Range-Wide Genomic Analysis Reveals Regional and Meta-Population Dynamics of Decline and Recovery in the Grey Seal

Abstract

Wildlife populations globally have experienced widespread historical declines due to anthropogenic and environmental impacts, yet for some species, contemporary management and conservation programmes have enabled recent recovery. The impacts of decline and recovery on genomic diversity and, vice versa, the genetic factors that contribute to conservation success or failure are rich areas for inquiry, with implications for shaping how we manage species into the future. To comprehensively characterise these processes in natural systems requires range-wide sampling and international collaboration, particularly for species with wide dispersal capabilities, broad geographic distributions, and complex regional metapopulation dynamics. Here, we present the first range- and genome-wide population genomic analysis of grey seals based on 3812 nuclear SNPs genotyped in 188 samples from 17 localities. Our analyses support the existence of three main grey seal populations centred in the NW Atlantic, NE Atlantic and Baltic Sea, and point to the existence of previously unrecognised substructure within the NE Atlantic. We detected remarkably low levels of genetic diversity in the NW Atlantic population, and demographic analyses revealed a turbulent history of NE Atlantic and Baltic Sea grey seals, with bottlenecks in the Middle Ages and the 20th century due to hunting and habitat alterations. We found some localities deviated from isolation by distance patterns, likely reflecting wide-scale metapopulation dynamics associated with recolonisation and recovery in regions where they were historically extirpated. We identify at least six grey seal genetic populations and reveal marked genetic effects of past declines and recent recovery across the species' range.

Keywords: Halichoerus grypus; conservation genomics; hunting; management units; marine mammals; recovery; top‐predator.

FIGURE 1

Range‐wide population genomic structure of the grey seal inferred by PCA. (A) Map of sampling localities; (B) Range‐wide population structure for PC1‐PC2, suggesting three main genetic clusters; (C) PC1‐PC2 for Northeast Atlantic and Baltic populations only; (D) PC1‐PC2 for Northeast Atlantic populations only. See Figures S7–S10 for additional PC axes. The fraction of total variation in the dataset explained for each PC is provided as a percentage. Localities within a broader region are colour coded with blue from the Northwest Atlantic, orange from the Northeast Atlantic, and red from the Baltic Sea.

FIGURE 2

Grey seal population genomic structure assessed by admixture analysis in NGSadmix for K2‐6, see Figure S11 for K6‐17. Arrows below K = 6 indicate grey seals that are migrants or admixed individuals between different regional populations.

FIGURE 3

Comparison of standardised F _ST values with geographical distances between localities to test for isolation by distance across the grey seal's range (A), as well as within the Northeast Atlantic (B) and Baltic Sea (C).

FIGURE 4

Connectivity and diversity of grey seals inferred from (A) effective migration parameter (N _m) assessed with divMigrate and (B) genetic diversity estimated as the proportion of heterozygous sites per individual. The legend indicating the sampling locality region is applicable to both subplots. The arrow weight legend for N _m indicates the relative strength of effective migration. Black arrows indicate effective migration between different regions while effective migration within a region is coloured according to the region.

FIGURE 5

Demographic analyses for the NE Atlantic (orange) and Baltic Sea (red) regions for the past (A) 200 and (B) 20 generations using GONE (Santiago et al. 2020). The NW Atlantic region was excluded from this analysis due to a limited sample size. Forty iterations were run excluding 10% of the population with each iteration to calculate a mean (bolded line) and 95% confidence intervals (shaded ribbons).