A hypothesis-driven statistical approach for identifying ecosystem indicators of coho and Chinook salmon marine survival. (May 2021) - Sobocinski, Kathryn L.; Greene, Correigh M.; Anderson, Joseph H.; Kendall, Neala W.; Schmidt, Michael W.; Zimmerman, Mara S.; Kemp, Iris M.; Kim, Su; Ruff, Casey P.
Graphical abstract: Highlights: Salmon marine survival declined in Puget Sound in the 1980s and failed to recover. Used hypothesis-driven framework of indicators for salmon marine survival. Analyzed factors related to ecology, environmental conditions, and human impacts. No single factor explains declines in marine survival. Predation, hatchery timing, and anthropogenic impacts are strongest model factors. Abstract: Efforts to understand causes of declines in productivity of species of concern often involve retrospective evaluation of multiple possible causes based on trends in relevant ecological indicators. We describe a hypothesis testing framework for examining declines in marine survival for coho and Chinook salmon in the Salish Sea. Independent populations of both anadromous species have declined over the last 50 years, prompting extensive examination of mortality in different life stages. Previous studies have identified declining trends in marine survival, and we re-evaluated these trends in light of a number of possible hypotheses for declines. We laid out seven potential explanations for declines: changes in predator buffering related to abundance and timing, density-dependent or -independent food availability, water quality, timing of freshwater delivery to Puget Sound, and anthropogenic impacts. We compiled ecosystem indicators relevant to these hypotheses and used generalized additive models (GAMs) to examine multivariate relationships with survival from multiple coho and Chinook salmon stocks. We also developed additional models using the most informative indicators based on variable importance weighting (VIW) from the seven hypothesis groups. We examined how these models explained overall trends in marine survival, as well as survival in three temporal stanzas (before, during, and after a major decline, based on statistical breakpoint analysis). Across the entire time series, best fitting models explained 30–40% of the variation in the survival data. Best fitting models were from multiple hypotheses, including predation (abundance and timing), competition, water quality, and anthropogenic impacts; the freshwater delivery hypothesis was the least supported. Different models performed best (lowest error) during different stanzas of the coho salmon marine survival time series and the two VIW models were generally the top performing models, but performance varied in different years. Indicators with the strongest support included seal abundance, herring abundance, timing of hatchery salmon releases, and indicators related to water properties like stratification and temperature. These findings suggest that multiple processes embedded in several of our hypotheses influence marine survival but that an ecological "smoking gun" for Salish Sea salmon declines will remain elusive.