Biodiversity accumulates hierarchically by means of ecological and evolutionary processes and feedbacks. Within ecological communities drift, dispersal, speciation, and selection operate simultaneously to shape patterns of biodiversity. Reconciling the relative importance of these is hindered by current models and inference methods, which tend to focus on a subset of processes and their resulting predictions. Here we introduce massive ecoevolutionary synthesis simulations (MESS), a unified mechanistic model of community assembly, rooted in classic island biogeography theory, which makes temporally explicit joint predictions across three biodiversity data axes: (i) species richness and abundances, (ii) population genetic diversities, and (iii) trait variation in a phylogenetic context. Using simulations we demonstrate that each data axis captures information at different timescales, and that integrating these axes enables discriminating among previously unidentifiable community assembly models. MESS is unique in generating predictions of community‐scale genetic diversity, and in characterizing joint patterns of genetic diversity, abundance, and trait values. MESS unlocks the full potential for investigation of biodiversity processes using multidimensional community data including a genetic component, such as might be produced by contemporary eDNA or metabarcoding studies. We combine MESS with supervised machine learning to fit the parameters of the model to real data and infer processes underlying how biodiversity accumulates, using communities of tropical trees, arthropods, and gastropods as case studies that span a range of data availability scenarios, and spatial and taxonomic scales.
MacArthur and Wilson's theory of island biogeography has been a foundation for obtaining testable predictions from models of community assembly and for developing models that integrate across scales and disciplines. Historically, however, these developments have focused on integration across ecological and macroevolutionary scales and on predicting patterns of species richness, abundance distributions, trait data and/or phylogenies. The distribution of genetic variation across species within a community is an emerging pattern that contains signatures of past population histories, which might provide an historical lens for the study of contemporary communities. As intraspecific genetic diversity data become increasingly available at the scale of entire communities, there is an opportunity to integrate microevolutionary processes into our models, moving towards development of a genetic theory of island biogeography.
We aim to promote the development of process‐based biodiversity models that predict community genetic diversity patterns together with other community‐scale patterns. To this end, we review models of ecological, microevolutionary and macroevolutionary processes that are best suited to the creation of unified models, and the patterns that these predict. We then discuss ongoing and potential future efforts to unify models operating at different organizational levels, with the goal of predicting multidimensional community‐scale data including a genetic component.
Our review of the literature shows that despite recent efforts, further methodological developments are needed, not only to incorporate the genetic component into existing island biogeography models, but also to unify processes across scales of biological organization. To catalyse these developments, we outline two potential ways forward, adopting either a top‐down or a bottom‐up approach. Finally, we highlight key ecological and evolutionary questions that might be addressed by unified models including a genetic component and establish hypotheses about how processes across scales might impact patterns of community genetic diversity.
- Award ID(s):
- 1927510
- NSF-PAR ID:
- 10493342
- Author(s) / Creator(s):
- ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; more »
- Publisher / Repository:
- Wiley
- Date Published:
- Journal Name:
- Global Ecology and Biogeography
- Volume:
- 32
- Issue:
- 1
- ISSN:
- 1466-822X
- Page Range / eLocation ID:
- 4 to 23
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Location Ten volcanic archipelagos.
Time period From 23 Ma to the present.
Major taxa studied Endemic land snails.
Methods Initially, we assembled geological island characteristics of area, isolation and ontogeny for all studied islands. We then characterized island‐scale biotic variables, including the species diversity and functional diversity of snail communities. From these data, we assessed relationships between island and snail community variables as predicted by the GDM, focusing initially on the islands of the Galápagos archipelago and thereafter with a broader analysis of 10 archipelagoes.
Results As in other studies of island assemblages, in Galápagos we find a hump‐shaped curve of species richness, with depauperate snail faunas on early‐ontogeny islands, increasing species richness on mid‐ontogeny islands and low species richness on islands in late ontogeny. We find exceptionally low functional diversity on early‐ontogeny islands that increases through mid‐ontogeny, whereas late‐ontogeny islands exhibit a range of functional diversity. The analysis including all 10 archipelagos indicates a major role of archipelago‐specific factors. In both sets of analyses, functional diversity is exceptionally low on early‐ontogeny islands, and island ontogeny is a significant predictor of morphology.
Main conclusions Consistent patterns of functional diversity across island ontogeny on all examined archipelagos indicate a common role for habitat filtering, ecological opportunity and competition in a diversity of systems, leading to predictable changes in functional diversity and average morphology through island ontogeny, whereas patterns of species richness appear subject to archipelago‐specific factors.
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Time period Present day, future.
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1111/geb.13604
