Table 1.
Locus-wise genetic variability in walnut germplasm.
Fig 1.
Genetic relationships among walnut genotypes.
(A) Neighbor-joining cluster analysis using pair-wise Nei and Li distance matrix. (B) Principal components analysis using multilocus microsatellite genotype data.
Fig 2.
Population structure inferred from a model based Bayesian cluster analysis.
(A) Posterior probabilities (Ln Pr X|K) averaged over 20 replicate runs, (B) The ad hoc statistic delta K related to the second order rate of change of log probability of data between successive values of K with a distinct peak at K = 5 with some minor peaks at K = 9, 13, and 16, and (C) Bayesian Inferred population structure of walnut for K = 5 groups.
Table 2.
Within-group genetic variability in walnut.
Fig 3.
Inverse distance weighted (IDW) interpolation of allelic diversity estimates in walnut.
(A) allelic richness, (B) private allelic richness, and (C) expected levels of heterozygosity among walnut geographic groups.
Table 3.
Partitioning genetic variation within and among geographic groups in walnut.
Table 4.
Genetic differentiation among geographic groups in walnut.
Table 5.
Pair-wise FST values showing genetic differentiation among geographic groups in walnut.
Table 6.
Model settings (evaluation metrics) for AICc-selected MaxEnt model predictions.
Fig 4.
Ecological niche modeling of walnut distributions.
AICc-selected model prediction of occurrence of walnut for current, last glacial maximum (LGM; 21–18 kyr BP), and last interglacial (LIG; 130–107 kyr BP) climatic conditions for the data set filtered at 10 km with 137 occurrence points (refer to Table 6 for feature class and regularization multiplier settings).
Table 7.
Pair-wise Schoener’s D statistic measuring niche similarity among the current, LGM, and LIG model predictions.