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

Context Methods 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. Objectives Here we present a novel, spatially explicit method that we...

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Bibliographic Details
Published in:Landscape Ecology
Main Authors: Norman, Anita J, Strønen, Astrid Vik, Fuglstad, Geir-Arne, Ruiz-Gonzalez, Aritz, Kindberg, Jonas, Street, Nathaniel R., Spong, Göran
Format: Article in Journal/Newspaper
Language:English
Published: 2017
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Online Access:https://vbn.aau.dk/da/publications/dfedddb4-cc99-470a-b39d-2938598dbe61
https://doi.org/10.1007/s10980-016-0434-2
https://vbn.aau.dk/ws/files/272986505/Landscape_relatedness_detecting_contemporary_fine_scale_spatial_structure_in_wild_populations.pdf
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Summary:Context Methods 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. Objectives Here 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. Methods We 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. Results Two areas were identified as differentiated from the remaining population. Further analysis suggests that inbreeding has occurred in at least one of these areas. Conclusions LandRel 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.