Application of the Stream Salmonid Simulator (S3) to the restoration reach of the Trinity River, California--Parameterization and calibration

Abstract

In this report, we constructed and parameterized the Stream Salmonid Simulator (S3) for the 64-kilometer “Restoration Reach” of the Trinity River, just downstream of Lewiston Dam in northern California. S3 is a deterministic life-stage-structured population model that tracks daily growth, movement, and survival of juvenile salmon. A key theme of the model is that river flow affects habitat availability and capacity, which in turn drives density-dependent population dynamics. To explicitly link population dynamics to habitat quality and quantity, the river environment is constructed as a one-dimensional series of linked habitat units, each of which has an associated daily timeseries of discharge, water temperature, and useable habitat area or carrying capacity. In turn, the physical characteristics of each habitat unit and the number of fish occupying each unit drive survival and growth within each habitat unit and movement of fish among habitat units. The physical template of the Restoration Reach was formed by classifying the river into 356 meso-habitat units comprised of runs, riffles, and pools. For each habitat unit, we developed a timeseries of daily flow, water temperature, amount of available spawning habitat, and fry and parr carrying capacity. Capacity timeseries were constructed using state-of-the-art models of spatially explicit hydrodynamics and quantitative fish habitat relationships developed for the Trinity River. These variables were then used to drive population dynamics such as egg growth and survival and juvenile movement, growth, and survival. We estimated key movement and survival parameters by calibrating the model to five years of weekly juvenile abundance estimates from a rotary screw trap located near the downstream terminus of the Restoration Reach. The calibration consisted of replicating historical conditions as closely as possible (for example, flow; temperature; spawner abundance, spawning location and timing, and hatchery releases), and then running the model to predict weekly abundance passing the trap location. We also evaluated alternative model structures that included either density-independent movement and survival, density-dependent survival, or density-dependent movement. AIC model selection criterion was used to evaluate the strength of evidence for alternative model structures to replicate the observed abundance estimates.