Spatial population genetics is a field that studies how different evolutionary processes shape geographical patterns of genetic variation. This field is currently hampered by the lack of a deep understanding of the impact of different evolutionary processes shaping the genetic diversity observed across a continuous space (Bradburd and Ralph 2019). Luckily, the recent development of slendr (Petr et al. 2023), which uses the simulator SLiM (Haller and Messer 2023), provides a powerful tool to perform simulations to analyze the impact of different evolutionary parameters on spatial patterns of genetic variation. Here, Ianni-Ravn, Petr, and Racimo 2023 present a series of well-designed simulations to study how three evolutionary factors (dispersal distance, competition distance, and mate choice distance) shape the geographical structure of genealogies.

The authors model the dispersal distance between parents and their offspring using five different distributions. Then, the authors perform simulations and they contrast the correspondence between the distribution of observed parent-offspring distances (called DD in the paper) and the distribution used in the simulations (called DF). The authors observe a reasonable correspondence between DF and DD. The authors then show that the competition distance, which decreases the fitness of individuals due to competition for resources if the individuals are close to each other, has small effects on the differences between DD and DF. In contrast, the mate choice distance (which specifies how far away can a parent go to choose a mate) causes discrepancies between DD and DF. When the mate choice distance is small, the individuals tend to cluster close to each other. Overall, these results show that the observed distances between parents and offspring are dependent on the three parameters inspected (dispersal distance, competition distance, and mate choice distance) and make the case that further ecological knowledge of each of these parameters is important to determine the processes driving the dispersal of individuals across geographical space. Based on these results, the authors argue that an “effective dispersal distance” parameter, which takes into account the impact of mate choice distance and dispersal distance, is more prone to be inferred from genetic data.

The authors also assess our ability to estimate the dispersal distance using genealogical data in a scenario where the mating distance has small effects on the dispersal distance. Interestingly, the authors show that accurate estimates of the dispersal distance can be obtained when using information from all the parents and offspring going from the present back to the coalescence of all the individuals to the most recent common ancestor. On the other hand, the estimates of the dispersal distance are underestimated when less information from the parent-offspring relationships is used to estimate the dispersal distance.

This paper shows the importance of considering mating patterns and the competition for resources when analyzing the dispersal of individuals. The analysis performed by the authors backs up this claim with carefully designed simulations. I recommend this preprint because it makes a strong case for the consideration of ecological factors when analyzing the structure of genealogies and the dispersal of individuals. Hopefully more studies in the future will continue to use simulations and to develop analytical theory to understand the importance of various ecological processes driving spatial genetic variation changes.

References

Bradburd, Gideon S., and Peter L. Ralph. 2019. “Spatial Population Genetics: It’s About Time.” Annual Review of Ecology, Evolution, and Systematics 50 (1): 427–49. https://doi.org/10.1146/annurev-ecolsys-110316-022659.

Haller, Benjamin C., and Philipp W. Messer. 2023. “SLiM 4: Multispecies Eco-Evolutionary Modeling.” The American Naturalist 201 (5): E127–39. https://doi.org/10.1086/723601.

Ianni-Ravn, Mariadaria K., Martin Petr, and Fernando Racimo. 2023. “Exploring the Effects of Ecological Parameters on the Spatial Structure of Genealogies.” bioRxiv, ver. 3 peer-reviewed and recommended by Peer Community in Evolutionary Biology. https://doi.org/10.1101/2023.03.27.534388.

Petr, Martin, Benjamin C. Haller, Peter L. Ralph, and Fernando Racimo. 2023. “Slendr: A Framework for Spatio-Temporal Population Genomic Simulations on Geographic Landscapes.” Peer Community Journal 3 (e121). https://doi.org/10.24072/pcjournal.354.