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. 2020 May 17;10(12):5651-5669.
doi: 10.1002/ece3.6306. eCollection 2020 Jun.

Small coastal streams-Critical reservoirs of genetic diversity for trout (Salmo trutta L.) in the face of increasing anthropogenic stressors

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Small coastal streams-Critical reservoirs of genetic diversity for trout (Salmo trutta L.) in the face of increasing anthropogenic stressors

R Andrew King et al. Ecol Evol. .

Abstract

We used microsatellite markers to investigate levels and structuring of genetic diversity in trout (Salmo trutta L.) sampled from 16 rivers along the south coast of Cornwall in southwest England. This region is characterized by many small coastal streams with a few larger catchments. At a regional level, genetic structuring of contemporary populations has been influenced by a combination of events, including the last Ice Age and also more recent human activities over the last millennium. All populations are shown to have gone through strong genetic bottlenecks, coinciding with increased exploitation of mineral resources within catchments, beginning during the Medieval period. At more local levels, contemporary human-induced habitat fragmentation, such as weir and culvert construction, has disproportionally affected trout populations in the smaller catchments within the study area. However, where small catchments are relatively unaffected by such activities, they can host trout populations with diversity levels comparable to those found in larger rivers in the region. We also predict significant future loses of diversity and heterozygosity in the trout populations inhabiting small, isolated catchments. Our study highlights how multiple factors, especially the activity of humans, have and continue to affect the levels and structuring of genetic diversity in trout over long timescales.

Keywords: Salmo trutta; bottleneck; habitat fragmentation; microsatellite; migration barriers.

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Conflict of interest statement

None declared.

Figures

FIGURE 1
FIGURE 1
Map showing the sampling location of Salmo trutta in southwest England. Inset shows Britain with Cornwall highlighted in black. Full site details are given in Table 1
FIGURE 2
FIGURE 2
Results of the STRUCTURE analysis for the 26 south Cornwall samples of resident trout: top panel—all populations (K = 2), middle panel—western populations (K = 6), and bottom panel—eastern populations (K = 4)
FIGURE 3
FIGURE 3
Correlation between geographic distance (km) and genetic distance (linear F ST) for (a) the full data set (r 2 = .003, p = .327), (b) the larger rivers data set (removing the six outlier small stream populations: r 2 = .193, p = .001), and (c) data for trout from the River Fowey only (r 2 = .146, p = .119)
FIGURE 4
FIGURE 4
Contemporary and historical gene flow diagrams based on the results of BayesAss and migrate‐n, respectively. Rivers abbreviations are as given in Table 1. Rivers are colored in shades of red and green representing the rivers belonging to the western and eastern groups, respectively, as identified in the STRUCTURE analysis (Figure 2). Arrow direction represents direction of gene flow between rivers. Bumps in the contemporary plot represent self‐assignment of fish to their own river
FIGURE 5
FIGURE 5
Plot showing predicted future reductions in observed heterozygosity (H O), compared to current levels based on Linkage Disequilibrium (LD) and sibship‐based estimates of effective population size (N e). Red and orange boxplots show the predicted reductions in HO for the larger, non‐outlier rivers and the outlier streams (Helford River, Kennall, Percuil, Portmellon, Par, and Polperro), respectively, using LD‐derived N e, while blue and light blue boxplots show the predicted reductions in HO for non‐outlier and outlier rivers, respectively, using sibship‐derived N e
Figure A1
Figure A1
Discriminant Analysis of Principal Components (DAPC) analyses for trout from 16 south Cornish rivers. Each dot represents a sampled individual fish and rivers are coloured in shades of red and green to represent the rivers belonging to the western and eastern groups, respectively, as identified in the STRUCTURE analysis (Figure 2). Scatter plots representing DAPC1 v DAPC 2 (a, c, e) and DAPC1 v DAPC3 (b, d, f). (a and b) scatter plots for all 16 rivers (N inds = 1077); (c and d) first hierarchical analysis (N rivers = 12, N inds = 881), removing samples from the Helford, Portmellon, Percuil and Kennall rivers; and (e and f) second hierarchical analysis (N rivers = 10, N inds = 801), removing samples from the Helford, Portmellon, Percuil, Kennall, Par and Polperro rivers
Figure A2
Figure A2
Results for Queller & Goodnight’s (1989) relatedness statistic, as calculated in GenAlEx v6.502. Black dots—mean intra‐population relatedness (±95% CIs); red dots—upper and lower 95% confidence intervals about the null hypothesis of no difference in mean relatedness within rivers as determined by permutation
Figure A3
Figure A3
VarEff analysis of the ten population groupings identified from the STRUCTURE analyses. Plots show the posterior density distribution for the log current effective population size (black lines) and for 300 generation ago (grey lines)
Figure A4
Figure A4
Examples of barriers in four streams in south Cornwall. Clockwise from top left: the mouth of the Mevagissey Stream; a canalised section of the Portmellon stream; the mouth of the Portmellon stream; the Polperro flowing through one of several culverts in Polperro village; heavily silted impounded section of the Kennall River at the Kennall Vale gunpowder works; barrier to upstream movement of trout, Kennall Vale.

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