1. INTRODUCTION
Genetic diversity is the basis for species evolution, and high genetic
diversity is vital for adaptation to changing climate, habitats, and
diseases (Bitter et al., 2019; Lai et al., 2019). Genetic diversity
plays a substantial role for ecosystem function, and can affect
ecosystem resilience, stability, and services in a similar manner as
species diversity (Cook-Patton et al., 2011; Yang et al., 2015). Low
genetic diversity increases the risk of extinction (Spielman et al.,
2004; Hellmair & Kinziger, 2014).
International policy, including the UN Convention on Biological
Diversity (CBD; www.cbd.int ), identifies intraspecific diversity
(=genetic diversity within species) as one of the three pillars of
biodiversity that should be identified, monitored, conserved, and
sustainably used. However, the implementation of this policy has long
lagged behind, and particularly so for genetic diversity (Laikre et al.,
2010; Hoban et al., 2013; Bruford et al., 2017).
The CBD Strategic Plan for 2011-2020 had a goal to safeguard genetic
diversity (www.cbd.int/sp; Goal C);
the Target associated with this goal focusses on cultivated species,
their wild relatives and socio-economically important species. The main
indicator to monitor progress towards this target follows number and
threat status of local animal breeds (Tittensor et al., 2014). So far,
strategic targets and indicators for genetic diversity of wild species
have been missing, but proposals for such measures that can be applied
globally have recently been presented for the CBD “post-2020” global
biodiversity framework (Díaz et al., 2020; Laikre et al., 2020; Hoban et
al., 2020, 2021a). The three pragmatic indicators for genetic diversity
proposed for global use include 1) the proportion of populations within
species with an effective population size Ne≥ 500, 2) the proportion of
genetically distinct populations maintained within species, and 3) the
number of species and populations in which genetic diversity is being
monitored using DNA-based methods (Laikre et al., 2020; Hoban et al.,
2020). Several countries are starting to apply these indicators (Drs.
Jessica da Silva, Alicia Mastretta-Yanes, Henrik Thurfjell, pers.comm.).
Also, several countries have moved forward with respect to monitoring
genetic diversity using DNA-based techniques (i.e., applying Indicator 3
of Laikre et al., 2020/Hoban et al., 2020). Countries in the forefront
include Switzerland where five key species were recently identified for
an ambitious pilot project involving sampling over full species ranges
and using whole genome resequencing (Martin Fischer pers. comm.;
www.gendiv.ethz.ch). In Scotland, a
scorecard method using published information on genetic diversity and
knowledge of experts has been adopted and applied to 26 species
identified as of particular concern (Hollingsworth et al., 2020). In
Sweden, the Swedish Environmental Protection Agency (SEPA) has
prioritized species for monitoring (Posledovich et al., 2020a, b) and
have initiated work on a few of these species. The Swedish Agency for
Marine and Water Management (SwAM) has run a science-management
collaboration to develop a pilot program for monitoring genetic
diversity over contemporary time frames using DNA-based techniques and
three new DNA-based indicators (Johannesson & Laikre, 2020). Here, we
present and apply these indicators for the first time.
Specifically, we map and monitor genetic diversity within and between
populations over time using brown trout in alpine lake systems in
protected areas in central Sweden as a model. The brown trout was
selected due to the availability of temporally separate samples (from
the 1970s and from the 2010s). The species is suitable also because of
its tendency to form genetically distinct populations over even
restricted areas (Bekkevold et al., 2020), thus enabling monitoring of
the between population diversity component. We were particularly
interested in mapping the potential occurrence of multiple, genetically
distinct populations in the same small lake (so-called cryptic sympatry;
Andersson, 2021). Such hidden biodiversity has only been documented in
two cases for brown trout (Ryman et al., 1979; Andersson et al., 2017a;
Saha et al., 2021) but may be more common than currently recognized
because of limited statistical power in detecting them using typically
applied sample sizes (Jorde et al., 2018). Finally, the brown trout
carries a key ecological role in these lakes where it is a top predator
and often the only fish species; its cultural and socio-economic value
is also high (Frank et al., 2011; Marco-Rius et al., 2013).