Science Stories: Adventures in Bay-Delta Data

Blog by Rosemary Hartman, Data collated by Nick Rasmussen

Our last post gave you an introduction to the water weeds of the Delta. Invasive submerged aquatic vegetation is taking over the waterways, making it difficult for boaters, fish, water project operations, and scientific researchers (Khanna et al. 2019). As we described in the blog “Getting into the weeds”, they are hard to control too. But how do we collect data on aquatic weeds and what do those data look like?

How do we collect data?

There are two main types of data that we can work with (see IEP Technical Report 92 (PDF) for details). The first, is collected with areal photographs, and is known as ‘remote sensing’ (Figure 1). A specialized camera (sensor) is mounted on a platform (a drone, airplane, or satellite), and it can collect a regular-old photograph, or a hyperspectral photograph that records a lot of wavelengths of light that our eyes can’t see. Because different types of plants reflect different spectra of light (they are different colors) these photographs can be used to map location and extent of vegetation (Figure 2).

Figure 1. Diagram showing how remote sensing works. Light from the sun is reflected by objects on the ground. Different wavelengths of light are reflected differently. The sensor (camera) on the platform (airplane, satellite, drone, etc) registers the different wavelengths and stores them as an image file. Later, experts can classify the images based on which wavelengths of light were reflected.

The UC Davis Center for Spatial Technologies and Remote Sensing (CSTARS) has been mapping vegetation in the Delta using hyperspectral imagery collected with airplanes for most of the last 20 years (like the map in Figure 2). They create maps every year and share their data online via the Knowledge Network for Biocomplexity.

Figure 2. Hyperspectral image map of Suisun Marsh collected by CSTARS. Colors are used to represent different vegetation types (they aren't really that color).

Hyperspectral imagery is very good for identifying floating aquatic vegetation and terrestrial vegetation, but the water makes it hard to identify submersed vegetation. We can map where submersed vegetation is, but not what kind of vegetation is there. To look at community composition, we need to actually get out in the field and check on the weeds directly. To survey submersed weeds, researchers use a thatch rake (Figure 3) – an evil looking tool with sharp tines on one end and a long handle.

Figure 3. A thatch rake being used to sample aquatic vegetation. Photo from the Department of Water Resources.

To measure weeds, researchers either lower the rake into the water and twist it around to pick up the weeds, or they drag the rake behind the boat. When they pull the rake in, they rank the coverage of weeds on the rake head and identify the weeds to species. Several different groups have been collecting these data over the past twenty years– the State Parks Division of Boating and Waterways (DBW), UC Davis (including CSTARS), SePRO Corporation, and the Department of Water Resources. Dr. Nick Rasmussen (DWR) recently integrated all these datasets into one data publication available on the Environmental Data Initiative. He developed the data set because he was helping to write a series of reports about the environmental impact of drought and drought-related management actions. Those reports required rounding up aquatic vegetation data quickly, but at the time, virtually none of it was readily available. He wanted to fix that.

It ended up being a fun challenge for Nick because he got to learn how to create a fully reproducible process for integrating the dataset – including some hard decisions about how best to combine data that was collected in very different ways. He did all the cleaning and formatting in R scripts that are made available in a public GitHub repository.

What do the data look like?

Well, because these data were collected by different programs for different purposes, there are pretty big differences in number of samples and distribution of samples over the years (Figure 4). So it’s a little difficult to detect trends.

Figure 4. Graph of number of submerged vegetation rake samples per year in the integrated vegetation dataset.

However, when we look at the relative abundance of different species that have shown up in the rake sample data (Figure 5), we can really see an expansion in Potamogeton richardsonii (Richardson’s pondweed, black bars in figure 5) and Najas guadalupensis (southern naiad, brown bars in figure 5) after 2014. It’s not clear whether these species, both native to California, were recent invaders in the Delta or whether early surveys didn’t know how to tell the difference between them and similar looking species such as Potamogeton crispus (curlyleaf pondweed, red bars in Figure 5).

