Scientists identify key challenges and solutions for integrating environmental DNA into fisheries stock assessments.
A scientist filters water samples in the R/V Bell M. Shimada Chemistry Lab. Credit: UW APL/Phil LaMothe.
Environmental DNA (eDNA) is a valuable tool that can enhance fish stock assessments by providing a non-invasive, cost-effective, and scalable way to monitor fish populations. Challenges remain in fully integrating eDNA into stock assessment frameworks. But ongoing research and collaboration are paving the way for its wider adoption and contribution to sustainable fisheries management.
Specific recommendations for each stage of eDNA collection
What expertise is needed in a collaborative research team
How to develop a population index (time series that tracks changes in the size of a population) that can be used to assess the trends in species presence and abundance across multiple years
eDNA is the genetic material shed by organisms into the surrounding environment. For example, a fish sheds its DNA as it swims through the ocean, which disperses into the water around it. Some sources of eDNA include scales, skin cells, mucus, feces, and gametes. This genetic material can be recovered from environmental samples—such as from water collected during research surveys—and used to identify fish species. More fish shed more eDNA, providing a link between the amount of eDNA and species abundance.
A stock assessment aims to estimate:
What is the absolute biomass (total weight of all living individuals) of a species
How its population changes over time
Whether the current population size is healthy compared to long-term trends
Stock assessments provide critical information to fishery management councils and managers, which use this information to set rules for sustainable harvest.
“To be integrated into a stock assessment, an eDNA survey needs to give scientists helpful information to track changes in the number of fish over space and time,” said Diana Baetscher, lead author and research geneticist with Alaska Fisheries Science Center’s Auke Bay Laboratories. “These data also need to include some measure of uncertainty. In other words, the accuracy of the measurements are based on how the samples were collected. This helps scientists who develop fish stock assessments combine different types of data—like surveys, fish sizes, and catch numbers—into models to produce the best possible estimates of changes in biomass.”
Challenges and Solutions
A central goal of managing fish species is understanding where they live (their distribution) and how many of them exist (their biomass or abundance). Accurately estimating this information is difficult. It involves drawing conclusions about a population based on observations from representative samples of individuals. NOAA Fisheries gets most of this information from two sources:
Fish collected in nets during research surveys
Data collected by fishery observers on commercial fishing boats and in processing plants
There are high data quality standards for including new data in a stock assessment. eDNA surveys must be carefully designed and implemented to optimize long-term data collection, usability, and cost-effectiveness.
Key technical and scientific challenges that previously limited wider use of eDNA in marine fisheries stock assessments include:
Building a clear link between eDNA and species abundance
Reducing detection errors by avoiding or quantifying false positives (detecting a species that isn’t actually there) and false negatives (missing a species that is present)
Understanding how eDNA spreads across space and time
Gathering biological information in conjunction with eDNA surveys—traditional surveys that physically collect fish provide biological data such as fish age, weight, or reproductive status; eDNA surveys do not directly provide biological data, but can be paired with other surveys or fishery observer collections that do
Measuring uncertainty in eDNA results
Overcoming skepticism about new survey methods to be used for stock assessments
These challenges can be overcome by improving how we describe the quantitative and spatial characteristics of eDNA. This means better understanding how much eDNA is present and how it spreads in the environment. It is also important to develop widely accepted best practices for designing experiments and analyzing data. Clear guidelines will help ensure that results are consistent and reliable. Another key step is conducting thorough evaluations to identify and then measure the uncertainty in estimates from eDNA surveys. This allows scientists to better represent and improve the accuracy of their findings. Finally, eDNA surveys can be combined with other types of data, such as trawl surveys, acoustic monitoring, and video observations. Using these complementary methods together gives a more accurate understanding of marine species populations.
Bridging Disciplines to Maximize the Impact of eDNA Data
Research teams must clearly define their goals from the beginning to ensure eDNA data are collected and used effectively.
“Bringing together geneticists, modelers, stock assessors, survey technicians, and fisheries managers ensures that eDNA data fills real science and management needs,” said Wes Larson, co-author and manager for the Genetics Program at the Alaska Fisheries Science Center. “When everyone’s at the table, we can design surveys that are both doable in the field and valuable for decision-making.”
