Stock assessment of Southwest Pacific blue shark

Citation

Neubauer, P., Large, K., & Brouwer, S. (2021). Stock assessment of Southwest Pacific blue shark. WCPFC-SC17-2021/SA-WP-03 (August 10 2021 Rev.1). Report to the Western and Central Pacific Fisheries Commission Scientific Committee. Seventeenth Regular Session, 11–19 August 2021. Electronic meeting.

Summary

This analysis assesses the south Pacific blue shark stock in the Western and Central Pacific Ocean (WCPO) hereafter referred to as the Southwest Pacific.

Blue shark are caught in large numbers in a range of fisheries in the Southwest Pacific. Blue shark in the Southwest Pacific are thought to make up a single stock, but an initial attempt at assessing this stock in 2016 was not successful. Here, we used a range of CPUE indices, length frequencies and predicted catch scenarios to infer stock status and trends of blue shark in this region.

The stock assessment was set up in Stock Synthesis as a three-fleet model, using an approach with fleets covering: high-latitude fisheries on juveniles and adults around New Zealand and South-Eastern Australia; the EU-Spain mid-latitude fishery that operates to the north and east of New Zealand; and, a high latitude and high seas fishery capturing adult sharks. The model was run for a 26 year period from 1995 to 2020, with the start year taken to be 1995 due to highly uncertain catches prior to this period. The catches were reconstructed from observer data and were comparable to previous analyses, albeit at lower median estimated total catches. The catch reconstruction model also produced high uncertainties in catches between the mid 1990s and early 2000s. A range of catch scenarios were applied in this assessment to reflect these uncertainties.

In addition to catches, discard rates are uncertain for all but the most recent (i.e., last ~5) years in the time series, as are catches from the driftnet fisheries that operated in south Tasman and north-east Australian waters in the 1980s. Additional uncertainties pertain to individual CPUE time series from log-sheet data, as any individual time series is likely to suffer from changing degrees of under-reporting (although we attempted to address this problem by grooming out vessels with poor reporting records).

To adequately reflect uncertainties, we ran an extensive sensitivity grid with nine grid axes, covering catch, discard, CPUE and biological assumptions, totalling over 3500 models. Across the sensitivity grid, a large majority of stock trajectories showed a decline from relatively high stock levels in 1995, reflecting increasing effort during that time, followed by a steady increase in biomass as effort plateaued and discard rates increased, especially in lower latitude fisheries. The mean outcome suggested a current stock status near SB0, with a range of outcomes between 0.58 to 1.49SB0. Dynamic surplus production models provided additional support for the conclusion that the stock has likely recovered from low levels in the mid to late 2000s to levels close to the estimates of biomass under average recruitment.

CPUE series, although in agreement about recent increases in the stock, were in conflict with regards to stock size (average recruitment) and, consequently, were the largest drivers of differences among sensitivity runs. Removing the EU-Spain time series or removing initial years from the New Zealand index led to lower estimates of stock status and altogether lower stock trajectories, while including all indices with equal weight led to consistently higher stock status outcomes.

Although the sensitivity analysis highlighted a number of uncertainties, we found a number of consistent patterns in the outcomes:

  • The most influential axes of uncertainty was the weighting and inclusion of CPUE indices; high uncertainty remains in many model outputs across the sensitivity grid.

  • The stock biomass was low throughout the region through the early 2000s following the expansion of longline fishing effort in the region.

  • Estimates across the uncertainty grid largely indicated that the stock has recovered from lower biomass levels.

  • 90% of model runs indicate that fishing mortality at the end of the assessment period was below FMYS and 96% of model runs show that the biomass is above SBMYS, with high estimated spawning biomass levels near those expected under F=0 and average recruitment across model runs, and minimum estimated SB of 0.3SB0.

  • Fishing mortality has declined over the last decade and is currently relatively low. This is largely as a result of most sharks being released upon capture in the majority of longline fleets.

  • Finally, considered against all conventional reference points the stock on average does not appear to be overfished and overfishing is not occurring.

Given some of the fundamental uncertainties highlighted in this assessment, we recommend:

  • Increased effort to re-construct catch histories for sharks (and other bycatch species) from a range of sources. Our catch reconstruction models showed that model assumptions and formulation can have important implications for reconstructed catches. Additional data sources, such as log-sheet reported captures from reliably reporting vessels, may be incorporated into integrated catch-reconstruction models to fill gaps in observer coverage.

  • Dynamic/non-equilibrium reference points, such as SBF=0 be investigated for shark stock status, as they may be more appropriate for fisheries with uncertain early exploitation history and strong environmental influences.

  • Additional tagging be carried out using satellite tags in a range of locations, especially known nursery grounds in South-East Australia and New Zealand, as well as high seas areas to the north and east of New Zealand, where catch-rates are high. Such tagging may help to resolve questions about the degree of natal homing and mixing of the stock.

  • Tagging may also help to obtain better estimates of natural mortality, if carried out in sufficient numbers. This could be taken up as part of the WCPFC Shark Research Plan to assess the feasibility and scale of such an analysis.

  • Additional growth studies from a range of locations could help build a better understanding of typical growth, as well as regional growth differences. Current growth data are conflicting, despite evidence that populations at locations of current tagging studies are likely connected or represent individuals from the same population.

  • Genetic/genomic studies could be undertaken to augment the tagging work to help resolve these stock/sub-stock structure patterns.