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Exploring heterogeneity in diversification patterns across the tree of life using probabilistic models

Abstract : In this PhD thesis, I present different approaches based on probabilistic models for quantifying and explaining heterogeneity in the diversification process across the tree of life, all in the probabilistic modeling framework. In the first chapter, we focus on the general shape of phylogenetic trees, and propose a new metric for the quantification of the age-richness relationship of the subclades within a tree. The study of this metric in a dataset of empirical phylogenies shows that they diverge from the expectation under an homogeneous speciation model, possibly because of within-clade speciation rates variations. In the second chapter of the thesis, I focus on a finer scale description of diversification rates variations, and introduce a new method to estimate lineage-specific diversification rates within a phylogeny. Compared to previously existing methods that aim at identifying a few diversification rate shifts with large effect, ours propose a more gradual view of diversification rate evolution. We apply our approach to a dataset of empirical phylogenies, and show that Intra-clade variations accounts a large part of the rate variations in the whole dataset, suggesting suggest that models with many gradual changes may be more appropriate than models with few punctuated shifts for describing the evolution of diversification rates. Finally, the last chapter considers more directly one of the possible cause of variation in diversification rates, which is the presence of inter-species ecological interaction. We build an eco-evolutionary model for the emergence of mutualistic, antagonistic and neutral bipartite interaction communities, and study it prediction on species and trait diversity, as well as on several key network structure metrics. Our model generates realistic network structures, antagonistic communities being more modular and less nested than mutualistic ones. We find that antagonistic interactions foster both species and trait diversity, while mutualistic interactions generate strong stabilizing selection, with a negative impact on both diversity measures.
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Odile Maliet. Exploring heterogeneity in diversification patterns across the tree of life using probabilistic models. Biodiversity. Sorbonne Université, 2018. English. ⟨NNT : 2018SORUS081⟩. ⟨tel-02502827⟩

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