Whether it's redfin pickerel in the Kennebec River or sturgeon in the Great Lakes, nearly one-third of freshwater fish species are facing possible extinction, threatening food supplies, ecosystems and outdoor recreation.
As conservationists work to preserve these species, the University of Maine assistant professor Christina Murphy asked herself if there was an easier way to identify threats to fish before they become endangered.
After five years of data collection, programming and testing, Murphy and her colleagues developed a computer model that identifies potential threats to more than 10,000 freshwater species worldwide. Encouragingly, the majority of species accounted for in the model could still be safeguarded before becoming endangered, like Maine's Arctic Char (Salvelinus alpinus) and certain char populations around in the world.
The model identifies threats beyond traditional assessments by analyzing 52 variables, including damming, water abstraction, habitat degradation, pollution, economics and invasive species. Using publicly available data, the tool can make identifying and protecting freshwater fish more cost-effective.
"This uses new metrics to identify what is working to keep species from being listed," said Murphy, who also serves as assistant unit leader for the U.S. Geological Survey's Maine Cooperative Fish and Wildlife Research Unit. "Managers may be able to protect a lot of fish."
The tool allows for more proactive conservation by recognizing ecological, environmental and socioeconomic patterns that are working for fish, helping wildlife stewards implement targeted protections that benefit multiple species at once.
"The big takeaways are the socioeconomic impact on conservation potential, and that we are better at identifying what works for species than what doesn't," Murphy said "Managers can set up new conservation programs based on what has worked in the past because a lot of species share what works."
Researchers incorporated data from 12 publicly available sources, the majority from the International Union for Conservation of Nature.
They programmed and trained artificial intelligence to analyze millions of nonlinear connections among species, determining which are in immediate danger and why. Users can examine the conditions driving risks and assess whether those threats exist for species not yet in immediate danger. Researchers also validated the model against existing assessments.
"Our results suggest conservation works like human health: the signals of 'well-being' are often more consistent than the many pathways to illness. For freshwater fishes, safe conditions tend to be predictable, while extinction risk can come from countless combinations of threats," shared co-author J. Andres Olivos, postdoc at Oregon State University.
Murphy and her colleagues believe their tool can be used in conservation and regional planning efforts, and hope it can be leveraged to design new models for protecting birds, trees and other flora and fauna.
"People sometimes go in to protect species when it's already too late. With our model, decision makers can deploy resources in advance before a species becomes imperiled," said Ivan Arsmendi, an associate professor in Oregon State University's College of Agricultural Sciences.
Murphy began the project in 2020 as a postdoctoral researcher at Oregon State, where she worked with Arismendi and Olivos in collaboration with scientists from the USGS, the U.S. Forest Service and the University of Girona in Catalonia, Spain. The team shared their findings in a research paper published in the journal Nature Communications .
