Science Stories: Adventures in Bay-Delta Data

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).

Blog by Rosemary Hartman, Data by Tiffany Brown, Sarah Perry, and Vivian Klotz. Photos from BSA submitted to DWR.

The base of the estuarine food web is phytoplankton – microscopic, floating, single-celled organisms drifting on the currents (“phyto” meaning “plant” and “plankton” meaning “drifter"). Most people know that trees produce oxygen, but phytoplankton put them to shame. Phytoplankton in rivers, lakes, and oceans worldwide produce an estimated 80% of the world’s supply of oxygen. Phytoplankton are also the base of the aquatic food web – providing food for zooplankton, other invertebrates, and fish. They are also the source of the omega-3 fatty acids that make seafood so good for you!

The Environmental Monitoring Program, a collaborative team of scientists and technicians from DWR, USBR, and CDFW, have been collecting phytoplankton samples to monitor the status and trends of phytoplankton in the San Francisco Estuary for the past forty years, and just recently made their data from 2008-2021 available online!

How are the data collected?

• The monitoring program crew go out on DWR’s premier research vessel, the Sentinel, once per month and visit 24 fixed stations and 2-4 ‘floating’ stations across San Pablo Bay, Suisun Bay, and the Delta.
• At each station, scientists collect a 60 mL water sample from 1 meter depth and stain it with Lugol’s iodine solution to make the phytoplankton easier to see.
• The samples are shipped to a lab where highly-trained taxonomists identify and count the phytoplankton under high-powered microscopes.

What do the data look like?

For each sample, we see the count (number of cells) for each type of plankton as well as the size (biovolume) of these cells.

• Each phytoplankter is identified to genus or species, but we often lump them into larger taxonomic groups to make it easier to see trends in the data. These groups are based on genetic and morphologic similarity, so they have similar shapes, pigments, motility, etc. Our understanding of the microbial tree of life is constantly evolving, so it is vital that we keep our entire data set up to date on the latest science as we categorize these groups.
• The phytoplankton samples are collected at the same time as water quality, nutrients, and zooplankton samples, so you can put all the data together if you want to see the bigger picture.

What trends do we see?

• There was a big change in average biovolume and relative abundance of cyanobacteria in 2014 when we switched contracting laboratories. Differences in methods made a big difference in the data, and we’re still trying to work out the consequences (See Figure 1 and Figure 2).

• We always catch more critters in the spring and summer, when days are long and temperatures are warm (Figure 3, Figure 4).

• Cyanobacteria are very small in comparison to other phytoplankton, so even when we catch a lot of them we don’t get much biovolume. Looking at the graphs, Figure 3 shows the biovolume of each phytoplankton group in each sample while Figure 4 shows the number of organisms in each group in each sample. The cyanobacteria are hard to see in the biovolume graph, but they totally dominate the number-of-organisms graph!
• Environmental factors frequently impact abundance of phytoplankton. For example, if we plot the abundance of each group versus net freshwater flow coming through the Delta, we find higher concentrations of most groups during months with higher flow (Figure 5).

There are lots more questions we could ask with this dataset. Are certain taxa more common in wet years or dry years? Do certain taxa occur more frequently in salty water or fresh water? How have abundances of certain taxa changed over time? With a dataset like this, the sky is the limit! If you see anything interesting in the data, we encourage you to join the Water Quality and Phytoplankton Project Work Team to share what you see!

What’s your favorite phytoplankton? These are some of the most common taxa in our samples:

• Cyanobacteria - Bacteria that photosynthesize! Some can even fix nitrogen out of the atmosphere. Others can produce toxins harmful to fish and wildlife, but most are harmless.
  
• Centric Diatoms - Big critters that look like wagon wheels and have a case (also called a ‘test’) made of glass-like silica. Considered very tasty and nutritious for zooplankton.
  
• Pennate Diatoms - Closely related to centric diatoms, these guys also have a silica shell and are highly nutritious. Unlike centric diatoms, they are shaped like canoes and frequently live on surfaces instead of being part of the plankton.
  
• Green Algae - Green cells that can be single or colonial and also have some flagellated species. They are also the distant ancestors of land plants.
  
• Cryptophytes - Single-celled algae with a pocket in one end with two flagella sticking out of it.
  
• Euglenoids - Single cells with a flagellum that are frequently heterotrophic – they can eat other cells or photosynthesize to produce energy.
  
• Crysophytes - Also known as “golden algae”, these guys have two flagella and many are encased in a silica cyst.
  
• Dinoflagellates - These single-celled algae have two flagella, one that circles their “waist” and one streaming off the side. They are more common in marine waters than freshwater, and can cause “red tides” which are harmful to fish.
  

