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Interannual climate variability improves niche estimates for ectothermic but not endothermic species
Climate is an important limiting factor of species’ niches and it is therefore regularly included in ecological applications such as species distribution models (SDMs). Climate predictors are often used in the form of long-term mean values, yet many species experience wide climatic variation over th...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10397316/ https://www.ncbi.nlm.nih.gov/pubmed/37532828 http://dx.doi.org/10.1038/s41598-023-39637-x |
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author | Karger, Dirk Nikolaus Saladin, Bianca Wüest, Rafael O. Graham, Catherine H. Zurell, Damaris Mo, Lidong Zimmermann, Niklaus E. |
author_facet | Karger, Dirk Nikolaus Saladin, Bianca Wüest, Rafael O. Graham, Catherine H. Zurell, Damaris Mo, Lidong Zimmermann, Niklaus E. |
author_sort | Karger, Dirk Nikolaus |
collection | PubMed |
description | Climate is an important limiting factor of species’ niches and it is therefore regularly included in ecological applications such as species distribution models (SDMs). Climate predictors are often used in the form of long-term mean values, yet many species experience wide climatic variation over their lifespan and within their geographical range which is unlikely captured by long-term means. Further, depending on their physiology, distinct groups of species cope with climate variability differently. Ectothermic species, which are directly dependent on the thermal environment are expected to show a different response to temporal or spatial variability in temperature than endothermic groups that can decouple their internal temperature from that of their surroundings. Here, we explore the degree to which spatial variability and long-term temporal variability in temperature and precipitation change niche estimates for ectothermic (730 amphibian, 1276 reptile), and endothermic (1961 mammal) species globally. We use three different species distribution modelling (SDM) algorithms to quantify the effect of spatial and temporal climate variability, based on global range maps of all species and climate data from 1979 to 2013. All SDMs were cross-validated and accessed for their performance using the Area under the Curve (AUC) and the True Skill Statistic (TSS). The mean performance of SDMs using only climatic means as predictors was TSS = 0.71 and AUC = 0.90. The inclusion of spatial variability offers a significant gain in SDM performance (mean TSS = 0.74, mean AUC = 0.92), as does the inclusion of temporal variability (mean TSS = 0.80, mean AUC = 0.94). Including both spatial and temporal variability in SDMs shows the highest scores in AUC and TSS. Accounting for temporal rather than spatial variability in climate improved the SDM prediction especially in ectotherm groups such as amphibians and reptiles, while for endothermic mammals no such improvement was observed. These results indicate that including long term climate interannual climate variability into niche estimations matters most for ectothermic species that cannot decouple their physiology from the surrounding environment as endothermic species can. |
format | Online Article Text |
id | pubmed-10397316 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-103973162023-08-04 Interannual climate variability improves niche estimates for ectothermic but not endothermic species Karger, Dirk Nikolaus Saladin, Bianca Wüest, Rafael O. Graham, Catherine H. Zurell, Damaris Mo, Lidong Zimmermann, Niklaus E. Sci Rep Article Climate is an important limiting factor of species’ niches and it is therefore regularly included in ecological applications such as species distribution models (SDMs). Climate predictors are often used in the form of long-term mean values, yet many species experience wide climatic variation over their lifespan and within their geographical range which is unlikely captured by long-term means. Further, depending on their physiology, distinct groups of species cope with climate variability differently. Ectothermic species, which are directly dependent on the thermal environment are expected to show a different response to temporal or spatial variability in temperature than endothermic groups that can decouple their internal temperature from that of their surroundings. Here, we explore the degree to which spatial variability and long-term temporal variability in temperature and precipitation change niche estimates for ectothermic (730 amphibian, 1276 reptile), and endothermic (1961 mammal) species globally. We use three different species distribution modelling (SDM) algorithms to quantify the effect of spatial and temporal climate variability, based on global range maps of all species and climate data from 1979 to 2013. All SDMs were cross-validated and accessed for their performance using the Area under the Curve (AUC) and the True Skill Statistic (TSS). The mean performance of SDMs using only climatic means as predictors was TSS = 0.71 and AUC = 0.90. The inclusion of spatial variability offers a significant gain in SDM performance (mean TSS = 0.74, mean AUC = 0.92), as does the inclusion of temporal variability (mean TSS = 0.80, mean AUC = 0.94). Including both spatial and temporal variability in SDMs shows the highest scores in AUC and TSS. Accounting for temporal rather than spatial variability in climate improved the SDM prediction especially in ectotherm groups such as amphibians and reptiles, while for endothermic mammals no such improvement was observed. These results indicate that including long term climate interannual climate variability into niche estimations matters most for ectothermic species that cannot decouple their physiology from the surrounding environment as endothermic species can. Nature Publishing Group UK 2023-08-02 /pmc/articles/PMC10397316/ /pubmed/37532828 http://dx.doi.org/10.1038/s41598-023-39637-x Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Karger, Dirk Nikolaus Saladin, Bianca Wüest, Rafael O. Graham, Catherine H. Zurell, Damaris Mo, Lidong Zimmermann, Niklaus E. Interannual climate variability improves niche estimates for ectothermic but not endothermic species |
title | Interannual climate variability improves niche estimates for ectothermic but not endothermic species |
title_full | Interannual climate variability improves niche estimates for ectothermic but not endothermic species |
title_fullStr | Interannual climate variability improves niche estimates for ectothermic but not endothermic species |
title_full_unstemmed | Interannual climate variability improves niche estimates for ectothermic but not endothermic species |
title_short | Interannual climate variability improves niche estimates for ectothermic but not endothermic species |
title_sort | interannual climate variability improves niche estimates for ectothermic but not endothermic species |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10397316/ https://www.ncbi.nlm.nih.gov/pubmed/37532828 http://dx.doi.org/10.1038/s41598-023-39637-x |
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