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Predicting effects of multiple interacting global change drivers across trophic levels

pmid: 36461630
pmc: PMC7614140
AbstractGlobal change encompasses many co‐occurring anthropogenic drivers, which can act synergistically or antagonistically on ecological systems. Predicting how different global change drivers simultaneously contribute to observed biodiversity change is a key challenge for ecology and conservation. However, we lack the mechanistic understanding of how multiple global change drivers influence the vital rates of multiple interacting species. We propose that reaction norms, the relationships between a driver and vital rates like growth, mortality, and consumption, provide insights to the underlying mechanisms of community responses to multiple drivers. Understanding how multiple drivers interact to affect demographic rates using a reaction‐norm perspective can improve our ability to make predictions of interactions at higher levels of organization—that is, community and food web. Building on the framework of consumer–resource interactions and widely studied thermal performance curves, we illustrate how joint driver impacts can be scaled up from the population to the community level. A simple proof‐of‐concept model demonstrates how reaction norms of vital rates predict the prevalence of driver interactions at the community level. A literature search suggests that our proposed approach is not yet used in multiple driver research. We outline how realistic response surfaces (i.e., multidimensional reaction norms) can be inferred by parametric and nonparametric approaches. Response surfaces have the potential to strengthen our understanding of how multiple drivers affect communities as well as improve our ability to predict when interactive effects emerge, two of the major challenges of ecology today.
- Institut National des Sciences de l'Univers France
- ETH Zurich Switzerland
- Namur Institute for Complex Systems Belgium
- Leibniz Institute for Zoo and Wildlife Research Germany
- University of Zurich Switzerland
570, Food Chain, Climate Change, reaction norms, 577, 2306 Global and Planetary Change, 333, thermal performance curves, Opinions, 2300 General Environmental Science, 10127 Institute of Evolutionary Biology and Environmental Studies, [SDV.EE]Life Sciences [q-bio]/Ecology, consumer-resource model, Environmental Chemistry, global change, Ecosystem, General Environmental Science, Global and Planetary Change, species interactions, Ecology, consumer–resource model ; Climate Change [MeSH] ; global change ; Environmental Chemistry ; Ecosystem [MeSH] ; Ecology [MeSH] ; Global and Planetary Change ; Biodiversity [MeSH] ; thermal performance curves ; Ecology ; reaction norms ; General Environmental Science ; Food Chain [MeSH] ; multiple stressors ; species interactions, Biodiversity, [SDE.BE] Environmental Sciences/Biodiversity and Ecology, multiple stressors, [SDV.EE] Life Sciences [q-bio]/Ecology, environment, 2304 Environmental Chemistry, 570 Life sciences; biology, 590 Animals (Zoology), consumer–resource model, [SDE.BE]Environmental Sciences/Biodiversity and Ecology, environment, 2303 Ecology
570, Food Chain, Climate Change, reaction norms, 577, 2306 Global and Planetary Change, 333, thermal performance curves, Opinions, 2300 General Environmental Science, 10127 Institute of Evolutionary Biology and Environmental Studies, [SDV.EE]Life Sciences [q-bio]/Ecology, consumer-resource model, Environmental Chemistry, global change, Ecosystem, General Environmental Science, Global and Planetary Change, species interactions, Ecology, consumer–resource model ; Climate Change [MeSH] ; global change ; Environmental Chemistry ; Ecosystem [MeSH] ; Ecology [MeSH] ; Global and Planetary Change ; Biodiversity [MeSH] ; thermal performance curves ; Ecology ; reaction norms ; General Environmental Science ; Food Chain [MeSH] ; multiple stressors ; species interactions, Biodiversity, [SDE.BE] Environmental Sciences/Biodiversity and Ecology, multiple stressors, [SDV.EE] Life Sciences [q-bio]/Ecology, environment, 2304 Environmental Chemistry, 570 Life sciences; biology, 590 Animals (Zoology), consumer–resource model, [SDE.BE]Environmental Sciences/Biodiversity and Ecology, environment, 2303 Ecology
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).20 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
