Landscape genetics in a changing world: disentangling historical and contemporary influences and inferring change

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.

Beyond the snapshot: Landscape genetic analysis of time series data reveal responses of American black bears to landscape change

“…(2011) found higher correlations between land cover and black bear gene flow in landscapes where forest cover was highly fragmented compared to landscapes of contiguous forest. Yet, the absence of a landscape effect on 2002 SGS may reflect a time lag between when landscape change occurs and when SGS response to landscape change becomes evident (Anderson et al., 2010; Epps & Keyghobadi, 2015). However, when dispersal rates and distances are large, as exhibited in the NLP black bear population (Draheim, 2015; Draheim et al., 2016; Moore et al., 2014), shorter or no time lags are expected (Epps & Keyghobadi, 2015).…”

“…Yet, the absence of a landscape effect on 2002 SGS may reflect a time lag between when landscape change occurs and when SGS response to landscape change becomes evident (Anderson et al., 2010; Epps & Keyghobadi, 2015). However, when dispersal rates and distances are large, as exhibited in the NLP black bear population (Draheim, 2015; Draheim et al., 2016; Moore et al., 2014), shorter or no time lags are expected (Epps & Keyghobadi, 2015). Also, legacy effects of historical landscape processes may be reduced using genetic markers with higher mutations rates (i.e., microsatellites) that reach mutation–drift equilibrium quickly and genetic measures that respond rapidly to changes in connectivity (e.g., Dps) (Anderson et al., 2010).…”

The value of space‐for‐time substitution for studying fine‐scale microevolutionary processes

“…Unlike stationary landscape scenarios, in which population sizes are also expected to be stationary, selective forces can potentially cause non-stationary changes in population demographics that could affect how populations experience mutation and drift (Haig 1998, Epps and Keyghobadi 2015, Kozma et al 2016). For example, some studies have evaluated the loss of genetic variation over time on non-stationary landscapes to demonstrate IBT.…”

Union of phylogeography and landscape genetics

“…The temporal scale is one of the more common ways of differentiating the fields, with phylogeography examining time scales on the order of millions of years (more typical of lineage divergence and speciation events), but landscape genetics examining more shallow time scales closer to thousands of years B.P. However, the advent and proliferation of next-generation sequencing and nonmodel organism genomics now allow evolutionary biologists to investigate both neutral and adaptive genetic diversity at a variety of temporal scales (38,39). Both historic and contemporary environmental, geographic, and ecological factors influence patterns of genetic variation (e.g., refs.…”