{"id":45368991,"url":"https://github.com/cjabradshaw/demo-genetic","last_synced_at":"2026-02-21T15:20:04.204Z","repository":{"id":231985949,"uuid":"783183127","full_name":"cjabradshaw/demo-genetic","owner":"cjabradshaw","description":"Code for SLiM 4.0 demo-genetic models examining the population effects of genetic 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unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["conservation","demography","density-feedback","genetic-rescue","genetics","inbreeding-depression","marsupials","population-genetics","slim"],"created_at":"2026-02-21T15:20:03.606Z","updated_at":"2026-02-21T15:20:04.199Z","avatar_url":"https://github.com/cjabradshaw.png","language":"R","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Demo-genetic models to simulate genetic rescue\n\u003ca href=\"https://zenodo.org/doi/10.5281/zenodo.10939288\"\u003e\u003cimg src=\"https://zenodo.org/badge/DOI/10.5281/zenodo.10939288.svg\" alt=\"DOI\"\u003e\u003c/a\u003e\u003cbr\u003e\n\u003cimg align=\"right\" src=\"www/GRiconTransp.png\" alt=\"genetic rescue icon\" width=\"180\" style=\"margin-top: 20px\"\u003e\nCode for \u003ca href=\"http://www.messerlab.org/slim\"\u003e\u003cem\u003eSLiM\u003c/em\u003e\u003c/a\u003e 4.0 demo-genetic models examining the population effects of genetic rescue \u003cbr\u003e\n\u003cbr\u003e\n\u003cem\u003eSLiM\u003c/em\u003e ('\u003cstrong\u003eS\u003c/strong\u003eelection on \u003cstrong\u003eLi\u003c/strong\u003enked \u003cstrong\u003eM\u003c/strong\u003eutations') is an \u003ca href=\"http://doi.org/10.1086/723601\"\u003eindividual-based, forward-in-time simulator\u003c/a\u003e designed for studies of evolutionary genetics. \u003cbr\u003e\n\u003cbr\u003e\n\u003ca href=mailto:julian.beaman@flinders.edu.au\u003eJulian Beaman\u003c/a\u003e \u0026 \u003ca href=mailto:corey.bradshaw@flinders.edu.au\u003eCorey Bradshaw\u003c/a\u003e \u003cbr\u003e\n\u003ca href=\"https://globalecologyflinders.com/\"\u003eGlobal Ecology\u003c/a\u003e | \u003cem\u003ePartuyarta Ngadluku Wardli Kuu\u003c/em\u003e \u003cbr\u003e\nFlinders University \u003cbr\u003e\nApril 2024 \u003cbr\u003e\n\u003cbr\u003e\nAccompanies paper:\u003cbr\u003e\n\u003cbr\u003e\n\u003ca href=\"https://www.flinders.edu.au/people/julian.beaman\"\u003eBeaman, JE\u003c/a\u003e, \u003ca href=\"https://molecularecology.flinders.edu.au/molecular-ecology-lab/people/postdoctoral-fellows/dr-katie-gates-2/\"\u003eK Gates\u003c/a\u003e, \u003ca href=\"https://www.flinders.edu.au/people/frederik.saltre\"\u003eF Saltré\u003c/a\u003e, \u003ca href=\"https://www.sydney.edu.au/science/about/our-people/academic-staff/carolyn-hogg.html\"\u003eCJ Hogg\u003c/a\u003e, \u003ca href=\"https://www.sydney.edu.au/science/about/our-people/academic-staff/kathy-belov.html\"\u003eK Belov\u003c/a\u003e, \u003ca href=\"https://scholar.google.com/citations?user=2xF8xocAAAAJ\u0026hl=en\"\u003eK Ashman\u003c/a\u003e, \u003ca href=\"https://www.flinders.edu.au/people/karen.burkedasilva\"\u003eK Burke da Silva\u003c/a\u003e, \u003ca href=\"https://www.flinders.edu.au/people/luciano.beheregaray\"\u003eLB Beheregaray\u003c/a\u003e, \u003ca href=\"https://www.flinders.edu.au/people/corey.bradshaw\"\u003eCJA Bradshaw\u003c/a\u003e. 2025. \u003ca href=\"http://doi.org/10.1111/eva.70092\"\u003eA guide for developing demo-genetic models to simulate genetic rescue\u003c/a\u003e. \u003cem\u003eEvolutionary Applications\u003c/em\u003e 18:e 70092. doi:10.1111/eva.70092\n\u003cbr\u003e\n\u003cbr\u003e\nAlso available as a pre-print:\u003cbr\u003e\n\u003cbr\u003e\nBeaman, JE, K Gates, F Saltré, CJ Hogg, K Belov, K Ashman, K Burke da Silva, LB Beheregaray, CJA Bradshaw. 2024. \u003ca href=\"http://doi.org/10.21203/rs.3.rs-4244443/v1\"\u003eDeveloping demo-genetic models to simulate genetic rescue\u003c/a\u003e. \u003cem\u003eResearch Square\u003c/em\u003e doi:10.21203/rs.3.rs-4244443/v1\n\u003cbr\u003e\n\n### Abstract\nGenetic rescue is a conservation management strategy that reduces the negative effects of genetic drift and inbreeding in small and isolated populations. However, such populations might already be vulnerable to random fluctuations in growth rates (demographic stochasticity). Therefore, the success of genetic rescue depends not only on the genetic composition of the source and target populations but also on the emergent outcome of interacting demographic processes and other stochastic events. Developing predictive models that account for feedback between demographic and genetic processes (‘demo-genetic feedback’) is therefore necessary to guide the implementation of