%0 Journal Article %1 champer2024resource %A Champer, Samuel E. %A Chae, Bryan %A Haller, Benjamin C. %A Champer, Jackson %A Messer, Philipp W. %D 2024 %I Cold Spring Harbor Laboratory %J bioRxiv %K SLiM simulations spatial_demography spatial_models %R 10.1101/2024.01.13.575512 %T Resource-explicit interactions in spatial population models %U https://www.biorxiv.org/content/early/2024/01/15/2024.01.13.575512 %X Continuous-space population models can yield significantly different results from their panmictic counterparts when assessing evolutionary, ecological, or population-genetic processes. However, the computational burden of spatial models is typically much greater than that of panmictic models due to the overhead of determining which individuals interact with one another and how strongly they interact. Though these calculations are necessary to model local competition that regulates the population density, they can lead to prohibitively long runtimes. Here, we present a novel modeling method in which the resources available to a population are abstractly represented as an additional layer of the simulation. Instead of interacting directly with one another, individuals interact indirectly via this resource layer. We find that this method closely matches other spatial models, yet can dramatically increase the speed of the model, allowing the simulation of much larger populations. Additionally, models structured in this manner exhibit other desirable characteristics, including more realistic spatial dynamics near the edge of the simulated area, and an efficient route for modeling more complex heterogeneous landscapes.Competing Interest StatementThe authors have declared no competing interest.

@article{champer2024resource, abstract = {Continuous-space population models can yield significantly different results from their panmictic counterparts when assessing evolutionary, ecological, or population-genetic processes. However, the computational burden of spatial models is typically much greater than that of panmictic models due to the overhead of determining which individuals interact with one another and how strongly they interact. Though these calculations are necessary to model local competition that regulates the population density, they can lead to prohibitively long runtimes. Here, we present a novel modeling method in which the resources available to a population are abstractly represented as an additional layer of the simulation. Instead of interacting directly with one another, individuals interact indirectly via this resource layer. We find that this method closely matches other spatial models, yet can dramatically increase the speed of the model, allowing the simulation of much larger populations. Additionally, models structured in this manner exhibit other desirable characteristics, including more realistic spatial dynamics near the edge of the simulated area, and an efficient route for modeling more complex heterogeneous landscapes.Competing Interest StatementThe authors have declared no competing interest.}, added-at = {2024-01-21T19:30:44.000+0100}, author = {Champer, Samuel E. and Chae, Bryan and Haller, Benjamin C. and Champer, Jackson and Messer, Philipp W.}, biburl = {https://www.bibsonomy.org/bibtex/292ec4b33de41e73654004df4c1491b36/peter.ralph}, doi = {10.1101/2024.01.13.575512}, elocation-id = {2024.01.13.575512}, eprint = {https://www.biorxiv.org/content/early/2024/01/15/2024.01.13.575512.full.pdf}, interhash = {a63e01a0947120ce61c8d0af15e368bd}, intrahash = {92ec4b33de41e73654004df4c1491b36}, journal = {bioRxiv}, keywords = {SLiM simulations spatial_demography spatial_models}, publisher = {Cold Spring Harbor Laboratory}, timestamp = {2024-01-21T19:30:44.000+0100}, title = {Resource-explicit interactions in spatial population models}, url = {https://www.biorxiv.org/content/early/2024/01/15/2024.01.13.575512}, year = 2024 }