Synergistic interactions among growing stressors increase risk to an Arctic ecosystem
Autor: | George H. Leonard, Kevin R. Arrigo, Gert L. van Dijken, Matthew M. Mills, Lisa M. Wedding, Anna Zivian, Fiorenza Micheli, M. Levi, Richard M. Bailey, Andreas Merkl, Nicholas T. Ouellette, Mary A. Cameron, J. M. A. van der Grient, Stephen G. Monismith, Jim Leape, Lucie Hazen |
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Rok vydání: | 2019 |
Předmět: |
0106 biological sciences
endocrine system Conservation of Natural Resources 010504 meteorology & atmospheric sciences Science Climate Change Oceans and Seas Population Fisheries General Physics and Astronomy 010603 evolutionary biology 01 natural sciences behavioral disciplines and activities General Biochemistry Genetics and Molecular Biology Article Ecosystem services Animals Ecosystem Ice Cover Biomass education 0105 earth and related environmental sciences Trophic level education.field_of_study Multidisciplinary Overfishing Ecology Arctic Regions Fishes Temperature General Chemistry Models Theoretical Food web Environmental sciences Habitat destruction Ocean sciences Arctic Phytoplankton Environmental science Systems biology psychological phenomena and processes Algorithms Ursidae |
Zdroj: | Nature Communications Nature Communications, Vol 11, Iss 1, Pp 1-8 (2020) |
ISSN: | 2041-1723 |
Popis: | Oceans provide critical ecosystem services, but are subject to a growing number of external pressures, including overfishing, pollution, habitat destruction, and climate change. Current models typically treat stressors on species and ecosystems independently, though in reality, stressors often interact in ways that are not well understood. Here, we use a network interaction model (OSIRIS) to explicitly study stressor interactions in the Chukchi Sea (Arctic Ocean) due to its extensive climate-driven loss of sea ice and accelerated growth of other stressors, including shipping and oil exploration. The model includes numerous trophic levels ranging from phytoplankton to polar bears. We find that climate-related stressors have a larger impact on animal populations than do acute stressors like increased shipping and subsistence harvesting. In particular, organisms with a strong temperature-growth rate relationship show the greatest changes in biomass as interaction strength increased, but also exhibit the greatest variability. Neglecting interactions between stressors vastly underestimates the risk of population crashes. Our results indicate that models must account for stressor interactions to enable responsible management and decision-making. Multiple co-occurring stressors may affect food webs in ways that are not predictable by studying individual stressors. Here the authors apply a network interaction model to a marine food web in the Arctic, finding that nonlinear interactions between stressors can more than double the risk of population collapse compared to simpler simulations. |
Databáze: | OpenAIRE |
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