Patterns of genetic diversity.
We
estimated changes in patterns of genetic diversity between the three
datasets using a variety of metrics using Excel add-on GenAlex V6.5
(Peakall & Smouse 2006; Peakall & Smouse 2012). These include the
percentage of monomorphic loci, expected heterozygosity (He), observed
heterozygosity (ho) and the diversity q-profile of
“effective-number” diversity metrics qD as
Box1 in Sherwin et al. (2017). These are the effective number of alleles
on three scales: allelic richness ((\({}^{0}D\)) or q = 0), Shannon’s
information ((\({}^{1}D\)) or q = 1), and heterozygosity
((\({}^{2}D\)) or q = 2). \({}^{2}D\) from Shannon’s information index
is mathematically intermediate between the number of different alleles,
and the effective number of alleles derived from heterozygosity (Sherwinet al. 2017, 2021); it therefore avoids either the former’s heavy
emphasis on rare alleles (and resulting problems of estimation due to
the likelihood of undetected alleles), or the latter’s very heavy
dependency on common alleles (thus largely ignoring rare alleles which
can be very important for adaptation). Differences ofqD metrics between datasets were assessed using
a Wilcoxon test, with each locus being used as an independent assessment
of genetic diversity. While it is unlikely that all loci were truly
independent, the effect of this non-independence should not be large
enough to impact the findings (Waples et al. 2021).