Science Stories: Adventures in Bay-Delta Data

By Peter Nelson

The Challenge

Spring-run Chinook salmon (“spring-run”) are listed as threatened under both the California Endangered Species Act and the Federal Endangered Species Act. Like most salmon, these fish are anadromous: The adults, having grown and matured in the ocean, return to their natal stream to spawn, and the juveniles, after rearing in freshwater, eventually migrate downstream to the ocean (see Figure 1). During that downstream migration, juvenile salmon are exposed to a gauntlet of threats, including warm water temperatures, predators of all sorts, and “taking the wrong turn” through water diversions and getting lost on their way to the ocean. Managing or reducing the risk posed by water diversions is a responsibility of the Department of Water Resources, and to do that water managers need to know the number and timing of those outmigrating juvenile spring-run as they enter the Delta. Coming up with an accurate prediction of this—what’s termed a Juvenile Production Estimate (PDF) or JPE—is not simple. This is the first of a two part piece about our efforts to develop a JPE, both what’s been accomplished and what’s planned, as well as a timeline.

Figure 1. Spring-run chinook have a complex life cycle. The adults migrate upstream in January through March, but instead of spawning right away like most salmon they hold in coldwater pools all summer and spawn in the fall. Diagram by Rosemary Hartman, Department of Water Resources. Click to enlarge.

The Approach

We know when to expect adult spring-run to return to their natal streams to spawn based on past experience: Humans, beginning with the indigenous peoples of the West Coast, have been observing these runs for generations, and we might reasonably expect that the numbers of returning adult salmon are a decent predictor of the juvenile fish those returning salmon will eventually produce. Observations by multiple teams of biologists of adult salmon throughout the Central Valley allow us to predict the likely numbers of juvenile spring-run expected to migrate downstream and enter the Delta on the way to the Pacific Ocean each year. “Hold on a minute,” you might say, “What about the water in those streams? If the creeks are low and the water is warm, surely those baby salmon won’t do as well as they might when conditions are good.” You’d be right! The number of reproducing salmon—the parents—isn’t a perfect predictor of the number of offspring: There are many environmental factors that affect juvenile production, but, based on past studies of salmon ecology, we can include factors like flow in our analysis of the likely number of juveniles that will be produced by the annual return of adult salmon (for example, see Michel 2019; Singer et al. 2020).

These estimates, however, are just that—we can’t know exactly how the varying amount of water will affect the survival of juvenile salmon as they grow and migrate, but we should get reasonably close, and we have another source of information to improve our estimates, the number of outmigrating juveniles that we observe directly as they swim towards the Delta: The streams where spring-run spawn regularly have rotary screw traps (Video) (RSTs, Figure 2) on them. These devices divert migrating juveniles into a holding pen where biologists count and measure them each day before releasing them back into the stream to continue their journey to the sea. Data from these RSTs give us another check on our estimates based on spawner production, and are themselves an alternative means for estimating spring -run juvenile production.

Figure 2. A rotary screw trap floating in the Yolo Bypass Toe Drain with its cone out of the water (not sampling). Photo courtesy of the Department of Water resources.

One last point: In order for water managers to use these predictions for how many (and when) spring-run are expected to reach the Delta, these estimates need to happen each year before spring-run are expected to enter the Delta when water managers need to make decisions about their operations. This is especially tricky for estimates that rely on that RST data because it only takes a few weeks for juvenile salmon to travel from the RSTs to the Delta. This means that the process of counting adult salmon and (especially) juvenile salmon in the RSTs, entering those data into a shared database, and crunching the numbers to produce a JPE must be fast, efficient and accurate.

Gathering Information

This is a collaborative, interagency effort, which we began by holding a broad-based, public workshop in September 2020 with the Department of Fish and Wildlife (see Nelson et al. 2022 for details) and writing a science plan (PDF) with our agency partners to determine what monitoring data were needed to develop a spring-run JPE. Estimating an annual spring-run JPE is complicated by (1) the broad geographic and geologic range of Central Valley streams that support spring-run, (2) the challenge of developing a holistic, coordinated multi-agency monitoring framework for generating quantitative estimates of juvenile spring-run across their range, (3) the variable life history displayed across the spring-run streams, and (4) the difficulty of distinguishing juvenile spring-run from other run types (fall run, late-fall run, and winter run) found in the same streams (we will talk more about distinguishing salmon run type in our next blog post).

