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Dryad

Data for: Co-evolution of dormancy and dispersal in spatially autocorrelated landscapes

Cite this dataset

Cenzer, Meredith (2022). Data for: Co-evolution of dormancy and dispersal in spatially autocorrelated landscapes [Dataset]. Dryad. https://doi.org/10.5061/dryad.dbrv15f40

Abstract

The evolution of dispersal can be driven by spatial processes, such as landscape structure, and temporal processes, such as disturbance. Dormancy, or dispersal in time, is generally thought to evolve in response to temporal processes. In spite of broad empirical and theoretical evidence of trade-offs between dispersal and dormancy, we lack evidence that spatial structure can drive the evolution of dormancy. Here, we develop a simulation-based model of the joint evolution of dispersal and dormancy in spatially heterogeneous landscapes. We show that dormancy and dispersal are each favored under different landscape conditions, but not simultaneously under any of the conditions we tested. We further show that, when dispersal distances are short, dormancy can evolve directly in response to landscape structure. In this case, selection is primarily driven by benefits associated with avoiding kin competition. Our results are similar in both highly simplified and realistically complex landscapes.

Methods

These data were collected using a spatially explicit individual-based simulation. The full dataset was generated using code in the ./src.zip folder and summarized using code in the ./code to summarize full datasets.zip folder. The summarized datasets are in the ./model_output.zip folder. The figures in the manuscript can be generated using code in the ./figure code.zip folder. Descriptions of all files are in the README.

Usage notes

To access these data, you will need to use R or RStudio.

Funding

Natural Sciences and Engineering Research Council of Canada, Award: 05103-2018