全球变化知识资源中心

Aim Conventional species distribution models (SDMs) usually focus on the species level but disregard intraspecific variability. Phylogeographic structure and evolutionary significant units (ESU) have been proposed as pragmatic proxies to incorporate intraspecific differentiation in SDMs. Nevertheless, the efficiency of using these proxies in SDMs has been poorly investigated. We analysed how the projections of current and future climatically suitable areas can be affected when using ESU-based or lineage-based models compared to a species-level model. Location West-Palaearctic region. Methods As examples, we used three bumblebee species (133,787 observations). We assessed potential climatic niche differentiation between species level, lineages and ESUs, by determining the niche position and niche breadth for each classification level by outlying mean index analyses. Subsequently, we developed SDMs for each species and classification level separately using boosted regression trees prior to a comparison of their performances. Finally, we used the alternative models to project the extent of climatically suitable areas in 2070. Results We found that in spite of highly similar overall model accuracy, integrating intraspecific variability significantly increases model sensitivity (i.e., better predicting presences) while decreased model specificity (i.e., over-predicting the range). Consequently, both predictions of current and projections of future suitable conditions differed among the three approaches. Main conclusions We showed that although integrating lineage or ESU information did not improve the accuracy of conventional species-level SDMs, it led to considerably different conclusions. As SDM-based climatic risk assessments are increasingly used to help and improve conservation plans, divergences and limitations of each modelling approach should be taken into account for developing efficient biodiversity management strategies. Lineage and ESU-based SDMs offer the advantage to draw attention to species in which allopatric populations could display physiologically different responses to climate change when they lead to different results than species-based models.