Science Stories: Adventures in Bay-Delta Data

By Rosemary Hartman

Delta Smelt

Wakasagi

You’ve probably heard of Delta Smelt (Hypomesus transpacificus), and you may have heard of their cousin, the Longfin Smelt (Spirinchus thaleichthys), but there is a third osmerid in the estuary. The Wakasagi (Hypomesus nipponensis), also known as Japanese Smelt, is in the same genus as Delta Smelt, and was once thought to be the same species. It is native to Japan, but was introduced to reservoirs in California by the California Department of Fish and Game in the 1950s, and now it is established throughout the watershed, including the Delta.

But what does this brother of the Delta Smelt do? Is there sibling rivalry? A group of IEP scientists was curious, so they decided to look at all of our existing data to see when, where, how big, and how many Wakasagi are in the Delta and how their environmental tolerances and diet compares to Delta Smelt. A paper about their analysis recently came out in the Journal San Francisco Estuary and Watershed Sciences.

In order to compare Delta Smelt and Wakasagi, they looked at all the data from thirty different fish datasets from San Francisco Bay, Suisun Marsh/Suisun Bay, the Delta, and the watershed (see map below). This resulted in a dataset with over 250,000 individual Wakasagi! They also looked at data from special studies of Wakasagi and Delta Smelt growth and diets in the Yolo Bypass.

They found some similarities between delta smelt and Wakasagi – both fish really like hanging out in the Sacramento Deep Water Ship Channel and both like eating calanoid copepods (a particularly tasty variety of zooplankton). They spawn at about the same time, but Wakasagi are usually a little earlier (though this varies from year to year), and Wakasagi usually grow a little faster. They are similar enough that they sometimes interbreed and produce hybrid offspring.

Wakasagi aren’t the same as Delta Smelt though. Wakasagi aren’t actually very common in the Delta, instead finding their homes further upstream in reservoirs (they especially seem to like the Feather River, the screw trap there catches tens to hundreds of thousands of Wakasagi per year!). In the Delta they are mostly in the northern region, which might be just them washing in from upstream. Though they were mostly found in freshwater reaches of the Delta, Wakasagi can actually tolerate a wider range of salinity and temperatures than Delta Smelt, but they seem to prefer cooler temperatures.

So, are Wakasagi competing with Delta Smelt for limited food resources? Maybe a bit, but while they play a similar ecological role when they do overlap, they don’t overlap spatially very often, and both Delta Smelt and Wakasagi are rare in the Delta. However, they overlap enough that areas that are good for Wakasagi are probably good for Delta Smelt too. Delta Smelt are becoming more and more endangered, so we can use Wakasagi as indicators of good Delta Smelt conditions and as substitutes for smelt in some laboratory experiments.

Major similarities and differences between Delta Smelt and Wakasagi

Delta Smelt	Wakasagi	Comparison
Annual life span	Annual life span
Spawn later	Spawn earlier
Eat calanoid copepods	Eat calanoid copepods
Grow slower	Grow faster
Narrower tolerances	Wider tolerances
Endangered	More common
Native	Non native
Mostly semi-anadromous	Mostly freshwater
Small and silver	Small and silver
Loves the North Delta	Loves the North Delta
Smells like cucumber	Smells like fish

 

Further reading

• Davis BE, Adams JB, Lewis LS, Hobbs JA, Ikemiyagi N, Johnston C, Mitchell L, Shakya A, Schreier B, Mahardja B. 2022. Wakasagi in the San Francisco Bay–Delta Watershed: Comparative Trends in Distribution and Life-History Traits with Native Delta Smelt. San Francisco Estuary and Watershed Science. 20(3).
• Calfish Website (UC Davis)
• Swanson C, Reid T, Young PS, Cech JJ. 2000. Comparative environmental tolerances of threatened delta smelt (Hypomesus transpacificus) and introduced wakasagi (H. nipponensis) in an altered California estuary. Oecologia. 123:384-390
• Fisch KM, Mahardja B, Burton RS, May B. 2014. Hybridization between delta smelt and two other species within the family Osmeridae in the San Francisco Bay-Delta. Conservation Genetics. 15(2):489-494

Lots of Interagency Ecological Program (IEP) scientists research fish. Of the 22 surveys in IEP's Research Fleet, 17 are primarily focused on fish. But fish in the San Francisco Estuary are hard to catch these days. Over the past thirty years, Delta Smelt, Longfin Smelt, and even the notoriously hardy Striped Bass have declined precipitously (CDFW FMWT data). To figure out how to reverse these declines, we need an understanding of the “bottom-up” processes that exert control on these populations—we need to study fish food. Therefore, we need to increase our understanding of what pelagic fish eat: zooplankton.