Monitoring

Most of the monitoring in spring-run streams is conducted by the staff of several governmental agencies (e.g., Deer Creek), gathering data on the numbers and timing of returning adults and of migrating juveniles, and tracking the changes in these metrics from year-to-year, but monitoring historically was designed to focus on local management needs, employed multiple methods and focused on different life stages across the watershed. Some work has been done to integrate data on number of returning adults (CDFW's GrandTab dataset, which produced the graph of returning adults, Figure 3 below). However, a spring-run JPE will require more a coordinated approach with the means of combining data from more than 40 monitoring programs from eight regions, several governmental agencies, and nearly two dozen data stewards and managers, using diverse methods and having large discrepancies in monitoring histories. These are significant challenges, but they can be met as long as we’re aware of the limitations (see below).

Figure 3. Total escapement (number of returning adults) by tributary for 2000-2022. Click for an enlarged version broken out by tributary.

In addition to gathering data on the number and timing of returning adults and departing juveniles, we’ll also need data on year-to-year salmon spawning success and on the survival of those outmigrating juveniles as they move from higher elevation habitats through lower, slower and warmer tributaries, and as they migrate down the mainstem of the Sacramento River to finally reach the Delta (streams with major spring-run spawning are shown in Figure 4).

Environmental conditions too are crucial: Preeminent are the quantity of water in the system and water temperature; we know that these have strong effects on salmon survivorship and behavior. The number and location of predators also vary from year to year and can affect the number of juvenile spring-run reaching the Delta.

Figure 4. Map of the Sacramento River watershed highlighting the rivers and streams where data is being collected for the spring-run JPE. Some spring-run also spawn in the San Joaquin watershed, but they have not been added to the spring-run JPE dataset yet. Click to enlarge.

Data Management

You may have heard the expression, “garbage in, garbage out”? Wherever the phrase originated, it certainly applies to ecology! Quality data and metadata (how, when, where, and by whom the data are collected) are critical to an accurate spring-run JPE and its application to salmon conservation and water management. DWR led the formation of a team to design a data management system. This team conducted extensive outreach to the various monitoring programs for the seven spring-run spawning streams identified as most important to the JPE.

This data management system is now a reality, and is designed to provide timely access to machine-readable monitoring data and metadata. To meet the annual deadlines for calculating a spring-run JPE, new RST data must be compatible across programs and reported rapidly. Building the initial dataset took over a year because of historical inconsistencies in data reporting across monitoring programs, but state and federal agencies are collaborating to make newly collected data compatible from the moment of data entry. Data from some monitoring programs are now acquired automatically from digital entry and uploads are occurring directly from the field daily; the rest of the monitoring programs will move to this “field-to-cloud” data entry system over the next several years, improving data quality and the greatly facilitating the ease of access. All historical RST data are now publicly available from the Environmental Data Initiative (use search term “JPE”), and new RST data will be added to this repository on a weekly basis. Indeed, one of the most exciting and novel aspects of the spring-run JPE effort is that it has unified much of the existing data reporting from multiple agencies monitoring along with new monitoring under a common goal and purpose.

The spring-run JPE data management program

• has now standardized data collection methodologies, schemas, encodings, and processing protocols;
• produces machine-readable data for all RST monitoring programs (adult data will follow soon);
• uploads data in near real-time to a shared data management system; and
• makes data publicly accessible in a simple format.

This system allows us to look at all the different data sources at once to learn new things! For example, if we plot the catch of salmon from the rotary screw traps at Mill Creek, the Feather River, Knights Landing, and Delta Entry from upstream to downstream (Figure 5) we see that the most upstream site (Mill Creek) catches salmon earlier than the downstream sites and catches a lot more of them. Moving downstream the catch gets smaller and smaller as juvenile salmon get lost, eaten, or die along the way. Mill Creek also has juvenile salmon leaving the stream as late as May or June, but very few of these fish make it all the way down to the Delta, indicating that later migrants might have a harder time surviving.

Figure 5. Plot of rotary screw trap catch over time for the spring of 2023 at several locations in the Central Valley. Click to enlarge.

In our next post on the spring-run JPE, we’ll describe the cutting-edge genetic tools we’re using to distinguish spring-run from the other Central Valley Chinook, the quantitative modeling we’re developing that pulls in all of the salmon and environmental data and actually produced a juvenile production estimate along with an indication of our confidence in that estimate, the peer-review process that will critique our program and recommend improvements, and where we expect to take this spring -run JPE program next.

