Fisheries genomics of snapper (Chrysophrys auratus) along the west Australian coast

Abstract

The efficacy of fisheries management strategies depends on stock assessment and management actions being carried out at appropriate spatial scales. This requires understanding of spatial and temporal population structure and connectivity, which is challenging in weakly structured and highly connected marine populations. We carried out a population genomics study of the heavily exploited snapper (Chrysophrys auratus) along ~2600 km of the Australian coastline, with a focus on Western Australia (WA). We used 10,903 filtered SNPs in 341 individuals from eight sampling locations to characterize population structure and connectivity in snapper across WA and to assess if current spatial scales of stock assessment and management agree with evidence from population genomics. Our dataset also enabled us to investigate temporal stability in population structure as well as connectivity between WA and its nearest, eastern jurisdictional neighbour. As expected for a species influenced by the extensive ocean boundary current in the region, low genetic differentiation and high connectivity were uncovered across WA. However, we did detect strong isolation by distance and genetic discontinuities in the mid-west and south-east. The discontinuities correlate with boundaries between biogeographic regions, influenced by on-shelf oceanography, and the sites of important spawning aggregations. We also detected temporal instability in genetic structure at one of our sites, possibly due to interannual variability in recruitment in adjacent regions. Our results partly contrast with the current spatial management of snapper in WA, indicating the likely benefits of a review. This study supports the value of population genomic surveys in informing the management of weakly structured and wide-ranging marine fishery resources.

Bioregional boundaries and genomically-delineated stocks in snapper (Chrysophrys auratus) from southeastern Australia

“…At a broad scale, the population structure of snapper in southeastern Australia is predominately shaped by two genetic discontinuities (i.e., the Murray River Mouth and the Vic-NSW border) which correspond to the boundaries between the three biogeographic provinces in the region – Flindersia, Maugea and Peronia (see Figure 1). Coastal distance was not a dominant driver of genetic distance for snapper in this region, which contrasts with recent work done in the western part of the species’ range (Bertram et al, 2022). Very few published population genetic studies on finfish in southeastern Australian with high dispersal potential across all life stages have reported structuring corresponding to these biogeographic boundaries.…”

“…These results indicate the persistence of the genomic signal of local recruitment and fidelity of adults associated with these two important spawning sites. This result is concordant with similar work done in the western part of the range of snapper at the major spawning site Cockburn Sound (Bertram et al, 2022). Despite the smaller size of the 2010 Northern Gulf St Vincent sample compared to the 2018/19 one (26 vs 39 individuals), it still captured dispersal from the Vic stock into the gulf in the form of a full migrant.…”

“…Despite Spencer Gulf and Gulf St Vincent supporting different spawning aggregations (Fowler, 2016), which reproduce simultaneously during the summertime, as well as the small differences inferred with sPCA, the two localities form part of the same genetic stock. This contrasts with Western Australia and Vic, where major spawning sites are represented by separate genetic stocks (this study and Bertram et al, 2022). It is possible that the Spencer Gulf and Gulf St Vincent spawning groups originated from a single ancestral coastal population during the LGM when the gulfs were dry (James and Bone, 2010).…”

“…Raw sequence reads were put through a bioinformatic pipeline as in Bertram et al (2022) to produce a high-quality SNP dataset. Briefly, raw data was demultiplexed using the process_radtags module of STACKS 2.0 (Catchen et al, 2013).…”

“…As a result, the value of genetic methods in addressing important fisheries management issues has increased in recent years. There are numerous examples in the recent literature where large SNP datasets were able to detect levels of genetic structuring in fishery important marine species for which microsatellite datasets previously could not (e.g., Van Wyngaarden et al, 2017; Silliman, 2019; Petrolo et al, 2021; Bertram et al, 2022).…”