Growth Analysis of Rhizophora Mucronata Mangrove in Ngurah Rai Forest Park (Sanur) Bali Province, Indonesia
Bibliographic record
Abstract
Mangrove forests were a typical type of tropical and subtropical forest, growing along beaches or river mouths that were affected by tides. Mangroves were often found in coastal areas that were protected from the onslaught of waves and sloping areas. Mangrove forest ecosystems had the function of absorbing carbon dioxide (CO2) from the air and storing carbon in the form of biomass. This research was conducted in September 2017. This study aimed to determine the growth, carbon stocks and biomass in mangrove forests in the area of Taman Hutan Raya Ngurah Rai (Sanur) Denpasar. Making research plots used the transect method with a size of 20 meters x 50 meters as many as 3 plots along the coast. From the measurement results, the total value of the base area in plot A was 2.37 m2 / tree, branch-free volume was 16.57 m3 / tree, biomass was 13,591 tons / plot, carbon stock was 6,795 tons / plot, the average increment was 0, 29 cm / year / tree. While the results of the measurement of the total value of the base area in plot B was 13.20 m2 / tree, branch-free volume of 14.87 m3 / tree, biomass of 8,420 tons / plot, carbon stock of 4,210 tons / plot, average increment amounting to 0.39 cm / year / tree. Furthermore, the total value of the base area in plot C was 12.96 m2 / tree, branch-free volume was 14.83 m3 / tree, biomass was 8,265 tons / plot, carbon stock was 4,132 tons / plot, the average increment was 0, 40 cm / year / tree. The salinity value of plot A = 0.10% with a pH of 6.68, plot B = 0.09% with a pH of 6.78 and plot C = 0.08% with a pH of 6.78. Based on the calculation results, it could be concluded that the total biomass value of plot A = 13,592 tons / plot, plot B = 14,866 tons / plot and plot C = 8,265 on / plot and then carbon stock plot A = 6,796 tons / plot, plot B = 8,420 tons / plot and plot C = 4.133 tons / plot. The average increment per tree obtained values for plot A = 0.29 cm / tree / year, plot B = 0.39 cm / tree / year and plot C = 0.40 cm / tree / year.
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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 | 0.001 | 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".