Science Stories: Adventures in Bay-Delta Data

By Pete Nelson

What’s this post about?

A Juvenile Production Estimate (JPE), as we discussed in Part 1 of this essay, is an estimate of the number and timing of outmigrating juvenile spring-run Chinook Salmon (“spring run”) as they enter the Sacramento-San Joaquin Delta. It is an important tool for protecting these fish because it helps water managers anticipate when these salmon may be at risk of becoming entrained in water diversions as well as serving as an important check on the status of this population. In this part, I’ll describe the cutting-edge genetic and modeling tools we’re using to distinguish spring run from the other Central Valley Chinook. This series will finish with a final installment full of the quantitative modeling we’re developing to pull in all the salmon and environmental data and actually produce a forecast of juvenile spring-run production.

Distinguishing spring-run Chinook from other salmon

Ronald Reagan once said, “A tree’s a tree: How many more do you need to look at?” I don’t know about Mr. Reagan, but most of us could probably tell that there’s a difference between a valley oak from a ponderosa pine (hint: one has pinecones and the other has acorns); however, even the best fish biologists can’t tell a spring-run from a fall-run Chinook based on looks alone.

Table 1. Central Valley Chinook salmon life cycle timing.

Until recently, the most practical way to separate the four different runs (remember? there are fall run, late fall run, winter run, and, of course, spring run) was to consider the size of the fish and the day of the year it was observed. Each run spawns during a different time of the year, and if those developing eggs and fry grow at approximately the same rate, you might expect that spring run, with peak spawning in September and October, are going to be a little larger than fall run, which spawn about two months later (Table 1). Similarly, late fall- and winter-run fish, which begin their spawning even later are likely to be smaller still. As you peruse Table 1, you’ll see that the four runs spawn during different times of the year (light blue bars), but there’s a lot of overlap, particularly between spring run and fall run. When you factor in variations in water temperature and food availability across the watershed, which directly affect the duration of egg incubation and larval and juvenile growth, there’s even more potential for overlap in size between the runs. To make run identification more challenging still, the juveniles from different spawning locations are typically moving downstream during roughly the same timeframe (November through July), and juveniles from some runs (especially late fall run and spring run) over-summer where they can find cold enough water and don’t migrate down until the following migration season, but typically earlier in the season and at a much larger size. Nonetheless, observing outmigrating juveniles with the first rains in November, you’d probably expect the largest of these fish to be late fall-run and spring-run fish that delayed migrating to the ocean and spent their first summer in their natal streams, with successively smaller fish being young-of-the-year winter run, spring run, and fall run.

Figure 1. River length-at-date (LAD) run identification curves (colored panels) and the genetic identity of fish (panels A-D) for juvenile Chinook collected at Chipps Island ( from Johnson et al. 2017). Word is, this figure is based on older genetic results and a lot of the bigger fall-run here are probably spring-run or late fall-run (thanks Brett Harvey!).

Counting cards, counting salmon

Now take a look at Figure 1. The background of each panel, made up of curved shapes, is colored to indicate the predicted size ranges on any given day of the year for the four run-types: Fall run as orange, late fall run as green, winter run as blue, and spring run as purple. These colors are generated using a mathematical formula that relates a fish’s length-at-date or LAD to a particular run-type. For example, looking at the blue winter-run curves, you’ll see that they (the fish and the shapes) start small, early in the time period—not even 50 mm long in September—but growing to 200 mm as early as about April. Therefore, if the models are correct, we would expect a small, 50 mm fish in October to be the progeny of parents who returned to fresh water in the winter (winter run). Similarly, a 75 mm fish in October is likely to be a late fall-run fish, and a juvenile 80 mm or larger in October is expected to be a fall-run fish. That’s if the fish play by our rules! Now look at the black dots on these graphs: Each dot represents the size of an actual individual, outmigrating juvenile salmon that was genetically identified as belonging to one of the four run-types, and the dots don’t all stay in the colored curve where we’d expect based on length. Still need convincing that these models aren’t perfect? Figure 2 compares the percentage of outmigrants belonging to each run as determined by LAD versus genetic test, and the success of the LAD approach at predicting run type could only be described as abysmal. Bottom line: LAD models are a less than dependable option for identifying the run of a juvenile salmon. Still, LAD does provide the foundation for another important element of our JPE program: probabilistic length-at-date or PLAD models.

Figure 2. Percent of total juvenile Chinook salmon by field year assigned to each run (rows), based on length-at-date (LAD) criteria versus genetic analysis (from Brandes et al. 2021).

The PLAD approach also uses the size of a juvenile salmon and the date captured to assign run type, but, employing a similar approach to counting cards when trying to beat your nephew during a competitive game of “Hi-Lo”^[1],; PLAD also uses probabilistic modeling to estimate the uncertainty associated with that run assignment. Figure 3 shows how two run types might be distinguished with varying degrees of confidence based on day of capture, size, and our history of genetically determined run types of that date and size combination. Here, the larger the fish, the more likely it is to be from that “blue” run type. Each contour line is defined by a probability measure. That measure of probability relies on our database of juvenile salmon captures where we’ve used genetic techniques to determine the run-type for juveniles sampled across a range of sizes, dates and locations of capture. We’re particularly careful to retain a tissue sample from fish with a low probability PLAD run assignment; later genetic analysis is expected to improve our model’s accuracy. As this database is expanded, our ability to include such factors as the tributary where the salmon was captured and environmental factors (e.g., flow and temperature) likely to affect growth rates will be improved. In other words, the PLAD model does not provide a run-type determination with complete certainty, but it should dramatically improve our ability to distinguish between these runs and it’s cheaper, quicker, and easier than doing the genetics on every single fish we sample.

