with a resolution of 10 × 10 km were used in the analyses. Generalized additive models (GAM) were constructed, for each of 98 species, to estimate the probability of occurrence as a function of climate variables. Model performance was measured using the area under the curve (AUC) of a receiver operating characteristic (ROC) plot. Observed differences in modelling accuracy among species were related to the species’ geographical attributes using multivariate GAM. Results Accuracies of the climate–butterfly models varied from low to very high (AUC values 0.59–0.99), with a mean of 0.79. The modelling performance was related negatively to the latitudinal range and prevalence, and positively to the spatial autocorrelation of the species distribution. These three factors accounted for 75.2% of the variation in the modelling accuracy. Species at the margin of their range or with low prevalence were better predicted than widespread species, and species with clumped distributions better than scattered dispersed species. Main conclusions The results from this study indicate that species’ geographical attributes highly influence the behaviour and uncertainty of species–climate models, which should be taken into account in biogeographical modelling studies and assessments of climate change impacts.

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ABSTRACT Aim We explored the effects of prevalence, latitudinal range and spatial autocorrelation of species distribution patterns on the accuracy of bioclimate envelope models of butterflies. Location Finland, northern Europe. Methods The data of a national butterfly atlas survey (NAFI) carried out in 1991–2003 with a resolution of 10 × 10 km were used in the analyses. Generalized additive models (GAM) were constructed, for each of 98 species, to estimate the probability of occurrence as a function of climate variables. Model performance was measured using the area under the curve (AUC) of a receiver operating characteristic (ROC) plot. Observed differences in modelling accuracy among species were related to the species’ geographical attributes using multivariate GAM. Results Accuracies of the climate–butterfly models varied from low to very high (AUC values 0.59–0.99), with a mean of 0.79. The modelling performance was related negatively to the latitudinal range and prevalence, and positively to the spatial autocorrelation of the species distribution. These three factors accounted for 75.2% of the variation in the modelling accuracy. Species at the margin of their range or with low prevalence were better predicted than widespread species, and species with clumped distributions better than scattered dispersed species. Main conclusions The results from this study indicate that species’ geographical attributes highly influence the behaviour and uncertainty of species–climate models, which should be taken into account in biogeographical modelling studies and assessments of climate change impacts.

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Available abstract

ABSTRACT Aim We explored the effects of prevalence, latitudinal range and spatial autocorrelation of species distribution patterns on the accuracy of bioclimate envelope models of butterflies. Location Finland, northern Europe. Methods The data of a national butterfly atlas survey (NAFI) carried out in 1991–2003 with a resolution of 10 × 10 km were used in the analyses. Generalized additive models (GAM) were constructed, for each of 98 species, to estimate the probability of occurrence as a function of climate variables. Model performance was measured using the area under the curve (AUC) of a receiver operating characteristic (ROC) plot. Observed differences in modelling accuracy among species were related to the species’ geographical attributes using multivariate GAM. Results Accuracies of the climate–butterfly models varied from low to very high (AUC values 0.59–0.99), with a mean of 0.79. The modelling performance was related negatively to the latitudinal range and prevalence, and positively to the spatial autocorrelation of the species distribution. These three factors accounted for 75.2% of the variation in the modelling accuracy. Species at the margin of their range or with low prevalence were better predicted than widespread species, and species with clumped distributions better than scattered dispersed species. Main conclusions The results from this study indicate that species’ geographical attributes highly influence the behaviour and uncertainty of species–climate models, which should be taken into account in biogeographical modelling studies and assessments of climate change impacts.

Key concepts: Species distribution, Environmental niche modelling, Range (aeronautics), Generalized additive model, Climate change, Ecology, Butterfly, Geography

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