Sustainability issues of commercial non-timber forest product extraction in West Suriname
Bibliographic record
Abstract
BACKGROUND: Non-timber forest products (NTFPs) have been traded for millennia by indigenous communities. Current increased demands driven by globalisation, however, put more pressure on local harvesters and their surrounding ecosystems. The safeguarding of indigenous access rights to harvesting grounds is needed, either through communal land titles or collaborative management agreements, both to secure prior indigenous rights and to minimise further negative ecological impacts. METHODS: This study was carried out in two indigenous communities in West Suriname located along the Corentyne River. We assessed the three economically most important NTFPs for each community. We determined the land tenure status of harvesting grounds and negative impacts on target species and/or ecosystem. Ethnobotanical data were collected (n = 53), and semi-structured interviews were held with hunters and gatherers (n = 13). Local and national maps were acquired, and their data merged. RESULTS: Results showed that the communities have no tenure security over their most important harvesting sites. These collection sites are State owned and some under (active) logging concession. All of the traded wild animal populations had decreased because of increased local and non-local commercial interest, especially the stingray Potamotrygon boesemani (first described in 2008), which was traded for US$250 per live specimen. The stingray population had become imperilled within months as local and (inter-) national regulations for this species are non-existent. CONCLUSIONS: We stress the urgent need for collaborative management agreements over the harvesting sites between the government of Suriname and the indigenous communities to prevent further non-local developments and harvesting to disturb the local economy. An immediate moratorium on the export of P. boesemani is necessary to prevent the extinction of this endemic stingray.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".