1 Abstract
The purpose of this article is to introduce an implementation framework enabling us, using available genetic samples, to understand and foresee the behavior of species living in a fragmented and temporally changing environment. To this aim, we first present a model of coalescence which is conditioned to environment, through an explicit modeling of population growth and migration. The parameters of this model can be infered using Approximate Bayesian Computation techniques, which supposes that the considered model can be efficiently simulated. We next present Quetzal, a C++ library composed of reusable generic components and designed to efficiently implement a wide range of coalescence-based environmental demogenetic models.
Copyright
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