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Single nucleotide polymorphism‐based dispersal estimates using noninvasive sampling
Author(s) -
Norman Anita J.,
Spong Göran
Publication year - 2015
Publication title -
ecology and evolution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.17
H-Index - 63
ISSN - 2045-7758
DOI - 10.1002/ece3.1588
Subject(s) - biological dispersal , pedigree chart , biology , isolation by distance , single nucleotide polymorphism , sampling (signal processing) , ecology , genetics , genotype , gene flow , demography , genetic variation , population , computer science , filter (signal processing) , sociology , computer vision , gene
Quantifying dispersal within wild populations is an important but challenging task. Here we present a method to estimate contemporary, individual‐based dispersal distance from noninvasively collected samples using a specialized panel of 96 SNP s (single nucleotide polymorphisms). One main issue in conducting dispersal studies is the requirement for a high sampling resolution at a geographic scale appropriate for capturing the majority of dispersal events. In this study, fecal samples of brown bear ( Ursus arctos) were collected by volunteer citizens, resulting in a high sampling resolution spanning over 45,000 km 2 in Gävleborg and Dalarna counties in Sweden. SNP genotypes were obtained for unique individuals sampled ( n  = 433) and subsequently used to reconstruct pedigrees. A Mantel test for isolation by distance suggests that the sampling scale was appropriate for females but not for males, which are known to disperse long distances. Euclidean distance was estimated between mother and offspring pairs identified through the reconstructed pedigrees. The mean dispersal distance was 12.9 km ( SE 3.2) and 33.8 km ( SE 6.8) for females and males, respectively. These results were significantly different (Wilcoxon's rank‐sum test: P ‐value = 0.02) and are in agreement with the previously identified pattern of male‐biased dispersal. Our results illustrate the potential of using a combination of noninvasively collected samples at high resolution and specialized SNP s for pedigree‐based dispersal models.

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