SFEWS: Volume 19, Issue 2
Welcome to the June issue of San Francisco Estuary and Watershed Science. At midyear in 2021, research surrounding the San Francisco Estuary looks forward. Here, six articles in four categories offer advances in science using new technologies and a re-examination of past efforts.
Photo: CA Dept. of Water Resources, public domain.
In Honor of Dr. Larry R. Brown
Herbold et al. remember Dr. Larry R. Brown, who died suddenly in February of 2021. This note captures how important his scientific work was in the San Francisco Estuary and why he will be intensely missed by many of his colleagues.
Photo: Canva stock image
Preparing Scientists, Policymakers, and Managers for a Fast-Forward Future
To accelerate forward-looking science, policy, and management in the Delta, Norgaard et al. propose that the State of California create a Delta Science Visioning Process to fully and openly assess the challenges of more rapid change to science, policy, and management and offer appropriate solutions, including legislation.
Photo: CA Dept. of Water Resources, public domain
Ecological Effects of Climate-Driven Salinity Variation in the San Francisco Estuary: Can We Anticipate and Manage the Coming Changes?
Ghalambor et al. review and summarize the presentations and discussions that arose during the symposium “Ecological and Physiological Impacts of Salinization of Aquatic Systems from Human Activities,” which brought together an interdisciplinary group of scientists, managers, and policy-makers to answer the central question: can we use existing knowledge and future projections to predict and manage anticipated ecological impacts?
Photo: Canva stock image
Effects of Tidally Varying River Flow on Entrainment of Juvenile Salmon into Sutter and Steamboat Slough
Previous studies suggest that fish generally “go with the flow”—however, complex tidal hydrodynamics at sub-daily time-scales may be decoupled from net flow. To further examine entrainment of acoustically tagged juvenile Chinook Salmon into Sutter and Steamboat sloughs, Romine et al. modeled routing of acoustic tagged juvenile salmon as a function of tidally varying hydrodynamic data. Results indicate that discharge, the proportion of flow that entered the slough, and the rate of change of flow were good predictors of the probability of an individual fish being entrained.
Photo: John Burau
Examining Retention-at-Length of Pelagic Fishes Caught in the Fall Midwater Trawl Survey
A study was conducted in 2014-2015 to investigate and quantify the efficiency of the Fall Midwater Trawl for catching the endangered fish species Delta Smelt (Hypomesus transpacificus). Mitchell and Baxter revisit the same gear efficiency study and further utilize the data set by fitting selectivity curves for three additional pelagic fish species: Threadfin Shad (Dorosoma petenense), American Shad (Alosa sapidissima), and Mississippi Silverside (Menidia beryllina), and by applying more statistically sensitive approaches.
Photo: Lara Mitchell
Use of the SmeltCam as an Efficient Fish Sampling Alternative Within the San Francisco Estuary
Resource managers often rely on long-term monitoring surveys to detect trends in biological data. However, no survey gear is 100% efficient, and many sources of bias can both detect or miss biological trends. Huntsman et al. evaulate the SmeltCam, an imaging apparatus developed as a sampling alternative to long-term trawling gear surveys within the San Francisco Estuary, with the potential to reduce handling stress on sensitive species like the Delta Smelt (Hypomesus transpacificus).
Photo: Ken Newman
Volume 7, Issue 2, 2009
Nearshore Areas Used by Fry Chinook Salmon, Oncorhynchus tshawytscha, in the Northwestern Sacramento–San Joaquin Delta, California
We reported the geographic distribution and the densities and catch rates of fry Chinook salmon, Oncorhynchus tshawytscha, found in different substrata and nearshore zones in the northwestern Sacramento-San Joaquin Delta of the San Francisco Estuary, California, USA. Nearshore zones in the fresh-water, tidally influenced northwest delta were dominated by riprap, and contained sparse sections of tule beds, beaches, and riparian zones. A total of six beach seine sites and eight electrofish sites were sampled during winter 2001 along the Sacramento River, Steamboat Slough, Miner Slough, Prospect Island Marsh, Prospect Slough, and Liberty Island Marsh. Overall, fry densities were higher on the Sacramento River and Steamboat Slough and lower in Liberty and Prospect Island marshes. Chinook salmon fry were significantly larger in the Sacramento River than in Steamboat Slough during March. Highest densities of Chinook salmon fry were observed in shallow beaches than in riprap nearshore zones. Fry densities also increased with Secchi depth and richness of non-native predators, suggesting increased predation risk by opportunistic predators. Shallow nearshore environments in conveyance channels, such as Steamboat Slough and the Sacramento River, seem important for Chinook salmon fry rearing. Conversely, riprap in these channels could reduce fry rearing habitat. Although fry catch rates by electrofishing did not differ greatly among riparian, riprap, beach and tule nearshore zones, they were on average about one-third higher in beaches. Evaluating potential impacts of habitat quality on growth and survival of fry seems key to further assess and monitor restoration efforts in the delta.
Simulations of circulation in the San Francisco Estuary were performed with the three-dimensional TRIM3D hydrodynamic model using a generic length scale turbulence closure. The model was calibrated to reproduce observed tidal elevations, tidal currents, and salinity observations in the San Francisco Estuary using data collected during 1996-1998, a period of high and variable freshwater flow. It was then validated for 1994-1995, with emphasis on spring of 1994, a period of intensive data collection in the northern estuary. The model predicts tidal elevations and tidal currents accurately, and realistically predicts salinity at both the seasonal and tidal time scales. The model represents salt intrusion into the estuary accurately, and therefore accurately represents the salt balance. The model’s accuracy is adequate for its intended purposes of predicting salinity, analyzing gravitational circulation, and driving a particle-tracking model. Two applications were used to demonstrate the utility of the model. We estimated the components of the longitudinal salt flux and examined their dependence on flow conditions, and compared predicted salt intrusion with estimates from two empirical models.
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The State and federal water projects decoupled long-term trends in annual mean outflow and salinity from long-term trends in precipitation. The water projects also dampen seasonal and annual outflow and salinity variability. Despite this, both seasonal and annual timescale outflow and salinity are generally more variable in the water project era concordant with watershed precipitation. We re-constructed monthly time series of precipitation, outflow, and salinity for the northern reach. These include salinity at Port Chicago (since 1947), Beldons Landing (since 1929), and Collinsville (since 1921), Delta outflow (since 1929), and a San Francisco Estuary watershed precipitation index (since 1921). We decomposed data into seasonal, decadal, and trend components to clarify the superposition of variability drivers. With the longest time series over 1000 months, these are the longest data records in the estuary save for Golden Gate tide. We used the precipitation index to compare trends and variability in climate forcing to outflow and salinity trends before and after construction of the water projects and the Suisun Marsh Salinity Control Gate. We test the widely held conceptual model that water project reservoir and Delta export operations reduce seasonal and annual outflow variability. We found that the water projects influence the trend of the annual and some monthly means in outflow and salinity, but exert far less influence on variability. We suggest that climate is the primary variability driver at timescales between one-month and ~20 years. We underscore the understanding that identifying trends and mechanisms requires data sets that are longer than the timescale of the lowest frequency forcing mechanism.