Saturday, 28 January 2017

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

2017 Jan 11;284(1846). pii: 20161979. doi: 10.1098/rspb.2016.1979.

Author information

  • 1Estación Biológica de Doñana-CSIC, Américo Vespucio s.n., 41092 Sevilla, Spain
  • 2Dep. Biologia Animal, Vegetal i Ecologia, Autonomous University of Barcelona, 08193 Cerdanyola del Vallés, Spain.
  • 3Forest Sciences Centre of Catalonia (CEMFOR-CTFC), InForest Joint Research Unit (CSIC-CTFC-CREAF), Crta. Sant Llorenç de Morunys, Km 2, 25280 Solsona, Spain.
  • 4CIBIO/InBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos da Universidade do Porto, Campus Agrário de Vairão, R. Padre Armando Quintas, 4485-661 Vairão, Portugal.
  • 5CREAF, 08193 Cerdanyola del Vallés, Spain.
  • 6CSIC, 08193 Cerdanyola del Vallés, Spain.
  • 7Estación Biológica de Doñana-CSIC, Américo Vespucio s.n., 41092 Sevilla, Spain.


Historical species records offer an excellent opportunity to test the predictive ability of range forecasts under climate change, but researchers often consider that historical records are scarce and unreliable, besides the datasets collected by renowned naturalists. Here, we demonstrate the relevance of biodiversity records developed through citizen-science initiatives generated outside the natural sciences academia. We used a Spanish geographical dictionary from the mid-nineteenth century to compile over 10 000 freshwater fish records, including almost 4 000 brown trout (Salmo trutta) citations, and constructed a historical presence-absence dataset covering over 2 000 10 × 10 km cells, which is comparable to present-day data. There has been a clear reduction in trout range in the past 150 years, coinciding with a generalized warming. We show that current trout distribution can be accurately predicted based on historical records and past and present values of three air temperature variables. The models indicate a consistent decline of average suitability of around 25% between 1850s and 2000s, which is expected to surpass 40% by the 2050s. We stress the largely unexplored potential of historical species records from non-academic sources to open new pathways for long-term global change science.


Salmo trutta; citizen science; climate change; distribution forecast; historical ecology; species distribution models