Science Stories: Adventures in Bay-Delta Data

When you are running a long-term monitoring program, it’s easy to keep plugging away doing the same old thing over and over again. That’s what “long term monitoring” is all about right? But is the survey we designed 40 years ago still giving us useful data? With new sampling gear, new statistics, and new mandates, can we improve our monitoring to better meet our needs? These questions have been on the minds of Interagency Ecological Program (IEP) researchers, so an elite team spent over a year doing a rigorous evaluation of three of IEP’s fisheries surveys to figure out how we can improve our monitoring program. The team was assembled with representatives from multiple agencies who each brought something to the table: guidance and facilitation, experience using the data, regulatory background, quantitative skills, and outside statistical expertise. This wasn’t the first time IEP reviewed itself, but it was the first time they tried to take a really quantitative look at it. The team focused on trying to assess the ability of the datasets to answer types of management questions based on themes, so multiple surveys were reviewed together.

The Team

• Dr. Steve Culberson, IEP Lead Scientist - Guidance and Facilitation
• Stephanie Fong, IEP Program Manager – Guidance and Facilitation
• Dr. Jereme Gaeta, CDFW Senior Environmental Scientist – Quantitative Ecologist
• Dr. Brock Huntsman, USGS Fish Biologist – Quantitative Ecologist
• Dr. Sam Bashevkin, DSP Senior Environmental Scientist – Quantitative Ecologist
• Brian Mahardja, USBR Biologist – Quantitative Ecologist and Data User
• Dr. Mike Beakes USBR Biologist – Quantitative Ecologist and Data User
• Dr. Barry Noon, Colorado State University – Independent statistical consultant
• Fred Feyrer, USGS Fish Biologist – Data User
• Stephen Louie, State Water Board Senior Environmental Scientist – Regulator
• Steven Slater, CDFW Senior Environmental Scientist - Principal Investigator – FMWT
• Kathy Hieb, CDFW Senior Environmental Scientist – Principal Investigator – Bay Study
• Dr. John Durand – UC Davis, Principal Investigator – Suisun Marsh Survey

The Surveys

• Fall Midwater Trawl (FMWT) – One of the cornerstones of IEP since 1967, this California Department of Fish and Wildlife (CDFW) survey runs from September-December every year and was originally designed to monitor the impact of the State Water Project and Central Valley Project on yearling striped bass.
• San Francisco Bay Study – On the water since 1980, Bay Study was also run by the CDFW and runs year-round from the South Bay to the Confluence. It also monitors the effects of the Projects on fish communities.
• Suisun Marsh Survey – Starting in 1979, the Suisun Marsh Survey is conducted by UC Davis with funding from the Department of Water Resources. This survey describes the impact of the Projects and the Suisun Marsh Salinity Control Gates on fish in the Marsh.

The Gear

• The otter trawl – A big net towed along the ground behind a boat, this type of net targets fish that hang out on the bottom (“demersal fishes”). This net only samples the bottom in deep water, but will sample most of the water column in shallower channels (less than 3 meters deep).
• The midwater trawl – Another big net, but this one starts at the bottom and is pulled in toward the boat while trawling, gradually reducing the depth of the net so all depths are sampled equally. This net targets fish that like living in open water (“pelagic fishes”).

The question: Can we make it better?

Figure1. The team assembled to see how surveys could generate the best data to inform decisions and fulfill their regulatory mandates.

The question seemed simple – but the answer was unexpectedly complex. While the surveys all targeted similar fish, used similar gear, and went to similar places, they all had enough differences in their survey design, mandates, and institutional history that looking at them together wasn’t easy.

The first step in the review process was, perhaps, the most difficult. The team had to get the buy-in from all the leaders of the surveys under review, all the regulators mandating that the surveys take place, all the people critical of the surveys as they currently stand, and the supervisors of the team who were going to devote a large percentage of their time to the effort. Getting trust from multiple interest groups was challenging, but it was also one of the most rewarding and exciting parts of the process. Stephanie reflected: “We plan to incorporate more of their recommendations in upcoming reviews and increase our collaboration with them… it also would have been helpful if we could have spent more time up front with getting buy-in from those being reviewed and those critical of the surveys.”

Once everyone was on board, the team took a deep dive into the background behind each survey. Why was it established? How have the data been used in the past? Has it made any changes over time? How are the data currently shared and used? Putting together this information gave them a great appreciation for the broad range of experience within IEP. In particular, the team needed to pay attention to the regulatory mandates that first called for the surveys (such as Endangered Species Act Biological Opinions and Water Rights Decisions), to make sure the surveys were still meeting their needs.

