Fig. 4: Results of variation partitioning and RDA biplots. | Heredity

Fig. 4: Results of variation partitioning and RDA biplots.

From: Physical geography, isolation by distance and environmental variables shape genomic variation of wild barley (Hordeum vulgare L. ssp. spontaneum) in the Southern Levant

Fig. 4

A Variation partitioning of SNP variation and population structure. Left and middle columns: explained SNP variation estimated by RDA models using population structure and spatial autocorrelation as covariates, respectively. Right column: population structure explained by environment and space. Environment, space and population structure are represented by twelve environmental variables, dbMEMs, and ancestry coefficients (K = 4) in RDA models. B Percentage of SNP variation explained by environmental variables. The simple_single and partial_single show individual effects estimated based on RDA models fitting one environmental variable at a time. The simple_margin and partial_margin show marginal effects estimated based on RDA models fitting all environmental variables. The partial_single and partial_margin are estimated based on partial RDA conditioned on population structure. C Biplot of simple RDA. D Biplot of partial RDA conditioned on population structure. The arrows represent correlations of the environmental variables with RDA axes that are shown in greater detail in Table S6. Abbreviation in the biplots: Asp aspect, CVR CoefVar_Rain, ET Elevation+Temperature, LRS Latitude+Rain+Solar_rad, Slp Slope, SBD Soil_bulk_density, SCC1 Soil_carbon_content (0–15 cm), SCC2 Soil_carbon_content (30 cm), SpH Soil_pH, SSC Soil_silt_content, SWC Soil_water_capacity, SDT StdDev_Temperature.

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