• Causal modelling;
  • genetic diversity;
  • genetic structure;
  • historical barriers;
  • landscape genetics;
  • population fragmentation


Aim  The study of geographical discontinuities in the distribution of genetic variability in natural populations is a central topic in both evolutionary and conservation research. In this study, we aimed to analyse (1) the factors associated with genetic diversity at the landscape spatial scale in the highly specialized grasshopper Mioscirtus wagneri and (2) to identify the relative contribution of alternative factors to the observed patterns of genetic structure in this species.

Location  La Mancha region, Central Spain.

Methods  We sampled 28 populations of the grasshopper M. wagneri and genotyped 648 individuals at seven microsatellite loci. We employed a causal modelling approach to identify the most influential variables associated with genetic differentiation within a multiple hypothesis-testing framework.

Results  We found that genetic diversity differs among populations located in different river basins and decreases with population isolation. Causal modelling analyses showed variability in the relative influence of the studied landscape features across different spatial scales. When a highly isolated population is considered, the analyses suggested that geographical distance is the only factor explaining the genetic differentiation between populations. When that population is excluded, the causal modelling analysis revealed that elevation and river basins are also relevant factors contributing to explaining genetic differentiation between the studied populations.

Main conclusions  These results indicate that the spatial scale considered and the inclusion of outlier populations may have important consequences on the inferred contribution of alternative landscape factors on the patterns of genetic differentiation even when all populations are expected to similarly respond to landscape structure. Thus, a multiscale perspective should also be incorporated into the landscape genetics framework to avoid biased conclusions derived from the spatial scale analysed and/or the geographical distribution of the studied populations.