Landscape genetics

Landscape genetics emerged as its own discipline after the seminal article entitled "Landscape genetics: combining landscape ecology and population genetics" by Manel et al. appeared in the journal Trends in Ecology and Evolution in 2003. According to that article, the concept that landscape patterns affect how organisms are distributed dates back to the 18th and 19th centuries in the writings of Augustin Pyramus de Candolle and Alfred Russel Wallace.[3] The modern field is interdisciplinary and integrates not only population genetics and landscape ecology, but also the field of spatial statistics.[4] As of 2008, over 655 articles had been published in the field in a variety of genetics and ecological journals.[2]

Map of the McArthur Lake Wildlife Corridor in northern Idaho, United States. It links to adjacent wilderness areas.

Landscape genetics has advanced ecological and evolutionary theory by facilitating an understanding of how gene flow and adaptation occur in real heterogeneous landscapes. It has also allowed for the estimation of functional connectivity across landscapes.[4] Elucidating landscape features that act as barriers or facilitators of dispersal can inform the construction or preservation of wildlife corridors that connect fragmented landscapes. Landscape genetics can also help predict how diseases will spread across a landscape or how proposed management actions will affect populations. Finally, landscape genetics can help predict how well populations will adapt to continuing global change.[2]

A study published in 2012[7] analyzed the landscape genetics of white tail deer in Wisconsin and Illinois.  They extracted DNA from the lymph nodes of 2,069 harvested deer across 64 townships.  Fifteen microsatellite markers were used for genotyping.  A Bayesian population assignment test found no distinct subpopulations based on the genetic data.  Correlograms were used to elucidate fine-scale social structure, and found that more heavily forested and fragmented townships had more genetic relatedness between individual deer.  Spatial principal component analysis was used to elucidate broad-scale population connectivity.  Partial Mantel tests found a correlation between genetic distance and geographic barriers, particularly roads and rivers.  However, these were not absolute barriers and did not divide the deer into distinct subpopulations.

The finding of high genetic connectivity among the sampled deer has management implications for the setting of harvest number and population goals.  The finding of high genetic connectivity also has implications for the spread of chronic wasting disease among deer.

As a new and fast growing interdisciplinary field with no explicitly identified best practices, it has been subject to a number of flaws in both study design and interpretation.[10] A 2016 publication[2] identified four common pitfalls of landscape genetics research that should be targeted for correction. These include assuming gene flow is always advantageous, over-generalizing results, failing to consider other processes that affect the genetic structure of populations, and mistaking quantitative methods for robust study design.[10] In particular, authors have been encouraged to report their sampling design, reproducibility of molecular data, and details on the spatial data set and spatial analyses utilized.[2] Because the effects of landscape on gene flow are not universal, sweeping generalities cannot be made, and species-specific studies are necessary.[2]

Many of these pitfalls result from the interdisciplinary nature of landscape genetics, and could be avoided with better collaboration among specialists in the fields of population genetics, landscape ecology, spatial statistics, and geography.[6]