Landscape relatedness: detecting contemporary fine-scale spatial structure in wild populations

Anita J Norman,Göran Spong,Aritz Ruiz-Gonzalez,Nathaniel R Street,Geir-Arne Fuglstad,Jonas Kindberg,Astrid V Stronen

doi:10.1007/s10980-016-0434-2

Abstract

ContextMethods for detecting contemporary, fine-scale population genetic structure in continuous populations are scarce. Yet such methods are vital for ecological and conservation studies, particularly under a changing landscape.ObjectivesHere we present a novel, spatially explicit method that we call landscape relatedness (LandRel). With this method, we aim to detect contemporary, fine-scale population structure that is sensitive to spatial and temporal changes in the landscape.MethodsWe interpolate spatially determined relatedness values based on SNP genotypes across the landscape. Interpolations are calculated using the Bayesian inference approach integrated nested Laplace approximation. We empirically tested this method on a continuous population of brown bears (Ursus arctos) spanning two counties in Sweden.ResultsTwo areas were identified as differentiated from the remaining population. Further analysis suggests that inbreeding has occurred in at least one of these areas.ConclusionsLandRel enabled us to identify previously unknown fine-scale structuring in the population. These results will help direct future research efforts, conservation action and aid in the management of the Scandinavian brown bear population. LandRel thus offers an approach for detecting subtle population structure with a focus on contemporary, fine-scale analysis of continuous populations.

Highlights

Knowledge of contemporary spatial structuring of populations is an important basis for ecological studies in addition to informing and facilitating conservation of a species (Bossart and Prowell 1998; Palsbøll 1999)
landscape relatedness (LandRel) offers an approach for detecting subtle population structure with a focus on contemporary, fine-scale analysis of continuous populations
Most genetic structure methods are based on assignment tests where individuals are ‘assigned’ to a subpopulation that is most fitting to their genotype (Manel et al 2005)

Summary

Introduction

Knowledge of contemporary spatial structuring of populations is an important basis for ecological studies in addition to informing and facilitating conservation of a species (Bossart and Prowell 1998; Palsbøll 1999). Many methods have been developed to study genetic structure and while each method is informative, there are limitations that make certain types of analysis difficult. Most genetic structure methods are based on assignment tests where individuals are ‘assigned’ to a subpopulation that is most fitting to their genotype (Manel et al 2005). Kinship-based methods are a type of assignment test that identifies and locates highly related individuals as inferred through molecular markers (Broquet et al 2009; Palsbøll et al 2010). One common limitation of assignment methods is that they are based on the island population model (Latter 1973)

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