Predicting future patterns of freshwater fish extinctions
Host Institute: Evolution and Biological Diversity, University Toulouse 3, France (www.edb.ups-tlse.fr)
Closing date for application: 1st April 2011
Duration: 24 months
The world is entering a major extinction crisis, the so called “Sixth Extinction” and this is particularly true for freshwater ecosystems that are among the most threatened on Earth. Among freshwater taxa, fishes are the best known regarding biodiversity. Fishes are also useful indicators of aquatic ecosystem health and sustainability and provide many economic services. Consequently a better understanding of the determinants of fish species extinctions is an attainable and critical step toward predictive models of freshwater ecosystems responses to global change.
In that context, the aim of the project “FISHLOSS” (ANR “Sixth Extinction”) is twofold. First, to draw an ecological and evolutionary framework for both natural and human driven freshwater fish extinctions at several spatial scales (from the site to the globe) by using a multidisciplinary approach combining ecology, biogeography, phylogenetics, paleontology, and biometry. Second, we intend to use this framework as an explanatory and predictive tool to identify species that are extinction-prone and to provide expected extinction rates under different scenarios of future climate change. As available evidence suggests that area of occupancy is a good predictor of background extinction rate, FISHLOSS consortium intends to establish a general relationship between background extinction rate and area of occupancy (EAR, extinction-area relationship). EAR could then be used to predict how much the extinction probability of a population will increase if its area of occupancy decreases.
Predicting future extinction rates
The successful applicant will apply a range of climate niche models, General Circulation Models (GCM) and greenhouse Gas Emissions Scenarios (GES) to a set of stream fish species occurrences. Then he will produce fish species distribution forecasts and will combine these forecasts (i.e., ensemble forecasting) with previously defined extinction-area relationships.
Future extinction rates will be predicted in two case studies: France (ONEMA database) and Africa (FAUNAFRI database, a compilation of geo-referenced occurrences of fish species over the African continent). The final outputs of this work will be to identify/cartography the combination basin-species having the highest predicted extinction probability (France), and the basins having the highest predicted extinction probability of endemic species (Africa).
• PhD in quantitative ecology or biostatistics
• Knowledge of species distribution modelling
• Working knowledge of large databases
Please send a CV (no more than 5 pages) outlining research experience and interests, publications, a list of skills and other relevant professional information.