Multi-scale and multi-site resampling of a study area in spatial genetics: implications for flying insect species
Author(s) -
Julien Haran,
JeanPierre Rossi,
J. A. Pajares,
Luís Bonifácio,
Pedro Naves,
Alain Roques,
Géraldine Roux
Publication year - 2017
Publication title -
peerj
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.927
H-Index - 70
ISSN - 2167-8359
DOI - 10.7717/peerj.4135
Subject(s) - resampling , sampling (signal processing) , gene flow , biological dispersal , scale (ratio) , ecology , inference , sampling design , spatial ecology , biology , geography , genetic variation , statistics , computer science , cartography , population , gene , mathematics , genetics , artificial intelligence , demography , filter (signal processing) , sociology , computer vision
The use of multiple sampling areas in landscape genetic analysis has been recognized as a useful way of generalizing the patterns of environmental effects on organism gene flow. It reduces the variability in inference which can be substantially affected by the scale of the study area and its geographic location. However, empirical landscape genetic studies rarely consider multiple sampling areas due to the sampling effort required. In this study, we explored the effects of environmental features on the gene flow of a flying long-horned beetle ( Monochamus galloprovincialis ) using a landscape genetics approach. To account for the unknown scale of gene flow and the multiple local confounding effects of evolutionary history and landscape changes on inference, we developed a way of resampling study areas on multiple scales and in multiple locations (sliding windows) in a single large-scale sampling design. Landscape analyses were conducted in 3*10 4 study areas ranging in scale from 220 to 1,000 km and spread over 132 locations on the Iberian Peninsula. The resampling approach made it possible to identify the features affecting the gene flow of this species but also showed high variability in inference among the scales and the locations tested, independent of the variation in environmental features. This method provides an opportunity to explore the effects of environmental features on organism gene flow on the whole and reach conclusions about general landscape effects on their dispersal, while limiting the sampling effort to a reasonable level.
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom