Mangroves enhance local fisheries catches: a global meta‐analysis
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Mangroves are among the most productive ecosystems in tropical and subtropical regions. Historically, mangroves are assumed to support artisanal fisheries, leading decision‐makers to protect mangroves based on this premise. However, this relationship remains unclear, despite positive correlations obtained in different geographical regions. Here, we provide the first meta‐analysis of the mangroves–fisheries linkage at a global level. After conducting a systematic review, 23 publications containing 51 studies estimating the mangrove–fishery linkage were obtained. A random effect model was used to estimate the effect size (Pearson's correlation coefficient) of each individual study as well as the overall effect size. We found strong evidence for the mangrove–fishery linkage with an overall effect size of r = 0.72 (95% CI : 0.61–0.81), and substantial heterogeneity was observed ( Q = 143.88, df = 50, P < 0.01). The countries where the studies were carried out were the only significant moderator ( Q M = 26.07, P < 0.01), while fisheries types ( i.e . crab, fish, shellfish, prawn and total) and global regions were not good predictors of the relationship. Our results show that mangrove area is a good predictor of fishery catches overall, confirming the importance of conserving such habitats.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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 it