If you’ve spent any time around fish people, you’ve probably heard the word “zooplankton”, but you might not really know what it means. Zooplankton are small animals that live in open water and cannot actively swim against the current (“plankton” means “floating” in Greek). They include crustaceans (copepods, water fleas, larval crabs, etc.), jellyfish, rotifers, and larval fish. Most of them are hard to see without a microscope, so they are easy to overlook – but you’d miss them if they weren’t there because most of your favorite fish rely on zooplankton for food.

Fortunately, the IEP Zooplankton Project Work Team has been tackling the problem head-on. The group got started when Louise Conrad and Rosemary Hartman were both collecting zooplankton samples near the same restoration site. They thought “We’d be able to say a lot more about the restoration site if we combined our data sets!” But with samples collected using different gear and identified by different taxonomists, it proved more difficult than they originally thought. They needed a team of experts to help them figure out how to deal with the differences in their data. So the Zooplankton Synthesis Team was born! The original team included Karen Kayfetz, Madison Thomas, April Hennessy, Christina Burdi, Sam Bashevkin, Trishelle Tempel, and Arthur Barros, but soon grew as more people heard about the discussions they were having.

The team started by identifying the major zooplankton datasets that IEP collects and dealing with tricky data integration questions:

• Can you integrate data sets when the critters were collected with different mesh sizes?
• What do you do when one data set identifies the organisms to genus and another one identifies down to species?
• What if these levels of identification change over time?
• Does preservation method impact the dataset?

To integrate data sets, the team standardized variable names, standardized taxon names, and summarized taxa based on their lowest common level of resolution.

While working through these sticky questions, they compiled what they learned about the individual zooplankton surveys into a technical report (PDF) describing each survey and how they are similar and different. They published a data package integrating five different surveys into a single dataset and Sam put together a fantastic web application that allows users to filter and download the data with a click of a button.

The team had put together the data, but there was more work to do. They realized they needed to do more if they wanted people to use their data. Lots of data on zooplankton get collected, but few research articles are published about zooplankton, and zooplankton data are rarely used to inform management decisions. To get the broader scientific community excited about zooplankton in the estuary, the ZoopSynth team worked with the Delta Science Program to host a Zooplankton Ecology Symposium with zooplankton researchers from across the estuary and across the country (you can watch the Symposium recording on YouTube.). From this symposium they learned a few important lessons to help increase communication and visibility of zooplankton data and research:

• Managers and scientists should work together to develop clear goals and objectives for management actions. Is there a threshold of zooplankton biomass or abundance to achieve? Or is the goal simply higher biomass of certain taxa? This will make it easier to design a study that provides management-relevant results.
• Scientists should understand the management goals and keep the end goal in mind. If the end goal is fish food, study taxa that are most common in fish diets. If the primary interest is contaminant effects, focus on sensitive species.
• We need to start using new tools like automated imagery and DNA along with traditional microscopy to collect better data faster.
• We need to maximize the accessibility of zooplankton data to scientists and managers. Scientists should share data in publicly available places in easy-to-read formats. Similarly, managers should share lessons learned from management actions widely, and use them for adaptive management. Both scientists and managers should be encouraged to ask questions of each other to ensure both understand the best uses for zooplankton data.

These lessons, (and more!) are summarized in a recent essay published in San Francisco Estuary and Watershed Sciences. If that’s too much reading, the team also produced some fact sheets summarizing the major take-home messages of the essay and the symposium:

• Fact Sheet for Managers
• Fact Sheet for Zooplankton Researchers

The team has expanded into an official IEP Project Work Team that meets monthly to discuss new zooplankton research ideas, share analyses, look at cool pictures of bugs, and talk about trends. If you’re interested in joining, contact Sam at Sam.Bashevkin@Deltacouncil.ca.gov

• Kayfetz K, Bashevkin SM, Thomas M, Hartman R, Burdi CE, Hennessy A, Tempel T, Barros A. 2020. Zooplankton Integrated Dataset Metadata Report (PDF). IEP Technical Report 93. Sacramento, California: California Department of Water Resources.
• Bashevkin S.M., R. Hartman, M. Thomas, A. Barros, C. Burdi, A. Hennessy, T. Tempel, and K. Kayfetz. 2020. Interagency Ecological Program: Zooplankton abundance in the Upper San Francisco Estuary from 1972-2018, an integration of 5 long-term monitoring programs ver 1. Environmental Data Initiative.
• Hartman R, Bashevkin SM, Barros A, Burdi CE, Patel C, Sommer T. 2021. Food for Thought: Connecting Zooplankton Science to Management in the San Francisco Estuary. San Francisco Estuary and Watershed Science. 19(3):art1.
• Kimmerer W, Ignoffo TR, Bemowski B, Moderan J, Holmes A, Bergamaschi B. 2018. Zooplankton Dynamics in the Cache Slough Complex of the Upper San Francisco Estuary. San Francisco Estuary and Watershed Science. 16(3).

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).

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