The next step was putting the data together, and here’s where it got hard. The team had to find all the data, interpret the metadata, and convert it into standard formats that were comparable between surveys. Even basic things like the names of fish were different. In the FMWT data, a striped bass was “1”, in the Suisun Marsh data a striped bass was “SB”, and in the Bay Study data a striped bass was “STRBAS”. The team quickly identified a few easy steps that could improve the programs without changing a single survey protocol!

1. Make all data publicly available on the web in the form of non-proprietary flat files (such as text or .csv spreadsheets)
2. Create detailed metadata documents describing all the information needed to understand the survey (assume the person reading it is a total stranger who knows nothing about your program!)

Figuring out better methods of storing and sharing data is relatively easy, but how do we decide whether we should change when and where and how the surveys actually catch fish? The surveys were all intended to track changes in the fish community, but community-level changes are complex, with over 100 fish species in the estuary. The team decided to divide the task into three parts:

1. Figure out how to quantify bias between the surveys for individual fish (seeing if some surveys are more likely to catch certain species than the other surveys, Figure 2).
2. Create a better definition of the “fish community” by identifying which groups of species are caught together more often (Figure 3).
3. See what happens when we change how often we sample or how many stations we sample. Do we lose any information if we do less work?

Figure 2. The quantitative ecologists used a form of hierarchical clustering to figure out which groups of fish are most frequently caught together, and which species is most indicative of each group. The indicator species are the ones with the gold stars. Figure adapted from IEP Survey Review Team (2021).

Going through this process involved pulling out all the fancy math and computer programing. Sam, Brian, Jereme, Mike, and Brock explored the world of generalized additive models, principle tensor analysis, Bayesian generalized linear mixed models, hierarchical cluster analysis, and things involving overdispersion in negative binomial distributions. If there were a way to Math their way to the answer, they were going to find it!

Figure 3. The team also evaluated biases in sampling gear. Sampling bias occurs when the gear doesn't sample all fish consistently. Sometimes they miss fish of certain sizes, fish that live in certain habitats, or fish that can evade the nets.

For better or worse, Math and a 1-year pilot effort will only get you so far. The team could develop some recommendations, scenarios, and new methods, but it will be up to management to decide how to continue the review effort and then implement change. Their results highlighted a few key points that will be useful in reviewing the rest of IEP’s surveys and making decisions about changes:

1. Involving stakeholders early in the review process will increase transparency, facilitate sharing of ideas, and promote community understanding.
2. We need to characterize the biases of our sampling gear in order to make stronger conclusions about fish populations.
3. Identifying distinct communities of fish helps us track changes over time and space.
4. We can use Bayesian simulation methods to test the impacts of altered sampling designs on our understanding of estuarine ecology.
5. These sort of reviews take time and effort by a highly skilled set of scientists, so IEP will need to dedicate a lot of staff to a full review of all their surveys.

Further Reading

• IEP Long-term Survey Review Team. 2021. Interagency Ecological Program Long-term Monitoring Element Review: Pilot approach and methods development (2020). IEP Technical Report #96. 206 pp. (request document by contacting iep@wildlife.ca.gov)
• Tempel, T. L., et al. (2021). "The value of long-term monitoring of the San Francisco Estuary for Delta Smelt and Longfin Smelt (PDF)." California Fish and Wildlife Special CESA Issue: 148-171.
• Stompe, D. K., et al. (2020). "Comparing and Integrating Fish Surveys in the San Francisco Estuary: Why Diverse Long-Term Monitoring Programs are Important." San Francisco Estuary and Watershed Science 18(2).

One of life’s greatest joys is playing with data. However, not everyone has the time or experience needed to make fancy graphs. Fortunately, availability of on-line web applications that allow people with no data analysis experience to visualize status and trends of data across space and time has exploded in recent years.

Figure 1. Fish love data, but they need a little help making their graphs.

One of the first data visualization tools was the mapping widgets on the CDFW website. These maps allow you to plot the catch for different fish species as different size bubbles, and have been available since the late 1990s:

• 20mm Survey
• Fall Midwater Trawl
• Summer Townet
• Spring Kodiak Trawl

But we needed better ways to display data from multiple surveys at once at the click of a button. The website Bay Delta Live was launched in 2007 as a home for Bay-Delta data and data visualizations. It includes summaries, graphs, and interactive visualizations for water quality, operations, fish monitoring, and special studies.

