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).