Carey, K.C., M. Kent, C. B. Schreck, C. E. Couch, L. Whitman, and J. T. Peterson. Modeling the effects of stream temperature and human disturbance on prespawn mortality of spring Chinook salmon in an adaptive management framework. North American Journal of Fisheries Management
Abstract
Premature mortality of adult Chinook salmon (Oncorhynchus tshawytscha) is a major barrier to population recovery. Previous studies have attributed population declines to loss of habitat caused by water impoundments and other forms of development. The Willamette River Basin, OR typifies the problems faced by fishery managers in the Pacific Northwest. Although adult salmon are trapped and transported upstream of dams so they can access historic spawning grounds, annual rates of prespawn mortality (PSM) are high (often >40%) and may limit recovery of natural populations if not reduced. The purpose of this study was to identify and develop potential factors related to PSM into a conceptual model with the aim of incorporating future monitoring data to facilitate adaptive management of outplanting operations. We evaluated PSM in Fall Creek of the Willamette River Basin prior to transport facility improvements in summer and fall of 2010-2017 and post-improvement in 2020-2021. We estimated PSM and conducted exploratory analyses to identify possible non-transport sources of stress that may contribute to the observed high PSM rates. Candidate factors included long-term elevated temperature exposure, elevated temperature exposure below the trap, total number outplanted fish, and monthly human disturbance of outplanted fish. We then developed and fit three models each representing a hypothesis of the factor influencing PSM, incorporated them into a single decision model, and conducted sensitivity analyses. PSM averaged 66% over the study period and was greater for females. The top two management actions based on simulation results were to exclude human activity from Fall Creek in August and July, which reduced expected PSM rates to 37% and 38%. Sensitivity analyses indicated that the most influential decision model component was the choice of alternative model. We illustrate how annual monitoring data can be used to update the decision model and improve management, which can ultimately support recovery efforts.