Figure5. Graph of relative abundance of each species across all rake sample surveys by year. No sampling occurred 2011-2013. Click for a version that shows separate plots for each species.

To make the story a little more complicated, these species aren’t found evenly throughout the Delta. Both Potamogeton richardsonii and Najas guadalupensis are found chiefly in Franks Tract (Figure 6) and not in any of the other regions of the Delta. SePRO and DBW conduct extensive sampling every year within Franks Tract (see Caudill et al. 2019 (PDF)), but not as high an intensity in other areas, so high abundance there throws off the Delta-wide data if it is not weighted by location.

Figure 6. Average relative abundance of different types of submerged vegetation by region of the Delta for the entire dataset. Click for a version that shows separate plots for each species.

We can also look at the hyperspectral maps to give us a record of total coverage of submerged weeds by year (Figure 7). We can see that total coverage of weeds really increased between 2008 and 2017, then remained about the same from 2017 to 2022.

Figure 7. Graph of percent of waterways in the Delta covered with submerged vegetation by year. Triangles indicate missing years.

However, it is often more interesting to look at a smaller area of the Delta and see how vegetation shifts from year to year (Figure 8, 9). For example, distribution of weeds in Franks Tract – a large, open-water area of the Delta – changed dramatically when a barrier was installed in West False River in 2015 and 2021-2022. The open-water area in the middle of the tract filled in during 2015, but the area on the eastern side of the tract started to clear out during 2021-2022 (see Hartman et al, 2022 (PDF) for more information).

Figure 8. Map showing the location of Franks Tract - a large, open-water area with extensive vegetation and the site of many vegetation surveys by DBW and SePRO. Maps of vegetation in Franks Tract through the years are in Figure 9, below.

Figure 9. Hyperspectral image of Franks Tract showing installations of a barrier in West False River during 2015, 2021, and 2022, and resulting changes in distribution of submerged aquatic vegetation. Click to enlarge.

Between all these surveys, we’ve collected a lot of data on weeds, but we haven’t done an extensive analysis. There are lots more questions waiting to be asked! How does the distribution of weeds change with floods and droughts? Which species of weeds grow in shallow versus deep water? Are any species expanding in range? Download the dataset yourself and take a look!

Further reading

• Borgnis E, Boyer KE. 2015. Salinity tolerance and competition drive distributions of native and invasive submerged aquatic vegetation in the upper San Francisco Estuary. Estuaries and Coasts.39(3)1-11.
• Boyer KE, Safran SM, Khanna S, Patten MV. 2023. Landscape Transformation and Variation in Invasive Species Abundance Drive Change in Primary Production of Aquatic Vegetation in the Sacramento–San Joaquin Delta. San Francisco Estuary and Watershed Science. 20(4).
• Caudill J, Jones AR, Anderson L, Madsen JD, Gilbert P, Shuler S, Heilman MA. 2019. Aquatic plant community restoration following the long-term management of invasive Egeria densa with fluridone treatments. Management of Biological Invasions. 10(3):473-485.
• Christman MA, Khanna S, Drexler JZ, Young MJ. 2023. Ecology and Ecosystem Effects of Submerged and Floating Aquatic Vegetation in the Sacramento–San Joaquin Delta. San Francisco Estuary and Watershed Science. 20(4) 
• Hartman R, Rasmussen N, Bosworth D, Berg M, Ateljevich E, Flynn T, Wolf B, Pennington T, Khanna S. 2022. Temporary Urgency Change Petition of 2021 and Emergency Drought Salinity Barrier; Impact on Harmful Algal Blooms and Aquatic Weeds in the Delta (PDF). Report to the State Water Resources Control Board. Sacramento, CA. 
• IEP Aquatic Vegetation PWT, Khanna S, Conrad JL, Caudill J, Christman M, Darin G, Ellis D, Gilbert P, Hartman R, Kayfetz K et al. 2018. Framework For Aquatic Vegetation Monitoring in the Delta (PDF). Sacramento, CA: Interagency Ecological Program. Technical Report 92.
• Khanna S, Acuna S, Contreras D, Griffiths WK, Lesmeister S, Reyes RC, Schreier B, Wu BJ. 2019. Invasive Aquatic Vegetation Impacts on Delta Operations, Monitoring, and Ecosystem and Human Health (PDF). IEP Newsletter. 36(1):8-19.
• Khanna S, Ustin SL, Hestir EL, Santos MJ, Andrew M. 2022. The Sacramento-San Joaquin Delta genus and community level classification maps derived from airborne spectroscopy data. Knowledge Network for Biocomplexity. 
• Rasmussen NL, Conrad JL, Green H, Khanna S, Wright H, Hoffmann K, Caudill J, Gilbert P. 2022. Efficacy and fate of fluridone applications for control of invasive submersed aquatic vegetation in the estuarine environment of the Sacramento-San Joaquin Delta. Estuaries and Coasts. 45:1842-1860.
• Rasmussen N. 2023. Submersed aquatic vegetation community composition in the Sacramento-San Joaquin Delta integrated across four surveys ver 1. Environmental Data Initiative.

