--- _id: '11640' abstract: - lang: eng text: Spatially explicit population genetic models have long been developed, yet have rarely been used to test hypotheses about the spatial distribution of genetic diversity or the genetic divergence between populations. Here, we use spatially explicit coalescence simulations to explore the properties of the island and the two-dimensional stepping stone models under a wide range of scenarios with spatio-temporal variation in deme size. We avoid the simulation of genetic data, using the fact that under the studied models, summary statistics of genetic diversity and divergence can be approximated from coalescence times. We perform the simulations using gridCoal, a flexible spatial wrapper for the software msprime (Kelleher et al., 2016, Theoretical Population Biology, 95, 13) developed herein. In gridCoal, deme sizes can change arbitrarily across space and time, as well as migration rates between individual demes. We identify different factors that can cause a deviation from theoretical expectations, such as the simulation time in comparison to the effective deme size and the spatio-temporal autocorrelation across the grid. Our results highlight that FST, a measure of the strength of population structure, principally depends on recent demography, which makes it robust to temporal variation in deme size. In contrast, the amount of genetic diversity is dependent on the distant past when Ne is large, therefore longer run times are needed to estimate Ne than FST. Finally, we illustrate the use of gridCoal on a real-world example, the range expansion of silver fir (Abies alba Mill.) since the last glacial maximum, using different degrees of spatio-temporal variation in deme size. acknowledgement: ES was supported by an IST studentship provided by IST Austria. BT was funded by the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie Independent Fellowship (704172, RACE). This project received further funding awarded to KC from the Swiss National Science Foundation (SNSF CRSK-3_190288) and the Swiss Federal Research Institute WSL. We thank Nick Barton for many invaluable discussions and his comments on the thesis chapter and this manuscript. We thank Peter Ralph and Jerome Kelleher for useful discussions and Bisschop Gertjan for comments on this manuscript. We thank Fortunat Joos for providing us with the raw data from the LPX-Bern model for silver fir, and Willy Tinner for helpful insights about the demographic history of silver fir. We also thank the editor Alana Alexander for useful comments and advice on the manuscript. Open access funding provided by Eidgenossische Technische Hochschule Zurich. article_processing_charge: Yes (via OA deal) article_type: original author: - first_name: Eniko full_name: Szep, Eniko id: 485BB5A4-F248-11E8-B48F-1D18A9856A87 last_name: Szep - first_name: Barbora full_name: Trubenova, Barbora id: 42302D54-F248-11E8-B48F-1D18A9856A87 last_name: Trubenova orcid: 0000-0002-6873-2967 - first_name: Katalin full_name: Csilléry, Katalin last_name: Csilléry citation: ama: Szep E, Trubenova B, Csilléry K. Using gridCoal to assess whether standard population genetic theory holds in the presence of spatio-temporal heterogeneity in population size. Molecular Ecology Resources. 2022;22(8):2941-2955. doi:10.1111/1755-0998.13676 apa: Szep, E., Trubenova, B., & Csilléry, K. (2022). Using gridCoal to assess whether standard population genetic theory holds in the presence of spatio-temporal heterogeneity in population size. Molecular Ecology Resources. Wiley. https://doi.org/10.1111/1755-0998.13676 chicago: Szep, Eniko, Barbora Trubenova, and Katalin Csilléry. “Using GridCoal to Assess Whether Standard Population Genetic Theory Holds in the Presence of Spatio-Temporal Heterogeneity in Population Size.” Molecular Ecology Resources. Wiley, 2022. https://doi.org/10.1111/1755-0998.13676. ieee: E. Szep, B. Trubenova, and K. Csilléry, “Using gridCoal to assess whether standard population genetic theory holds in the presence of spatio-temporal heterogeneity in population size,” Molecular Ecology Resources, vol. 22, no. 8. Wiley, pp. 2941–2955, 2022. ista: Szep E, Trubenova B, Csilléry K. 2022. Using gridCoal to assess whether standard population genetic theory holds in the presence of spatio-temporal heterogeneity in population size. Molecular Ecology Resources. 22(8), 2941–2955. mla: Szep, Eniko, et al. “Using GridCoal to Assess Whether Standard Population Genetic Theory Holds in the Presence of Spatio-Temporal Heterogeneity in Population Size.” Molecular Ecology Resources, vol. 22, no. 8, Wiley, 2022, pp. 2941–55, doi:10.1111/1755-0998.13676. short: E. Szep, B. Trubenova, K. Csilléry, Molecular Ecology Resources 22 (2022) 2941–2955. date_created: 2022-07-24T22:01:43Z date_published: 2022-11-01T00:00:00Z date_updated: 2023-08-03T12:11:01Z day: '01' ddc: - '570' department: - _id: NiBa doi: 10.1111/1755-0998.13676 ec_funded: 1 external_id: isi: - '000825873600001' file: - access_level: open_access checksum: 3102e203e77b884bffffdbe8e548da88 content_type: application/pdf creator: dernst date_created: 2023-02-02T08:11:23Z date_updated: 2023-02-02T08:11:23Z file_id: '12477' file_name: 2022_MolecularEcologyRes_Szep.pdf file_size: 6431779 relation: main_file success: 1 file_date_updated: 2023-02-02T08:11:23Z has_accepted_license: '1' intvolume: ' 22' isi: 1 issue: '8' language: - iso: eng license: https://creativecommons.org/licenses/by-nc/4.0/ month: '11' oa: 1 oa_version: Published Version page: 2941-2955 project: - _id: 25AEDD42-B435-11E9-9278-68D0E5697425 call_identifier: H2020 grant_number: '704172' name: Rate of Adaptation in Changing Environment publication: Molecular Ecology Resources publication_identifier: eissn: - 1755-0998 issn: - 1755-098X publication_status: published publisher: Wiley quality_controlled: '1' scopus_import: '1' status: public title: Using gridCoal to assess whether standard population genetic theory holds in the presence of spatio-temporal heterogeneity in population size tmp: image: /images/cc_by_nc.png legal_code_url: https://creativecommons.org/licenses/by-nc/4.0/legalcode name: Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) short: CC BY-NC (4.0) type: journal_article user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8 volume: 22 year: '2022' ...