Sustainable Fishing Yields of Commercial Fish in Jatibarang Reservoir, Indonesia
Bibliographic record
Abstract
The Nile tilapia (Oreochromis niloticus) is a predominant species that commercially fished in Jatibarang Reservoir.About 72% of the total catch from the Reservoir consists of the Nile tilapia.Fishing activity is intense since a substantial number of fishers, both local and outsiders, have engaged in the fishery for decades.Although restocking of the species has regularly been conducted annualy, the indication of decreasing Nile tilapia stock still exists and has become a concern of the local management authorities.This research aims to evaluate and determine the sustainable potential yield of Nile tilapia in the Jatibarang Reservoir using the Length-Based Thomson & Bell prediction model as part of the improvement of previous studies on carrying capacity and economic beneficiary.A series of observations on biological data of individual species, such as the length-weight, gonadal maturity stage, and sex differentiation, were collected daily for nine months, from March to December 2018 were performed as a database for the analysis.The predicted population parameters indicated that the asymptotic length (L) and growth rate (K) are 58.2 cm and 0.51/year, respectively.The relative fishing mortality (F/M) is 0.39, indicating a relatively low harvest rate.The estimated Maximum Sustainable Yield for the Nile tilapia in Jatibarang Reservoir is about 9.76 tons/yr.This result would contribute to developing the baselines for the local fisheries management plan of Jatibarang Reservoir by the local authority to support the alternative source of income for surrounding communities.
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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 | 0.000 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".