By Shruti Khanna and Rosemary Hartman

Figure 1. The hard-working staff of the UC Davis Center for Spatial Technologies and Remote Sensing survey water weeds using large thatch rakes. Image credit: UC Davis.

If you’ve ever tried to take a boat across one of the large, flooded islands in the Delta, there is a good chance you’ve gotten your propeller snagged on water weeds. Submersed aquatic vegetation (which is the fancy, scientific term for ‘water weeds’) have been getting worse and worse in recent years, with invasive species taking over areas that were previously open water. Most of these weeds are introduced species from South America, but even some of our native species have been expanding rapidly. Weeds were the subject of several papers in the most recent State of Bay Delta Science, they were the subject of a recent paper synthesizing many years of herbicide data to look at weed control effectiveness at a landscape scale, and data on aquatic weeds in the Delta has been published in several different datasets. Classification maps are now available for all aquatic plants in the Delta for most of 2004-2022 (with 2023 in the works) and there is a new, integrated dataset made up of vegetation samples from four different programs. Together, these data and publications are increasing our understanding of where weeds are a problem and what to do about it.

The recent paper “Multi-year landscape-scale efficacy of fluridone treatment of invasive submerged aquatic vegetation in the Sacramento San Joaquin Delta”, published earlier this year in Biological Invasions, was an excellent example of how many datasets could be integrated and used to answer a major management question. Water weeds have been managed with herbicides by California State Parks Division of Boating and Waterways for years, but its always seemed like a Sisyphean affair – constant use of herbicides and mechanical removal while weeds just keep growing back (for more info, see recent special issue of the Journal of Aquatic Plant Management). This gave lead author Dr. Shruti Khanna the idea that someone should look at whether the treatments were working. So she enlisted the help of Dr. Jereme Gaeta – statistician extraordinaire, Dr. Edward Gross – an expert in hydrodynamic modeling, and Dr. Louise Conrad – who could provide both scientific and policy advice.

For Shruti, the best part was working with the other members of the team: “Honestly, what I enjoyed most was working with Jereme on this project. He brought methods of analysis to the table that I couldn't have dreamed of when I was doing my PhD. I just didn't have the know-how. So, it was a very complementary effort - my remote sensing and geospatial skills to extract spatial information and integrate it with diverse other datasets, his statistical skills to create a nuanced GAM model to explore the data, and Louise's expert knowledge on the treatment program, its history, and management perspective made the publication a lot stronger. It was Jereme's idea to add Ed's hydrodynamic modeling of water speed to our analysis. Incorporating speed gave a whole new perspective to our study and turned out to be critical to understanding why treatment is sometimes not effective."

They gathered data gathered in the field on when and where weeds were treated, annual maps of weed distribution collected with hyperspectral imagery, and predicted current speed based on hydrodynamic models. The final integrated dataset was made of five diverse datasets with field data tables, rasters, vectors, and model output. They then created a statistical model to see whether multiple years of herbicide treatment resulted in lower probability of weeds. They found that when high levels of herbicide were applied there was a lower probability of weeds being there, but only at low current speeds (See figure 2). If the water was moving quickly, all the herbicide would be washed away and there was no effect of treatment (See figure 3).

