ArticlePeerJ2019
Spatial genetic structure in
Article in PeerJ, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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0 citing papers in PubMed, 3 citations in OpenAlex.
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Authors and funding
8 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundSpatial genetic structure (SGS) analysis is a powerful approach to quantifying gene flow between trees, thus clarifying the functional connectivity of trees at population and landscape scales. The findings of SGS analysis may be useful for conservation and management of natural populations and plantations.
methodsDNA fingerprinting was performed using the amplified fragment length polymorphism (AFLP) technique. In order to estimate the SGS at population and landscape levels, we measured the geographical (spatial) distance as the Euclidean distance. We also estimated the genetic distances between individuals using the pairwise kinship coefficient.
resultsThe results showed non-significant autocorrelation in four out of five seed stands studied (i.e., a mainly random distribution in the space of the genetic variants of DISCUSSION: SGS was detected at the landscape scale, supporting the theory of isolation by distance as a consequence of restricted pollen and seed dispersal. However, the SGS may also have been generated by our sampling strategy. We recommended establishing a close network of seed stands of
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