A similar website, SacPas, was built specifically for synthesizing, summarizing, and displaying data for salmonids in the Central Valley. It allows a user to visualize data on salmon abundance, temperature thresholds, river conditions, and hydrologic conditions. It also lets you play with a nifty Chinook Salmon population model and download all the underlying data.

Figure 2. FLowWest's Central Valley Instream Rearing Habitat Calculator shiny app

Custom-built websites like Bay Delta Live and SacPas are great, but they are built by web developers, not fisheries scientists. Now, thanks to user-friendly data display tools such as Tableau and the increase in coding literacy among environmental scientists, more and more people can create their own on-line data visualizations. This means the number of data visualizations apps has grown astronomically in the past few years, and many apps are custom-built for specific scientific questions.

The Delta Science Program now hosts a number of these visualizations built with the R package “shiny’

Figure 3. You can now map all the stations monitored by IEP's long-term surveys.

• NEW: Map all the monitoring stations sampled by IEP’s long-term monitoring surveys (My personal favorite!)
• Put together all of the IEP zooplankton data with the Zooplankton integrated data set.
• Look at Salmon acoustic telemetry stations and release locations for the Sacramento River.
• Check out the future with the Delta Social Climate Change Vulnerability Risk app and Delta Flood Risk app.
• Look at Long-term Temperature Trends using point values from IEP surveys going back to 1959.

Other Shiny apps have launched recently on a variety of other platforms:

• Avery Kruger and Dylan Stompe (UC Davis) integrated all the data from IEP’s long-term fish monitoring in their Bay Delta Live SF Estuary Integrated Fish Survey Visualizer V1.00 app.
• Check out Delta imports and exports app.
• ICF’s incidental take app looks at hydrodynamics and fish salvage.
• Cramer Fish Sciences has made a Delta Hydrodynamics app. (Because you can never have too many ways of looking at hydrodynamics)
• Cramer’s Loss Calculator app.
• Cramer also produced an Emigrating Salmonid Habitat Estimation app, if you want to see how baby fish move out of the river.
• And if you haven’t had enough salmon, there is also the Winter Run Life Cycle Model Shiny app.
• The FlowWest Central Valley Instream Rearing Habitat Calculator app.
• The CalFishTrack acoustic telemetry Shiny app, and
• FlowWest’s SHOWR dashboard for looking at Shasta Reservoir operations to protect winter run Chinook Salmon.

Figure 4. CalFishTrack includes a Shiny App of their Survival Travel time And Routing Simulation (STARS).

USGS has developed several new dashboards for mapping water and water quality data:

• Water Dashboard
• Groundwater
• Water Quality

With all these tools out there, it’s one big data playground! If you’re interested in making your own, it’s easy to get started with Shiny. Visit the Learn Shiny video tutorial!

By Rosemary Hartman, Brian Mahardja, and Vanessa Tobias

We are now half-way through Water Year 2021 (which started in October of 2020) and it seems likely that California will experience another dry year. The frequency of prolonged drought events is projected to increase due to climate change and the San Francisco Estuary system is expected to have more wild swings between floods and droughts. This was in the mind of a handful of IEP scientists back during the last California drought of 2012-2015. They were wondering, which fish species are negatively impacted by drought, and would they rebound in numbers after the drought is over? Brian Mahardja, Vanessa Tobias, Shruti Khanna, Lara Mitchell, Peggy Lehman, Ted Sommer, Larry Brown, Steven Culberson, and J. Louise Conrad published the results of their study in a recent journal article.

The Delta’s fish community is unique, with a melting pot of native fish and introduced fish. The native fish evolved with California’s regular cycles of droughts and floods. Some of the non-native fish come from ecosystems that are usually less volatile, so may have a harder time resisting the negative effects of drought and bouncing back. However, other introduced fish are considered “weedy” species that take advantage of disturbance. They might be particularly good at bouncing back after a drought.

The IEP researchers used data collected covering previous droughts in California to test these hypotheses. They compared fish abundance as measured by the CDFW Fall Midwater Trawl and the USFWS Delta Juvenile Fish Monitoring Program Beach Seines before, during, and after the droughts of 1976-1977, 1987-1994, 2001-2002, 2007-2010 and 2012-2016 (Figure 1).

Figure 1. Periods of drought in the Sacramento San-Joaquin Delta over the past 50 years. Figure is copied from Mahardja et al. 2021.

