A spatial genomic approach identifies time lags and historical barriers to gene flow in a rapidly fragmenting Appalachian landscape

Abstract

The resolution offered by genomic data sets coupled with recently developed spatially informed analyses are allowing researchers to quantify population structure at increasingly fine temporal and spatial scales. However, both empirical research and conservation measures have been limited by questions regarding the impacts of data set size, data quality thresholds and the timescale at which barriers to gene flow become detectable. Here, we used restriction site associated DNA sequencing to generate a 2,140 single nucleotide polymorphism (SNP) data set for the copperhead snake (Agkistrodon contortrix) and address the population genomic impacts of recent and widespread landscape modification across an ~1,000‐km2 region of eastern Kentucky, USA. Nonspatial population‐based assignment and clustering methods supported little to no population structure. However, using individual‐based spatial autocorrelation approaches we found evidence for genetic structuring which closely follows the path of a historically important highway which experienced high traffic volumes from c. 1920 to 1970 before losing most traffic to a newly constructed alternative route. We found no similar spatial genomic signatures associated with more recently constructed highways or surface mining activity, although a time lag effect may be responsible for the lack of any emergent spatial genetic patterns. Subsampling of our SNP data set suggested that similar results could be obtained with as few as 250 SNPs, and a range of thresholds for missing data exhibited limited impacts on the spatial patterns we detected. While we were not able to estimate relative effects of land uses or precise time lags, our findings highlight the importance of temporal factors in landscape genetics approaches, and suggest the potential advantages of genomic data sets and fine‐scale, spatially informed approaches for quantifying subtle genetic patterns in temporally complex landscapes.

Past forest cover explains current genetic differentiation in the Carpathian newt (Lissotriton montandoni), but not in the smooth newt (L. vulgaris)

“…Our results for L. montandoni , corroborating previous work (e.g. Holzhauer et al, 2006; Maigret et al, 2020; Spear & Storfer, 2008), imply that it takes time for the genetic effects of increased connectivity to manifest themselves in some species. Our results show a time lag of ~10 generations in L. montandoni , suggesting that the impact of forest‐cover changes over the last 40 years on genetic differentiation has not yet fully manifested, particularly the increased connectivity across the Podkarpackie region.…”

Shared patterns of population genomic variation and phenotypic response across rapid range expansions in two invasive lady beetle species

“…Our analyses used a nearest-neighbor connection network accounting for multiple samples at each sampling site (type = 6) with k = 20 and k = 25 neighbors for P14 and H. variegata, respectively. This connection network scheme was created to maximize connectivity across spatially distinct samples while accounting for sampling differences between species and potential long-distance dispersal events among sampling sites (Maigret, Cox, & Weisrock, 2020). We estimated the significance of global and local structure with 999 permutations through adegenet (Montano & Jombart, 2017) .…”

Current and Forthcoming Approaches for Benchmarking Genetic and Genomic Diversity

“…The availability of more sensitive assays being developed by advancing technology and the possibility of sequencing entire genomes may improve our abilities to detect small changes, including evidence of inbreeding, other small-population effects, and restricted dispersal across different forms of habitat barriers (Corlett, 2017;Kozakiewicz et al, 2019;Maigret et al, 2020). For example, based on a dataset of approximately 2000 SNPs for the copperhead snake (Agkistrodon contortrix), Maigret et al (2020) were able to detect evidence for subtle genetic structuring closely following the path of a highway that experienced high traffic volumes between 1920 to 1970 in eastern Kentucky, United States, but has now lost most traffic to a newly constructed alternative route. Their results add evidence revealing subtle impacts of anthropogenic fragmentation of landscapes, but also highlight the importance of temporal factors in landscape genetics, showing that temporal lags may impact our ability to detect the detrimental effects of land use change.…”