Economic benefits of biodiversity exceed costs of conservation at an African rainforest reserve
Bibliographic record
Abstract
Economic research on biodiversity conservation has focused on the costs of conservation reserves and the benefits of intact ecosystems; however, no study has simultaneously considered the costs and benefits of species diversity, a fundamental component of biodiversity. We quantified the costs and benefits of avian biodiversity at a rainforest reserve in Uganda through a combination of economic surveys of tourists, spatial land-use analyses, and species-area relationships. Our results show that revising entrance fees and redistributing ecotourism revenues would protect 114 of 143 forest bird species (80%) under current market conditions. This total would increase to 131 species (approximately 90%) if entrance fees were optimized to capture the tourist's willingness to pay for forest visits and the chance of seeing increased numbers of bird species. In contrast, the cost of purchasing agricultural land for ecological rehabilitation of the avian habitat would be economically prohibitive. These results suggest that local biodiversity markets could play a positive role in tropical conservation strategies if the appropriate institutions for redistribution can be developed.
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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 | 0.005 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| 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".