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Predicting climate change impacts on poikilotherms using physiologically guided species abundance models
Poikilothermic animals comprise most species on Earth and are especially sensitive to changes in environmental temperatures. Species conservation in a changing climate relies upon predictions of species responses to future conditions, yet predicting species responses to climate change when temperatu...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
National Academy of Sciences
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10104529/ https://www.ncbi.nlm.nih.gov/pubmed/37011195 http://dx.doi.org/10.1073/pnas.2214199120 |
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author | Wagner, Tyler Schliep, Erin M. North, Joshua S. Kundel, Holly Custer, Christopher A. Ruzich, Jenna K. Hansen, Gretchen J. A. |
author_facet | Wagner, Tyler Schliep, Erin M. North, Joshua S. Kundel, Holly Custer, Christopher A. Ruzich, Jenna K. Hansen, Gretchen J. A. |
author_sort | Wagner, Tyler |
collection | PubMed |
description | Poikilothermic animals comprise most species on Earth and are especially sensitive to changes in environmental temperatures. Species conservation in a changing climate relies upon predictions of species responses to future conditions, yet predicting species responses to climate change when temperatures exceed the bounds of observed data is fraught with challenges. We present a physiologically guided abundance (PGA) model that combines observations of species abundance and environmental conditions with laboratory-derived data on the physiological response of poikilotherms to temperature to predict species geographical distributions and abundance in response to climate change. The model incorporates uncertainty in laboratory-derived thermal response curves and provides estimates of thermal habitat suitability and extinction probability based on site-specific conditions. We show that temperature-driven changes in distributions, local extinction, and abundance of cold, cool, and warm-adapted species vary substantially when physiological information is incorporated. Notably, cold-adapted species were predicted by the PGA model to be extirpated in 61% of locations that they currently inhabit, while extirpation was never predicted by a correlative niche model. Failure to account for species-specific physiological constraints could lead to unrealistic predictions under a warming climate, including underestimates of local extirpation for cold-adapted species near the edges of their climate niche space and overoptimistic predictions of warm-adapted species. |
format | Online Article Text |
id | pubmed-10104529 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | National Academy of Sciences |
record_format | MEDLINE/PubMed |
spelling | pubmed-101045292023-04-15 Predicting climate change impacts on poikilotherms using physiologically guided species abundance models Wagner, Tyler Schliep, Erin M. North, Joshua S. Kundel, Holly Custer, Christopher A. Ruzich, Jenna K. Hansen, Gretchen J. A. Proc Natl Acad Sci U S A Biological Sciences Poikilothermic animals comprise most species on Earth and are especially sensitive to changes in environmental temperatures. Species conservation in a changing climate relies upon predictions of species responses to future conditions, yet predicting species responses to climate change when temperatures exceed the bounds of observed data is fraught with challenges. We present a physiologically guided abundance (PGA) model that combines observations of species abundance and environmental conditions with laboratory-derived data on the physiological response of poikilotherms to temperature to predict species geographical distributions and abundance in response to climate change. The model incorporates uncertainty in laboratory-derived thermal response curves and provides estimates of thermal habitat suitability and extinction probability based on site-specific conditions. We show that temperature-driven changes in distributions, local extinction, and abundance of cold, cool, and warm-adapted species vary substantially when physiological information is incorporated. Notably, cold-adapted species were predicted by the PGA model to be extirpated in 61% of locations that they currently inhabit, while extirpation was never predicted by a correlative niche model. Failure to account for species-specific physiological constraints could lead to unrealistic predictions under a warming climate, including underestimates of local extirpation for cold-adapted species near the edges of their climate niche space and overoptimistic predictions of warm-adapted species. National Academy of Sciences 2023-04-03 2023-04-11 /pmc/articles/PMC10104529/ /pubmed/37011195 http://dx.doi.org/10.1073/pnas.2214199120 Text en Copyright © 2023 the Author(s). Published by PNAS. https://creativecommons.org/licenses/by/4.0/This open access article is distributed under Creative Commons Attribution License 4.0 (CC BY) (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Biological Sciences Wagner, Tyler Schliep, Erin M. North, Joshua S. Kundel, Holly Custer, Christopher A. Ruzich, Jenna K. Hansen, Gretchen J. A. Predicting climate change impacts on poikilotherms using physiologically guided species abundance models |
title | Predicting climate change impacts on poikilotherms using physiologically guided species abundance models |
title_full | Predicting climate change impacts on poikilotherms using physiologically guided species abundance models |
title_fullStr | Predicting climate change impacts on poikilotherms using physiologically guided species abundance models |
title_full_unstemmed | Predicting climate change impacts on poikilotherms using physiologically guided species abundance models |
title_short | Predicting climate change impacts on poikilotherms using physiologically guided species abundance models |
title_sort | predicting climate change impacts on poikilotherms using physiologically guided species abundance models |
topic | Biological Sciences |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10104529/ https://www.ncbi.nlm.nih.gov/pubmed/37011195 http://dx.doi.org/10.1073/pnas.2214199120 |
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