Using distribution patterns of small fishes to assess small fish by‐catch in tropical shrimp trawl fisheries
Bibliographic record
Abstract
Abstract Ecologically sound fisheries management and improving future food security require that small fish by‐catch in tropical shrimp trawl fisheries is maintained at, or reduced to, sustainable levels; restricting trawling in particular places, or at particular times, has been suggested as a means for achieving this goal. The purpose of our research was to compare patterns in occurrence, density and body size across depth, latitude and time for four small fish taxa caught as by‐catch in the southernGulf ofCalifornia shrimp trawl fishery:Diplectrumspp.,Prionotus stephanophrys,Pseudupeneus grandisquamisandStellifer illecebrosus. We then used these results to explore the potential for trawler impacts on these taxa, and the possible placement and timing of fishing restrictions to mitigate potential impacts. Our results confirmed, however, the difficulties of regulating such fisheries for multiple by‐catch species, in that their distribution patterns varied in a way that precludes a ‘one size fits all’ solution. The four taxa analysed – only four of the hundreds obtained as by‐catch in this fishery – exhibited distribution patterns at odds with one another. Observed intra‐ and inter‐taxon variations in the relative importance of different spatial and temporal variables in determining occurrence, density and size argues that several permanent trawl closures covering a range of depths and latitudes, and not temporal ones, might be required to mitigate potential trawl impacts on these fishes. Our results also suggested a higher potential for impact onS. illecebrosusthan the other taxa: occurrence and density of the former declined, whereas occurrence or density of the others increased across the study area as the fishing season progressed.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".