Modelling entanglement rates to estimate mortality of marine birds in British Columbia commercial salmon gillnet fisheries
Bibliographic record
Abstract
Incidental mortality of marine birds in fisheries is an international conservation concern, including in Canada where globally significant populations of vulnerable diving species overlap with coastal gillnet fisheries. In British Columbia (BC), commercial salmon gillnet fishing effort was historically very high (>200,000 days fished annually in the early 1950's), and although this fishery has declined, over 6,400 days were fished annually in the 2006-2016 decade. Observations of seabird bycatch within the commercial fishery, however, are limited in both scope (comprising <2% of cumulative effort 2001-2016) and in time (being available only from 1995 onwards and only for a small number of areas). Using onboard fishery observer data from commercial, test and experimental fisheries (1995-2016), we developed two models to estimate the number of marine birds captured per set in sockeye (Oncorhynchus nerka) and chum (O. keta) salmon gillnet fisheries employing a Generalized Linear Mixed Modeling (GLMM) approach in a hierarchical Bayesian framework, with observer data post-stratified by fisheries management area and year. Using estimates of total commercial fishing effort (estimated number of sets, 2001-2016) we applied the models to extrapolate annual take for the main bird species (or groups) of interest. Multinomial probability estimates of species composition were calculated based upon a sample of 852 birds identified to species that were associated with sockeye or chum fisheries, enabling estimates (with CIs) of potential numbers of the mostly commonly observed species (common murres (Uria aalge), rhinoceros auklets (Cerorhinca monocerata), and marbled murrelets (Brachyramphus marmoratus)) entangled annually in commercial sockeye and chum salmon gillnet fisheries throughout BC. Conservative estimates of annual losses to entanglement were greatest for common murres (2,846, 95% CI: 2,628-3,047), followed by rhinoceros auklets (641, CI: 549-770) and marbled murrelets (228 CI: 156-346). Populations of all three of these alcids species are currently in decline in BC and entanglement mortality is a conservation concern. Gillnet mortality has been identified as a longstanding threat to marbled murrelet populations, which are recognized as Threatened in the Canada and the United States of America (USA). In addition, 622 (CI: 458-827) birds from 12 other species were estimated to be entangled annually. We conclude that cumulative mortality from incidental take in salmon gillnet fisheries is one of the largest sources of human-induced mortality for marine birds in BC waters, a conservation concern impacting both breeders and visiting migrants.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.041 | 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".