4 | APPLICATION OFQST–FST COMPARISONS TO
PLANT BIOLOGY
Many Q ST–F ST comparisons
falling roughly into seven categories (viz . local adaptation,
sexual selection, evolutionary stasis, human-induced evolution,
artificial selection, biological invasions, and management and/or
conservation) can be applied to plant biology, have been conducted to
infer ecological and evolutionary processes. Perhaps the most commonly
studied issue is to identify natural selection as a cause of broad-scale
clinal variation in morphological and life-history traits (local
adaptation, e.g., in Campanulastrum americanum [Prendeville et
al., 2013], in Helianthus maximiliani [Kawakami et al.,
2011], in two subspecies of Antirrhinum majus [Marin et al.,
2020] or various tree species [Savolainen et al., 2007]). As an
example of sexual selection, Yu et al. (2011) detected sex-specific
selection as the cause of the evolution of sexual dimorphism inSilene latifolia . Using Pinus pinaster as a study species,
Lamy et al. (2011) identified selective constraints explaining
phenotypic uniformity across species distributions (evolutionary stasis,
i.e., canalization or uniform selection).
Other examples are the demonstration of how human-induced habitat
changes can either cause or impair adaptation (human-induced evolution,
e.g., in Thlaspi caerulescens [Jiménez-Ambriz et al., 2007]
and Arabidopsis halleri [Meyer et al., 2010]). In addition,
studies on how selective breeding shapes diversification and population
structuring of crop species (artificial selection) have been conducted
in Oryza sativa (Sreejayan et al., 2011) and Zea mays(Pressoir & Berthaud, 2004). By performingQ ST–F ST comparisons
between the invasive species’ native and invasive ranges (biological
invasions), several researchers provided information on the evolution of
invasiveness and the adaptive potential of invasive plant species such
as Hypericum canariense (Dlugosch & Parker, 2007),Ambrosia artemisiifolia (Chun et al., 2011), Lythrum
salicaria (Chun et al., 2009), and Geranium carolinianum (Shirk
& Hamrick, 2014).
For management purposes, Gravuer et al. (2005) identified units or
populations suitable for translocation in Liatris scariosa .
Furthermore, some authors demonstrated that setting conservation
priorities should not be based only on neutral marker diversity and thatQ ST–F ST comparisons can
be used to identify populations that are suitable for translocation inArabis fecunda (McKay et al., 2001) and Araucaria araucana(Bekessy et al., 2003). The last two issues, i.e., conservation and
management, will be the focus of the next section.
5 |
INSIGHTS INTO CONSERVATION AND RESTORATION DERIVED FROMQST–FST COMPARISONS
Because F ST estimates are significantly lower in
trees than in most herbaceous perennials and annuals, Chung et al.
(2020) recommended that conservation genetic strategies be designed
differently for tree species versus other types of plant species. That
is, seeds of most tree species (which generally show low values ofF ST) could be sourced from a few populations
distributed across the species’ range, whereas seeds of rare herbaceous
species (often with high F ST values) should be
taken from many populations to capture the highly localized genetic
diversity. Based on a small body of available data on seed plant species
(data from Lamy et al., 2012; De Kort et al., 2013; Leinonen et al.,
2013), on average, Q ST is higher thanF ST in common forest tree species, indicating
that their quantitative traits have been subject to diversifying
selection and local adaptation (Kremer et al., 1997; Savolainen et al.,
2007). It has been suggested that more populations would be needed to
preserve enough AGV for adaptively significant quantitative traits than
for NGV, particularly in trees (McKay et al., 2001; Hamrick et al.,
2006; Chung et al., 2020). More specifically, conservation practitioners
may need information about how to capture most AGV and NGV based on
known levels of NGV and AGV from population or conservation genetic
studies.
