San Francisco Estuary and Watershed Science

There has been considerable debate about effects of entrainment of endangered Delta Smelt (Hypomesus transpacificus) at water export facilities located in the Sacramento–San Joaquin River Delta. In this paper we use a behavior-driven movement model (BMM) to simulate the movement of adult Delta Smelt, which, in conjunction with a population dynamics model, estimates the proportion of the population that is lost to entrainment, i.e., proportional entrainment loss (PEL). Parameters of the population model are estimated by maximum likelihood by comparing predictions to data from Fall Midwater Trawl (FMWT) and Spring Kodiak Trawl (SKT) surveys, as well as to daily salvage estimates. Our objectives are to evaluate different movement behavior hypotheses, to rank estimates of PEL based on how well predictions fit the data, and to sharpen our understanding of the data to inform future research and monitoring decisions.

We applied the modeling framework to data from water year 2002—a year when salvage was high—and tested 30 combinations of six behavior and five population dynamics models. More complex process and observation assumptions in the population model led to much improved fits in most cases, but did not appreciably influence PEL predictions, which were largely determined by movement predictions from the BMMs. Estimates of PEL varied considerably among behaviors (2% to 40%). The model with the highest predictive capability explained 98% of the variation in FMWT data across regions, 70% of the variation in SKT data across regions and surveys, and 28% and 43% of the daily variation in salvage at federal and state fish screening facilities, respectively. The PEL estimate from this model was 35%, more than double the original estimate from Kimmerer (2008) of 15%. While PEL estimates provided in this study should be considered preliminary, our framework for testing combined behavior-driven movement models and population dynamics models is an improvement compared to earlier efforts.

Monitoring is an essential component in ecosystem management, and leveraging existing data sources for multiple species of interest can be one effective way to enhance information for management agencies. Here, we analyzed juvenile Chinook Salmon (Oncorhynchus tshawytscha) bycatch data that has been collected by the recently established Enhanced Delta Smelt Monitoring program (EDSM), a survey designed to estimate the abundance and distribution of the San Francisco Estuary’s (estuary) endangered Delta Smelt (Hypomesus transpacificus). Two key aspects of the EDSM program distinguish it from other fish surveys in the estuary: a stratified random sampling design and the spatial scale of its sampling effort. We integrated the EDSM data set with other existing surveys in the estuary, and used an occupancy model to assess differences in the probability of detecting Delta Smelt across gear types. We saw no large-scale differences in size selectivity, and while detection probability varied among gear types, cumulative detection probability for EDSM was comparable to other surveys because of the program’s use of replicate tows. Based on our occupancy model and sampling effort in the estuary during spring of 2017 and 2018, we highlighted under-sampled regions that saw improvements in monitoring coverage from EDSM. Our analysis also revealed that each sampling method has its own benefits and constraints. Although the use of random sites with replicates, as conducted by EDSM, can provide more statistically robust abundance estimates relative to traditional methods, the use of fixed stations and simple methods such as beach seining may provide a more cost-effective way to monitor salmon occurrence in certain regions of the estuary. Leveraging the strengths of each survey’s method can enable stronger inferences on salmon abundance and distribution. Careful consideration of these trade-offs is crucial as the management agencies of the estuary continue to adapt and improve their monitoring programs.

Delta Smelt, Hypomesus transpacificus, is an endangered pelagic fish native to the San Francisco Estuary. The distribution of Delta Smelt in the estuary shifts landward from low-salinity habitat to freshwater habitat before spawning. This spawning migration often coincides with the first substantial freshwater inflow to the estuary during winter. To accomplish this landward shift in distribution, Delta Smelt are believed to use the tides by swimming to faster-moving currents during flood tides and then repositioning themselves to slower-moving currents to reduce seaward movement on ebb tides. Studies have hypothesized that the swimming behavior of Delta Smelt during this period is influenced by environmental conditions such as salinity and turbidity. The details of these swimming behaviors—including the extent to which flows, salinity, and turbidity affect behaviors and distributions—are uncertain. The spawning migration is of management interest because an increase in observed counts of Delta Smelt at the South Delta water-export facilities has coincided roughly with the spawning migration in many years. In this study, we investigated a range of hypothesized swimming behaviors using a three-dimensional particle-tracking model for water year 2002 during the spawning migration, and compared the predicted distributions of Delta Smelt to distributions inferred from catch data. Our goal was to improve understanding of the influence of Delta Smelt swimming on distribution, and, ultimately, to develop a modeling tool to help management agencies identify conditions associated with entrainment losses. Predictions of Delta Smelt distributions and entrainment varied greatly among behaviors. Without swimming, Delta Smelt would be rapidly transported seaward of Suisun Bay, while continuous tidal migration would move them deep into the interior Delta. These behaviors and a simple turbidity-driven behavior model predicted distributions inconsistent with observations, while more complex behavior rules allowed improved predictions.

The San Francisco Estuary is an incredibly diverse ecosystem with a mosaic of aquatic habitats inhabited by a number of economically, culturally, and ecologically important fish species. To monitor the temporal and spatial trends of this rich fish community, long-term fish monitoring programs within the estuary use a variety of gear types to capture fish species across life stages and habitats. However, concerns have been raised that current sampling gears may fail to detect certain species—or life stages—that inhabit areas that are not accessible by current gear types (e.g., riprap banks, shallow vegetated areas). Boat electrofishing is one sampling method that has been proposed to supplement current long-term fish monitoring in the upper estuary. In this study, we used fish catch data from past boat electrofishing studies, a long-term beach seine survey, and a couple of long-running trawl surveys to compare the relative probability of detecting various fishes across these sampling gears. Overall, we found that boat electrofishing led to notable improvements in the detection rates for many native and non-native fishes we examined. Boat electrofishing gear was better at detecting the majority of species in the spring (20 out of 38 species, 53%) and fall-winter (24 out of 34 species, 70%) sampling periods. Based on these findings, we recommend that resource managers consider the implementation of a long-term boat electrofishing survey to help them in their long-term conservation planning for fishes within the upper estuary.

Managing endangered species is challenging when increased rarity leads to an inability to detect their responses to environmental conditions. In the San Francisco Estuary, the state and federally listed Delta Smelt (Hypomesus transpacificus) has declined to record low numbers, elevating concern over entrainment at the State Water Project (SWP) and Central Valley Project (CVP) water export facilities. The objective of this study was to: (1) revisit previous work on factors that affect adult Delta Smelt collected at the SWP and CVP fish collection facilities using updated conceptual models and a new statistical approach; and (2) to determine factors that affect salvage at time-scales of interest to management. Boosted Regression Tree (BRT) models were applied to salvage data at the SWP and CVP, aggregated into two response categories: a “first flush” response that represented daily salvage from the start of the entrainment window to the 50% midpoint of observed salvage, and a “seasonal” response that included daily salvage from the entire entrainment window. Precipitation, sub-adult abundance, Yolo Bypass flow, and exports best explained first flush salvage at both the SWP and CVP. The seasonal models included a similar set of influential variables, but the relative influence of precipitation was lower compared to the first flush models., Yolo Bypass flow was more influential for seasonal salvage at the SWP, compared to the CVP; Old and Middle River flow was more influential for seasonal salvage at the CVP. Although the rank of variable importance that explains salvage differed slightly between first flush and seasonal time-scales, this study suggests that salvage is most influenced by hydrodynamics, water quality, and population abundance. The application of BRT models to predict salvage is limited, because salvage has been low since federal protections were implemented in 2008. Forecast models that integrate real-time variables with fish behavior models may improve Delta Smelt management.