Potential for ecological nonlinearities and thresholds to inform Pacific salmon management. Issue 12 (8th December 2020) - Munsch, Stuart H.; Andrews, Kelly S.; Crozier, Lisa G.; Fonner, Robert; Gosselin, Jennifer L.; Greene, Correigh M.; Harvey, Chris J.; Lundin, Jessica I.; Pess, George R.; Samhouri, Jameal F.; Satterthwaite, William H.
Abstract: Ecology is often governed by nonlinear dynamics. Nonlinear ecological relationships can include thresholds—incremental changes in drivers that provoke disproportionately large ecological responses. Among the species that experience nonlinear and threshold dynamics are Pacific salmon ( Oncorhynchus spp.). These culturally, ecologically, and economically significant fishes are in many places declining and management focal points. Often, managers can influence or react to ecological conditions that salmon experience, suggesting that nonlinearities, especially thresholds, may provide opportunities to inform decisions. However, nonlinear dynamics are not always invoked in management decisions involving salmon. Here, we review reported nonlinearities and thresholds in salmon ecology, describe potential applications that scientists and managers could develop to leverage nonlinear dynamics, and offer a path toward decisions that account for ecological nonlinearities and thresholds to improve salmon outcomes. It appears that nonlinear dynamics are not uncommon in salmon ecology and that many management arenas may potentially leverage them to enable more effective or efficient decisions. Indeed, decisions guided by nonlinearities and thresholds may be particularly desirable considering salmon management arenas are often characterized by limited resources and mounting ecological stressors, practical constraints, and conservation challenges. More broadly, many salmon systems are data‐rich and there are an extensive range of ecological contexts in which salmon are sensitive to anthropogenic decisions. Approaches developed to leverage nonlinearities in salmon ecology may serve as examples that may inform analogous approaches in other systems and taxa.