Using AI to GO FISH: Strengthening Climate-Resilient Inland Fisheries

A new NCEAS working group is combining artificial intelligence and global expertise to strengthen climate resiliency in inland fisheries

Inland fisheries are easy to overlook next to their ocean counterparts, but they punch well above their weight by providing employment, affordable food, and a way of life for communities around the world. Yet these systems are increasingly threatened by a rapidly changing natural world. Sustaining inland fisheries requires building their climate resilience, but first, scientists need better ways to connect the wealth of data relevant to inland fisheries that already exists.

Climate resilience, in this context, means a fishery and the people who rely on it can withstand climate-related shocks and continue operating rather than collapsing when conditions change. Building that resilience starts with anticipating change instead of just reacting to it, which in turn depends on having reliable, comparable data about what is happening across river basins. That is the gap a new NCEAS working group is trying to close.

The Morpho Initiative working group, GO FISH: Guidelines On core data for climate-resilient inland FISHeries, is working to build that foundation. The interdisciplinary team is developing shared data standards that will make inland fisheries data easier to integrate, analyze, and apply to conservation and management. The team convened for the first time in person at NCEAS in Santa Barbara this past June, starting a collaboration that will span disciplines, continents, and river basins.

 

 

Building a common language for inland fisheries

Creating common data standards may sound like behind-the-scenes work, but it lays the foundation for future scientific discovery. When datasets can "speak the same language," researchers can combine information collected by different organizations, compare ecosystems across regions, and develop models that reveal patterns impossible to detect from isolated datasets.

The scale of that challenge requires expertise from across disciplines and around the world, explains Gretchen Stokes (Baylor University), one of the PIs on the project:

"Our working group brings together 18 experts from 10 countries with expertise in fisheries science, computational modeling, basin management, climate adaptation, geospatial analysis, community-based fisheries management, and global policy. We really need that geographic and disciplinary diversity because no single discipline can solve this challenge alone."

That diversity is essential because inland fisheries remain one of the most data-limited areas of environmental science. As Stokes puts it:

"We're tackling one of the biggest barriers to sustainable inland fisheries management: data limitations. Inland fisheries data are disparate, non-standardized, and often entirely lacking for the world's most important inland fisheries."

Although satellite observations have transformed our ability to monitor environmental change, Stokes notes that they cannot replace field observations or local expertise:

"Earth observation data have transformed our ability to monitor environmental change, but they can't tell the whole story. So it's important to ground truth with field data. The challenge is that local data are often sparse, inconsistent, and expensive to collect across highly heterogeneous freshwater landscapes. Our goal is to determine which on-the-ground data are truly indispensable, so managers can focus limited resources on collecting the information that matters most for promoting climate-resilient fisheries."

Those efforts are increasingly urgent. "Inland fisheries are often overlooked, yet they support the nutrition, livelihoods, and well-being of hundreds of millions of people around the world," Abby Lynch (USGS), the other PI on the project, said. "Freshwater ecosystems support very high biodiversity yet they occupy less than one percent of Earth's surface water and are among the most threatened ecosystems on the planet."

As environmental conditions continue to shift, Lynch hopes standardized data can help managers make decisions before ecosystems reach critical tipping points:

"As climate change, water development, and habitat degradation continue to reshape rivers and lakes, developing strategies for fisheries management and conservation that help adapt to changing conditions can support both people and nature. Building climate resilience means giving managers the information they need to anticipate change, respond proactively, and sustain fisheries before critical thresholds are crossed."

 

 

Where AI fits in and where human expertise remains essential

To help answer these increasingly complex issues, the team is turning to artificial intelligence not to replace scientific expertise, but to make sense of enormous volumes of environmental data.

"The availability of environmental data today can sometimes seem overwhelming," Bonnie Myers (USGS), another member of the project, points out. "A growing array of variables can now be measured rapidly and at high resolutions. The task of analyzing it is simply too large for people to do efficiently on their own."

AI allows researchers to integrate satellite observations with fisheries monitoring data collected across river basins, helping identify patterns, detect redundancies, and determine which information provides the greatest value for understanding fisheries.

"AI allows us to integrate satellite observations with fisheries monitoring data collected across basins, identify patterns, detect redundancies, and determine which information provides the greatest value for understanding fisheries," Myers explained.

But the technology is only as valuable as the people interpreting the results:

"While AI is a valuable resource for this work, it cannot serve as a decision maker. This is where human expertise remains essential for interpreting results, understanding the ecological and social context of each basin, validating the models, and ensuring that our findings are practical for fishery managers. The strongest outcomes come from combining advanced analytics and modeling with the experience and expertise of the people who know these fisheries best."

 

Starting strong

The team's first meeting gave researchers an opportunity to begin building that collaborative foundation. Participants discussed the policy implications of their work while exploring how AI could help integrate information from satellites, fisher organizations, and fishery managers across five major river basins: the Mekong, Amazon, Danube, Niger, and Mississippi. These basins all vary in the data they collect and what it looks like, making streamlining essential.

"Our first working group was a huge success!" Stokes said. "One of the most exciting outcomes from our first meeting was a shared motivation for the policy implications of the work and a deeper understanding of the key components that we will leverage to effect positive change."

The meeting also generated enthusiasm around using AI to combine highly variable data sources collected across continents:

"There was enthusiasm around using AI not just to analyze data, but to synergistically fuse and validate highly variable data sources from satellites, fisher organizations, and fishery managers across major basins in five continents: the Mekong, Amazon, Danube, Niger, and Mississippi basins. Having a shared vision gives us a strong foundation as we move into integrating datasets from some of the world's most important inland fisheries."

 

 

What comes next

Looking ahead, the team sees AI as an opportunity to shift conservation from reacting to environmental change toward anticipating it.

"By bringing together satellite observations and field measurements, AI can help detect patterns and identify early warning signals that would otherwise be difficult to collate at basin and regional scales," Lynch said.

"Ultimately, success isn't about using more technology; it's about making better decisions," Lynch added. "If AI helps us provide fishery managers with clearer, faster, and more actionable information, then we can better support freshwater biodiversity, strengthen food security, and build ecosystems that are more resilient in a changing climate." By turning disparate data into a shared language, GO FISH is giving the people who manage the world's inland fisheries a better shot at keeping them, and the communities they sustain, resilient.