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      Interactive effects of multiple stressors vary with consumer interactions, stressor dynamics and magnitude

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          Abstract

          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.

          Abstract

          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 inter‐actions, with interaction type depending on initial conditions, experiment duration, stressor dynamics and consumer presence

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          Most cited references69

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          TOWARD A METABOLIC THEORY OF ECOLOGY

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            Quantifying the evidence for ecological synergies.

            There is increasing concern that multiple drivers of ecological change will interact synergistically to accelerate biodiversity loss. However, the prevalence and magnitude of these interactions remain one of the largest uncertainties in projections of future ecological change. We address this uncertainty by performing a meta-analysis of 112 published factorial experiments that evaluated the impacts of multiple stressors on animal mortality in freshwater, marine and terrestrial communities. We found that, on average, mortalities from the combined action of two stressors were not synergistic and this result was consistent across studies investigating different stressors, study organisms and life-history stages. Furthermore, only one-third of relevant experiments displayed truly synergistic effects, which does not support the prevailing ecological paradigm that synergies are rampant. However, in more than three-quarters of relevant experiments, the outcome of multiple stressor interactions was non-additive (i.e. synergies or antagonisms), suggesting that ecological surprises may be more common than simple additive effects.
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              Interactions among ecosystem stressors and their importance in conservation.

              Interactions between multiple ecosystem stressors are expected to jeopardize biological processes, functions and biodiversity. The scientific community has declared stressor interactions-notably synergies-a key issue for conservation and management. Here, we review ecological literature over the past four decades to evaluate trends in the reporting of ecological interactions (synergies, antagonisms and additive effects) and highlight the implications and importance to conservation. Despite increasing popularity, and ever-finer terminologies, we find that synergies are (still) not the most prevalent type of interaction, and that conservation practitioners need to appreciate and manage for all interaction outcomes, including antagonistic and additive effects. However, it will not be possible to identify the effect of every interaction on every organism's physiology and every ecosystem function because the number of stressors, and their potential interactions, are growing rapidly. Predicting the type of interactions may be possible in the near-future, using meta-analyses, conservation-oriented experiments and adaptive monitoring. Pending a general framework for predicting interactions, conservation management should enact interventions that are robust to uncertainty in interaction type and that continue to bolster biological resilience in a stressful world.
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                Author and article information

                Contributors
                m.turschwell@griffith.edu.au
                Journal
                Ecol Lett
                Ecol Lett
                10.1111/(ISSN)1461-0248
                ELE
                Ecology Letters
                John Wiley and Sons Inc. (Hoboken )
                1461-023X
                1461-0248
                27 April 2022
                June 2022
                : 25
                : 6 ( doiID: 10.1111/ele.v25.6 )
                : 1483-1496
                Affiliations
                [ 1 ] Coastal and Marine Research Centre School of Environment and Science Australian Rivers Institute Griffith University Gold Coast Queensland Australia
                [ 2 ] Naos Marine Laboratories Smithsonian Tropical Research Institute Balboa Ancón Republic of Panama
                [ 3 ] ringgold 8001; College of Science and Engineering James Cook University Townsville Australia
                [ 4 ] Quantitative Landscape Ecology iES—Institute for Environmental Sciences University Koblenz‐Landau Landau in der Pfalz Germany
                [ 5 ] Research Unit of Environmental and Evolutionary Biology Namur Institute of Complex Systems and Institute of Life, Earth, and the Environment University of Namur Namur Belgium
                [ 6 ] Wildlife Conservation Society Canada Whitehorse Yukon Territory Canada
                [ 7 ] School of Environment and Sustainability University of Saskatchewan Saskatoon Saskatchewan Canada
                [ 8 ] Department of Zoology University of Oxford Oxford UK
                [ 9 ] ringgold 8748; Environment Department University of York York UK
                [ 10 ] Syngenta Crop Protection AG Basel Switzerland
                [ 11 ] Earth to Ocean Research Group Department of Biological Sciences Simon Fraser University Burnaby British Columbia Canada
                [ 12 ] ringgold 396117; Aquatic Ecology and Water Quality Management Group Wageningen University Wageningen The Netherlands
                [ 13 ] ringgold 396117; Wageningen Environmental Research Wageningen The Netherlands
                Author notes
                [*] [* ] Correspondence

                Mischa P. Turschwell, Australian Rivers Institute, 170 Kessels Road Nathan, QLD 4111, Australia.

                Email: m.turschwell@ 123456griffith.edu.au

                Author information
                https://orcid.org/0000-0002-6307-9604
                https://orcid.org/0000-0003-1537-0859
                https://orcid.org/0000-0002-4060-973X
                https://orcid.org/0000-0003-2860-1580
                https://orcid.org/0000-0003-2227-1111
                https://orcid.org/0000-0001-7162-1830
                https://orcid.org/0000-0001-6223-1291
                https://orcid.org/0000-0002-7271-4091
                Article
                ELE14013
                10.1111/ele.14013
                9320941
                35478314
                e2ac43b7-2a8c-4f94-b455-0070e37c9b07
                © 2022 The Authors. Ecology Letters published by John Wiley & Sons Ltd.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 30 March 2022
                : 30 November 2021
                : 04 April 2022
                Page count
                Figures: 6, Tables: 1, Pages: 14, Words: 9412
                Funding
                Funded by: Australian Research Council , doi 10.13039/501100000923;
                Award ID: DP180103124
                Award ID: FT210100792
                Funded by: Griffith University , doi 10.13039/501100001791;
                Categories
                Letter
                Letters
                Custom metadata
                2.0
                June 2022
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.1.7 mode:remove_FC converted:26.07.2022

                Ecology
                antagonism,consumer‐resource,seagrass,stressor interactions,synergy
                Ecology
                antagonism, consumer‐resource, seagrass, stressor interactions, synergy

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