Statistical methods to identify mechanisms in studies of eco-evolutionary dynamics

Evolutionary and ecological dynamics can occur on similar timescales and thus influence each other. While it has been shown that the relative contribution of ecological and evolutionary change to population dynamics can vary, it still remains unknown what influences these differences. Here, we test whether prey populations with increased variation in their defense and competitiveness traits will have a stronger impact of evolution for predator growth rates. We controlled trait variation by pairing distinct clonal lineages of the green alga Chlamydomonas reinhardtii with known traits as prey with the rotifer Brachionus calyciforus as predator and compared those results with a mechanistic model matching the empirical system. We measured the impact of evolution (shift in prey clonal frequency) and ecology (shift in prey population density) for predator growth rate and its dependency on trait variation using an approach based on a two-way ANOVA. Our experimental results indicated that higher trait variation, i.e., a greater distance in trait space, increased the relative contribution of prey evolution to predator growth rate over 3-4 predator generations, which was also observed in model simulations spanning longer time periods. In our model, we also observed clone-specific results, where a more competitive undefended prey resulted in a higher evolutionary contribution, independent of the trait distance. Our results suggest that trait combinations and total prey trait variation combine to influence the contribution of evolution to predator population dynamics, and that trait variation can be used to identify and better predict the role of eco-evolutionary dynamics in predator-prey systems.

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Detection of eco-evolutionary dynamics in communities using Joint Species Distribution Models

Pantel,

Hermann

2024

Preprint

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Biodiversity at the metacommunity scale is typically influenced by a number of environmental, spatial, biotic, and stochastic factors. At the same time, these factors impact the evolution of individual species, as sites present different local selection pressures and connectivity can impact gene flow and genetic drift. Identifying the relative impacts of environmental, spatial, biotic, and other drivers on community composition across spatial and temporal scales has been greatly facilitated by joint species distribution models, but these models have yet to consider the impact of microevolution on community composition. We used Heirarchical Models of Species Communities (HMSC) to analyze simulated data of an populations and communities, including in a large evolving metacommunity model, to establish whether HMSC can sufficiently quantify the contribution of phenotypic evolution for metacommunity composition. The models successfully partitioned variance contributed by environmental, spatial, and evolving phenotypic drivers, and also estimated site- and year-specific covariance. We also applied the HMSC with trait evolution model to an existing dataset studying trait change and community dynamics in an experimental aquatic plant system. The study of eco-evolutionary dynamics may require data that reflects numerous complex, interacting processes and it is necessary to have flexible, generalized statistical models to analyze this data. JSDM models such as HMSC present one promising path for analysis of eco-evolutionary dynamics in multi-species communities.

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Statistical methods to identify mechanisms in studies of eco-evolutionary dynamics

Cited by 5 publications

References 102 publications

Species Richness Gradients

Species Richness Gradients

Range of trait variation in prey determines evolutionary contributions to predator growth rates

Detection of eco-evolutionary dynamics in communities using Joint Species Distribution Models

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