Though it sounded simple, the process ended up not being very straightforward. Even the definition of what a “drought” was turned out to be complicated. If you’re from the East Coast of the US, five months without rain is a “drought”. But in California, we would just call that “summer”. For Californians, we need lower-than-normal precipitation for multiple years in a row before we start worrying. Drought is often defined by its impact on people – dry soil conditions, low water storage, and water supply problems – but what does drought mean if you are a fish? The team had to make decisions. They also had to decide which components of the ecosystem to look at. At first they wanted to look at everything IEP monitors – water quality, phytoplankton, zooplankton, and fish, but decided that just doing fish was hard enough!

It was a big team working on the project, and they each brought skills to the analysis. Brian, Lara, Vanessa, and Shruti had a lot of experience with complex statistics and data analysis. Lara was “an R Wizard” who streamlined the data processing. Ted and Larry brought their fish expertise and deep knowledge of the system. Steve and Peggy provided hydrologic and water quality knowledge. Louise was the lead of the IEP synthesis program and organized the overall drought synthesis effort. Even though several authors changed jobs midway through the project, the great thing about working in the IEP community is that the new employers were supportive of seeing the project through, since they knew it would help the IEP community as a whole.

The team found that many fish species declined in abundance during the drought (they had “low resistance to disturbance”), particularly pelagic species such as Delta Smelt, American Shad, and young Striped Bass (Figure 2). Many of these species had the ability to “bounce back” after the drought (they had “high resilience”), however some species never returned to their former abundance (such as the Delta Smelt). Other fish species didn’t decline during the droughts (they had “higher resistance”). These included many of the fish of the littoral habitat, including Largemouth Bass, Redear Sunfish, and Chinook Salmon. A few of the non-native littoral species even increased in abundance during some of the droughts, particularly Mississippi Silversides and Bluegill.

Climate change is likely to increase the frequency and severity of droughts. If these results hold true, we could see a shift in the fish community away from native pelagic fish and towards more non-native littoral fish. Because freshwater flow is a tightly managed commodity, particularly during drought conditions, finding a balance of water use for people and water use for native species will become increasingly difficult.

Figure 2. Fish populations have different responses when it comes to drought. Many of the pelagic species decline, but bounce back. Some don't bounce back quite as well. Many littoral fish don't decline, or even increase in population during droughts. Fish photos from US Bureau of Reclamation.

Learn More

• Durand, J. R., F. Bombardelli, W. E. Fleenor, Y. Henneberry, J. Herman, C. Jeffres, M. Leinfelder–Miles, J. R. Lund, R. Lusardi, A. D. Manfree, J. Medellín-Azuara, B. Milligan, and P. B. Moyle. 2020. Drought and the Sacramento-San Joaquin Delta, 2012–2016: Environmental Review and Lessons. San Francisco Estuary and Watershed Science 18(2). DOI: 10.15447/sfews.2020v18iss2art2
• Department of Water Resources Drought Activities
• Kimmerer, W., F. Wilkerson, B. Downing, R. Dugdale, E. S. Gross, K. Kayfetz, S. Khanna, A. E. Parker, and J. K. Thompson. 2019. Effects of Drought and the Emergency Drought Barrier on the Ecosystem of the California Delta. San Francisco Estuary and Watershed Science 17(3). DOI: 10.15447/sfews.2019v17iss3art2
• National Integrated Drought Information System.
• Mahardja, B., V. Tobias, S. Khanna, L. Mitchell, P. Lehman, T. Sommer, L. Brown, S. Culberson, and J. L. Conrad. 2021. Resistance and resilience of pelagic and littoral fishes to drought in the San Francisco Estuary. Ecological Applications, 31(2): e02243. DOI: 10.1002/eap.2243
• Singer, G. P., E. D. Chapman, A. J. Ammann, A. P. Klimley, A. L. Rypel, and N. A. Fangue. 2020. Historic drought influences outmigration dynamics of juvenile fall and spring-run Chinook Salmon. Environmental Biology of Fishes 103(5):543-559. DOI: 10.1007/s10641-020-00975-8

By: Rosemary Hartman (CA Department of Water Resources), Pascale Goertler (Delta Science Program), Brian Mahardja (US Bureau of Reclamation), and Ted Sommer (CA Department of Water Resources).