Further Reading

• Atlas WI, Ban NC, Moore JW, Tuohy AM, Greening S, Reid AJ, Morven N, White E, Housty WG, Housty JA et al. 2020. Indigenous Systems of Management for Culturally and Ecologically Resilient Pacific Salmon (Oncorhynchus spp.) Fisheries. BioScience. 71(2):186-204.
• Nelson PA, Baerwald M, Burgess O, Bush E, Collins A, Cordoleani F, DeBey H, Gille D, Goertler PAL, Harvey B et al. 2022. Considerations for the Development of a Juvenile Production Estimate for Central Valley Spring-Run Chinook Salmon. San Francisco Estuary and Watershed Science. 20(2).
• Cordoleani F, Satterthwaite WH, Daniels ME, Johnson MR. 2020. Using Life-Cycle Models to Identify Monitoring Gaps for Central Valley Spring-Run Chinook Salmon. San Francisco Estuary and Watershed Science. 18(4).
• Harvey BN, Jacobson DP, Banks MA. 2014. Quantifying the Uncertainty of a Juvenile Chinook Salmon Race Identification Method for a Mixed-Race Stock. North American Journal of Fisheries Management. 34(6):1177-1186.
• Michel CJ. 2019. Decoupling outmigration from marine survival indicates outsized influence of streamflow on cohort success for California’s Chinook salmon populations. Canadian Journal of Fisheries and Aquatic Sciences. 76(8):1398-1410.
• Satterthwaite WH, Cordoleani F, O'Farrell MR, Kormos B, Mohr MS. 2018. Central Valley Spring-Run Chinook Salmon and Ocean Fisheries: Data Availability and Management Possibilities. San Francisco Estuary and Watershed Science. 16(1).
• Singer GP, Chapman ED, Ammann AJ, Klimley AP, Rypel AL, Fangue NA. 2020. Historic drought influences outmigration dynamics of juvenile fall and spring-run Chinook Salmon. Environmental Biology of Fishes. 103(5):543-559.

We all know climate change is going to be rough. We expect increases in temperature, changes in rainfall (where, when, and how much), and local extinctions or migration of plants and wildlife as the climate shifts. Climate change can sound abstract and is often spoken of as a phenomenon of the future, despite the changes we are already seeing in our surroundings. These changes affect the San Francisco Estuary and will eventually make it necessary to adjust the way we manage our water in California if we want to lessen the impact on those ecosystems. To better understand the impacts of climate change and to better inform management strategies, a group of Interagency Ecological Program (IEP) scientists wanted to find out how much is known about climate change in the Sacramento-San Joaquin Delta, Suisun Bay and Suisun Marsh and how management actions can lessen these effects. To do this, they gathered scientists with broad expertise – from zooplankton to aquatic vegetation – and created the Climate Change Project Work Team.

The team decided to start by creating a conceptual model (similar to the Baylands Goals model created for the San Francisco Bay) and synthesize already published research in a technical report. A conceptual model is an organized way of thinking through a particular problem, system, or idea in a visual way to make it easier to see and understand connections. Conceptual models are especially helpful when working in groups as while it is developed everyone participates and has to think through the problem and understands why the model looks like it does when it’s done. The climate change conceptual model made by the group let them see how the Estuary responds to different environmental drivers and that in turn showed what subjects to read about to find the answers they were looking for. The Climate Change conceptual model (Figure 1) started with global-scale changes in the top box, which impact landscape-scale environmental conditions in the Estuary. Those landscape-scale conditions influence site-level environmental change. For example, increases in global air temperature cause increases in water temperature in the rivers and bays, which in turn impact the temperatures experienced by each critter in the rivers. These climate-change effects also interact with landscape management (such as levee construction or wetland restoration) to impact the aquatic environment at a site.

Figure 1. The Climate Change Project Work Team's conceptual model.

Putting together the conceptual model and writing a synthesis of what we know so far is useful in other ways as well. It allowed the team to find out where there are things we need to study more if we want to be able to give better answers about what will happen in our aquatic ecosystems. The model highlighted three aquatic ecosystems in the estuary where organisms will experience different effects from climate change. The largest ecosystem in the Estuary today is open water. Marshes and floodplains make up a much smaller proportion of the habitat, but are still highly important to native species. Three different teams of scientists went on to review literature on the different ecosystems, diving into the current status of fish, benthic invertebrates, plankton and aquatic vegetation, and trying to predict changes and risks.

So, what did the teams find?

Out of the three, the open water ecosystem will be most impacted by drought and warmer temperatures. The changes brought by this will make this ecosystem more suitable for many of the invasive fish, invertebrates and aquatic vegetation, though higher salinity conditions during droughts may also favor some native fishes and aquatic vegetation (Figure 2). Predictions of future Delta temperatures have found that Delta Smelt's spawning window may be greatly restricted, further stressing this endangered fish (Brown et al. 2016).

