Predicting responses to climate change using a joint species, spatially dependent physiologically guided abundance...

Area of Science:

• Ecology and climate change biology
• Aquatic ecology
• Physiological ecology

Background:

• Predicting species' responses to climate warming often involves extrapolating current relationships to novel conditions, leading to inaccurate projections.
• Incorporating species' thermal physiology and accounting for spatial dependencies can enhance the realism of ecological predictions for poikilotherms.

Purpose of the Study:

• To develop and apply a joint species, spatially dependent physiologically guided abundance (jsPGA) model for predicting multispecies responses to climate warming.
• To assess the impact of projected climate warming on the abundance and distribution of eight fish species in Minnesota lakes.

Main Methods:

• The study utilized a novel jsPGA model employing a basis function approach to capture both species and spatial dependencies.
• The model was applied to predict the abundance and extirpation probabilities of eight fish species under future climate scenarios in Minnesota lakes.

Main Results:

• A cold-adapted fish species exhibited high probabilities of extirpation across its current range under projected warming.
• Other species showed varying predicted changes in abundance, correlating with their thermal physiology.
• While strong species dependencies were not widely identified, spatial dependencies varied, highlighting the importance of accounting for both.

Conclusions:

• The jsPGA model offers a robust framework for predicting the impact of novel thermal conditions on poikilotherm abundance, distribution, and extirpation risk.
• Integrating physiological traits and spatial factors is crucial for accurate ecological forecasting in a changing climate.