Multi‐level patterns in population genetics: Variogram series detects a hidden isolation‐by‐distance‐dominated structure of Scandinavian brown bears Ursus arctos

Abstract

Large‐scale pattern‐oriented approaches are useful to understand the multi‐level processes that shape the genetic structure of a population. Matching the scales of patterns and putative processes is both a key to success and a challenge. We have developed a simple statistical approach, based on variogram analysis, that identifies multiple spatial scales where the population pattern, in this case genetic structure, have highest expression (i.e. the spatial scales at which the strength of patterning of isolation‐by‐distance (IBD) residual variance reached maximum) from empirical data and, thus, at which scales it should be studied relative to the underlying processes. The approach is applicable to any spatially explicit pairwise data, including genetic, morphological or ecological distance or similarity of individuals, populations and ecosystems. To exemplify possible applications of this approach, we analysed microsatellite genotypes of 1,530 brown bears from Sweden and Norway. The variogram approach identified two scales at which population structure was strongest, thus indicating two different scale‐dependent processes: home‐range‐related processes at scales <35 km, and subpopulation division at scales >98 km. On the basis of this, we performed a scale‐explicit analysis of genetic structure using DResD analysis and compared the results with those obtained by the Bayesian clustering implemented in structure. We found that the genetic cluster identified in central Scandinavia by Structure is caused by IBD, with distinct gene flow barriers to the south and north. We discuss possible applications and research perspectives to further develop the approach.

Demographic and genetic approaches to study dispersal in wild animal populations: A methodological review

“…Similarly, Schregel et al. () developed a simple statistical framework based on variogram analysis allowing the identification of the multiple spatial scales at which various biological processes have the highest influence on patterns of genetic structure (Box 4).…”

Multi-level patterns of genetic structure and isolation by distance in the widespread plant Mimulus guttatus

“…A further issue with studying genetic structure is going from pattern to process, when a range of scale-dependent and temporally variable processes together shape the spatial arrangement of genetic variation (Schregel et al 2018). At a local scale, the amount of dispersal and the strength and pattern of microgeographic selection, are expected to jointly affect spatial dynamics and patterns of relatedness (Vekemans & Hardy 2004).…”

ResDisMapper: An r package for fine‐scale mapping of resistance to dispersal

“…In this function, users can specify the geographical distance range over which IBD residuals are considered when calculating resistance. This is important because different spatial scales can give substantially different patterns (Schregel et al, ). The geographical distance range can be specified by either (a) using prior knowledge of the typical dispersal range of the species under consideration, or (b) testing different spatial scales and seeing which scale corresponds to that where the genetic correlation between individuals reaches zero (Epperson, ).…”