Figure 3. Conceptual depiction of probabilistic length-at-date (PLAD) juvenile salmon size ranges for two runs (from Nelson et al. 2023).

Genetics

Thus far, we’ve been blithely referring to the use of “genetics” for distinguishing amongst Chinook run types without a care in the world for the hard-working folks who extract the DNA from these fish and examine the sequence of molecules contained therein. So how do they do it? DNA sequences can be used for differentiating amongst groups at varying levels—blood found at a crime scene might be examined first at the species level: Is this blood from a human victim or is this merely evidence of poor kitchen practices where someone butchered that darned rooster who persisted in crowing at 4 AM every morning? DNA can be used to determine if this is poultry or human blood, and it can also be used to determine which human left that blood. As you might imagine, distinguishing between individual humans requires more detail (more genetic markers, more time and expense) than determining foul versus fowl. The laboratory techniques for making these determinations are continually being improved, and DWR is now using a method that allows field crews to take a tissue sample from a fish and right there, in as little as 30 minutes, learn whether that fish is a spring-run salmon or not. The fish is unharmed, the sampling is quick, and the process is relatively inexpensive.

Our team has several genetic tests that we employ, each giving results with varying levels of precision and each with different demands in terms of time, effort and cost. Our initial test uses a CRISPR-based technique known as SHERLOCK (Baerwald et al. in press). It’s fast and cheap—less than $2.26 per sample—and gives one of three results: Early/Early, Late/Late, and Early/Late. These three terms relate to Central Valley Chinook run timing and the knowledge that these behaviors have largely been attributed to a single genetic region. Like humans, each salmon has two copies of each gene; each juvenile salmon inherits either an Early or a Late gene from dad, and an Early or Late gene from mom. Thus, each juvenile salmon ends up with either two Early genes (Early/Early or “homozygous Early”) or two Late genes (Late/Late or “homozygous Late”), or the juvenile may end up with one of each gene (Early/Late—“heterozygous” as the geneticists would say). It turns out that both winter- and spring-run salmon are Early/Early, and Late/Late fish are either fall-run or late fall-run salmon. Additional testing can distinguish between winter and spring run. What about the Early/Late heterozygotes? Yet another genetic test may allow us to assign those fish to a specific run, but this test costs more and must be processed in the laboratory, which takes more time.

Not only are these genetic tests critical to the ostensibly simple counts (“three more spring run and one more winter run”) that go into calculating a JPE, but they also serve to improve our PLAD model, testing and refining our ability to predict how to make run assignments using only size and date. After all, the PLAD models are still the quickest and cheapest way to determine how many juvenile salmon are produced by each of the runs.

What next?

Maryam Mirzakhani, the amazing Iranian-born mathematician, said, “The beauty of mathematics only shows itself to more patient followers.” Similarly, our efforts to forecast the number of juvenile spring run each year requires a little patience...and requires what ecologists refer to as quantitative modeling. This is where we take the monitoring data, PLAD results and the output of genetic analyses, and join it with environmental information—principally water temperature and flow rates—to generate a final JPE number. But for this, you’ll have to wait for Part 3.

Further Reading

• Baerwald, M. R., E. C. Funk, A. M. Goodbla, M. A. Campbell, T. Thompson, M. H. Meek, and A. D. Schreier. Rapid CRISPR-Cas13a genetic identification enables new opportunities for listed Chinook salmon management. Molecular Ecology Resources. in press.
• Brandes, P. L., B. Pyper, M. Banks, D. Jacobson, T. Garrison, and S. Cramer. 2021. Comparison of Length-at-Date Criteria and Genetic Run Assignments for Juvenile Chinook Salmon Caught at Sacramento and Chipps Island in the Sacramento–San Joaquin Delta of California. San Francisco Estuary and Watershed Science. [accessed 2023 Jan 3]. 19 (3).
• Johnson, R., S. Windell, P. L. Brandes, J. L. Conrad, J. Ferguson, P. A. L. Goertler, B. N. Harvey, J. Heublein, J. A. Israel, D. W. Kratville, J. E. Kirsch, R. W. Perry, J. Pisciooto, W. R. Poytress, K. Reece, and B. G. Swart. 2017. Science Advancements Key to Increasing Management Value of Life Stage Monitoring Networks for Endangered Sacramento River Winter-Run Chinook Salmon in California. San Francisco Estuary and Watershed Science.  15 (3).
• Nelson, P. A., M. Baerwald, O. Burgess, E. Bush, A. Collins, F. Cordoleani, H. DeBey, D. Gille, P. A. L. Goertler, B. Harvey, R. C. Johnson, J. Kindopp, E. Meyers, J. Notch, C. C. Phillis, G. Singer, and T. Sommer. 2022. Considerations for the Development of a Juvenile Production Estimate for Central Valley Spring-Run Chinook Salmon. San Francisco Estuary and Watershed Science. 20 (2).

1. Hi-Lo is a simple card game in which the dealer turns over the top card in a full deck and the player then guesses whether the next card in the deck will be higher or lower than the first card. Guess right and the player wins; guess wrong and the dealer wins (if the cards are equal, then neither player wins). The process continues as each card is revealed in succession. To give a very simple example, if you count the face cards (Jacks, Queens, Kings—12 in the deck, total), and the dealer has revealed 10, chances are very good that a Queen is going to be followed by a lower card.