Figure 2. Impacts of climate change in open water ecosystems include harmful algal blooms, increased invasive clams, increased aquatic weeds, and increased invasive fishes, such as largemouth bass and Mississippi silversides.

Floodplains will experience major changes in timing and magnitude of inundation. Precipitation will become more variable with more frequent extreme floods and droughts. The larger storms we have seen lately benefit floodplains and the native fish that use them to spawn and feed, but only if they occur at the right time. Floods will shift to earlier in the season as more precipitation falls as rain instead of snow, keeping migratory species from being able to use the floodplain when they need it. More frequent droughts will mean the floodplain may not be available at all for years at a time (Figure 3). Management actions that increase the frequency or duration of floodplain inundation, such as the Yolo Big Notch Project, may become more important if floodplains are to be sustainable in the future.

Figure 3. Floodplains, which are important habitat for spawning Sacramento Splittail and juvenile Chinook Salmon will not be inundated as frequently as droughts become more frequent, and may experience earlier flooding as more precipitation falls as rain instead of snow.

Tidal marshes are relatively scarce, but very important habitats. They provide food and nursery habitat for many fish and waterbird species. Whether they will continue to exist where they are will depend on the amount of sediment that will deposit in the marshes to keep up with sea level rise. Some models show that the larger storms will bring more sediment to the Delta which will help the marshes remain, but other models show that much of our tidal marsh will drown, especially if they do not have gentle, sloping transitions to uplands. Restoration planners may need to prioritize areas with adequate transition zones if they want restoration sites to be sustainable in the long-term.

Figure 4. Tidal marshes may drown as sea levels rise unless they have gentle transitions to upland areas. They may also experience the same increases to invasive species and increased temperature as open water ecosystems.

Other members of the Climate Change PWT have been working on looking for temperature trends from our monitoring record. They have found evidence for increased temperatures over the past 50 years (Bashevkin et. al., 2021), lower temperatures during wetter years (Bashevkin and Mahardja, 2022), differences in temperatures at the top and bottom of the water (Mahardja et. al., 2022), and hotter temperatures in the South Delta (Pien et. al., draft manuscript).

For a young adult audience interested to learn more about the San Francisco Estuary, the Sacramento-San Joaquin Delta in general and how climate change will affect it and the species living there check out a collection called Where the river meets the ocean – Stories from San Francisco Estuary . Many of the scientists that are on the team who wrote the Climate Change Technical Report also wrote for this collection, published by Frontiers for Young Minds.

Further Reading:

Bashevkin, S. M., and B. Mahardja. in press. Seasonally variable relationships between surface water temperature and inflow in the upper San Francisco Estuary. Limnology and Oceanography

Bashevkin, S. M., B. Mahardja, and L. R. Brown. 2021. Warming in the upper San Francisco Estuary: Patterns of water temperature change from 5 decades of data.

Brown, L. R., L. M. Komoroske, R. W. Wagner, T. Morgan-King, J. T. May, R. E. Connon, and N. A. Fangue. 2016. Coupled downscaled climate models and ecophysiological metrics forecast habitat compression for an endangered estuarine fish. Plos ONE 11(1):e0146724. 

Colombano, D. D., S. Y. Litvin, S. L. Ziegler, S. B. Alford, R. Baker, M. A. Barbeau, J. Cebrián, R. M. Connolly, C. A. Currin, L. A. Deegan, J. S. Lesser, C. W. Martin, A. E. McDonald, C. McLuckie, B. H. Morrison, J. W. Pahl, L. M. Risse, J. A. M. Smith, L. W. Staver, R. E. Turner, and N. J. Waltham. 2021. Climate Change Implications for Tidal Marshes and Food Web Linkages to Estuarine and Coastal Nekton. Estuaries and Coasts.

Dettinger, M., J. Anderson, M. Anderson, L. Brown, D. Cayan, and E. Maurer. 2016. Climate change and the Delta. San Francisco Estuary and Watershed Science 14(3).

Knowles, N., C. Cronkite-Ratcliff, D. W. Pierce, and D. R. Cayan. 2018. Responses of Unimpaired Flows, Storage, and Managed Flows to Scenarios of Climate Change in the San Francisco Bay-Delta Watershed. Water Resources Research 54(10):7631-7650. 2

Mann, M. E., and P. H. Gleick. 2015. Climate change and California drought in the 21st century. Proceedings of the National Academy of Sciences 112(13):3858-3859.