Sébastien Barot

Sébastien Barot joined the Adaptive Dynamics Network in Ocotber 2000 to work in the European MODLIFE project with Ulf Dieckmann and Mikko Heino.
barot

barot

 This project aims at developing modern methods to study the evolution of life histories (complicated term used to sum up the various demographic features of plants and animals: survival, fecundity, age at first reproduction, and life expectancy) and more precisely the environmental feedback loop. His own project focused on the evolution of fish life histories. The main idea being that over-fishing of the sea fish results in high evolutionary pressure that has led to genetically based variations in, for example, the age and size at reproduction. Consequently the study is relevant both to improving our theoretical understanding of evolution and to helping find fishing strategies that are sustainable in terms of fish stocks, and that take into account the induced fish evolution: it is no use fishing loads of fish, even in a sustainable way, if those fish are getting smaller and smaller.

Mr. Barot studied forestry at the ENGREF (National School for Rural Engineering Waters and Forest, Nancy). He received his master's degree in ecology and then began working on a PhD at the University Pierre et Marie Curie in Paris. He worked in the CNRS laboratory entitled "Evolution and Functioning of Ecological Systems" in the "Biodiversity and Ecosystem functioning" team directed by Michel Loreau. During both his master's and PhD studies, he has worked on the demography of a savanna palm tree (Borassus aethiopum) in the Ivory Coast (Lampto field station founded in 1972).
Jean-Claude Menaut and Jacques Gignoux were his main advisors. He has mainly tried to disentangle the interactions predicted between the demography of a plant population, the spatial distribution of its individuals, and the preexisting environmental heterogeneity. He has collected the field data during two months a year. His work has consisted of (1) a lot of complicated data analysis to take into account all the possible interactions, (2) some modeling using matrix population models and the individual-based simulation approach.


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Last edited: 22 July 2013

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