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Interactive effects of multiple stressors vary with consumer interactions, stressor dynamics and magnitude
Predicting the impacts of multiple stressors is important for informing ecosystem management but is impeded by a lack of a general framework for predicting whether stressors interact synergistically, additively or antagonistically. Here, we use process‐based models to study how interactions generali...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9320941/ https://www.ncbi.nlm.nih.gov/pubmed/35478314 http://dx.doi.org/10.1111/ele.14013 |
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author | Turschwell, Mischa P. Connolly, Sean R. Schäfer, Ralf B. De Laender, Frederik Campbell, Max D. Mantyka‐Pringle, Chrystal Jackson, Michelle C. Kattwinkel, Mira Sievers, Michael Ashauer, Roman Côté, Isabelle M. Connolly, Rod M. van den Brink, Paul J. Brown, Christopher J. |
author_facet | Turschwell, Mischa P. Connolly, Sean R. Schäfer, Ralf B. De Laender, Frederik Campbell, Max D. Mantyka‐Pringle, Chrystal Jackson, Michelle C. Kattwinkel, Mira Sievers, Michael Ashauer, Roman Côté, Isabelle M. Connolly, Rod M. van den Brink, Paul J. Brown, Christopher J. |
author_sort | Turschwell, Mischa P. |
collection | PubMed |
description | Predicting the impacts of multiple stressors is important for informing ecosystem management but is impeded by a lack of a general framework for predicting whether stressors interact synergistically, additively or antagonistically. Here, we use process‐based models to study how interactions generalise across three levels of biological organisation (physiological, population and consumer‐resource) for a two‐stressor experiment on a seagrass model system. We found that the same underlying processes could result in synergistic, additive or antagonistic interactions, with interaction type depending on initial conditions, experiment duration, stressor dynamics and consumer presence. Our results help explain why meta‐analyses of multiple stressor experimental results have struggled to identify predictors of consistently non‐additive interactions in the natural environment. Experiments run over extended temporal scales, with treatments across gradients of stressor magnitude, are needed to identify the processes that underpin how stressors interact and provide useful predictions to management. |
format | Online Article Text |
id | pubmed-9320941 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-93209412022-07-30 Interactive effects of multiple stressors vary with consumer interactions, stressor dynamics and magnitude Turschwell, Mischa P. Connolly, Sean R. Schäfer, Ralf B. De Laender, Frederik Campbell, Max D. Mantyka‐Pringle, Chrystal Jackson, Michelle C. Kattwinkel, Mira Sievers, Michael Ashauer, Roman Côté, Isabelle M. Connolly, Rod M. van den Brink, Paul J. Brown, Christopher J. Ecol Lett Letters Predicting the impacts of multiple stressors is important for informing ecosystem management but is impeded by a lack of a general framework for predicting whether stressors interact synergistically, additively or antagonistically. Here, we use process‐based models to study how interactions generalise across three levels of biological organisation (physiological, population and consumer‐resource) for a two‐stressor experiment on a seagrass model system. We found that the same underlying processes could result in synergistic, additive or antagonistic interactions, with interaction type depending on initial conditions, experiment duration, stressor dynamics and consumer presence. Our results help explain why meta‐analyses of multiple stressor experimental results have struggled to identify predictors of consistently non‐additive interactions in the natural environment. Experiments run over extended temporal scales, with treatments across gradients of stressor magnitude, are needed to identify the processes that underpin how stressors interact and provide useful predictions to management. John Wiley and Sons Inc. 2022-04-27 2022-06 /pmc/articles/PMC9320941/ /pubmed/35478314 http://dx.doi.org/10.1111/ele.14013 Text en © 2022 The Authors. Ecology Letters published by John Wiley & Sons Ltd. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Letters Turschwell, Mischa P. Connolly, Sean R. Schäfer, Ralf B. De Laender, Frederik Campbell, Max D. Mantyka‐Pringle, Chrystal Jackson, Michelle C. Kattwinkel, Mira Sievers, Michael Ashauer, Roman Côté, Isabelle M. Connolly, Rod M. van den Brink, Paul J. Brown, Christopher J. Interactive effects of multiple stressors vary with consumer interactions, stressor dynamics and magnitude |
title | Interactive effects of multiple stressors vary with consumer interactions, stressor dynamics and magnitude |
title_full | Interactive effects of multiple stressors vary with consumer interactions, stressor dynamics and magnitude |
title_fullStr | Interactive effects of multiple stressors vary with consumer interactions, stressor dynamics and magnitude |
title_full_unstemmed | Interactive effects of multiple stressors vary with consumer interactions, stressor dynamics and magnitude |
title_short | Interactive effects of multiple stressors vary with consumer interactions, stressor dynamics and magnitude |
title_sort | interactive effects of multiple stressors vary with consumer interactions, stressor dynamics and magnitude |
topic | Letters |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9320941/ https://www.ncbi.nlm.nih.gov/pubmed/35478314 http://dx.doi.org/10.1111/ele.14013 |
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