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      Interdependent Phenotypic and Biogeographic Evolution Driven by Biotic Interactions

      1 , 2 , 1 , 3
      Systematic Biology
      Oxford University Press (OUP)

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          Abstract

          Biotic interactions are hypothesized to be one of the main processes shaping trait and biogeographic evolution during lineage diversification. Theoretical and empirical evidence suggests that species with similar ecological requirements either spatially exclude each other, by preventing the colonization of competitors or by driving coexisting populations to extinction, or show niche divergence when in sympatry. However, the extent and generality of the effect of interspecific competition in trait and biogeographic evolution has been limited by a dearth of appropriate process-generating models to directly test the effect of biotic interactions. Here, we formulate a phylogenetic parametric model that allows interdependence between trait and biogeographic evolution, thus enabling a direct test of central hypotheses on how biotic interactions shape these evolutionary processes. We adopt a Bayesian data augmentation approach to estimate the joint posterior distribution of trait histories, range histories, and coevolutionary process parameters under this analytically intractable model. Through simulations, we show that our model is capable of distinguishing alternative scenarios of biotic interactions. We apply our model to the radiation of Darwin’s finches—a classic example of adaptive divergence—and find limited support for in situ trait divergence in beak size, but stronger evidence for convergence in traits such as beak shape and tarsus length and for competitive exclusion throughout their evolutionary history. These findings are more consistent with presympatric, rather than postsympatric, niche divergence. Our modeling framework opens new possibilities for testing more complex hypotheses about the processes underlying lineage diversification. More generally, it provides a robust probabilistic methodology to model correlated evolution of continuous and discrete characters. [Bayesian; biotic interactions; competition; data augmentation; historical biogeography; trait evolution.]

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          Most cited references66

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          Community diversity: relative roles of local and regional processes.

          The species richness (diversity) of local plant and animal assemblages-biological communities-balances regional processes of species formation and geographic dispersal, which add species to communities, against processes of predation, competitive exclusion, adaptation, and stochastic variation, which may promote local extinction. During the past three decades, ecologists have sought to explain differences in local diversity by the influence of the physical environment on local interactions among species, interactions that are generally believed to limit the number of coexisting species. But diversity of the biological community often fails to converge under similar physical conditions, and local diversity bears a demonstrable dependence upon regional diversity. These observations suggest that regional and historical processes, as well as unique events and circumstances, profoundly influence local community structure. Ecologists must broaden their concepts of community processes and incorporate data from systematics, biogeography, and paleontology into analyses of ecological patterns and tests of community theory.
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            Detecting Correlated Evolution on Phylogenies: A General Method for the Comparative Analysis of Discrete Characters

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              Model selection in historical biogeography reveals that founder-event speciation is a crucial process in Island Clades.

              Founder-event speciation, where a rare jump dispersal event founds a new genetically isolated lineage, has long been considered crucial by many historical biogeographers, but its importance is disputed within the vicariance school. Probabilistic modeling of geographic range evolution creates the potential to test different biogeographical models against data using standard statistical model choice procedures, as long as multiple models are available. I re-implement the Dispersal-Extinction-Cladogenesis (DEC) model of LAGRANGE in the R package BioGeoBEARS, and modify it to create a new model, DEC + J, which adds founder-event speciation, the importance of which is governed by a new free parameter, [Formula: see text]. The identifiability of DEC and DEC + J is tested on data sets simulated under a wide range of macroevolutionary models where geography evolves jointly with lineage birth/death events. The results confirm that DEC and DEC + J are identifiable even though these models ignore the fact that molecular phylogenies are missing many cladogenesis and extinction events. The simulations also indicate that DEC will have substantially increased errors in ancestral range estimation and parameter inference when the true model includes + J. DEC and DEC + J are compared on 13 empirical data sets drawn from studies of island clades. Likelihood-ratio tests indicate that all clades reject DEC, and AICc model weights show large to overwhelming support for DEC + J, for the first time verifying the importance of founder-event speciation in island clades via statistical model choice. Under DEC + J, ancestral nodes are usually estimated to have ranges occupying only one island, rather than the widespread ancestors often favored by DEC. These results indicate that the assumptions of historical biogeography models can have large impacts on inference and require testing and comparison with statistical methods. © The Author(s) 2014. Published by Oxford University Press, on behalf of the Society of Systematic Biologists. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
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                Author and article information

                Journal
                Systematic Biology
                Oxford University Press (OUP)
                1063-5157
                1076-836X
                July 2020
                July 01 2020
                December 20 2019
                July 2020
                July 01 2020
                December 20 2019
                : 69
                : 4
                : 739-755
                Affiliations
                [1 ]Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT 06511, USA
                [2 ]Département de Biologie, Institut de Biologie de l’ENS (IBENS), École Normale Supérieure, CNRS, INSERM, Université PSL, 75005 Paris, France
                [3 ]Department of Biology, Washington University in St. Louis, St. Louis, MO 63130, USA
                Article
                10.1093/sysbio/syz082
                31860094
                895f0b95-da43-4314-b079-13250b0b63d1
                © 2019

                https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model

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