Assessment of carrying capacity for bivalve mariculture in subtropical and tropical regions: the need for tailored management tools and guidelines
Bibliographic record
Abstract
Abstract In a context of increasing global food demand, the aquaculture sector, and more particularly bivalve mariculture, has expanded significantly. While the impact of bivalve mariculture was initially overlooked, it is now widely recognized that this industry can significantly impact the ecosystem and its services. Carrying capacity assessment tools have been developed accordingly and have proved to be a useful and efficient aid for mariculture management. However, carrying capacity assessment tools have been mostly designed and implemented in developed temperate countries, while bivalve mariculture is mainly expanding today in tropical and subtropical zones. To what extent the existing carrying capacity assessment tools are suited for use in tropical and subtropical regions has received little attention, and thus constitutes a major issue. The present review aims to fill this gap and highlights the key points to consider for the carrying capacity assessment of bivalve mariculture in tropical and subtropical regions. In line with the requirements for the sustainable development of human activities, and increasing recognition of the need for better integration of social aspects in the management processes, carrying capacity assessment should be undertaken in a more holistic way. Thus, the social, economic and environmental aspects are taken into account in our analysis. A step‐process plan for the sustainable management of bivalve mariculture in tropical and subtropical countries, through the assessment of carrying capacity, is proposed and discussed to offer guidance for managers.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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".