Shipboard Technique Assesses the Base of the Marine Food Web in Near Real-Time

For decades, Alaska has been leading the way in gathering and using ecosystem information to inform fish and crab resource management decisions. Now, scientists at the Alaska Fisheries Science Center can rapidly provide managers with information about how changes in the marine environment affect the basis of the marine food web. Details about this new methodology were recently published in a paper describing this new Rapid Zooplankton Assessment (RZA).

The RZA can supply near real-time information about the abundance and species composition of zooplankton. Zooplankton are the floating animals that, along with phytoplankton, form the base of the marine food web. These data-coupled with long-term data sets-can provide a snapshot of ecosystem health and help forecast the productivity of our fisheries.

Zooplankton Abundance Informs Fisheries Productivity

Across the world, fisheries managers are turning more and more to ecosystem-based fisheries management. It's a holistic approach that aims to maintain the resilience and sustainability of an ecosystem. Not only does it recognize physical and biological information, but economic and social factors as well. It seeks to optimize benefits among a diverse set of societal goals, especially in the face of climate change.

Collecting ecosystem data is a huge and multifaceted task. Looking at one piece of the puzzle, our scientists have focused on more efficiently surveying zooplankton. It's vitally important prey for fish at many stages of their life. Most importantly, zooplankton is the primary food source when marine fish transition from egg stage to larval stage and first begin to feed. This is deemed the "critical period" during which many fish die without abundant food. This, in turn, impacts recruitment-meaning how many fish will survive to older life stages. Zooplankton abundance is a good indicator of how strong recruitment will be for a specific fishery.

Zooplankton are also important to seabirds and marine mammals like whales. And zooplankton respond more immediately to climate variability. They are a great indicator of the health of an ecosystem. They can also give us insight into future climate regimes based on how they have responded to marine heatwaves and other large-scale changes.

However, collecting and analyzing zooplankton data is complicated and scientists take a lot of samples. Each one takes significant time and expertise to count and identify these microscopic organisms. There's often a lag of up to a year between sample collection and data availability from a survey.

"We wanted to come up with a faster way to provide useful data to fisheries managers," recalls Dave Kimmel, the project lead and research oceanographer with our Ecosystems & FIsheries-Oceanography Coordinated Investigations Program. The result was the Rapid Zooplankton Assessment.

Rapid Zooplankton Assessment

Dave Kimmel continues, "Our main goals for the RZA were to create a technique that non-experts could execute, and that produced data that were available as we finished our surveys. In order for this to be effective, these counts had to to be reliable when compared to laboratory-processed abundances."

The process involves collecting zooplankton with paired bongo nets. Scientists collected samples from one side (net 1) and later processed them via traditional laboratory techniques at the Plankton Sorting and ID Centerin Szczecin, Poland. From the second side (net 2), scientists live-sorted the samples aboard the survey vessel to produce the RZA abundance.

For the RZA, the sorter received basic training, but was not a taxonomic expert. Just like the laboratory method in Poland, the sorter worked with a sub-sample. The RZA sample had to be processed in 20 minutes or less, while the traditional method takes 2-4 hours. And the RZA only produced counts for three categories:

1. Large copepods (>2 millimeters)
2. Small copepods (<2 millimeters)
3. Euphausiids (also known as krill)

These three categories were chosen because they are easy to identify and are the most important food sources for fish in that critical period of development.

To test the reliability of the RZA, scientists compared data between laboratory and RZA techniques from 11 surveys in the spring and summer from 2015 to 2019. All locations were in Alaska: Gulf of Alaska (five surveys), southeastern Bering Sea (three), and Arctic (three). RZA data proved robust and comparable to laboratory techniques. There was only one discrepancy (for small copepods in the spring season), which was minor. It can be corrected for by adjusting the models for RZA data analysis.

Overall, the team concluded that RZA is an effective method for estimating zooplankton abundance in the three categories sampled. And this abundance has a strong correlation to commercial fisheries productivity. Because this technique makes the data available at the end of a survey in near real-time, it's a useful data point to consider for effective fisheries management.

Applications in Fisheries Management

Prior to developing the technique, scientists realized the direct correlation between zooplankton abundance and productivity in certain fisheries. This was observed on both the Atlantic (with cod, mackerel, capelin) and Pacific coasts (with Pacific codand Alaska pollock).

To test the RZA application, scientists looked at pollock, a federally managed fish stock. Warm ocean conditions led to higher springtime abundance of small copepods in the Eastern Bering Sea, but to lower abundance of large copepods in late summer. In those years, age-0 pollock abundance was down. Further observations revealed that the biomass of age-3 pollock was also affected by large copepod abundance during their first year of life. Warm conditions in one year led to lower numbers of age-3 pollock 3 years later, while cooler conditions produced the opposite.

Using this correlation, along with the availability of RZA data in near real-time, fisheries managers began incorporating zooplankton data through a risk table approach. Risk tables augment fisheries stock assessment models by applying additional information that often relates to rapidly changing environmental conditions.

An example was when the Bering Sea experienced very warm conditions in 2018, including record-low sea ice. As expected from prior years, corresponding data from the RZA indicated zooplankton abundances were low, specifically for large copepods in late summer. This information was added to the risk table, informing managers that prey for juvenile fish may be inadequate.

This was compounded by the marine heatwave that occurred from 2014 to 2016. From past observations, we know that age-3 pollock would likely be diminished by warm conditions 3 years prior. We also know that the 2018 RZA data raised concerns about juvenile fish survivorship. As a result, fisheries managers recommended cuts to the 2018 pollock catch. This left more adults in the population to reproduce again the following year. The RZA zooplankton data was important to this proactive management strategy.

"What is exciting about RZA is that it can be used to quickly assess the zooplankton community," says Kimmel. "In fact, today is September 30, 2024 and I just got back from our fall survey. As of this morning, I am able to include this year's data into our ecosystem status reports without any additional sample processing. It will be presented to the North Pacific Fishery Management Council and used to inform management decisions on fishing quotas."

Technique Not a Replacement for Lab Processing

The RZA technique is valuable, but does not replace the tremendous value of fully processing zooplankton samples in the lab. Analyzing the sample for all zooplankton species is imperative for capturing information about the whole ecosystem.

RZA also positions us well to react to the rapid shifts in ecosystem conditions we are currently observing. Short-term and rapid changes are evident with warming trends and climate change, which impact overall fisheries production. This technique facilitates rapid incorporation of ecosystem data into fisheries management. And it's needed now more than ever to help managers adapt to variable conditions caused by climate change.

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