Substantial loss of trawlable biomass and lack of recovery in a marine ecosystem
Bibliographic record
Abstract
Profound changes in species assemblages are occurring in marine ecosystems worldwide and are essential to document. Here we use 51 years (1971-2021) of fishery-independent data from a standardized bottom-trawl research vessel survey (6440 independent fishing locations) in the southern Gulf of St. Lawrence covering 70,091 km² to evaluate trends in marine community structure and trawlable biomass across 122 fish and crustacean taxa. Survey data indicate a substantial decline in biomass and increase in turnover for taxa susceptible to bottom-trawl fishing gear in the southern Gulf of St. Lawrence marine ecosystem that corresponds with the reduction of several predatory fish and a major regime shift around the early 1990's. Unlike other marine regime shift examples, we observe a substantial net loss of trawlable biomass in the community, with limited compensatory response in small fish and crustacean biomass over nearly 30 years following the depletion of predatory groundfish. Overall, this unique case of reduced biomass and shift in community structure highlights the importance of maintaining and analyzing fishery-independent surveys over extended time series. Such information is vital to assessing the state of marine ecosystems and developing plans for recovery, as we face a future of untold challenges in managing marine ecosystems worldwide.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".