Adding pattern and process to eco-evo theory and applications
Citation:
White, J., N. Schumaker, R. Chock, AND S. Watkins. Adding pattern and process to eco-evo theory and applications. PLOS ONE . Public Library of Science, San Francisco, CA, 18(3):e0282535, (2023). https://doi.org/10.1371/journal.pone.0282535
Impact/Purpose:
Gene flow is an inherently spatial process, but the theories describing gene flow have mostly been developed using non-spatial mathematical models. We added an extensive genetics model to HexSim, a spatially-explicit individual-based simulation model, in order to examine how this body of genetics theory holds up when spatial structure is acknowledged. This manuscript describes the results of our initial test of genetics theories used in four fields: landscape genetics, population genetics, conservation biology, and evolutionary ecology. Not surprisingly, we find that space matters, and that the limits of traditional non-spatial models are significant. We argue that the availability of advanced eco-evolutionary simulation models (e.g. HexSim) has set the stage for the next wave of new theoretical developments in these four focal disciplines.
Description:
Eco-evolutionary dynamics result when interacting biological forces simultaneously produce demographic and genetic population responses. Eco-evolutionary simulators traditionally manage complexity by minimizing the influence of spatial pattern on process. However, such simplifications can limit their utility in real-world applications. We present a novel simulation modeling approach for investigating eco-evolutionary dynamics, centered on the driving role of landscape pattern. Our spatially-explicit, individual-based mechanistic simulation approach overcomes existing methodological challenges, generates new insights, and paves the way for future investigations in four focal disciplines: Landscape Genetics, Population Genetics, Conservation Biology, and Evolutionary Ecology. We developed a simple individual-based model to illustrate how spatial structure drives eco-evo dynamics. By making minor changes to our landscape’s structure, we simulated continuous, isolated, and semi-connected landscapes, and simultaneously tested several classical assumptions of the focal disciplines. Our results exhibit expected patterns of isolation, drift, and extinction. By imposing landscape change on otherwise functionally-static eco-evolutionary models, we altered key emergent properties such as gene-flow and adaptive selection. We observed demo-genetic responses to these landscape manipulations, including changes in population size, probability of extinction, and allele frequencies. Our model also demonstrated how demo-genetic traits, including generation time and migration rate, can arise from a mechanistic model, rather than being specified a priori. We identify simplifying assumptions common to four focal disciplines, and illustrate how new insights might be developed in eco-evolutionary theory and applications by better linking biological processes to landscape patterns that we know influence them, but that have understandably been left out of many past modeling studies.
