Landscape genetics in a changing world: disentangling historical and contemporary influences and inferring change |
| |
| Authors: | Clinton W Epps Nusha Keyghobadi |
| |
| Affiliation: | 1. Oregon State University, Corvallis, OR, USA;2. Department of Biology, Western University, London, ON, Canada |
| |
| Abstract: | Landscape genetics seeks to determine the effect of landscape features on gene flow and genetic structure. Often, such analyses are intended to inform conservation and management. However, depending on the many factors that influence the time to reach equilibrium, genetic structure may more strongly represent past rather than contemporary landscapes. This well‐known lag between current demographic processes and population genetic structure often makes it challenging to interpret how contemporary landscapes and anthropogenic activity shape gene flow. Here, we review the theoretical framework for factors that influence time lags, summarize approaches to address this temporal disconnect in landscape genetic studies, and evaluate ways to make inferences about landscape change and its effects on species using genetic data alone or in combination with other data. Those approaches include comparing correlation of genetic structure with historical versus contemporary landscapes, using molecular markers with different rates of evolution, contrasting metrics of genetic structure and gene flow that reflect population genetic processes operating at different temporal scales, comparing historical and contemporary samples, combining genetic data with contemporary estimates of species distribution or movement, and controlling for phylogeographic history. We recommend using simulated data sets to explore time lags in genetic structure, and argue that time lags should be explicitly considered both when designing and interpreting landscape genetic studies. We conclude that the time lag problem can be exploited to strengthen inferences about recent landscape changes and to establish conservation baselines, particularly when genetic data are combined with other data. |
| |
| Keywords: | equilibrium microsatellite mitochondrial DNA phylogeography scale
SNP
temporal time lag |
|
|
