Climate Change and Marine Food Webs: Navigating Structural Uncertainty Using Qualitative Network Analysis With Insights for Salmon Survival
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2025
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Journal Title:Global Change Biology
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Description:Effectively modeling the impact of climate change on any population requires careful consideration of diverse pressures. Potential changes in interactions with other species must be accounted for. As communities reassemble and shifts in abundance and distribution cascade throughout ecosystems, cumulative impacts on species of conservation concern need to be explicitly examined. A structured qualitative analysis of alternative responses to climate change across the food web can play a valuable role in the design and interpretation of quantitative models. A particular advantage of qualitative network analysis is the ease with which a wide range of scenarios representing structural and quantitative uncertainties can be explored. We tested 36 plausible representations of connections among salmon and key functional groups within the marine food web using qualitative network models. The scenarios differed in how species pairs were connected (positive, negative, or no interaction) and which species responded directly to climate change. Our analysis showed that certain configurations produced consistently negative outcomes for salmon, regardless of the specific values for most of the links. Salmon outcomes shifted from 30% to 84% negative when consumption rates by multiple competitor and predator groups increased following a press perturbation from climate. This scenario aligns with some recent observations during a marine heatwave. Feedbacks between salmon and mammalian predators were particularly important, as were indirect effects connecting spring‐ and fall‐run salmon. We also identified which links most strongly influenced salmon outcomes in other scenarios. Our results emphasize the importance of structural uncertainty in food webs and demonstrate a tool for exploring it, paving the way for more targeted and effective research planning.
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Source:Global Change Biology, 31(3)
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DOI:
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ISSN:1354-1013 ; 1365-2486
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Rights Information:CC BY-NC
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Compliance:Submitted
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Main Document Checksum:urn:sha-512:40015436150a81cb85b33badaac2301f96d6048a3f7ee188f8f1b4fa10d08bafe7167e08454f3014ba0de96674c52ba2ac5192e7f707e236e11d60f91a55e9bb
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