A new synthesis study indicates Striped Bass could start swimming up the Sacramento River earlier in the year as climate change progresses. You probably know “stripers” as popular game fish, and die-hard fishermen will tell you all about the best times and places to try and catch a big one. However, Striped Bass do not stay put. Stripers are “anadromous”, meaning that just like salmon, they begin their life in fresh water, migrate to the estuary and ocean, and eventually return to freshwater as adults to spawn. This study, by IEP Scientists Pascale Goertler, Brian Mahardja, and Ted Sommer, looked at one of our oldest data sets to examine fish migration patterns. Scientists in other systems have found a number of changes to migration timing of many species linked to climate change, and Pascale, Brian, and Ted were curious whether there had been any changes in our system. They found that adult Striped Bass migrated into the Central Valley later in the year when there was higher Delta outflow and cooler sea surface temperatures (Figure 1).

Figure 1. Diagram of how environmental conditions influence Striped Bass Migration. In the top panel, warm ocean temperatures and low freshwater flow correlate with earlier upstream migration. In the bottom panel, lower ocean temperature and higher flow mean Striped Bass hang around in the ocean or estuary for longer before migrating.

In order to figure this out, the team started with data from the CDFW Adult Striped Bass Survey. This survey has captured and tagged Stripers using gill nets and fyke traps throughout the Delta and the Sacramento River since 1969 (Figure 2). Having a really long-term data set let them correlate migration to climate factors, which has not been studied very often in migratory fishes, but it also caused problems. This is a “presence-only” data set, which means the researchers didn’t know whether there was no record for a given date because the monitoring crews didn’t sample, or because they sampled, but failed to catch any fish. The monitoring crews also didn’t record how long they were out in a consistent way. Did they only catch one fish because there weren’t many fish? Or because they only put the net in the water for five minutes instead of an hour? They didn’t have the crews from the 1970s to ask.

Figure 2. CDFW scientists have been monitoring Striped Bass populations using fyke traps such as this one since the 1960s. CDFW photo.

While the patterns Pascale and her colleagues found have held true over the past forty years of the data set they analyzed, migration timing could change in the future. Based on trajectory of climate change, we expect warmer sea surface temperature and lower outflow during late spring and early summer (as snowpack level decreases), which could mean earlier bass migration. Striped Bass are a voracious predator, so adult fish entering the estuary earlier in the year could mean a head-on collision with juvenile salmon moving out of the estuary. While Striped Bass have coexisted with salmon for the past 150 years, they are not native to California, and changes in predation patterns could affect already stressed salmon populations.

Learn More:

• Goertler, P., B. Mahardja, and T. Sommer. 2021. Striped bass (Morone saxatilis) migration timing driven by estuary outflow and sea surface temperature in the San Francisco Bay-Delta, California. Scientific Reports 11(1):1510.
• Morris Jr., J. A., R. A. Rulifson, and L. H. Toburen. 2003. Life history strategies of striped bass, Morone saxatilis, populations inferred from otolith microchemistry. Fisheries Research 62:53-63.
• Nobriga, M., and F. Feyrer. 2008. Diet composition in San Francisco Estuary striped bass: does trophic adaptability have its limits? Environmental Biology of Fishes 83(4):495-503 (PDF).
• Sabal, M., S. Hayes, J. Merz, and J. Setka. 2016. Habitat alterations and a nonnative predator, the Striped Bass, increase native Chinook Salmon mortality in the Central Valley, California. North American Journal of Fisheries Management 36(2):309-320.
• Sommer, T., F. Mejia, K. Hieb, R. Baxter, E. Loboschefsky, and F. Loge. 2011. Long-term shifts in the lateral distribution of age-0 striped bass in the San Francisco Estuary. Transactions American Fisheries Society 140:1451-1459.
• Stompe, D. and P. Moyle. Striped Bass in the San Francisco Estuary: Insight Into a Forgotten Past. California WaterBlog. UC Davis Center for Watershed Sciences. 11/18/2018.

IEP is best known for long-term monitoring surveys. You can find data, maps, and descriptions of monitoring elements dating back since the 1950s! But IEP is much more than just counting fish and recording salinity. We often use targeted research to answer specific questions, such as:

• Can we use genetics to tell the difference between runs of salmon?
• Does electrofishing work better than beach seines for looking at fish communities?
• Can we use cameras instead of nets to monitor fish?
• Do baby salmon get eaten by bass in some areas more than others?

We also periodically look back on the data we have collected by long-term monitoring and special studies and “synthesize” the results to answer questions that are too big to answer with one data set by itself. Recent synthesis projects have included:

• How does Delta outflow impact Delta Smelt habitat?
• How quickly does the system recover after a major drought?
• What are the consequences of climate change for the ecosystem?

In this space, we will be highlighting the work being done by these special studies and synthesis projects at IEP. Stay tuned!