Further Reading

• Barros, A.E. 2022. Interagency Ecological Program Zooplankton Study ver 11. Environmental Data Initiative.
• Battey, M. and S. Perry. 2022. Interagency Ecological Program: Discrete water quality monitoring in the Sacramento-San Joaquin Bay-Delta, collected by the Environmental Monitoring Program, 1975-2022. ver 8. Environmental Data Initiative.
• Brown LR, Kimmerer W, Conrad JL, Lesmeister S, Mueller–Solger A. 2016. Food webs of the Delta, Suisun Bay, and Suisun Marsh: an update on current understanding and possibilities for management. San Francisco Estuary and Watershed Science. 14(3).
• Cloern JE, Robinson A, Richey A, Grenier L, Grossinger R, Boyer KE, Burau J, Canuel EA, DeGeorge JF, Drexler JZ et al. 2016. Primary production in the Delta: then and now. San Francisco Estuary and Watershed Science. 14(3).
• Lehman P. 2022. The increase of cyanobacteria and benthic diatoms over 43 years in upper San Francisco Estuary, California. Estuarine, Coastal and Shelf Science. 275:107988.
• Lehman PW. 2007. The influence of phytoplankton community composition on primary productivity along the riverine to freshwater tidal continuum in the San Joaquin River, California. Estuaries and Coasts. 30(1):82-93.
• Perry, S.E., T. Brown, and V. Klotz. 2023. Interagency Ecological Program: Phytoplankton monitoring in the Sacramento-San Joaquin Bay-Delta, collected by the Environmental Monitoring Program, 2008-2021 ver 4. Environmental Data Initiative.
• Twining CW, Brenna JT, Hairston Jr. NG, Flecker AS. 2016. Highly unsaturated fatty acids in nature: what we know and what we need to learn. Oikos. 125(6):749-760.
• Wells, E. and Interagency Ecological Program. 2023. Interagency Ecological Program: Benthic invertebrate monitoring in the Sacramento-San Joaquin Bay-Delta, collected by the Environmental Monitoring Program, 1975-2022. ver 3. Environmental Data Initiative.

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

By Rosemary Hartman

With help from Arthur Barros and all the zooplankton taxonomists of the Stockton CDFW lab.

Photos by Tricia Bippus (CDFW)

Zooplankton never get as much appreciation as fish (Hartman et al. 2021), but even among zooplankton there are clear favorites. Copepods and mysid shrimp have dozens of publications dedicated to them, but rotifers often get the short end of the stick. Most papers about “zooplankton” in the San Francisco estuary don’t even mention rotifers. However, the Environmental Monitoring Program works very hard monitoring microzooplankton (guys smaller than 150 microns) and the expert taxonomists at CDFW’s Stockton laboratory spend hours counting and identifying rotifers in those samples. Rotifers are an important link in the food chain connecting bacteria, phytoplankton, and particulate organic matter to fish. They are eaten by larger zooplankton and larval fish (Plabbmann et al. 1997, Burris et al. 2022).

What is a rotifer anyway?

Rotifers are one of the simplest multi-cellular animals on earth, sometimes called "wheel animals" because they have a ciliated structure on their head that looks a little like a wheel. They are tiny, usually only half a millimeter long, and they eat phytoplankton and bits of organic material floating in the water.

How are the samples collected? Well, it starts with the field crew going out to long-term monitoring stations throughout the Delta. The crew lowers a pump nearly to the bottom, then raises the pump up slowly, sucking in water and zooplankton as it goes. The water is then passed through a 43-micron mesh net until 75 L of water have been filtered. All the critters in the net are carefully preserved in formalin, with a little bit of pink dye added to make the critters stand out better. See Kayfetz et al. (2020) (PDF) and the Zooplankton EDI publication metadata (Barros 2021b) for more information.

Back in the laboratory, trained taxonomists subsample the critters and carefully identify and count them under a microscope. Rotifers are tricky to identify, so most are only identified to the genus level, or lumped into “other rotifers”. The rotifers we see most frequently are:

Synchaeta spp.

• Swimming form: top-shaped with pointed foot and lateral auricles with bristles at the widest point, bristles around corona.
• Contracted form: roundish to donut-shaped with corona, auricles and foot sucked in. Not much clear space, organs more prominent than in Asplanchna.

Synchaeta bichornis

• Pointed ‘foot’ at posterior end, two ‘horns’ at the anterior end.
• Body usually curved into a shallow “C” shape.

Polyarthra spp.

• Body squarish with feather-like appendages at the “corners”.
• Appendages extend beyond length of the body.

Keratella spp.

• 6 prominent ‘teeth’ or hooks on the anterior margin. Posterior end variable, with zero, one, or two spines.
• Rigid lorica.

Trichocerca spp.

