2.4.1 Threshold values for indicators
Threshold values for indicators are regarded as helpful in management to
evaluate rates of change (Maria Jansson, SwAM, pers. comm.). Prosed
threshold values for the ΔH indicator relate to the
recommendation that in 100 years, a population should retain at least
95% of its heterozygosity (Allendorf & Ryman, 2002). The proposed
thresholds values for this indicator are: less than 0.05% reduction per
year, assuming constant rate of change (reflecting retention of c. 95%
heterozygosity after 100 years); this rate of reduction is suggested to
reflect status of color green for “Good” (Figure 3). A rate of
reduction between 0.06-0.3% per year (reflecting expected retention of
c. 75-94% heterozygosity over 100 years) is proposed to reflect status
“Warning”/yellow where further investigation of the reason for
reduction is warranted. Finally, a reduction rate of more than 0.3% per
year (resulting in ≤ 75% of genetic variation expected to be retained
after 100 years) reflects status red alert where prompt measures are
called for to understand the reason for decline and thereafter taking
immediate steps to halt the reduction and restore genetically safe
conditions.
Here, we apply indicator ΔH in each of the identified populations
(that occur in samples at both points in time) as well as to the
metapopulations that they belong to. Genetic diversity was measured as
expected heterozygosity
(H E),
observed heterozygosity (H O), allelic richness
(A R), number of alleles per locus
(N A), and proportion of polymorphic loci
(P L), and testing for potential changes was done
by t-tests and non-parametric Wilcoxon matched pairs tests. In cases
with statistically significant change, we translate the difference
between the two points in time approximately 40 years apart (details on
time span between samples in Table S1) into an annual change. Depending
on the observed rate of change we translate it into either of the three
indicator signals – green, yellow, or red (i.e., “Good”, “Warning”,
or “Alarm”). If genetic diversity within sampling localities does not
change (no statistically significant change) or with a statistically
significant increase over time we consider the ΔH indicator as
green/“Good”. We apply the same threshold values for annual genetic
reduction (i.e., ≤0.05%; 0.06-0.3%; ≤0.3%; Figure 3) for not onlyH E but also for the other measures of genetic
diversity (H O, A R,N A, P L).
Suggested thresholds for the N e indicator are
based on the conservation genetic rule of thumb thatN e≥50 and N e ≥500 is
necessary for a population’s short term and long-term survival,
respectively (Franklin, 1980; Jamieson & Allendorf, 2012). The proposed
thresholds are: N e≥500 (“Good”),
50<N e<500 (“Warning”), andN e<50 (“Alarm”), and should apply to
single isolated populations as well as to metapopulations. TheN e of local subpopulations of metapopulation
cannot be ignored, however. Rather, it is important that gene flow is of
a magnitude that assures that sufficient levels of genetic diversity
reaches the population so that the adaptive potential is maintained.
Laikre et al. (2016) suggested that the realized, local effective sizes
of metapopulations should also reflect inbreeding rates that are so low
that realized local N e≥500 for long term
viability to be attained.
In practice, however, it is not straightforward to estimate theN e that reflect the actual rate of inbreeding
(N eI) and/or loss of additive genetic variance
(N eAV) in substructured populations (Hössjer et
al., 2016; Ryman et al., 2014, 2019). Here, we useN e estimates from both the temporal
(N eV) and linkage disequilibrium methods
(N eLD; Section 3.2) and base classifications on
the estimate of these two that generally is the largest, in line with
recommendations for non-isolated populations (Ryman et al., 2019). We
apply this indicator to metapopulations as well as to separate
subpopulations.
For the ΔF ST indicator we are aware of no
previously suggested guideline or rule of thumb. We apply and extend the
proposal from Johannesson and Laikre (2020) that without detectable
change of F ST among populations over time, the
status of this indicator is classified as “Good” (Figure 3). With an
increase of F ST between the two points in time
that reflect a c. 25% decrease of genetic exchange between populations
(number of migrants is reduced by 25%) this is classified as
“Warning”. A decrease of F ST is expected with
increase of gene flow. Such increase can be warranted following
management activities to connect previously fragmented populations.
However, decrease of F ST can also be an effect of
homogenization following e.g. release activities. Such activities are
not expected to be carried out in the present case since all monitored
lakes are located in protected areas. However, large scale release
activities resulting in genetic homogenization have been documented in
e.g. Baltic salmon populations (Östergren et al., 2021). Thus, because
decreased divergence can also reflect a genetic threat, we propose (in
line with Johannesson & Laikre, 2020) that anF ST reduction representing c. 50% increase of
gene flow should classify as a “Warning” in cases where unwanted gene
flow can have occurred. With a ΔF ST reflecting a
50% decrease of the number of migrants or a 100% increase in genetic
exchange (number of migrants) this indicator is classified as “Alarm”.
Further, if one or more local population goes extinct over the
monitoring period this indicator is also classified as “Alarm”. We
note that these proposed limits are highly subjective and “forgiving”
with respect to changes of connectivity.
We apply the following approach (described in detail in Appendix S1) for
converting a statistically significant ΔF ST into
an indicator of change in genetic exchange (migration) between
subpopulations. Thus, we translate the observedF ST among subpopulations at the first point in
time (here denoted “past” and referring to the 1970-80s samples) to
the expected number of migrants by assuming an island model in
migration-drift equilibrium. This hypothetical island model has the same
number of subpopulations as the metapopulation considered, and the
subpopulation N e is set to the harmonic averageN e over those subpopulations. In the next step we
calculate limiting values for change of migration rates. Here we
consider a reduction of migration by 25% or 50% to correspond to
yellow/warning or red/alarm, respectively. Similarly, we consider an
increased migration rate of 50% or 100% to reflect yellow/warning or
red/alarm. Finally, we translate the limiting values of migration rates
into F ST values and compare them to the
empirically observed F ST at the second time point
(here denoted “present” and referring to the 2010 samples).