Integrating climate data and river modeling to reveal Chinook salmon habitat conditions in subarctic river basins

Abstract Climatic extremes can impact the productivity of aquatic species, affecting ecosystems and fishery‐dependent communities. Advances in climate products, such as gridded datasets and downscaled projections, may be useful for quantifying freshwater habitat conditions and predicting climate change effects on fish. However, limited guidance exists for selecting climate products to develop indicators of freshwater habitat conditions that influence fish population dynamics. Here, we develop an approach for identifying streamflow and stream temperature models to address this need. We evaluated skill in predicted versus observed streamflow and stream temperature, with predictions depending on different models and gridded climate data as inputs. The best performing models were used in a case study exploring habitat conditions influencing Chinook salmon in the Yukon and Kuskokwim River basins, two remote high‐latitude watersheds with few in situ habitat observations and recent salmon declines. Three modeled streamflow datasets had variable performance (median Nash–Sutcliffe efficiencies from 0.39 to 0.70). Three gridded temperature products differed in their ability to explain variation in weekly stream temperatures (median r 2 from 0.42 to 0.76). We selected a single gridded air temperature dataset to compare two novel predictive stream temperature models, both of which had good accuracy (root mean squared error [RMSE] of 1.19 and 0.95°C). Stream temperature indicators calculated from modeled daily data, maximum temperatures during adult migration and cumulative temperatures during juvenile rearing, had high spatial correlation across tributaries within the Yukon and Kuskokwim River basins and showed significant warming over the past 40 years. Streamflow indicators calculated from modeled daily data, maximum flow during spawning and median flow during rearing, had few trends and were largely uncorrelated within the Yukon River basin and moderately correlated within the Kuskokwim River basin. Overall, we found that generic measures of model performance varied considerably, and it was important to consider the models best suited to our case study. For both streamflow and stream temperature, multiple high‐performing models allowed estimation of ecologically relevant conditions affecting Chinook salmon. The approach we used to estimate local‐scale habitat conditions has value to identify synchronous conditions that may influence multiple salmon populations under a changing subarctic climate.

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Publication Details

Journal
Ecosphere
Published
2026-01-01
DOI
https://doi.org/10.1002/ecs2.70399
Citations
1
Primary Topic
Fish Ecology and Management Studies
Type
article
Field-Weighted Citation Impact
0.00
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article

Integrating climate data and river modeling to reveal Chinook salmon habitat conditions in subarctic river basins

Megan L. Feddern, Curry J. Cunningham, Erik R. Schoen, Andrew J. Newman et al.
1 citations
Ecosphere
Fish Ecology and Management Studies
article

Integrating climate data and river modeling to reveal Chinook salmon habitat conditions in subarctic river basins

Megan L. Feddern, Curry J. Cunningham, Erik R. Schoen, Andrew J. Newman, Rebecca Shaftel, Al von Finster, Jeff Falke, Stephanie A. McAfee, Margaret Perdue, Jon Schwenk, Josh Paul, Yifan Cheng, Vanessa R. von Biela
article en
1 citations

Abstract

Abstract Climatic extremes can impact the productivity of aquatic species, affecting ecosystems and fishery‐dependent communities. Advances in climate products, such as gridded datasets and downscaled projections, may be useful for quantifying freshwater habitat conditions and predicting climate change effects on fish. However, limited guidance exists for selecting climate products to develop indicators of freshwater habitat conditions that influence fish population dynamics. Here, we develop an approach for identifying streamflow and stream temperature models to address this need. We evaluated skill in predicted versus observed streamflow and stream temperature, with predictions depending on different models and gridded climate data as inputs. The best performing models were used in a case study exploring habitat conditions influencing Chinook salmon in the Yukon and Kuskokwim River basins, two remote high‐latitude watersheds with few in situ habitat observations and recent salmon declines. Three modeled streamflow datasets had variable performance (median Nash–Sutcliffe efficiencies from 0.39 to 0.70). Three gridded temperature products differed in their ability to explain variation in weekly stream temperatures (median r 2 from 0.42 to 0.76). We selected a single gridded air temperature dataset to compare two novel predictive stream temperature models, both of which had good accuracy (root mean squared error [RMSE] of 1.19 and 0.95°C). Stream temperature indicators calculated from modeled daily data, maximum temperatures during adult migration and cumulative temperatures during juvenile rearing, had high spatial correlation across tributaries within the Yukon and Kuskokwim River basins and showed significant warming over the past 40 years. Streamflow indicators calculated from modeled daily data, maximum flow during spawning and median flow during rearing, had few trends and were largely uncorrelated within the Yukon River basin and moderately correlated within the Kuskokwim River basin. Overall, we found that generic measures of model performance varied considerably, and it was important to consider the models best suited to our case study. For both streamflow and stream temperature, multiple high‐performing models allowed estimation of ecologically relevant conditions affecting Chinook salmon. The approach we used to estimate local‐scale habitat conditions has value to identify synchronous conditions that may influence multiple salmon populations under a changing subarctic climate.

EcosphereVol. 17(1)
NOAA National Marine Fisheries Service (US), NSF National Center for Atmospheric Research (US), United States Geological Survey (US), Bureau of Land Management (US), Fisheries and Oceans Canada (CA), United States Fish and Wildlife Service (US), Los Alamos National Laboratory (US), University of Alaska Fairbanks (US), Nevada Department of Wildlife (US), NOAA National Marine Fisheries Service Northwest Fisheries Science Center (US), U.S. Geological Survey, Alaska Science Center, University at Buffalo, State University of New York (US)
Climate action
Openalex Percentile: Top 97%
Fish Ecology and Management Studies
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