Science Response : Pacific Herring status in 2023 and forecast for 2024
Bibliographic record
Abstract
Pacific Herring (Clupea pallasii) abundance in British Columbia (BC) is assessed using a statistical catch-age (SCA) model (Martell et al. 2012). In 2017, the Pacific Herring stock assessment included updates to the SCA model, a bridging analysis to support these changes (Cleary et al. 2019), as well as the estimation of stock productivity and current stock status relative to the new limit reference point (LRP) of 0.3SB0 (Kronlund et al. 2017), where SB0 is estimated unfished spawning biomass. The structure of the SCA model has not changed since 2017. In 2016, Fisheries and Oceans Canada (DFO) committed to renewing the current management framework to address a range of challenges facing Pacific Herring stocks and fisheries in BC. Renewal of the management framework included engaging in a management strategy evaluation (MSE) process to evaluate the performance of candidate management procedures against a range of hypotheses about future stock and fishery dynamics. As part of the MSE process, a Canadian Science Advisory Secretariat (CSAS) regional peer review occurred in 2018, where performance of Pacific Herring management procedures (MPs) were assessed against conservation objectives for the Strait of Georgia (SoG) and West Coast of Vancouver Island (WCVI) stock assessment regions (SARs) (DFO 2019). Steps included operating model (OM) development (Benson et al. In press), fitting the OM to Pacific Herring stock and fishery monitoring data (OM conditioning), and closed-loop simulations of MP performance for alternative future natural mortality scenarios. In 2019, DFO initiated the MSE process for the Haida Gwaii (HG), Prince Rupert District (PRD), and Central Coast (CC) SARs (DFO 2020a). Updates to MP evaluations were then conducted for SoG and WCVI SARs in 2020 (DFO 2021a), and for all SARs herein. This assessment incorporates new science advice on choice of upper stock reference (USR) points for four Pacific Herring major SARs (PRD, CC, SoG, and WCVI). An analysis of options was completed in 2022 (DFO In press) and implementation of USRs will occur through the 2022/23 Integrated Fisheries Management Plan (IFMP). To support on-going consultations, five USR options are presented for PRD, CC, SoG and WCVI (Section “Application of MPs and harvest options for 2023”). For these four stocks we also update conditioning of the herring OM (Benson et al. In press) by including stock and fishery data from 1951 to 2021. These updates first appear in DFO (In press). MP evaluations presented in the harvest option tables reflect the latest OM updates. Since initiation of the Pacific Herring MSE process, results have been included in the annual stock assessment as follows: 1. The 2018 stock assessment includes MP recommendations for the SoG and WCVI SARs (DFO 2019). 2. The 2019 stock assessment includes MP recommendations for the HG, PRD, and CC SARs (DFO 2020b), and implements the previous years’ MP recommendations for the SoG and WCVI SARs. 3. The 2020 stock assessment includes an update to MP recommendations for the SoG and WCVI SARs (DFO 2021a), and implements the previous years’ MP recommendations for HG, PRD, and CC SARs. 4. The 2021 stock assessment includes an update to MP recommendations for the PRD and CC SARs (DFO 2021b), and implements the previous years MP recommendations for the SoG and WCVI SARs. MPs are not updated for HG because management measures to support long-term recovery of HG herring are being developed through the rebuilding plan process. This 2022 stock assessment includes MP recommendations for PRD, CC, SoG, and WCVI, derived by updating herring OM conditioning (Benson et al. In press) using the latest historic stock and fishery data from 1951 to 2021. USR options first presented in DFO (In press) are included to support selection of stock-specific USRs for implementation through the 2022/23 IFMP. Management measures to support long-term recovery of HG herring, including rebuilding objectives and USR, are documented in the draft HG herring rebuilding plan.1 Fisheries and Oceans Canada (DFO) Pacific Fisheries Management Branch requested that DFO Pacific Science Branch assess the status of British Columbia (BC) Pacific Herring stocks in 2022 and recommend harvest advice for 2023 as simulation-tested MPs to inform the development of the 2022/2023 IFMP, where appropriate. Estimated stock trajectories, current status of stocks for 2022, management procedure options, and harvest advice recommendations from those MPs for 2023 reflect methods of Cleary et al. (2019) and Benson et al. (In press) and, where applicable, recommendations from the aforementioned 2018, 2019, 2020, and 2021 MSE analyses (Section “Application of MPs and harvest options for 2023”). This Science Response results from the Science Response Process of September 15, 2022 on the Stock status update with application of management procedures for Pacific Herring (Clupea pallasii) in British Columbia: Status in 2022 and forecast for 2023.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.035 | 0.013 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".