Proc Biol Sci. 2017 Jan 11;284(1846). pii: 20161979. doi: 10.1098/rspb.2016.1979.
- 1Estación Biológica de Doñana-CSIC, Américo Vespucio s.n., 41092 Sevilla, Spain miguelclavero@ebd.csic.es.
- 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.
Abstract
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.
© 2017 The Author(s).
KEYWORDS:
Salmo trutta; citizen science; climate change; distribution forecast; historical ecology; species distribution models