Outside Pacific Spiny Dogfish Population Modelling in 2025
Notice bibliographique
Résumé
Pacific Spiny Dogfish is a long-lived shark species with late maturation and low fecundity resulting in very low productivity. These life-history characteristics require considering historical fishing impacts (e.g., since the 1940s), which constrain recovery potential and extend recovery timelines. Dogfish have been commercially fished since the mid-1870s with fishery dynamics varying over the past 150 years. A notable Vitamin A liver fishery in the 1940s peaked at 31,000 t in 1944. From 1950–1980, there was no targeted fishery. Between 1980 and 2009, a targeted commercial food fishery existed, with peak catches of around 4,000 t in 1988, 2004, and 2005. Since 2010, there has been no targeted fishery. Over the past decade, annual discards (greater than 1,000 t) have exceeded landings (less than 400 t). This assessment developed a two-sex, age-structured population dynamics model fit to fishery and survey catch, abundance indices, and length composition data for Dogfish in Pacific Marine Fisheries Commission (PMFC) major areas 3CD5ABCDE in British Columbia. Due to the species life history, spawning output (number of pups) was used to characterize stock status rather than spawning biomass. The Groundfish Integrated Fisheries Management Plan (IFMP) applies a 6% discard mortality for longline gear and 5% mortality for the first two hours of a trawl tow and an additional 5% mortality prorated for each subsequent hour. These values are lower than those from the literature, so this document considers discard mortality rates from the literature under low, base, and high assumptions: 8–36% for longline, 5–15% for hook and line, 27–86% for gillnet, and 19–56% for trawl. Future work could consider the effectiveness of Groundfish IFMP discard mortality rates in achieving fisheries management objectives. The assessment explored uncertainties related to life-history characteristics, natural mortality (M), discard mortality, the representativeness of abundance indices, the stock-recruit curve shape, and the potential increase in M. The assessment considered one base model, 15 sensitivity models with constant M, and five sensitivity models with increasing M. All models estimated a sharp decline in the spawning output in the 1940s due to the vitamin A fishery, followed by an increase driven by maturation of untargeted juvenile cohorts. A slower decline continued through to 2010, driven by increased fishing and decreasing reproductive output from aging cohorts. Estimated depletion (S/S0, spawning output over unfished spawning output) by 2023 was largely unaffected by alternative assumptions about growth, maturity, discard mortality, index of abundance inclusion, or stock productivity. Current depletion is inferred mainly from the recent decline in population indices and low catches relative to historical levels. Models allowing M to increase stepwise in 2010 fit the steep declines from the Synoptic trawl index, but resulted in a stock that would be unable to replace itself with continued high in the model. A Limit Reference Point (LRP) of 0.2S/S0 and candidate Upper Stock Reference (USR) of 0.4S/S0 are proposed based on the shape of the yield curve and approximate equivalence to DFO (2009) provisional reference points 0.4 and 0.8B/BMSY (biomass at maximum sustainable yield). The assessment furthermore proposes F0.4S0 (the fishing mortality that would take the stock to 0.4 S/S0 over the long term) as a candidate Removal Reference rate. All models estimated the stock to be below its LRP with very high likelihood (> 0.95 probability), placing the stock in the Critical Zone. The base model estimated S/S0 in 2023 to be 0.09 (0.08–0.09 95% confidence interval, CI). Across all constant M models, the median S/S0 was 0.09 with 95% CIs ranging from 0.06–0.12. The base model estimated F/F0.4S0 in 2023 to be 1.5 (1.3–1.6 95% CI). Across all constant M models, the median F/F0.4S0 was 1.5 with 95% CIs from 0.7–12.8. Spawning output was projected to remain below the LRP with very high likelihood in 2024– 2028 across all models and catch levels, including zero catch. Projections from 2024 to 2028 carried forward the average dead catch (landed Dogfish plus those assumed to die from discard mortality) ratios among the fleets calculated over the last five years. The maximum dead catch with ≥ 95% probability of F < F0.4S0 ranged from 0 t (low productivity scenario) to 250 t (high productivity scenario). In the base scenario, the maximum dead catch to maintain ≥ 95% probability of F < F0.4S0 was 150 t. Applying the low, base, and high discard mortality rates to average reported catch (~ 861 t) over the last five years resulted in 160 t, 315 t, and 423 t of dead catch per year. The limited productivity of Dogfish, estimated population size, and steep declines in two of three survey indices suggest that catches should be lower than the current 12,000 t total allowable catch to increase spawning output and achieve a high probability of F < F0.4S0. Key challenges in modeling Outside Dogfish population dynamics included a lack of early stock indexing data, difficulty estimating density-dependence in the stock-recruit curve, uncertainty in discard mortality rates, and differing rates of decline in three major survey indices. It is suggested that the assessment is revisited in approximately five years, with stock monitoring through population indices in the BC groundfish data synopsis reports in the interim.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,007 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».