Data from: Multi-level patterns in population genetics: variogram series detects a hidden isolation-by- distance- dominated structure of Scandinavian brown bears Ursus arctos

1. 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. 2. We have developed a simple statistical approach, based o...

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Main Authors: Schregel, Julia, Remm, Jaanus, Eiken, Hans Geir, Swenson, Jon E., Saarma, Urmas, Hagen, Snorre B.
Format: Article in Journal/Newspaper
Language:unknown
Published: 2018
Subjects:
Online Access:http://hdl.handle.net/10255/dryad.171928
https://doi.org/10.5061/dryad.vr61ks2
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spelling ftdryad:oai:v1.datadryad.org:10255/dryad.171928 2023-05-15T18:42:13+02:00 Data from: Multi-level patterns in population genetics: variogram series detects a hidden isolation-by- distance- dominated structure of Scandinavian brown bears Ursus arctos Schregel, Julia Remm, Jaanus Eiken, Hans Geir Swenson, Jon E. Saarma, Urmas Hagen, Snorre B. Scandinavia Holocene 2018-02-19T14:51:46Z http://hdl.handle.net/10255/dryad.171928 https://doi.org/10.5061/dryad.vr61ks2 unknown doi:10.5061/dryad.vr61ks2/1 doi:10.1111/2041-210x.12980 doi:10.5061/dryad.vr61ks2 Schregel J, Remm J, Eiken HG, Swenson JE, Saarma U, Hagen SB (2018) Multi-level patterns in population genetics: Variogram series detects a hidden isolation-by-distance-dominated structure of Scandinavian brown bears Ursus arctos. Methods in Ecology and Evolution 9(5): 1324-1334. http://hdl.handle.net/10255/dryad.171928 clustercore identification DResD gene flow isolation-by-distance isolation-by-resistance population boundaries spatial scale variogram Article 2018 ftdryad https://doi.org/10.5061/dryad.vr61ks2 https://doi.org/10.5061/dryad.vr61ks2/1 https://doi.org/10.1111/2041-210x.12980 2020-01-01T16:04:58Z 1. 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. 2. 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. 3. The variogram approach identified two scales at which population structure was strongest, thus indicating two different scale-dependent processes: home-rangerelated 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. 4. 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. Article in Journal/Newspaper Ursus arctos Dryad Digital Repository (Duke University) Norway
institution Open Polar
collection Dryad Digital Repository (Duke University)
op_collection_id ftdryad
language unknown
topic clustercore identification
DResD
gene flow
isolation-by-distance
isolation-by-resistance
population boundaries
spatial scale
variogram
spellingShingle clustercore identification
DResD
gene flow
isolation-by-distance
isolation-by-resistance
population boundaries
spatial scale
variogram
Schregel, Julia
Remm, Jaanus
Eiken, Hans Geir
Swenson, Jon E.
Saarma, Urmas
Hagen, Snorre B.
Data from: Multi-level patterns in population genetics: variogram series detects a hidden isolation-by- distance- dominated structure of Scandinavian brown bears Ursus arctos
topic_facet clustercore identification
DResD
gene flow
isolation-by-distance
isolation-by-resistance
population boundaries
spatial scale
variogram
description 1. 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. 2. 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. 3. The variogram approach identified two scales at which population structure was strongest, thus indicating two different scale-dependent processes: home-rangerelated 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. 4. 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.
format Article in Journal/Newspaper
author Schregel, Julia
Remm, Jaanus
Eiken, Hans Geir
Swenson, Jon E.
Saarma, Urmas
Hagen, Snorre B.
author_facet Schregel, Julia
Remm, Jaanus
Eiken, Hans Geir
Swenson, Jon E.
Saarma, Urmas
Hagen, Snorre B.
author_sort Schregel, Julia
title Data from: Multi-level patterns in population genetics: variogram series detects a hidden isolation-by- distance- dominated structure of Scandinavian brown bears Ursus arctos
title_short Data from: Multi-level patterns in population genetics: variogram series detects a hidden isolation-by- distance- dominated structure of Scandinavian brown bears Ursus arctos
title_full Data from: Multi-level patterns in population genetics: variogram series detects a hidden isolation-by- distance- dominated structure of Scandinavian brown bears Ursus arctos
title_fullStr Data from: Multi-level patterns in population genetics: variogram series detects a hidden isolation-by- distance- dominated structure of Scandinavian brown bears Ursus arctos
title_full_unstemmed Data from: Multi-level patterns in population genetics: variogram series detects a hidden isolation-by- distance- dominated structure of Scandinavian brown bears Ursus arctos
title_sort data from: multi-level patterns in population genetics: variogram series detects a hidden isolation-by- distance- dominated structure of scandinavian brown bears ursus arctos
publishDate 2018
url http://hdl.handle.net/10255/dryad.171928
https://doi.org/10.5061/dryad.vr61ks2
op_coverage Scandinavia
Holocene
geographic Norway
geographic_facet Norway
genre Ursus arctos
genre_facet Ursus arctos
op_relation doi:10.5061/dryad.vr61ks2/1
doi:10.1111/2041-210x.12980
doi:10.5061/dryad.vr61ks2
Schregel J, Remm J, Eiken HG, Swenson JE, Saarma U, Hagen SB (2018) Multi-level patterns in population genetics: Variogram series detects a hidden isolation-by-distance-dominated structure of Scandinavian brown bears Ursus arctos. Methods in Ecology and Evolution 9(5): 1324-1334.
http://hdl.handle.net/10255/dryad.171928
op_doi https://doi.org/10.5061/dryad.vr61ks2
https://doi.org/10.5061/dryad.vr61ks2/1
https://doi.org/10.1111/2041-210x.12980
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