Abstract

Climate change could increase species' extinction risk as temperatures and precipitation begin to exceed species' historically observed tolerances. Using long-term data for 66 bumble bee species across North America and Europe, we tested whether this mechanism altered likelihoods of bumble bee species' extinction or colonization. Increasing frequency of hotter temperatures predicts species' local extinction risk, chances of colonizing a new area, and changing species richness. Effects are independent of changing land uses. The method developed in this study permits spatially explicit predictions of climate change-related population extinction-colonization dynamics within species that explains observed patterns of geographical range loss and expansion across continents. Increasing frequencies of temperatures that exceed historically observed tolerances help explain widespread bumble bee species decline. This mechanism may also contribute to biodiversity loss more generally.

Highlights

  • America and Europe using a database of ~550,000 georeferenced occurrence records of 66 bumblebee species (Figure S1 and S2, Table S1; [1, 9])

  • We modelled change in probability of site occupancy with phylogenetic generalized linear mixed models using thermal position variables, precipitation position variables, the interaction between baseline thermal and precipitation position terms, and the interaction between change in thermal position and change in precipitation position

  • Using a spatially explicit method of measuring climatic position and its change over time, we show that risks of bumblebee extirpation rise in areas where local temperatures more frequently exceed species’ historical tolerances, while colonization probabilities in other areas rise as climate changes cause conditions to more frequently fall within species’ thermal limits

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Summary

Introduction

America and Europe using a database of ~550,000 georeferenced occurrence records of 66 bumblebee species (Figure S1 and S2, Table S1; [1, 9]). This between-period variation reflects the uncertainty within estimates of occupancy probability during a period, and likely drives the lower adjusted R2 values we see when comparing the detection-corrected and observed species richness models.

Results
Conclusion
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