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

Journal Article · 20 June 2024 · Ecology

DOI: https://doi.org/10.1002/ecy.4362 · OSTI ID:2375918

Custer, Christopher A.  ^[1]; North, Joshua S. ^[2]; Schliep, Erin M. ^[3]; Verhoeven, Michael R. ^[4]; Hansen, Gretchen J. A.  ^[4]; Wagner, Tyler  ^[5]

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1. Pennsylvania Cooperative Fish and Wildlife Research Unit, Department of Ecosystem Science and Management The Pennsylvania State University University Park Pennsylvania USA
2. Climate and Ecosystem Sciences Division Lawrence Berkeley National Laboratory Berkeley California USA
3. Department of Statistics North Carolina State University Raleigh North Carolina USA
4. Department of Fisheries, Wildlife, and Conservation Biology University of Minnesota St. Paul Minnesota USA
5. U.S. Geological Survey, Pennsylvania Cooperative Fish and Wildlife Research Unit The Pennsylvania State University University Park Pennsylvania USA

Abstract Predicting the effects of warming temperatures on the abundance and distribution of organisms under future climate scenarios often requires extrapolating species–environment correlations to climatic conditions not currently experienced by a species, which can result in unrealistic predictions. For poikilotherms, incorporating species' thermal physiology to inform extrapolations under novel thermal conditions can result in more realistic predictions. Furthermore, models that incorporate species and spatial dependencies may improve predictions by capturing correlations present in ecological data that are not accounted for by predictor variables. Here, we present a joint species, spatially dependent physiologically guided abundance (jsPGA) model for predicting multispecies responses to climate warming. The jsPGA model uses a basis function approach to capture both species and spatial dependencies. We apply the jsPGA model to predict the response of eight fish species to projected climate warming in thousands of lakes in Minnesota, USA. By the end of the century, the cold‐adapted species was predicted to have high probabilities of extirpation across its current range—with 10% of lakes currently inhabited by this species having an extirpation probability >0.90. The remaining species had varying levels of predicted changes in abundance, reflecting differences in their thermal physiology. Though the model did not identify many strong species dependencies, the variation in estimated spatial dependence across species suggested that accounting for both dependencies was important for predicting the abundance of these fishes. The jsPGA model provides a new tool for predicting changes in the abundance, distribution, and extirpation probability of poikilotherms under novel thermal conditions.

• Sponsoring Organization: USDOE
• Grant/Contract Number: NONE; AC02-05CH11231
• OSTI ID: 2375918
• Journal Information: Ecology, Journal Name: Ecology; ISSN 0012-9658
• Publisher: Wiley Blackwell (John Wiley & Sons)Copyright Statement
• Country of Publication: United States
• Language: English