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Demographic responses underlying eco-evolutionary dynamics as revealed with inverse modelling.

ABSTRACT: Changes in population dynamics due to interacting evolutionary and ecological processes are the direct result of responses in vital rates, that is stage-specific growth, survival and fecundity. Quantifying through which vital rates population fitness is affected, instead of focusing on population trends only, can give a more mechanistic understanding of eco-evolutionary dynamics. The aim of this study was to estimate the underlying demographic rates of aphid (Myzus persicae) populations. We analysed unpublished stage-structure population dynamics data of a field experiment with caged and uncaged populations in which rapid evolutionary dynamics were observed, as well as unpublished results from an individual life table experiment performed in a glasshouse. Using data on changes in population abundance and stage distributions over time, we estimated transition matrices with inverse modelling techniques, in a Bayesian framework. The model used to fit across all experimental treatments included density as well as clone-specific caging effects. We additionally used individual life table data to inform the model on survival, growth and reproduction. Results suggest that clones varied considerably in vital rates, and imply trade-offs between reproduction and survival. Responses to densities also varied between clones. Negative density dependence was found in growth and reproduction, and the presence of predators and competitors further decreased these two vital rates, while survival estimates increased. Under uncaged conditions, population growth rates of the evolving populations were increased compared to the expectation based on the pure clones. Our inverse modelling approach revealed how much vital rates contributed to the eco-evolutionary dynamics. The decomposition analysis showed that variation in population growth rates in the evolving populations was to a large extent shaped by plant size. Yet, it also revealed an impact of evolutionary changes in clonal composition. Finally, we discuss that inverse modelling is a complex problem, as multiple combinations of individual rates can result in the same dynamics. We discuss assumptions and limitations, as well as opportunities, of this approach.

SUBMITTER: Bruijning M

PROVIDER: S-EPMC6850177 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature

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Demographic responses underlying eco-evolutionary dynamics as revealed with inverse modelling.

Bruijning Marjolein M Jongejans Eelke E Turcotte Martin M MM

The Journal of animal ecology 20190318 5

Changes in population dynamics due to interacting evolutionary and ecological processes are the direct result of responses in vital rates, that is stage-specific growth, survival and fecundity. Quantifying through which vital rates population fitness is affected, instead of focusing on population trends only, can give a more mechanistic understanding of eco-evolutionary dynamics. The aim of this study was to estimate the underlying demographic rates of aphid (Myzus persicae) populations. We anal ...[more]

PMID: 30801697

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Project description:Heritable trait variation is a central and necessary ingredient of evolution. Trait variation also directly affects ecological processes, generating a clear link between evolutionary and ecological dynamics. Despite the changes in variation that occur through selection, drift, mutation, and recombination, current eco-evolutionary models usually fail to track how variation changes through time. Moreover, eco-evolutionary models assume fitness functions for each trait and each ecological context, which often do not have empirical validation. We introduce a new type of model, Gillespie eco-evolutionary models (GEMs), that resolves these concerns by tracking distributions of traits through time as eco-evolutionary dynamics progress. This is done by allowing change to be driven by the direct fitness consequences of model parameters within the context of the underlying ecological model, without having to assume a particular fitness function. GEMs work by adding a trait distribution component to the standard Gillespie algorithm - an approach that models stochastic systems in nature that are typically approximated through ordinary differential equations. We illustrate GEMs with the Rosenzweig-MacArthur consumer-resource model. We show not only how heritable trait variation fuels trait evolution and influences eco-evolutionary dynamics, but also how the erosion of variation through time may hinder eco-evolutionary dynamics in the long run. GEMs can be developed for any parameter in any ordinary differential equation model and, furthermore, can enable modeling of multiple interacting traits at the same time. We expect GEMs will open the door to a new direction in eco-evolutionary and evolutionary modeling by removing long-standing modeling barriers, simplifying the link between traits, fitness, and dynamics, and expanding eco-evolutionary treatment of a greater diversity of ecological interactions. These factors make GEMs much more than a modeling advance, but an important conceptual advance that bridges ecology and evolution through the central concept of heritable trait variation.

Dataset Information

Demographic responses underlying eco-evolutionary dynamics as revealed with inverse modelling.

Publications

Demographic responses underlying eco-evolutionary dynamics as revealed with inverse modelling.

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