Application of multimodel approach to assessing the stock status of anadromous Dolly Varden (Salvelinus malma malma) from the Rat River, Northwest Territories, Canada
Bibliographic record
Abstract
The northern form of anadromous Dolly Varden (Salvelinus malma malma) from the Rat River has sustained an important subsistence fishery for Gwich’in and Inuvialuit communities situated in the Mackenzie Delta, Northwest Territories, Canada. During the late 1970s and early 1980s, declines in catches and the size of fish captured in the subsistence fishery prompted a concern that the population was experiencing reductions in population abundance. Consequently, this prompted the development of an annual community-based fisheries-dependent monitoring program for Rat River Dolly Varden. Implemented in its current form in 1995, the time series of subsistence catch and biological information were collected from three long term fixed locations during the seasonal return migration. Information on aquatic environmental conditions (water level, turbidity, debris content, and temperature), fishing characteristics (mesh size, length of the gillnets and fishing duration), and catch per unit effort (CPUE) was collected. In this study, we applied generalized linear mixed models and zero-augmented models to standardize the CPUE time series (1996–2014) associated with environmental variables and fishing behaviour and optimize quantitative model-derived estimates of population dynamics parameters. Multimodel inference indicated the best model for CPUE standardization was the zero-inflated Hurdle. Using the standardized CPUE time series, subsistence harvest statistics, and biological data, we structured three stock assessment models: depletion-based stock reduction analysis, surplus production model, and integrated statistical catch-at-age. Applying the model parameter weighting method, we assessed the optimal values (median ± standard deviation) of MSY (maximum sustainable yield), NMSY (population abundance at MSY) and FMSY (fishing mortality rate at MSY) for Rat River Dolly Varden between 1995–2014 were 1,301 ± 188 fish, 10,813 ± 1,555 fish, and 0.18 ± 0.02 per year, respectively. Our results indicated that during the late 1990s, the Rat River Dolly Varden stock was likely over-harvested, but since then the voluntary reduction of subsistence catches has optimistically benefited the gradual recovery of the anadromous population abundance in the western Arctic.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".