Model testing by analyses of molecular variance (AMOVA) and multivariate matrix regressions (MMR).

The test statistic reported is the proportion of variance in the data that was accounted for by each model. For AMOVA this may be the proportion of variance among populations (FST, in bold case, where #groups = 1) or among groups (FCT, normal case, where #groups>1). Conditional MMR tests assess the proportion of marginal variation remaining after geography is taken into account. Sequential MMR tests fit the best model to the data and the statistic reported is that proportion of the remaining variation that is attributable to the second model. Models (P, phenotype; B, biogeography; G, geography; M, molecular; Lt, latitude; and Lg, longitude) are listed in the sequential order in which they were fitted to the regression. Significance was denoted *** (p<0.001), ** (p<0.01), * (p<0.05) or NS (not significant) after 10000 (AMOVA) or 9999 (MMR) permutations.

本研究报告的检验统计量为各模型对数据方差的解释比例。针对分子方差分析（AMOVA），该统计量可对应种群间方差比例（粗体格式的FST，当分组数#groups=1时），或组间方差比例（常规格式的FCT，当分组数#groups>1时）。条件MMR检验用于评估扣除地理因素影响后剩余的边际变异比例。序贯MMR检验先将最优模型拟合至数据集，报告的统计量为剩余变异中可归因于第二个模型的比例。模型缩写及对应含义如下：P代表表型、B代表生物地理、G代表地理因素、M代表分子数据、Lt代表纬度、Lg代表经度，上述模型按照其被纳入回归拟合的序贯顺序排列。显著性标记规则如下：经10000次（AMOVA）或9999次（MMR）置换检验后，p<0.001记为***，p<0.01记为**，p<0.05记为*，无统计学显著性记为NS（not significant）。