Population Genetic Structure in a Social Landscape: Barley in a Traditional Ethiopian Agricultural System

Type Journal Article - Evolutionary Applications
Title Population Genetic Structure in a Social Landscape: Barley in a Traditional Ethiopian Agricultural System
Author(s)
Volume 6
Issue 8
Publication (Day/Month/Year) 2013
Page numbers 1133-1145
URL https://www.researchgate.net/profile/Lila_Fishman/publication/259986659_Population_genetic_structure​_in_a_social_landscape_Barley_in_a_traditional_Ethiopian_agricultural_system/links/00b7d528142b75269​1000000.pdf
Abstract
Conservation strategies are increasingly driven by our understanding of the processes and patterns of gene flow across complex landscapes. The expansion of population genetic approaches into traditional agricultural systems requires understanding how social factors contribute to that landscape, and thus to gene flow. This study incorporates extensive farmer interviews and population genetic analysis of barley landraces (Hordeum vulgare) to build a holistic picture of farmer-mediated geneflow in an ancient, traditional agricultural system in the highlands of Ethiopia. We analyze barley samples at 14 microsatellite loci across sites at varying elevations and locations across a contiguous mountain range, and across farmer-identified barley types and management strategies. Genetic structure is analyzed using population-based and individual-based methods, including measures of population differentiation and genetic distance, multivariate Principal Coordinate Analysis, and Bayesian assignment tests. Phenotypic analysis links genetic patterns to traits identified by farmers. We find that differential farmer management strategies lead to markedly different patterns of population structure across elevation classes and barley types. The extent to which farmer seed management appears as a stronger determinant of spatial structure than the physical landscape highlights the need for incorporation of social, landscape, and genetic data for the design of conservation strategies in human-influenced landscapes.

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