Outside Pacific Spiny Dogfish Population Modelling in 2025
Bibliographic record
Abstract
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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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".