FST estimates
We collected FST and FST analogs as
measures of genetic differentiation (Holsinger & Weir, 2009; Meirmans
& Hedrick, 2011) which we collectively refer to FSTthroughout this paper. Assuming an island model of migration-drift
equilibrium, Wright (1951) developed a theoretical framework for
studying the gene frequency variation among subpopulations through the
fixation indices, i.e. F-statistics. In this model, FSTis the degree of gene differentiation among subpopulations for genes
that have only two alleles. Nei (1973) expanded the model for
polymorphic genes, and proposed GST as a measure of the
gene diversity partitioned among subpopulations, relative to the total
gene diversity of the population. Subsequently, Weir & Cockerham (1984)
proposed a standard measure of genetic structure θ based on Wright
(1951). The statistic θ is estimated per and across loci, and represents
the correlation of genes, or coancestry, among individuals in a given
population. Excoffier, Smouse, and Quattro (1992) proposed AMOVA
(Analysis of Molecular Variance) and corresponding statistic
φST; the proportion of genetic diversity partitioned
among populations. Finally, Hedrick (2005) proposed a standardized
measure of population differentiation, G’ST, which
accounts for the level of heterozygosity of the marker used for
genotyping individuals
(G’ST=GSToverall/GSTmax).
The most common statistic in our dataset was θ. When θ was reported per
loci, we took the mean across loci as the global FST for
that species. The AMOVA derived φST was also common.
Some studies reported both θ and φST, in which case we
used φST as it likely better represents genetic
structure among populations (Hey & Pinho, 2012). The statistics θ and
φST were, however, frequently almost equivalent. Another
common measure was GST; when reported for multiple pairs
of populations, we used the mean across all pairs. A few studies
reported G’ST. It was not possible to back-transform
G’ST to GST because such studies did not
report the maximum possible GST in their data (Hahn,
Michalski, Fischer, & Durka, 2016). Even though G’STpotentially yields a higher value than GST (or θ and
φST) based on the same data (Hedrick, 2005; Meirmans &
Hedrick, 2011), we still included G’ST values, reasoning
that any trend of variation in population genetic structure due to the
variables here tested should still be present.