• Mostly cylindrical, more or less curved, tapering at the anterior and posterior ends.
• Toes asymmetrical: one prominently elongated, filament-like, often held up ventrally.

Asplanchna spp.

• Like a clear bag with few organs inside, more clear space than Synchaeta.
• No ‘foot’. Contracted form with corona sucked in at one end.

“Other rotifers”

• Including Branchionus, Playais, colonial rotifers, Notholca, Filinia, and many more!

So, what can we learn from the rotifer data?

Well, we can start by graphing the average rotifer catch at all stations since the zooplankton survey began (Figure 1). The first thing that jumps out at you is that the standard deviation is HUGE! Rotifers (like all zooplankton) are highly variable critters with big changes from station to station, month to month, and year to year. The next thing that probably jumps out at you is that abundances were a LOT higher prior to 1980. What could have driven that decline?

But that is the average catch for ALL the rotifers lumped together. It might be interesting to look at each taxon individually (Figure 2). Here we can see that all species declined after 1980, but the biggest drops were seen Keratella, Polyarthra, and Trichocerca. Synchaeta didn’t show quite as big a drop. We can also see that Synchaeta is usually the most common taxa, while Asplanchna is pretty rare. Lots of other researchers have noticed a big drop in copepods and chlorophyll after 1986 when the invasive clam Potamocorbula amurensis started to take over the area (Kimmerer et al. 1994, Kimmerer and Thompson 2014, Kimmerer and Lougee 2015), but no one has looked at the post-1980 rotifer crash!

Since 1980, the biggest years for rotifers were 2017 and 2011, both of which were really wet years. Maybe rotifers like wetter years better? Let’s subset our data so we just have data from after 1980 and see how water year time affects rotifer catch (Figure 3). The pattern isn’t super clear – all taxa had high catches in 2017, but not all wet years had high catches, and some taxa (like Asplanchna) also had high catches during drier years. However, when we graph the average total rotifer catch versus the Sacramento Valley Index (a measure of water availability), we see a positive correlation between water flow and rotifer catch (Figure 4). Why might this be? Are they getting moved in from upstream? Or are they reproducing faster?

Of course, there are lots of different ways to display the data. We can make area plots, bar plots, streamflow plots, pie charts, maps, or pie charts on top of maps (Figure 5)! Different types of graphs help you see the data in different ways and pull out different patterns.

Are you interested in finding more patterns in the data?

You can visualize the data yourself on the ZoopSynth Shiny app (which also lets you download the data). However, before you dig in, be sure to read all of the metadata available on the Zooplankton EDI publication. You can also read some of the most recent Status and Trends reports published in the IEP newsletter for more ideas about useful patterns waiting for you to discover (Barros 2021a). Feel free to reach out if you have any questions or find any cool patterns! We love talking about zooplankton. Consider sharing your findings with the Zooplankton PWT too!

References and further reading

• Barros, A. 2021a. Zooplankton Trends in the Upper SFE, 1974-2018. IEP Newsletter 40:5-14.
• Barros, A. E. 2021b. Interagency Ecological Program Zooplankton Study ver 7. Environmental Data Initiative.
• Burris, Z. P. L., R. D. Baxter, and C. E. Burdi. 2022. Larval and juvenile Longfin Smelt diets as a function of fish size and prey density in the San Francisco Estuary. California Fish and Wildlife 108.
• Hartman, R., S. M. Bashevkin, A. Barros, C. E. Burdi, C. Patel, and T. Sommer. 2021. Food for Thought: Connecting Zooplankton Science to Management in the San Francisco Estuary. San Francisco Estuary and Watershed Science 19:art1.
• Kayfetz, K., S. M. Bashevkin, M. Thomas, R. Hartman, C. E. Burdi, A. Hennessy, T. Tempel, and A. Barros. 2020. Zooplankton Integrated Dataset Metadata Report (PDF). IEP Technical Report 93., California Department of Water Resources, Sacramento, California.
• Kimmerer, W. J., E. Gartside, and J. Orsi. 1994. Predation by an introduced clam as the likely cause of substantial declines in zooplankton of San Francisco Bay (PDF). Marine Ecology Progress Series 113:81-93.
• Kimmerer, W. J., and L. Lougee. 2015. Bivalve grazing causes substantial mortality to an estuarine copepod population. Journal of Experimental Marine Biology and Ecology 473:53-63.
• Kimmerer, W. J., and J. K. Thompson. 2014. Phytoplankton growth balanced by clam and zooplankton grazing and net transport into the low-salinity zone of the San Francisco Estuary. Estuaries and Coasts:1-17.
• Plabbmann, T., G. Maier, and H. B. Stich. 1997. Predation impacts of Cyclops vicinus on the rotifer community in Lake Constance in the Spring. Journal of Plankton Research 19:1069-1079.

