Dr. Noble Hendrix1
1QEDA Consulting
May 09, 2017 9:00 (PST): FSH 203
A court mandated life-cycle model to evaluate California Central Valley water operation effects on Chinook salmon
In 2009, NOAA Fisheries Central Valley California Office submitted a Biological Opinion on the operations of multiple water control structures (dams, routing gates, and export facilities), that was litigated by multiple water agencies. The Biological Opinion was remanded in 2011 by the judge, who also provided a strongly worded rebuking (fueled to some degree by the testimony of SAFS own Ray Hilborn) that stated, “this is the last time NMFS will be permitted to avoid studying, analyzing, and applying a life cycle model. NMFS’s chronic failure to do so now approaches bad faith in view of the undeniable importance of the information to resolve the perennial dispute over population dynamics. ”
NOAA Fisheries Southwest Fisheries Science Center shortly thereafter initated a life cycle modeling project to predict how various salmon populations would respond to suites of management actions, including changes to flow and export regimes, modification of water extraction facilities, and large-scale habitat restoration. I was asked to help with the first model in the project, which is a life cycle model for winter-run Chinook salmon (WRLCM). The WRLCM couples water planning models and physical models (e.g., HEC-RAS, DSM2, DSM2-PTM) and fishery models to evaluate management actions on winter-run population dynamics. I will describe the general model structure, the transition equations that define the movement and survival throughout the life cycle and linkages to physical models for integrating dynamics over finer spatial and temporal scales. Because the WRLCM was developed to evaluate management actions, the model sptial and temporal structure focuses on addressing questions of hydromanagment and habitat restoration. Unfortunately, this structure is not particularly well-suited for statistical estimation and presents numerous difficulties for estimating model parameters. We implemented a state-space structure and estimated the model parameters using a variant of the Expectation-Maximization algorithm to obtain MLE estimates and are actively pursuing MCMC approaches for Bayesian estimation. The fitted model is currently being used to evaluate proposed actions as part of a 2017 NOAA Fisheries Biological Opinion, meeting the judge’s 2011 request. More importantly, the calibrated WRLCM is providing a central framework that can be used to assess restoration projects, construct adaptive management frameworks, evaluate reintroduction success, simulate new monitoring designs, and prioritize recovery actions.