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Record W2787191456 · doi:10.5539/enrr.v8n1p61

Community-based Bamboo Stands Management in the Kali Bekasi Watershed, Indonesia

2018· article· en· W2787191456 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueEnvironment and Natural Resources Research · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicForest Ecology and Conservation
Canadian institutionsnot available
FundersUniversitas Indonesia
KeywordsBambooWatershedBiomass (ecology)Diversity indexEnvironmental scienceAgroforestryBiodiversityWatershed managementGeographyForestryEcologyBiologySpecies richnessComputer science

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.180
Threshold uncertainty score0.666

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.046
GPT teacher head0.277
Teacher spread0.231 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it