Abstract

Global biodiversity declines, largely driven by climate and land‐use changes, urge the development of transparent guidelines for effective conservation strategies. Species distribution modeling (SDM) is a widely used approach for predicting potential shifts in species distributions, which can in turn support ecological conservation where environmental change is expected to impact population and community dynamics. Improvements in SDM accuracy through incorporating intra‐ and interspecific processes have boosted the SDM field forward, but simultaneously urge harmonizing the vast array of SDM approaches into an overarching, widely adoptable, and scientifically justified SDM framework. In this review, we first discuss how climate warming and land‐use change interact to govern population dynamics and species’ distributions, depending on species’ dispersal and evolutionary abilities. We particularly emphasize that both land‐use and climate change can reduce the accessibility to suitable habitat for many species, rendering the ability of species to colonize new habitat and to exchange genetic variation a crucial yet poorly implemented component of SDM. We then unite existing methodological SDM practices that aim to increase model accuracy through accounting for multiple global change stressors, dispersal, or evolution, while shifting our focus to model feasibility. We finally propose a roadmap harmonizing model accuracy and feasibility, applicable to both common and rare species, particularly those with poor dispersal abilities. This roadmap (a) paves the way for an overarching SDM framework allowing comparison and synthesis of different SDM studies and (b) could advance SDM to a level that allows systematic integration of SDM outcomes into effective conservation plans.

Highlights

  • Accounting for multiple environmental changes and potential evolutionary responses can greatly improve model accuracy (Bellard et al, 2015; Titeux et al, 2016), providing Species distribution modeling (SDM) outcomes that better represent the potential distribution and the occupied distributional area of the species or community under study (Figure 1)

  • Even absence data recorded during field surveys are tricky to use and should be carefully handled depending on the aim of the undertaken Species distribution modeling (SDM) exercise (Hattab et al, 2017): mapping the occupied distributional area or modeling the potential distribution

  • We investigate how dispersal is limited both by the effects of the landscape structure and configuration, and by changes in biotic interactions within communities

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Summary

Introduction

Accounting for multiple environmental changes and potential evolutionary responses can greatly improve model accuracy (Bellard et al, 2015; Titeux et al, 2016), providing SDM outcomes that better represent the potential distribution and the occupied distributional area of the species or community under study (Figure 1).

Results
Conclusion
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