The Effect of Temporal and Environmental Conditions on Catch Rates of the Narrow-Barred Spanish Mackerel Setnet Fishery in Khanh Hoa Province, Vietnam
Bibliographic record
Abstract
Small-scale inshore fisheries significantly contribute to the total landing volumes and have an important role in Vietnamese socioeconomic development, food security, livelihoods, and social well-being. The setnet fishery has been used throughout coastal communities of Vietnam for many decades. Being a passive fishing gear, the catch efficiency of setnet depends on various conditions such as fish density, season, oceanography, environment, and others. However, very little information exists about the relationship between catch rates and national conditions. Recognizing this research gap, this study examined the effect of temporal and environmental conditions on the catch rates of the narrow-barred Spanish mackerel (Scomberomorus commerson) setnet fishery using long-term data from 2005 to 2016. Overall, the catch of narrow-barred Spanish mackerel decreased over the course of the study. The generalized additive model (GAM) showed that catch rates were significantly affected by sea surface temperature (SST), which peaked at 27 °C. After this temperature point, the catch rates significantly decreased. Temporal variables also contributed to the catch variation. The setnet caught the highest yield in April and May, and more fish were caught during periods of low nightlight intensity than during high illuminated periods. Our study contributes to the understanding of critical factors affecting the catch rates of valuable species, which helps to determine the optimal fishing process of the setnet fishery within the shifting of marine heatwaves.
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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 | 0.000 | 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".