Climate variables are not the dominant predictor of Arctic shorebird distributions
Competing theoretical perspectives about whether or not climate is the dominant factor influencing species’ distributions at large spatial scales have important consequences when habitat suitability models are used to address conservation problems. In this study, we tested how much variables in addi...
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Online Access: | http://dx.doi.org/10.1371/journal.pone.0285115 https://dx.plos.org/10.1371/journal.pone.0285115 |
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crplos:10.1371/journal.pone.0285115 2024-09-30T14:30:29+00:00 Climate variables are not the dominant predictor of Arctic shorebird distributions Anderson, Christine M. Fahrig, Lenore Rausch, Jennie Smith, Paul A. Bhadauria, Tunira National Science and Engineering Research Council Arcticnet Environment and Climate Change Canada W. Garfield Weston Foundation National Science and Engineering Research Council Environment and Climate Change Canada 2023 http://dx.doi.org/10.1371/journal.pone.0285115 https://dx.plos.org/10.1371/journal.pone.0285115 en eng Public Library of Science (PLoS) http://creativecommons.org/licenses/by/4.0/ PLOS ONE volume 18, issue 5, page e0285115 ISSN 1932-6203 journal-article 2023 crplos https://doi.org/10.1371/journal.pone.0285115 2024-09-03T04:13:55Z Competing theoretical perspectives about whether or not climate is the dominant factor influencing species’ distributions at large spatial scales have important consequences when habitat suitability models are used to address conservation problems. In this study, we tested how much variables in addition to climate help to explain habitat suitability for Arctic-breeding shorebirds. To do this we model species occupancy using path analyses, which allow us to estimate the indirect effects of climate on other predictor variables, such as land cover. We also use deviance partitioning to quantify the total relative importance of climate versus additional predictors in explaining species occupancy. We found that individual land cover variables are often stronger predictors than the direct and indirect effects of climate combined. In models with both climate and additional variables, on average the additional variables accounted for 57% of the explained deviance, independent of shared effects with the climate variables. Our results support the idea that climate-only models may offer incomplete descriptions of current and future habitat suitability and can lead to incorrect conclusions about the size and location of suitable habitat. These conclusions could have important management implications for designating protected areas and assessing threats like climate change and human development. Article in Journal/Newspaper Arctic Climate change PLOS Arctic PLOS ONE 18 5 e0285115 |
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English |
description |
Competing theoretical perspectives about whether or not climate is the dominant factor influencing species’ distributions at large spatial scales have important consequences when habitat suitability models are used to address conservation problems. In this study, we tested how much variables in addition to climate help to explain habitat suitability for Arctic-breeding shorebirds. To do this we model species occupancy using path analyses, which allow us to estimate the indirect effects of climate on other predictor variables, such as land cover. We also use deviance partitioning to quantify the total relative importance of climate versus additional predictors in explaining species occupancy. We found that individual land cover variables are often stronger predictors than the direct and indirect effects of climate combined. In models with both climate and additional variables, on average the additional variables accounted for 57% of the explained deviance, independent of shared effects with the climate variables. Our results support the idea that climate-only models may offer incomplete descriptions of current and future habitat suitability and can lead to incorrect conclusions about the size and location of suitable habitat. These conclusions could have important management implications for designating protected areas and assessing threats like climate change and human development. |
author2 |
Bhadauria, Tunira National Science and Engineering Research Council Arcticnet Environment and Climate Change Canada W. Garfield Weston Foundation National Science and Engineering Research Council Environment and Climate Change Canada |
format |
Article in Journal/Newspaper |
author |
Anderson, Christine M. Fahrig, Lenore Rausch, Jennie Smith, Paul A. |
spellingShingle |
Anderson, Christine M. Fahrig, Lenore Rausch, Jennie Smith, Paul A. Climate variables are not the dominant predictor of Arctic shorebird distributions |
author_facet |
Anderson, Christine M. Fahrig, Lenore Rausch, Jennie Smith, Paul A. |
author_sort |
Anderson, Christine M. |
title |
Climate variables are not the dominant predictor of Arctic shorebird distributions |
title_short |
Climate variables are not the dominant predictor of Arctic shorebird distributions |
title_full |
Climate variables are not the dominant predictor of Arctic shorebird distributions |
title_fullStr |
Climate variables are not the dominant predictor of Arctic shorebird distributions |
title_full_unstemmed |
Climate variables are not the dominant predictor of Arctic shorebird distributions |
title_sort |
climate variables are not the dominant predictor of arctic shorebird distributions |
publisher |
Public Library of Science (PLoS) |
publishDate |
2023 |
url |
http://dx.doi.org/10.1371/journal.pone.0285115 https://dx.plos.org/10.1371/journal.pone.0285115 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic Climate change |
genre_facet |
Arctic Climate change |
op_source |
PLOS ONE volume 18, issue 5, page e0285115 ISSN 1932-6203 |
op_rights |
http://creativecommons.org/licenses/by/4.0/ |
op_doi |
https://doi.org/10.1371/journal.pone.0285115 |
container_title |
PLOS ONE |
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18 |
container_issue |
5 |
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e0285115 |
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1811635407662612480 |