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Do climate envelope models transfer? A manipulative test using dung beetle introductions.

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Summary
This summary is machine-generated.

Climate envelope models (CEMs) predict species ranges, but this study found non-climatic factors also limit distributions. Validating CEMs with introduced species data reveals limitations in predicting climate-driven range shifts.

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Area of Science:

  • Ecology
  • Biogeography
  • Climate Change Biology

Background:

  • Climate envelope models (CEMs) are crucial for predicting species range shifts due to climate change.
  • However, the assumption that climate solely limits species distributions is rarely tested, and CEMs lack independent validation.
  • Dispersal, resources, and natural enemies can also influence species distributions, complicating model accuracy.

Purpose of the Study:

  • To test the predictive accuracy of CEMs developed in a native range when applied to an introduced range.
  • To assess whether climate is the sole limiting factor in species distributions by removing other constraints in the introduced range.
  • To identify instances where non-climatic factors significantly impact species distribution predictions.

Main Methods:

  • Utilized introduction data of five South African dung beetle species to Australia as a natural experiment.
  • Developed CEMs based on the native range climate data for each species.
  • Compared the predictive performance of native-range CEMs against observed distributions in the Australian introduced range, where climate is presumed the dominant constraint.

Main Results:

  • For two of the five species, native-range CEMs accurately predicted introduced-range distributions, supporting climate as the primary driver.
  • For the remaining three species, native-range CEMs performed poorly, indicating significant non-climatic limitations in their native habitats.
  • The study highlights that non-climatic factors are critical and must be integrated into species distribution models for reliable forecasting.

Conclusions:

  • CEMs can be effective when climate is the primary determinant of species distribution, as demonstrated in two species.
  • The predictive failure in three species underscores the importance of non-climatic factors (e.g., resources, natural enemies) in shaping species ranges.
  • Accurate forecasting of climate-driven range shifts requires incorporating relevant non-climatic variables and their interactions with climate, which remains a significant challenge.