Population Genetics Meets Ecology: A Guide to Individual‐Based Simulations in Continuous Landscapes
ABSTRACT Individual‐based simulation has become an increasingly crucial tool for many fields of population biology. However, continuous geography is important to many applications, and implementing realistic and stable simulations in continuous space presents a variety of difficulties, from modeling...
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| Format: | Article |
| Language: | English |
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Wiley
2025-04-01
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| Series: | Ecology and Evolution |
| Online Access: | https://doi.org/10.1002/ece3.71098 |
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| author | Elizabeth T. Chevy Jiseon Min Victoria Caudill Samuel E. Champer Benjamin C. Haller Clara T. Rehmann Chris C. R. Smith Silas Tittes Philipp W. Messer Andrew D. Kern Sohini Ramachandran Peter L. Ralph |
| author_facet | Elizabeth T. Chevy Jiseon Min Victoria Caudill Samuel E. Champer Benjamin C. Haller Clara T. Rehmann Chris C. R. Smith Silas Tittes Philipp W. Messer Andrew D. Kern Sohini Ramachandran Peter L. Ralph |
| author_sort | Elizabeth T. Chevy |
| collection | DOAJ |
| description | ABSTRACT Individual‐based simulation has become an increasingly crucial tool for many fields of population biology. However, continuous geography is important to many applications, and implementing realistic and stable simulations in continuous space presents a variety of difficulties, from modeling choices to computational efficiency. This paper aims to be a practical guide to spatial simulation, helping researchers to implement individual‐based simulations and avoid common pitfalls. To do this, we delve into mechanisms of mating, reproduction, density‐dependent feedback, and dispersal, all of which may vary across the landscape, discuss how these affect population dynamics, and describe how to parameterize simulations in convenient ways (for instance, to achieve a desired population density). We also demonstrate how to implement these models using the current version of the individual‐based simulator, SLiM. We additionally discuss natural selection—in particular, how genetic variation can affect demographic processes. Finally, we provide four short vignettes: simulations of pikas that shift their range up a mountain as temperatures rise; mosquitoes that live in rivers as juveniles and experience seasonally changing habitat; cane toads that expand across Australia, reaching 120 million individuals; and monarch butterflies whose populations are regulated by an explicitly modeled resource (milkweed). |
| format | Article |
| id | doaj-art-d62c688455844bd3af2b9dcfacf71f27 |
| institution | Kabale University |
| issn | 2045-7758 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | Wiley |
| record_format | Article |
| series | Ecology and Evolution |
| spelling | doaj-art-d62c688455844bd3af2b9dcfacf71f272025-08-20T03:26:53ZengWileyEcology and Evolution2045-77582025-04-01154n/an/a10.1002/ece3.71098Population Genetics Meets Ecology: A Guide to Individual‐Based Simulations in Continuous LandscapesElizabeth T. Chevy0Jiseon Min1Victoria Caudill2Samuel E. Champer3Benjamin C. Haller4Clara T. Rehmann5Chris C. R. Smith6Silas Tittes7Philipp W. Messer8Andrew D. Kern9Sohini Ramachandran10Peter L. Ralph11Center for Computational Molecular Biology Brown University Providence Rhode Island USAInstitute of Ecology and Evolution University of Oregon Eugene Oregon USAInstitute of Ecology and Evolution University of Oregon Eugene Oregon USADepartment of Computational Biology Cornell University Ithaca New York USADepartment of Computational Biology Cornell University Ithaca New York USAInstitute of Ecology and Evolution University of Oregon Eugene Oregon USAInstitute of Ecology and Evolution University of Oregon Eugene Oregon USAInstitute of Ecology and Evolution University of Oregon Eugene Oregon USADepartment of Computational Biology Cornell University Ithaca New York USAInstitute of Ecology and Evolution University of Oregon Eugene Oregon USACenter for Computational Molecular Biology Brown University Providence Rhode Island USAInstitute of Ecology and Evolution University of Oregon Eugene Oregon USAABSTRACT Individual‐based simulation has become an increasingly crucial tool for many fields of population biology. However, continuous geography is important to many applications, and implementing realistic and stable simulations in continuous space presents a variety of difficulties, from modeling choices to computational efficiency. This paper aims to be a practical guide to spatial simulation, helping researchers to implement individual‐based simulations and avoid common pitfalls. To do this, we delve into mechanisms of mating, reproduction, density‐dependent feedback, and dispersal, all of which may vary across the landscape, discuss how these affect population dynamics, and describe how to parameterize simulations in convenient ways (for instance, to achieve a desired population density). We also demonstrate how to implement these models using the current version of the individual‐based simulator, SLiM. We additionally discuss natural selection—in particular, how genetic variation can affect demographic processes. Finally, we provide four short vignettes: simulations of pikas that shift their range up a mountain as temperatures rise; mosquitoes that live in rivers as juveniles and experience seasonally changing habitat; cane toads that expand across Australia, reaching 120 million individuals; and monarch butterflies whose populations are regulated by an explicitly modeled resource (milkweed).https://doi.org/10.1002/ece3.71098 |
| spellingShingle | Elizabeth T. Chevy Jiseon Min Victoria Caudill Samuel E. Champer Benjamin C. Haller Clara T. Rehmann Chris C. R. Smith Silas Tittes Philipp W. Messer Andrew D. Kern Sohini Ramachandran Peter L. Ralph Population Genetics Meets Ecology: A Guide to Individual‐Based Simulations in Continuous Landscapes Ecology and Evolution |
| title | Population Genetics Meets Ecology: A Guide to Individual‐Based Simulations in Continuous Landscapes |
| title_full | Population Genetics Meets Ecology: A Guide to Individual‐Based Simulations in Continuous Landscapes |
| title_fullStr | Population Genetics Meets Ecology: A Guide to Individual‐Based Simulations in Continuous Landscapes |
| title_full_unstemmed | Population Genetics Meets Ecology: A Guide to Individual‐Based Simulations in Continuous Landscapes |
| title_short | Population Genetics Meets Ecology: A Guide to Individual‐Based Simulations in Continuous Landscapes |
| title_sort | population genetics meets ecology a guide to individual based simulations in continuous landscapes |
| url | https://doi.org/10.1002/ece3.71098 |
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