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Determinants of the biogeographical distribution of butterflies in boreal regions
Authors:M Luoto  R K Heikkinen  J Pöyry  K Saarinen
Institution:Research Programme for Biodiversity, Research Department, Finnish Environment Institute, Helsinki, Finland;and South Karelia Allergy and Environment Institute, Tiuruniemi, Finland
Abstract:Aim  We explored the relative contributions of climatic and land-cover factors in explaining the distribution patterns of butterflies in a boreal region.
Location  Finland, northern Europe.
Methods  Data from a national butterfly atlas survey carried out during 1991–2003, with a 10-km grain grid system, were used in these analyses. We used generalized additive models (GAM) and hierarchical partitioning (HP) to explore the main environmental correlates (climate and land-cover) of the realized niches of 98 butterfly species. The accuracy of the distribution models (GAMs) was validated by resubstitution and cross-validation approaches, using the area under the curve (AUC) derived from the receiver operating characteristic (ROC) plots.
Results  Predictive accuracies of the 98 individual environment–butterfly models varied from low to very high (cross-validated AUC values 0.48–0.99), with a mean of 0.79. The results of both the GAM and HP analyses were broadly concordant. Most of the variation in butterfly distributions is associated with growing degree-days, mean temperature of the coldest month and cover of built-up area in all six phylogenetic groups (butterfly families). There were no statistically significant differences in predictive accuracy among the different butterfly families.
Main conclusions  About three-quarters of the distributions of butterfly species in Finland appear to be governed principally by climatic, predominantly temperature-related, factors. This indicates that many butterfly species may respond rapidly to the projected climate change in boreal regions. By determining the ecological niches of multiple species, we can project their range shifts in response to changes in climate and land-cover, and identify species that are particularly sensitive to forecasted global changes.
Keywords:AUC  butterfly atlas  climate  distribution  Finland  GRASP  hierarchical partitioning  land-cover
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