Bamboo for global sustainability: a systematic review of its environmental and ecological implications, climate action, and biodiversity contributions
Bibliographic record
Abstract
Bamboo has garnered significant attention over the past two decades as a sustainable resource with a wide array of environmental benefits and emerged as a crucial resource in addressing global sustainability challenges. This systematic review synthesizes bibliometric data from the Web of Science (WOS), spanning 2004–2024, to explore the role of bamboo in global sustainability, focusing on its environmental advantages, biodiversity contributions, carbon sequestration potential, and the ecosystem services—provisioning, regulating, supporting, and cultural, it provides. Despite growing interest in bamboo’s ecological benefits, substantial research gaps exist regarding its long-term effects on biodiversity and ecosystem functioning, as well as the full extent of its role in mitigating climate impacts. This review aims to address these gaps by providing a comprehensive analysis of published research and offering new insights into bamboo’s multifaceted contributions to a number of environmental benefits and achieving sustainable development goals (SDGs). The novelty of this review lies in its integration of bibliometric analysis and qualitative synthesis, ensuring a more thorough understanding of trends, key research areas, and potential future directions. The methodology includes data extraction from WOS, followed by trend analysis, citation mapping, and thematic synthesis. Key findings reveal that bamboo plays a crucial role in carbon sequestration, biodiversity preservation, and soil conservation, while also enhancing water quality and mitigating land degradation. This indicates bamboo’s transformative potential in addressing climate change, promoting biodiversity, and supporting sustainable livelihoods. Furthermore, the study identifies critical gaps in research and policy integration, stressing the need for coordinated global efforts to fully realize bamboo’s benefits including its adaptability across different ecosystems, as well as its potential in combating global challenges such as climate change and deforestation. This review offers implications for policymakers, researchers, and practitioners seeking sustainable solutions in land management, climate action, and biodiversity conservation. The findings underscore bamboo’s unique potential as an eco-friendly, low-cost, and scalable solution for fostering global sustainability. The benefits of this study extend to promoting bamboo’s integration into conservation practices and green infrastructure projects globally.
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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 | 0.008 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.026 | 0.030 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".