Landscape genetics: combining landscape ecology and population genetics

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Abstract

Understanding the processes and patterns of gene flow and local adaptation requires a detailed knowledge of how landscape characteristics structure populations. This understanding is crucial, not only for improving ecological knowledge, but also for managing properly the genetic diversity of threatened and endangered populations. For nearly 80 years, population geneticists have investigated how physiognomy and other landscape features have influenced genetic variation within and between populations. They have relied on sampling populations that have been identified beforehand because most population genetics methods have required discrete populations. However, a new approach has emerged for analyzing spatial genetic data without requiring that discrete populations be identified in advance. This approach, landscape genetics, promises to facilitate our understanding of how geographical and environmental features structure genetic variation at both the population and individual levels, and has implications for ecology, evolution and conservation biology. It differs from other genetic approaches, such as phylogeography, in that it tends to focus on processes at finer spatial and temporal scales. Here, we discuss, from a population genetic perspective, the current tools available for conducting studies of landscape genetics.

Section snippets

The landscape genetics approach

Landscape genetics has emerged as the result of researchers explaining observed spatial genetic patterns by using landscape variables (Table 1). The most common spatial patterns described in the literature are: clines [8], isolation by distance [9], genetic boundaries (discontinuities) to gene flow 10, 11, metapopulations [12] and random patterns [13]. The identification of these spatial genetic patterns requires the collection of genetic data from many individuals (or populations) whose exact

Genetic tools facilitating landscape genetics

Technological advances have enabled researchers to use markers with varying temporal or spatial resolution (e.g. mitochondrial DNA, microsatellites, amplified fragment length polymorphisms and Y chromosomes). Dozens of markers are available for numerous taxa (e.g. ungulates [14], mammals carnivores [15], birds [16] and fish [17]). The next major advance involves increased numbers of markers [including single nucleotide polymorphisms (SNPs), mapped loci and candidate genes] combined with a

Statistical tools to identify spatial genetic patterns

In some situations, it is easy to define subpopulations or demes on the basis of spatial clustering of individuals (e.g. ponds of fish in isolated lakes or birds nesting on archipelago islands). When this is the case, methods such as Wright's fst or methods derived from assignment tests [24] might be preferred. However, individuals are often not arranged in a clustered distribution, but are uniformly distributed across space. This is when the landscape approach is most valuable.

From the

Correlating genetic patterns with landscape and environmental features

Once a spatial genetic pattern is identified, it is possible to test for correlations with environmental or landscape variables. Here, we describe statistical tests that correlate genetic patterns with environmental variables, and a visual approach that provides insight into the correlations.

Prospects

We have reviewed some advances in the analyses of genetic spatial patterns and their correlation with landscape and environmental features. The largest advance is the movement towards methods that do not require assumptions of population boundaries beforehand. The development of the fast-moving field of landscape genetics has benefited from the recent development of molecular tools and the new and existing statistical tools developed in landscape ecology. Landscape genetics should advance

Acknowledgements

M.K.S. was supported by the Northern Region of the US Forest Service, and the Rocky Mountain Research Station. K. McKelvey, F. Samson and J. Hoog provided helpful ideas for this review. We thank M. Arroyo, D. Tallmon, P. England and A. Peja-Pereira for comments on the paper and O. Hanotte and co-authors for providing Fig. 1b. We apologize to the many authors whose interesting and relevant work could not be cited because of space limitations.

Glossary

Glossary

Assignment test:
statistical approach that assigns an individual to the population from which its multilocus genotypes is most likely to be derived.
Cline:
a character gradient; continuous variation in a character through a series of contiguous or adjacent populations. In population genetics, the character could be multi-locus genotypes (at the individual level) or single locus allelic frequencies.
Conservation unit:
refers to either evolutionary significant unit or management unit, or any

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