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The Sacramento–San Joaquin Delta (hereafter, "the Delta") is one of the estuaries with the most invasive species in the world, and nonnative predators may be a major factor in the observed decline of Central Valley Chinook Salmon Oncorhynchus tshawytscha over recent decades. In order for managers to take actions that might reduce predation‐related mortality for these ecologically, culturally, and economically valuable fish, it is important to understand the factors influencing the distribution and abundance of piscivores in the Delta. In this study, we used a dual‐frequency identification sonar (i.e., DIDSON) to conduct mobile surveys to quantify the abundances of piscivores in the Delta. We then used these data to identify the habitat features that are correlated with the abundance of piscivores. Prior to conducting the surveys, we used DIDSON data from captured fish to develop an algorithm to distinguish piscivores from nonpiscivores with high confidence (98% accuracy). A generalized linear mixed‐effects model fit to these survey data indicated that predator abundances were most associated with areas of increased submerged aquatic vegetation patches, and channels that are straighter, with increased bathymetric complexity. When applied to the entire survey area, this model was successfully able to predict known areas of high predator densities. These results indicate that one approach to reduce predator densities in key locations throughout the Delta, and improve juvenile salmonid outmigration survival, is to reduce the extent of invasive submerged aquatic vegetation. Because experimental predator removals have been largely ineffective in the Delta, efforts to manipulate habitat to discourage nonnative predator recruitment and favor native species recruitment may provide a more effective solution to improve salmonid survival rates. [ABSTRACT FROM AUTHOR]

Predator–prey dynamics can have landscape-level impacts on ecosystems, and yet, spatial patterns and environmental predictors of predator–prey dynamics are often investigated at discrete locations, limiting our understanding of the broader impacts. At these broader scales, landscapes often contain multiple complex and heterogeneous habitats, requiring a spatially representative sampling design. This challenge is especially pronounced in California’s Sacramento–San Joaquin River Delta, where managers require information on the landscape-scale impacts of non-native fish predators on multiple imperiled native prey fish populations. We quantified relative predation risk in the southern half of the Delta (South Delta) in 2017 using floating baited tethers that record the exact time and location of predation events. We selected 20 study sites using a generalized random tessellation stratified survey design, which allowed us to infer relationships between key environmental covariates and predation across a broader spatial scale than previous studies. Covariates included distance-to-nearest predators, water temperature, turbidity, depth, bottom slope, bottom roughness, water velocity, and distance-to-nearest riverbank and nearest aquatic vegetation bed. Model selection determined the covariates that best predicted relative predation risk: water temperature, time of day, mean predator distance, and river bottom roughness. Using this model, we estimated predation risk for the South Delta landscape at a 1-day and 1-km resolution. This effort identified hot spots of predation risk and allowed us to generate predicted survival for migrating fish transiting the South Delta. This methodology can be applied to other systems to evaluate spatio-temporal dynamics in predation risk, and their biotic and abiotic predictors. [ABSTRACT FROM AUTHOR]

Populations of wild spring-run Chinook salmon in California's Central Valley, once numbering in the millions, have dramatically declined to record low numbers. Dam construction, habitat degradation, and altered flow regimes have all contributed to depress populations, which currently persist in only a few tributaries to the Sacramento River. Mill Creek (Tehama County) continues to support these threatened fish, and contains some of the most pristine spawning and rearing habitat available in the Central Valley. Despite this pristine habitat, the number of Chinook salmon returning to spawn has declined to record low numbers, likely due to poor outmigration survival rates. From 2013 to 2017, 334 smolts were captured and acoustic tagged while out-migrating from Mill Creek, allowing for movement and survival rates to be tracked over 250 km through the Sacramento River. During this study California experienced both a historic drought and record rainfall, resulting in dramatic fluctuations in year-to-year river flow and water temperature. Cumulative survival of tagged smolts from Mill Creek through the Sacramento River was 9.5% (±1.6) during the study, with relatively low survival during historic drought conditions in 2015 (4.9% ± 1.6) followed by increased survival during high flows in 2017 (42.3% ± 9.1). Survival in Mill Creek and the Sacramento River was modeled over a range of flow values, which indicated that higher flows in each region result in increased survival rates. Survival estimates gathered in this study can help focus management and restoration actions over a relatively long migration corridor to specific regions of low survival, and provide guidance for management actions in the Sacramento River aimed at restoring populations of threatened Central Valley spring-run Chinook salmon. [ABSTRACT FROM AUTHOR]

Low survival rates of Chinook salmon (Oncorhynchus tshawytscha) smolts in California's Central Valley have been attributed to multiple biological and physical factors, but it is not clear which factors have the largest impact. We used 5 years of acoustic telemetry data for 1709 late-fall Chinook salmon smolts to evaluate the effect of habitat- and predation-related covariates on outmigration survival through the Sacramento River. Using a Cormack–Jolly–Seber mark–recapture model, we estimated survival rates both as a function of covariates (covariate model) and as a function of river location and release year (spatial–temporal model). Our covariate model was overwhelmingly supported as the preferred model based on model selection criteria, suggesting the covariates adequately replicated spatial and temporal patterns in smolt survival. The covariates in the selected model included individual fish covariates, habitat-specific covariates, and temporally variable physical conditions. The most important covariate affecting salmon survival was flow. We describe the importance of these parameters in the context of juvenile salmon predation risk and suggest that additional research on predator distribution and density could improve model estimates. [ABSTRACT FROM AUTHOR]