An ecosystem-based management strategy evaluation of harvest control rules for Norwegian spring-spawning herring (<i>Clupea harengus</i> L.)
Bibliographic record
Abstract
Abstract Norwegian spring-spawning herring (Clupea harengus L.) play a vital ecological and socio-economic role in the Northeast Atlantic and Arctic Oceans, with several coastal states and fishing nations participating in the fishery. The stock collapsed in the 1960s due to environmental changes and overfishing, prompting changes in management. A harvest control rule was introduced in a long-term management plan agreed upon by the coastal states in 1999, aiding stock recovery. In 2018, the International Council for the Exploration of the Sea (ICES) conducted a benchmark and management strategy evaluation, leading to a revised long-term management plan implemented in 2019. Although Norwegian spring-spawning herring, as forage fish, are prime candidates for ecosystem-based fisheries management, the current ICES management strategy evaluation omitted ecosystem interactions. Our study employed an ecosystem-based operating model (Atlantis) to test and evaluate four threshold harvest control rules for Norwegian spring-spawning herring, considering uncertainty in recruitment and zooplankton biomass. The candidate harvest control rules included the previous long-term management plan (1999–2018), the current long-term management plan (2019–present), and two harvest control rules that varied the target fishing mortality and spawning stock biomass reference thresholds. In our results, the previous long-term management plan often led to greater long-term Norwegian spring-spawning herring biomass and catch with less catch variation, outperforming the current long-term management strategy. We discuss our findings in the context of balancing the parameterizations of harvest control rule reference points to support long-term catch and stock biomass under an ecosystem context. Incorporating ecosystem models into management strategy evaluation, alongside the more commonly used single-species models, offers a more comprehensive and nuanced understanding of the impacts of alternative fishery strategies when evaluating Norwegian spring-spawning herring harvest control rules. This aligns with ICES objectives for sustainable seafood provision and marine ecosystem understanding.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".