Population(s) to be protected in situ or to be sampled for seed banking
purposes could be estimated using the formulae: PNGV = 1 –F ST (orG ST)N for NGV, where
PNGV = proportion of NGV captured by sampling, N = number of
populations (Ceska et al., 1997; Hamrick et al., 2006) and PAGV = 1 –Q STN for AGV, where PAGV
= proportion of AGV captured by sampling. However, one should be aware
that if there are more than two alleles per locus for the neutral
markers, then Q ST and G STare on different scales, and the formulae PAGV = 1 –Q STN and PNGV = 1 –F STN cannot be
interpreted in the same way (J. D. Nason, pers. comm.). For
multi-allelic markers, it depends on µ whether this is
problematic. In addition, as Ф ST (a function of
the among-population variance component and the within-population
component, which is based on genetic distances among alleles for the
neutral markers) is conceptually similar to Q ST,
it is advisable to use Ф ST rather thanG ST, F ST, or θ(Edelaar et al., 2011). The calculations for 99% capture of AGV and NGV
can be key to figuring out ideal sample sizes, especially when resources
are limited. Based on the average values of De Kort et al. (2013) forF ST and Q ST (annuals,n = 19, 0.308 versus 0.451 [i.e., Q ST is
about 1.5 times greater than F ST]; herbaceous
perennials, n = 14, 0.267 versus 0.299
[Q ST is about 1.1 times greater]; woody
perennials, n = 18, 0.074 versus 0.269
[Q ST is about 3.6 times greater];
recalculated from De Kort et al.,
2013), to capture 99% of NGV and AGV for woody perennials, just two and
four populations would be needed using the abovementioned formulae,
respectively. On the other hand, on average, four populations of
herbaceous perennials would be needed to secure 99% of NGV and AGV,
respectively, because the average difference betweenQ ST and F ST is small
(0.032). For annuals, on average, four and six populations are needed to
secure 99% of NGV and AGV, respectively.
We apply this approach to a real-life example: for the widespread treePopulus balsamifera , Keller et al. (2011) reported a meanФ ST value of 0.067 estimated from 310 nuclear SNP
loci and a mean Q ST value of 0.421 (range =
0.127–0.832) obtained from 13 ecophysiological and phenological traits
originating from 20 populations across North America. To capture 99% of
NGV, two populations of this tree would be needed using the above
formula. When we apply the mean Q ST value to the
formula, at least six populations would be necessary to capture the same
level of AGV. However, the value of Q ST depends
on the trait under consideration: for traits with a highQ ST, more populations should be sampled than for
traits with a low Q ST. Given this, the prudent
thing would be not to use the average Q ST but the
maximum Q ST in these calculations. If this logic
is applied to P. balsamifera , as for bud setQ ST = 0.832, then up to 25 populations would need
to be targeted to maintain enough variation for the trait. This does not
mean that NGV is not essential; there is probably a reservoir of genetic
variation in every population that is neutral now but may be selectively
important if environmental conditions change. Furthermore, NGV can be
very informative about the populations’ past demography which is often
of interest in conservation biology (Frankham, 2015; Allendorf, 2017;
DeWoody et al., 2021; García-Dorado & Caballero, 2021).
The application of the above formulae to plants with different life
forms, as well as the example of Populus balsamifera , suggests
that conservation and management policies or actions based solely onF ST could potentially be misleading. Again, these
findings stress that guidelines and conservation genetic strategies
should be designed based on genetic information on both NGV and AGV
together for tree and herbaceous (whether perennial or annual) species.
In addition, managers or practitioners should design restoration and
conservation strategies by knowing that, on average,Q ST is about 3.6, 1.5, and 1.1 times greater thanF ST in woody plants, annuals, and herbaceous
perennials, respectively.
To summarize, F ST estimates appear to be more
closely related to AGV than within-population genetic diversity metrics
(e.g., H e,%P , or AR ) in seed plant species. Thus,F ST should be considered as a more predictable
parameter for conservation and restoration purposes. Together with the
metrics of H e, %P , or AR , the
particular degree of F ST (i.e., low, moderate, or
high) is important for prioritizing populations for collection and
identifying appropriate sources for reintroductions (Hamrick & Godt,
1996; Ottewell et al., 2016; Chung et al., 2021). Thus, the importance
of the proper consideration of F ST information
(and Q ST, if available) in conservation
management cannot be overstated, particularly when it comes to annuals
and herbaceous perennials.