Salmonid Restoration Federation
April 29 - May 2, 2025
Santa Cruz, California

Spring-run Monitoring, Modeling, and Coordinated Data Management: Building Tools to Guide and Track Recovery

Session Coordinator: Brett Harvey, California Department of Water Resources
 
Central Valley spring-run Chinook Salmon are protected under both the state and federal Endangered Species Act, but measures to protect and recover spring-run are challenged by the difficulty in tracking status and life stages of remnant populations across multiple streams and agency programs. The California Department of Fish and Wildlife and Department of Water Resources, U.S. Fish and Wildlife Service, NOAA Fisheries, and Bureau of Reclamation, plus agency partners, are collaborating to develop an approach for calculating an annual spring-run Chinook Salmon juvenile production estimate (SR JPE) for the Sacramento River and its tributaries. The SR JPE is a forecast of the juvenile spring-run abundance expected to migrate into the Delta each year. Although its immediate purpose is to support measures to protect and enhance spring-run populations, the SR JPE program supports salmon science and recovery planning beyond a JPE, beyond the Sacramento River, and beyond spring-run. This symposium describes the processes and partnerships formed to support an annual SR JPE and the outcomes of these partnerships, including: expanded monitoring, new genetics tools, a coordinated data management system among more than 20 data stewards across multiple state and federal agencies, a cloud-based data entry platform that ensures rapidly-reported cross-compatible data from over 40 individual sources, multiple models to track production, survival, and abundance across life stage and locations, and publicly accessible databases and model code. Model development involved coordination of field staff, geneticists, lab technicians, and modelers. Structured-Decision-Making guides development of alternative SR-JPE approaches, final approach selection for implementation, and coupled with the data management system provides a transparent framework to address multidimensional decisions, including updates of spring-run monitoring and models as new information is developed in the future.