More underappreciated data!

This is the second blog in our series on underutilized datasets from IEP.

San Francisco Bay Study’s Crab Catch dataset

Curated by Kathy Hieb and Jillian Burns

The San Francisco Bay Study has been sampling with otter trawls and midwater trawls throughout the San Francisco Bay, Suisun Bay, and Delta since 1980. Their fish data have been used in a number of scientific studies, regulatory decisions, and journal articles. However, did you know they measure and count crabs in their nets too?

Bay Study’s stations are all categorized as “Shoal” (shallow areas) or “Channel” (deeper samples). Crabs are collected by otter trawl, which is towed along the bottom of the water, scraping up whatever demersal fishes and invertebrates it comes across. Truth be told, it’s not the best way to catch crabs, because most crabs like hiding under rocks where they are out of the way of the net, but it does give us a metric of status and trends of some of the most common species of crabs, including the Pacific rock crab (Cancer productus), the graceful rock crab (Cancer gracilis, also known as the slender rock crab), the red rock crab, and everyone’s favorite, the Dungeness crab (Metacarcinus magister).

After the net has been towed on the bottom for five minutes, it’s brought on board the boat and the biologists count, measure, and sex the crabs they’ve caught (Figure 1). This can be tricky, because crabs can be FAST! Especially the smaller Dungeness crabs (Figure 2). The biologists have to be careful and pick up the crabs by their back side to avoid getting pinched by their claws, which definitely takes practice.

Once all the crabs are counted and measured, they are entered into a database that goes back to 1980. Bay's Study's Dungeness crab data have been used to help manage the commercial crab fishery because fisheries-independent data is valuable. From 1975 to 1978, an estimated 38-82% of the Dungeness crabs in the central California region rear in the San Francisco Estuary each year (Wilde and Tasto 1983). This dataset was also very helpful in tracking the introduction, expansion, and decline of the Chinese mitten crab (Eriocheir sinensis), which briefly took over the brackish regions of the estuary but declined as rapidly as it arrived (Figure 3. Rudnick et al 2003). Bay Study's crab data has also been combined with other datasets to see how the estuarine community as a whole responds to climate patterns and human impacts (Cloern et al. 2010).

However, a lot of questions remain to be asked of this dataset. Why did we see such high catch of Dungeness crabs in 2013 and 2016? What are the drivers between the lesser-studied crabs, such as the graceful rock crab? How does the salinity preference of each species of crab differ (Figure 4)? If you want to investigate these questions yourself, data are available on the CDFW file library website. But be careful, the data have a few hiccups in them, such as changes to sampling sites over time, missing samples during period of boat break-downs, and other caveats. Be sure to read the metadata and make sure you understand the data before using them.

Further reading

• Baxter, R., K. Hieb, S. Deleon, K. Fleming, and J. Orsi. 1999. Report on the 1980-1995 fish, shrimp and crab sampling in the San Francisco Estuary (PDF), Interagency Ecological Program Technical Report 63. Stockton, California. 503 pages. 
• Cloern, J. E., K. A. Hieb, T. Jacobson, B. Sanso, E. Di Lorenzo, M. T. Stacey, J. L. Largier, W. Meiring, W. T. Peterson, T. M. Powell, M. Winder, and A. D. Jassby. 2010. Biological communities in San Francisco Bay track large-sale climate forcing over the North Pacific (PDF). Geophysical Research Letters 37(L21602):6 pages.
• Cloern, J. E., and A. D. Jassby. 2012. Drivers of change in estuarine-coastal ecosystems: Discoveries from four decades of study in San Francisco Bay. Reviews of Geophysics 50(4):RG4001. 
• Rudnick, D. A., K. Hieb, K. F. Grimmer, and V. H. Resh. 2003. Patterns and processes of biological invasion: The Chinese mitten crab in San Francisco Bay. Basic and Applied Ecology 4(3):249-262.
• Rudnick, D., T. Veldhuizen, R. Tullis, C. Culver, K. Hieb, and B. Tsukimura. 2005. A life history model for the San Francisco Estuary population of the Chinese mitten crab, Eriocheir sinensis (Decapoda: Grapsoidea). Biological Invasions 7(2):333. doi:
• Rudnick, D. A., K. M. Halat, and V. H. Resh. 2000. Distribution, Ecology and Potential Impacts of the Chinese Mitten Crab (Eriocheir sinensis) in San Francisco Bay. Technical Completion REPORT UCAL-WRC-W-881, University of California. 
• Wild, P. W, & Tasto, R. N. (1983). Fish Bulletin 172. Life History, Environment, and Mariculture Studies of the Dungeness Crab, Cancer Magister, With Emphasis on The Central California Fishery Resource. UC San Diego: Library – Scripps Digital Collection.