AI Article Synopsis

  • Global climate change is linked to insect declines, with significant data gaps in understanding how insect communities, particularly in poleward regions, are responding to increasing temperatures.
  • Researchers studied 50 years of butterfly occupancy trends in under-sampled areas of North America, finding that cold-adapted species are declining more than warm-adapted ones.
  • The analysis revealed that species with warmer average ranges are more likely to increase in occupancy, indicating a shift in butterfly biodiversity in high-latitude North America and demonstrating the value of utilizing presence-only data for monitoring species distribution changes.

Article Abstract

Global climate change has been identified as a potential driver of observed insect declines, yet in many regions, there are critical data gaps that make it difficult to assess how communities are responding to climate change. Poleward regions are of particular interest because warming is most rapid while biodiversity data are most sparse. Building on recent advances in occupancy modeling of presence-only data, we reconstructed 50 years (1970-2019) of butterfly occupancy trends in response to rising minimum temperatures in one of the most under-sampled regions of North America. Among 90 modeled species, we found that cold-adapted species are far more often in decline compared with their warm-adapted, more southernly distributed counterparts. Furthermore, in a post hoc analysis using species' traits, we find that species' range-wide average annual temperature is the only consistent predictor of occupancy changes. Species with warmer ranges were most likely to be increasing in occupancy. This trend results in the majority of butterflies increasing in occupancy probability over the last 50 years. Our results provide the first look at macroscale butterfly biodiversity shifts in high-latitude North America. These results highlight the potential of leveraging the wealth of presence-only data, the most abundant source of biodiversity data, for inferring changes in species distributions.

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Source
http://dx.doi.org/10.1111/gcb.17205DOI Listing

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