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Determining how species move across complex and fragmented landscapes and interact with human-made barriers is a major research focus in conservation. Studies estimating functional connectivity from movement, dispersal or gene flow usually rely on a single study period and rarely consider variation over time. We contrasted genetic structure and gene flow across barriers for a metapopulation of desert bighorn sheep (Ovis canadensis nelsoni) using genotypes collected 2000-2003 and 2013-2015. Based on the recently observed but unexpected spread of a respiratory pathogen across an interstate highway previously identified as a barrier to gene flow, we hypothesized that bighorn sheep changed how they interacted with that barrier, and that shifts in metapopulation structure influenced gene flow, genetic diversity and connectivity. Population assignment tests, genetic structure and genetic recapture demonstrated that bighorn sheep crossed the interstate highway in at least one location in 2013-2015, sharply reducing genetic structure between two populations, but supported conclusions of an earlier study that such crossings were very infrequent or unknown in 2000-2003. A recently expanded population established new links and caused decreases in genetic structure among multiple populations. Genetic diversity showed only slight increases in populations linked by new connections. Genetic structure and assignments revealed other previously undetected changes in movements and distribution, but much was consistent. Thus, we observed changes in both structural and functional connectivity over just two generations, but only in specific locations. Movement patterns of species should be revisited periodically to enable informed management, particularly in dynamic and fragmented systems., (© 2018 John Wiley & Sons Ltd.)

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., (© 2015 John Wiley & Sons Ltd.)

Climate change is arguably the greatest challenge to conservation of our time. Most vulnerability assessments rely on past and current species distributions to predict future persistence but ignore species' abilities to disperse through landscapes, which may be particularly important in fragmented habitats and crucial for long-term persistence in changing environments. Landscape genetic approaches explore the interactions between landscape features and gene flow and can clarify how organisms move among suitable habitats, but have suffered from methodological uncertainties. We used a landscape genetic approach to determine how landscape and climate-related features influence gene flow for American pikas (Ochotona princeps) in Crater Lake National Park. Pikas are heat intolerant and restricted to cool microclimates; thus, range contractions have been predicted as climate changes. We evaluated the correlation between landscape variables and genetic distance using partial Mantel tests in a causal modelling framework, and used spatially explicit simulations to evaluate methods of model optimization including a novel approach based on relative support and reciprocal causal modelling. We found that gene flow was primarily restricted by topographic relief, water and west-facing aspects, suggesting that physical restrictions related to small body size and mode of locomotion, as well as exposure to relatively high temperatures, limit pika dispersal in this alpine habitat. Our model optimization successfully identified landscape features influencing resistance in the simulated data for this landscape, but underestimated the magnitude of resistance. This is the first landscape genetic study to address the fundamental question of what limits dispersal and gene flow in the American pika., (© 2014 John Wiley & Sons Ltd.)

There is widespread concern about impacts of land-use change on connectivity among animal and plant populations, but those impacts are difficult to quantify. Moreover, lack of knowledge regarding ecosystems before fragmentation may obscure appropriate conservation targets. We use occurrence and population genetic data to contrast connectivity for a long-lived mega-herbivore over historical and contemporary time frames. We test whether (i) historical gene flow is predicted by persistent landscape features rather than human settlement, (ii) contemporary connectivity is most affected by human settlement and (iii) recent gene flow estimates show the effects of both factors. We used 16 microsatellite loci to estimate historical and recent gene flow among African elephant (Loxodonta africana) populations in seven protected areas in Tanzania, East Africa. We used historical gene flow (FST and G'ST ) to test and optimize models of historical landscape resistance to movement. We inferred contemporary landscape resistance from elephant resource selection, assessed via walking surveys across ~15 400 km(2) of protected and unprotected lands. We used assignment-based recent gene flow estimates to optimize and test the contemporary resistance model, and to test a combined historical and contemporary model. We detected striking changes in connectivity. Historical connectivity among elephant populations was strongly influenced by slope but not human settlement, whereas contemporary connectivity was influenced most by human settlement. Recent gene flow was strongly influenced by slope but was also correlated with contemporary resistance. Inferences across multiple timescales can better inform conservation efforts on large and complex landscapes, while mitigating the fundamental problem of shifting baselines in conservation., (© 2013 Blackwell Publishing Ltd.)

Global warming is predicted to affect the evolutionary potential of natural populations. We assessed genetic diversity of 25 populations of desert bighorn sheep (Ovis canadensis nelsoni) in southeastern California, where temperatures have increased and precipitation has decreased during the 20th century. Populations in low-elevation habitats had lower genetic diversity, presumably reflecting more fluctuations in population sizes and founder effects. Higher-elevation habitats acted as reservoirs of genetic diversity. However, genetic diversity was also affected by population connectivity, which has been disrupted by human development. Restoring population connectivity may be necessary to buffer the effects of climate change on this desert-adapted ungulate.