Figure 2. Graph of model results from Khanna et al. 2023 showing probability of vegetation presence versus current speed. At low current speeds, fluridone decreased the probability of vegetation being present. But at high current speeds, there was no effect of fluridone. Graph reproduced from Khanna et al. 2023, with permission of the authors.

In a complicated, tidal system like the Delta, it is extremely difficult to control weeds when the herbicides get washed away by the tides more often than not. New tools are currently under investigation by members of the Delta Region Areawide Aquatic Weed Project, including the Division of Boating and Waterways, US Department of Agriculture, UC Davis, and others to get a better handle on this sticky problem.

Figure 3. Diagram of what is going on at herbicide treatment spots in the Delta. Fluridone comes in pellets which slowly release into the water column. When current speeds are low, water ‘sloshes’ back and forth a bit, but fluridone concentration remains high and weeds are killed. When current speeds are high, all the fluridone washes away before it can be effective. Image credit: Shruti Khanna, CDFW.

References

• Borgnis E, Boyer KE. 2015. Salinity tolerance and competition drive distributions of native and invasive submerged aquatic vegetation in the upper San Francisco Estuary. Estuaries and Coasts.1-11.
• Boyer KE, Safran SM, Khanna S, Patten MV. 2023. Landscape Transformation and Variation in Invasive Species Abundance Drive Change in Primary Production of Aquatic Vegetation in the Sacramento–San Joaquin Delta. San Francisco Estuary and Watershed Science. 20(4)
• Conrad JL, Thomas M, Jetter K, Madsen J, Pratt P, Moran P, Takekawa JY, Darin G, Kenison L. 2023. Invasive Aquatic Vegetation in the Sacramento–San Joaquin Delta and Suisun Marsh: The History and Science of Control Efforts and Recommendations for the Path Forward. San Francisco Estuary and Watershed Science. 20(4)
• IEP Aquatic Vegetation PWT, Khanna S, Conrad JL, Caudill J, Christman M, Darin G, Ellis D, Gilbert P, Hartman R, Kayfetz K et al. 2018. Framework For Aquatic Vegetation Monitoring in the Delta (pdf). Sacramento, CA: Interagency Ecological Program. No. Technical Report 92.
• Khanna S, Gaeta JW, Conrad JL, Gross ES. 2023. Multi-year landscape-scale efficacy analysis of fluridone treatment of invasive submerged aquatic vegetation in the Sacramento–San Joaquin Delta. Biological Invasions. 25:1827–1843
• Moran PJ, Madsen JD, Pratt PD, Bubenheim DL, Hard E, Jabusch T, Carruthers RI. 2021. An overview of the Delta Region Areawide Aquatic Weed Project for improved control of invasive aquatic weeds in the Sacramento–San Joaquin Delta. J Aquat Plant Manage. 59:2-15.
• Rasmussen N, Conrad JL, Green H, Khanna S, Caudill J, Gilbert P, Goertler P, Wright H, Hoffmann K, Lesmeister S et al. 2020. 2017-2018 Delta Smelt Resiliency Strategy Action for Enhanced Control of Aquatic Weeds and Understanding Effects of Herbicide Treatment on Habitat. (pdf) Sacramento, CA.
• Rasmussen NL, Conrad JL, Green H, Khanna S, Wright H, Hoffmann K, Caudill J, Gilbert P. 2022. Efficacy and fate of fluridone applications for control of invasive submersed aquatic vegetation in the estuarine environment of the Sacramento-San Joaquin Delta. Estuaries and Coasts. 45:1842-1860.
• Rasmussen, N. 2023. Submersed aquatic vegetation community composition in the Sacramento-San Joaquin Delta integrated across four surveys ver 1. Environmental Data Initiative. (Accessed 2023-06-05).

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

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.

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).