Historical citizen science to understand and predict climate-driven trout decline

Area of Science:

• Ecology and Evolutionary Biology
• Climate Change Science
• Biodiversity Informatics

Background:

• Historical species records are valuable for climate change impact assessments but often deemed scarce and unreliable.
• Citizen science initiatives, outside traditional academia, can generate robust biodiversity data.
• Nineteenth-century geographical dictionaries offer an underutilized source of historical ecological information.

Purpose of the Study:

• To assess the utility of non-academic, citizen science-derived historical data for ecological forecasting.
• To reconstruct historical freshwater fish distribution, specifically brown trout (Salmo trutta), in Spain.
• To model current and predict future brown trout distribution under climate change scenarios.

Main Methods:

• Compiled over 10,000 freshwater fish records, including nearly 4,000 brown trout citations, from a mid-19th-century Spanish geographical dictionary.
• Constructed a historical presence-absence dataset for brown trout across 2,000 10x10 km cells.
• Developed predictive models using historical, past, and present air temperature variables to assess current and future trout distribution.

Main Results:

• A significant reduction in brown trout range over the past 150 years was observed, correlating with rising temperatures.
• Current brown trout distribution was accurately predicted using historical data and temperature variables.
• Modeled average habitat suitability declined by approximately 25% from the 1850s to the 2000s.

Conclusions:

• Historical species records from non-academic, citizen science sources are highly relevant and reliable for long-term global change studies.
• Brown trout populations have experienced substantial range contraction due to climate warming.
• Projected suitability decline of over 40% by the 2050s highlights the ongoing threat of climate change to this species.