genetic rescue to minimise the risk of extinction of threatened populations. Here, we explain how the mutual reinforcement of genetic drift, inbreeding, and demographic stochasticity increases extinction risk in small populations. We then describe how these processes can be modelled by parameterising underlying mechanisms, including deleterious mutations with partial dominance and demographic rates with variances that increase as abundance declines. We combine our suggestions of model parameterisation with a comparison of the relevant capability and flexibility of five open-source programs designed for building genetically explicit, individual-based simulations. Using one of the programs, we provide a heuristic model to demonstrate that simulated genetic rescue can delay extinction of small virtual populations that would otherwise be exposed to greater extinction risk due to demo-genetic feedback. We then use a case study of threatened Australian marsupials to demonstrate that published genetic data can be used in one or all stages of model development and application, including parameterisation, calibration, and validation. We highlight that genetic rescue can be simulated with either virtual or empirical sequence variation (or a hybrid approach) and suggest that model-based decision-making should be informed by ranking the sensitivity of predicted probability/time to extinction to variation in model parameters (e.g., translocation size, frequency, source populations) among different genetic-rescue scenarios.\n\n\u003cimg align=\"right\" src=\"www/GRdecisionTree.jpg\" alt=\"genetic rescue decision tree\" style=\"margin-top: 20px\"\u003e\n\n##### \u003cstrong\u003eA decision tree for model-based guidance of genetic rescue.\u003c/strong\u003e\n\u003cbr\u003e\n\n## \u003ca href=\"https://github.com/cjabradshaw/demo-genetic/tree/main/scripts\"\u003eScripts\u003c/a\u003e\n- \u003ccode\u003edemographicAlleemodel.txt\u003c/code\u003e: \u003cem\u003eSLiM\u003c/em\u003e 4.0 code to generate a model of demographic Allee effects that included only the influence of demographic stochasticity on population growth.\n- \u003ccode\u003egenetic-Allee_model.txt\u003c/code\u003e: \u003cem\u003eSLiM\u003c/em\u003e 4.0 code to generate a model of genetic Allee effects that only included partially recessive deleterious mutations that accumulate in the population prior to an abrupt crash in abundance\n- \u003ccode\u003edemo-genetic-Allee_model.txt\u003c/code\u003e: \u003cem\u003eSLiM\u003c/em\u003e 4.0 code to generate a model of demo-genetic Allee effects that includes both demographic stochasticity as described in \u003ccode\u003edemographicAlleemodel.txt\u003c/code\u003e and partially recessive deleterious mutations as described in \u003ccode\u003egenetic-Allee_model.txt\u003c/code\u003e.\n- \u003ccode\u003erescue-scenario-4_model.txt\u003c/code\u003e: \u003cem\u003eSLiM\u003c/em\u003e 4.0 code to generate genetic rescue (scenario 4: 100 individuals moved 3 times at 250, 255, and 260 years after demographic decline) scenario.\n- \u003ccode\u003eR code Figure 3.R\u003c/code\u003e: R code to generate data for Figure 3.\n\n\u003cbr\u003e\n\u003cbr\u003e\n\u003cp\u003e\u003ca href=\"https://www.flinders.edu.au\"\u003e\u003cimg align=\"bottom-left\" src=\"www/Flinders_University_Logo_Horizontal_RGB_Master.png\" alt=\"Flinders University\" width=\"150\" style=\"margin-top: 20px\"\u003e\u003c/a\u003e \u0026nbsp; \u0026nbsp; \u003ca href=\"https://globalecologyflinders.com\"\u003e\u003cimg align=\"bottom-left\" src=\"www/GEL Logo Kaurna New Transp.png\" alt=\"GEL\" width=\"85\" style=\"margin-top: 20px\"\u003e\u003c/a\u003e \u0026nbsp; \u0026nbsp; \u0026nbsp; \u003ca href=\"https://molecularecology.flinders.edu.au/\"\u003e\u003cimg align=\"bottom-left\" src=\"www/MELlogo.png\" alt=\"MELFU logo\" width=\"110\" style=\"margin-top: 20px\"\u003e\u003c/a\u003e \u0026nbsp; \u0026nbsp; \u0026nbsp; \u003ca href=\"https://wildlife-genomics.sydney.edu.au/\"\u003e\u003cimg align=\"bottom-left\" src=\"www/USydlogo.png\" alt=\"USyd logo\" width=\"70\" style=\"margin-top: 20px\"\u003e\u003c/a\u003e \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u003ca href=\"https://wwf.org.au/\"\u003e\u003cimg align=\"bottom-left\" src=\"www/WWFlogo.webp\" alt=\"WWF logo\" width=\"50\" style=\"margin-top: 20px\"\u003e\u003c/a\u003e\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcjabradshaw%2Fdemo-genetic","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fcjabradshaw%2Fdemo-genetic","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcjabradshaw%2Fdemo-genetic/lists"}