Do closely related species interact with similar partners? Testing for phylogenetic signal in bipartite interaction networks

Whether interactions between species are conserved on evolutionary time-scales has spurred the development of both correlative and process-based approaches for testing phylogenetic signal in interspecific interactions: do closely related species interact with similar partners? Here we use simulations to test the statistical performances of the two approaches that are the most widely used in the field: Mantel tests and the Phylogenetic Bipartite Linear Model (PBLM). Mantel tests investigate the correlation between phylogenetic distances and dissimilarities in sets of interacting partners, while PBLM is a process-based approach that relies on strong assumptions about how interactions evolve. We find that PBLM often detects a phylogenetic signal when it should not. Simple Mantel tests instead have infrequent false positives and moderate statistical power; however, they often artifactually detect that closely related species interact with dissimilar partners. Partial Mantel tests, which are used to partial out the phylogenetic signal in the number of partners, actually fail at correcting for this confounding effect, and we instead recommend evaluating the significance of Mantel tests with network permutations constraining the number of partners. We also explore the ability of simple Mantel tests to analyze clade-specific phylogenetic signals. We provide general guidelines and an application on an interaction network between orchids and mycorrhizal fungi.ecological network, phylogenetic signal, Mantel tests, clade-specific signal, species interactions, mycorrhizal symbiosis

The Latitudinal Diversity Gradient: Novel Understanding through Mechanistic Eco-evolutionary Models

The latitudinal diversity gradient (LDG) is one of the most widely studied patterns in ecology, yet no consensus has been reached about its underlying causes. We argue that the reasons for this are the verbal nature of existing hypotheses, the failure to mechanistically link interacting ecological and evolutionary processes to the LDG, and the fact that empirical patterns are often consistent with multiple explanations. To address this issue, we synthesize current LDG hypotheses, uncovering their eco-evolutionary mechanisms, hidden assumptions, and commonalities. Furthermore, we propose mechanistic eco-evolutionary modeling and an inferential approach that makes use of geographic, phylogenetic, and trait-based patterns to assess the relative importance of different processes for generating the LDG.Additional co-authors: David Storch, Thorsten Wiegand, Allen H Hurlber

Quelques modèles probabilistes pour l'étude de l'hétérogénéité lors de la diversification de l'arbre du vivant

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.Dans cette thèse, je présente différentes approches pour quantifier et expliquer les variations dans le processus de diversification au sein de l’arbre du vivant. Toutes les approches présentées s’appuient sur des modèles probabilistes. Le premier chapitre s’intéresse à la forme générale des phylogénies, et propose une nouvelle mesure de la relation entre la richesse spécifique et la profondeur des clades au sein d’une phylogénie. Nous montrons que, dans les phylogénies empiriques, cette mesure s’écarte de la valeur attendue pour un processus de diversification homogène entre les lignées, possiblement à cause de la présence de variations du taux de diversification au sein des groupes étudiés. Dans le deuxième chapitre, je m’intéresse à une description à plus fine échelle de ces variations de taux, et présente une nouvelle méthode pour estimer des vitesses de diversification lignée-spécifiques dans les phylogénies empiriques. Contrairement aux méthodes existantes, qui considère que les taux de diversifications varient par des sauts rares et de grande amplitude, la nôtre propose une vision plus graduelle de l’évolution de la vitesse de diversification. Nous appliquons notre méthode à un jeu de données empirique et montrons que la variabilité du taux de diversification est aussi forte au sein des clades qu’entre les clades, ce qui s’accorde bien avec cette vision d’une évolution progressive des taux de diversification. Enfin, le troisième chapitre se concentre sur une des explications possibles à la présence de variabilité dans les vitesses d’accumulation d’espèces, en présentant un modèle individu-centré permettant d’étudier l’effet de différent types d’interactions écologiques sur le processus de diversification. Nous étudions les prédictions de ce modèle pour la diversité obtenue, ainsi que sur plusieurs mesures caractérisant la structure des réseaux d’interactions. Notre modèle génère des réseaux d’interactions écologiques réalistes, avec des réseaux plus modulaires et moins emboités dans les communautés antagonistes que dans les communautés mutualistes. La présence d’interactions antagonistes favorise la diversification de la communauté, du point de vue de la variabilité en traits comme de celui du nombre d’espèces, tandis que les interactions mutualistes entravent la création de diversité, du fait d’une forte sélection stabilisante

Fast and Accurate Estimation of Species-Specific Diversification Rates Using Data Augmentation

International audienceAbstract Diversification rates vary across species as a response to various factors, including environmental conditions and species-specific features. Phylogenetic models that allow accounting for and quantifying this heterogeneity in diversification rates have proven particularly useful for understanding clades diversification. Recently, we introduced the cladogenetic diversification rate shift model, which allows inferring multiple rate changes of small magnitude across lineages. Here, we present a new inference technique for this model that considerably reduces computation time through the use of data augmentation and provide an implementation of this method in Julia. In addition to drastically reducing computation time, this new inference approach provides a posterior distribution of the augmented data, that is the tree with extinct and unsampled lineages as well as associated diversification rates. In particular, this allows extracting the distribution through time of both the mean rate and the number of lineages. We assess the statistical performances of our approach using simulations and illustrate its application on the entire bird radiation.[Birth–death model; data augmentation; diversification; macroevolution.

An individual‐based model for the eco‐evolutionary emergence of bipartite interaction networks

International audienceHow ecological interaction networks emerge on evolutionary time scales remains unclear. Here we build an individual-based eco-evolutionary model for the emergence of mutualistic, antagonistic and neutral bipartite interaction networks. Exploring networks evolved under these scenarios, we find three main results. First, antagonistic interactions tend to foster species and trait diversity, while mutualistic interactions reduce diversity. Second, antagonistic interactors evolve higher specialisation, which results in networks that are often more modular than neutral ones; resource species in these networks often display phylogenetic conservatism in interaction partners. Third, mutualistic interactions lead to networks that are more nested than neutral ones, with low phylogenetic conservatism in interaction partners. These results tend to match overall empirical trends, demonstrating that structures of empirical networks that have most often been explained by ecological processes can result from an evolutionary emergence. Our model contributes to the ongoing effort of better integrating ecological interactions and macroevolution

InferenceFunctions

R code for the inference of the model parameter

A model with many small shifts for estimating species-specific diversification rates

International audienceUnderstanding how and why diversification rates vary through time, space, and across species groups is key to understanding the emergence of today's biodiversity. Phylogenetic approaches aimed at identifying variations in diversification rates during the evolutionary history of clades have focused on exceptional shifts subtending evolutionary radiations. While such shifts have undoubtedly affected the history of life (1),identifying smaller but more frequent changes is important as well. We develop ClaDS, a new Bayesian approach for estimating branch-specific diversification rates on a phylogeny, that relies on a model with changes in diversification rates at each speciation event. We show using Monte-Carlo simulations that the approach performs well at inferring both small and large changes in diversification. Applying our approach to bird phylogenies covering the entire avian radiation, we find that diversification rates are remarkably heterogeneous within evolutionary restricted species groups. Some groups such as Accipitridae (hawks and allies) cover almost the full range of speciation rates found across the entire bird radiation. As much as 76% of the variation in branch-specific rates across this radiation is due to intra-clade variation, suggesting that a large part of the variation in diversification rates is due to many small rather than few large shifts

Simulation_ntagged

R code for the simulation of the mode

Analyzing diversification dynamics using barcoding data: the case of an obligate mycorrhizal symbiont

International audienc