18.06.2026 | Haoyun Liu | WSL News
Researchers from the Swiss Federal Institute for Forest, Snow and Landscape Research (WSL) propose a tool which predicts, up to three weeks in advance, when river fish in Switzerland are at risk from heat. As heatwaves become more frequent with climate change, this early detection system gives the time to act and protect fish populations from future heatwaves.
- A forecasting tool detects when river fish are at risk from heat stress in Switzerland.
- The system estimates future risk using water temperature predictions and the heat sensitivity of local fish populations.
- The forecasts are openly accessible online to help manage river ecosystems proactively and protect fish populations.
Preparing for weather extremes ¶
When do rivers become too hot for river fish in Switzerland? To predict when river fish are at risk from heatwaves, ecologists and climatologists at the Swiss Federal Institute for Forest, Snow and Landscape Research WSL joined forces with experts from across Switzerland to develop a forecasting tool, published in the Journal of Ecological Modelling. The forecasts are updated twice a week and publicly available on drought.ch.
With heatwaves becoming more frequent and severe due to climate change, fish are particularly at risk, as their body temperature depends entirely on their environment. Unable to cool themselves down, fish are ectothermic, more commonly referred to as “cold-blooded” animals. “When the water temperature rises, chemical reactions in the fish’s cells change — and that’s what we call heat stress”, defines Camille Albouy, senior researcher at the joint WSL and ETH research group Ecosystems and Landscape Evolution.
From past data to future risk ¶
The new tool predicts, up to three weeks in advance, how at-risk fish populations are from heat across Switzerland. The predictions are based on three parameters: water temperature forecasts, fish physiology and species distribution. WSL’s hydrological forecasting group developed the water temperature forecasts. “Our machine-learning model, trained on data from the past 10 years, uses the latest water temperature observations and weather forecasts to predict river temperatures”, explains Ryan Padrón Flasher, one of the group’s members.
Not all fish are equally sensitive to heat. Searching through published data, the authors gathered information on the temperature limits of 59 fish species found in Swiss rivers. This is the temperature at which their ability to swim, and therefore to escape from dangerous conditions, is impaired. The authors found non-native fish species to have a temperature tolerance 1.4°C higher than native species on average. The bighead carp (Hypophthalmichthys nobilis) held the highest tolerance of 32.3°C, while the burbot (Lota lota) was the least tolerant, with 24.1°C.
Finally, as fish species are unevenly present across Switzerland, including information on their distribution makes the forecasts location specific. “It’s a constant compromise between the complexity and quality of the model”, explains Camille Albouy. “As the idea was to develop a map of risk for the whole of Switzerland, based on the best climate predictions, we had to keep it simple and focus on what matters for management.”
With the help of hindsight ¶
To evaluate the forecasts, the scientists applied their tool on data from summer 2018, when around three tonnes of river fish died in Switzerland. “We wanted to see how well we could retrospectively predict the observed fish mortality”, says Camille Albouy. However, this proved more challenging than expected. “Data on fish mortality are limited,” he clarifies, “so we reached out to practitioners to see if their observations matched our predictions.”
Out of the three reported cases of fish mortality in 2018, the tool predicted two correctly. Across the remaining locations, forecasts were 70% accurate, successfully identifying areas of low and moderate risk. However, at five sites the tool overestimated the level of risk, likely because it does not include finer-scale information like local population sizes or the presence of cooler refuges within rivers. “It’s a promising start” says Camille Albouy, “now we need to see if it grows into a long-term solution for Swiss rivers.”
Updated on 19 June 2026: An earlier version of this article contained the term “early warning system.” We have replaced it with “early detection system.”
Contact ¶
Adeline Bonaglia, adelineemma.bonaglia(at)uzh.ch
Publication ¶
Bonaglia, A., Shen, C., Padrón, R. S., Bogner, K., Fopp, F., Rubin, A., … Pellissier, L. (2025). Sub-seasonal forecasting of thermal stress for Swiss river fishes during heatwaves. Ecological Modelling, 507, 111171 (14 pp.). https://doi.org/10.1016/j.ecolmodel.2025.111171
Copyright ¶
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