Modelling the loss of genetic diversity in vole populations in a spatially and temporally varying environment
Authored by Christopher J Topping, C Pertoldi, LA Bach, S Ostergaard
Date Published: 2003
Sponsors:
Danish Natural Sciences Research Council
Platforms:
C++
Model Documentation:
Other Narrative
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Mathematical description
Model Code URLs:
Model code not found
Abstract
Altering environmental conditions affects the genetic composition of
populations via demographic and selective responses by creating of
variety of population substructuring types. Classical genetic approaches
can predict the genetic composition of populations under long-term or
structurally stable conditions, but exclude factors such as animal
behaviour, environmental structure, and breeding biology, all of which
influence genetic diversity. Most populations are unique in some of
these characteristics, and therefore may be unsuitable for the classical
approach. Here, an alternative approach using a genetically explicit
individual-based model (IBM) coupled to a dynamic landscape model was
used to obtain measures for the genetic status of simulated vole
populations. The rate of loss of expected heterozygosity (H-e) was
calculated for simulated populations using two levels of spatial and
temporal heterogeneity. Results showed that both spatial and temporal
heterogeneity exerted an influence on the rate of loss of genetic
diversity, but the precise effect was a balance between the effects of
population sub-structuring, the frequency of founder effects and
population size. These were in turn related to habitat availability and
their influence on vole behaviour. Interaction between spatial and
temporal dynamics altered the ratio of effective population size to
census size. This indicates an altered reproductive potential, crucial
in conservation biology applications. However, when the loss of
heterozygosity was corrected for the harmonic mean of the population
size, the rate of loss was almost identical in the four scenarios.
Unlike classical genetic models, IBMs are flexible enough to mimic real
population processes under a range of environmental and behavioural
conditions. We conclude that IBMs incorporating explicit genetics
provide a promising new approach to the evaluation of the effect of
animal behaviour, and random and man-induced events on the genetic
composition of populations. They also provide a new platform from which
to investigate the implication of real world deviations from assumptions
of traditional genetic models.
Tags
behavior
Dynamics
Metapopulation
Consequences
Field voles
Microtus-agrestis
Effective size