Community-based Bamboo Stands Management in the Kali Bekasi Watershed, Indonesia
Bibliographic record
Abstract
A high rate of vegetation clearing around the upper stream of Kali Bekasi watershed currently causes various environmental problems, such as floods. The impacts occur predominantly in downstream area, mostly affecting cities, due to a disruption of the ecosystem in the upper stream. The main function of the upper stream to humans is acting as a buffer to protect downstream areas from flooding, run-off, as well as biodiversity protection. To achieve this, many varieties of plant are grown including bamboo plantations, which serve as a buffer plants on critical land especially with steep contours. In this study we aim to provide a better understanding of the effectiveness of different bamboo stands buffering to improve information for making management recommendation. We examine different points along the stream by mapping bamboo distribution, analyzing bamboo and non-bamboo (tree) stands diversity and biomass, and provide recommendations for bamboo management based on combining our findings with local ecological knowledge. We implemented image classification analysis for classifying bamboo and non-bamboo land use cover. We also measured bamboo and non-bamboo diversity by using Shannon’s-Wienner diversity index. Our results showed that bamboo occupies approximately 5,360.89 ha or 11.39% of total area with six bamboo species. The highest bamboo diversity index was in the upper part of the Kali Bekasi watershed (0.62). In contrary, the highest bamboo biomass index was found in the lower part of the upper stream of Kali Bekasi watershed (98.96 ton ha-1). We also discovered about 29 species of tree (230 trees) and 27 above-ground plant species in the surveyed area. As a result of our findings, we propose a shift towards bamboo agroforestry management in a mixed garden of talun form, where the community implement their local knowledge on bamboo cultivation and management to maintain the bamboo. This option could improve cooperation among farmers and the local community in order to conserve bamboo and tree species diversity in harmony to local wisdom.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".