Climate Change and Marine Food Webs: Navigating Structural Uncertainty Using Qualitative Network Analysis With Insights for Salmon Survival Global Change Biology

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.

有效模拟气候变化对任意种群的影响，需审慎考量各类多样压力，且必须纳入与其他物种间相互作用的潜在变化。随着生物群落重组、丰度与分布的变化在生态系统中逐级传递，针对受保护物种的累积影响需得到明确检视。对食物网内各组分应对气候变化的不同响应开展结构化定性分析，可为定量模型的设计与解读提供重要支撑。定性网络分析的突出优势之一，在于能够便捷地探索涵盖结构与定量不确定性的多样化场景。

我们借助定性网络模型，针对海洋食物网内鲑鱼与关键功能群间的36种合理关联表征展开了测试。这些场景的差异体现在两方面：一是物种对间的关联类型（正相互作用、负相互作用或无相互作用），二是哪些物种会直接响应气候变化。分析结果显示，特定配置下鲑鱼会持续出现负面结果，且该结果不受多数关联的具体数值影响。当气候引发的持续压力扰动导致多个竞争者与捕食者类群的取食速率上升时，鲑鱼出现负面结果的比例从30%升至84%。该场景与近期海洋热浪期间的部分观测结果相符。鲑鱼与哺乳类捕食者间的反馈效应尤为关键，连接春季洄游与秋季洄游鲑鱼的间接效应亦是如此。我们还明确了在其他场景中对鲑鱼结果影响最强的关联。

本研究结果凸显了食物网中结构不确定性的重要性，并提供了一种探索该不确定性的工具，为更具针对性与实效性的研究规划铺平了道路。