The use of agent-based modelling of genetics in conservation genetics studies

Cino Pertoldi*, Chris Topping

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

8 Citations (Scopus)

Abstract

Animal Landscape and Man Simulation System a genetically explicit agent-based model was used to obtain measures for the genetic and demographic status of simulated populations. This investigation aimed to test the applicability of this approach for assessing the effect of environmental perturbations on populations' temporal and spatial dynamics. This was achieved by assessing how three simple scenarios with increasing degree of environmental disturbance, simulated by populations bottlenecks repeated at different intervals, affected the genetic and demographic characteristics of the simulated population. Model outputs from a simplified landscape scenario concurred with theoretical expectations validating the model in a qualitative way. Differences in medians, means and coefficient of variation of the observed (Ho) and expected heterozygosity (He), population census size (N), effective population size (Ne), inbreeding coefficient (F) and Ne/N ratio were observed for simulated populations. Impacts occurred rapidly after simulated bottleneck events and genetic estimates were less variable, and therefore more reliable, than demographic estimates. Precise genetic consequences of the bottlenecks repeated at different intervals, and resulting population perturbations, are a complex balance between effects on population sub-structure, size and founding events. Agent-based models are appropriate tools to simulate these interactions, being sufficiently flexible to mimic real population processes under a range of environmental conditions. Such models incorporating explicit genetics provide a promising new approach to evaluate the impact of environmental changes on genetic composition of populations.

Original languageEnglish
JournalJournal for Nature Conservation
Volume12
Issue number2
Pages (from-to)111-120
Number of pages10
ISSN1617-1381
DOIs
Publication statusPublished - 1 Jan 2004
Externally publishedYes

Keywords

  • Agent-based model
  • Dynamic landscape
  • Effective population size
  • Field vole
  • Genetic diversity

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