Pacific Herring Status in 2024 and Forecast for 2025
Bibliographic record
Abstract
Pacific Herring (Clupea pallasii) abundance in British Columbia (BC) is assessed using a statistical catch-age (SCA) model (Martell et al. 2011). In 2017, the Pacific Herring stock assessment included updates to the SCA model, a bridging analysis to support these changes (Cleary et al. 2019), and 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. In 2022, upper stock reference (USR) point options were introduced for the major stock assessment regions (SARs) and this assessment includes estimates of stock status relative to productive period USRs (DFO 2023a). The overall 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) SARs (DFO 2019). Steps included operating model (OM) development (Benson et al. 2022), 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 PRD, CC, SoG, and WCVI in 2023 (DFO 2022, 2023a). This assessment includes new science advice on choice of USR points for four of the five major Pacific Herring SARs: HG, PRD, CC, and WCVI. Note that the SoG SAR is assessed in DFO (2025) using a new modelling framework (Johnson et al. 2024). An analysis of USR options for PRD, CC, SoG, and WCVI was completed in 2022 (DFO 2023a) and provisional USRs based on productive periods identified for each SAR was implemented in the 2022/23 Integrated Fisheries Management Plan (IFMP). Since initiation of the Pacific Herring MSE process, MP evaluations have been included in the annual stock assessment as follows: 1. The 2018 stock assessment included MP recommendations for the SoG and WCVI SARs (DFO 2019). 2. The 2019 stock assessment included MP recommendations for the HG, PRD, and CC SARs, and implemented MP recommendations from previous years for the SoG and WCVI SARs (DFO 2020b). 3. The 2020 stock assessment included updated MP recommendations for the SoG and WCVI SARs, and implemented MP recommendations from previous years for the HG, PRD, and CC SARs (DFO 2021a). 4. The 2021 stock assessment included updated MP recommendations for the PRD and CC SARs, and implemented MP recommendations from previous years for the SoG and WCVI SARs (DFO 2021b). 5. The 2022 stock assessment included updated MP recommendations for the PRD, CC, SoG, and WCVI SARs (DFO 2022). 6. The 2023 stock assessment implemented MPs from previous years for the PRD, CC, SoG, and WCVI SARs (DFO 2024). Note that MPs for HG and SoG are not currently updated through this process. Management measures to support long-term recovery of HG herring are being developed through the HG rebuilding plan process.1MPs for SoG are updated in DFO (2025) using methods from Johnson et al. (2024). This 2024 stock assessment includes MP recommendations for PRD, CC, and WCVI, derived in 2022 by updating herring OM conditioning (Benson et al. 2022) using the historic stock and fishery data from 1951 to 2021 (DFO 2022). There are no new MP evaluations for 2024 (all probability metrics reflect the MP evaluations presented in 2022). 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 2024 and recommend harvest advice for 2025 using simulation-tested MPs to inform the development of the 2024/2025 IFMP, where appropriate. Estimated stock trajectories, current status of stocks for 2024, management procedure options, and harvest advice recommendations from those MPs for 2025 reflect methods of Cleary et al. (2019) and Benson et al. (2022) and, where applicable, recommendations from the aforementioned 2018, 2019, 2020, 2021, 2022, and 2023 MSE analyses (Section “Application of MPs and harvest options for 2025”). This Science Response results from the regional peer review of September 23, 2024 on the 2024/2025 Pacific Herring Stock Assessment, Forecast of Mature Stock Biomass, and Harvest Options for 2025 (HG, PRD, CC, WCVI). 1Haida Gwaii ’íináang | iinang Pacific Herring: An ecosystem overview and ecosystem-based rebuilding plan. Approved by the Minister of Fisheries and Oceans, the Council of Haida Nation and Parks Canada. April 2024. In Press.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".