Protecting ecosystem services and biodiversity in the world's watersheds
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.
Bibliographic record
Abstract
Abstract Despite unprecedented worldwide biodiversity loss, conservation is not at the forefront of national or international development programs. The concept of ecosystem services was intended to help conservationists demonstrate the benefits of ecosystems for human well‐being, but services are not yet seen to truly address human need with current approaches focusing mostly on financial gain. To promote development strategies that integrate conservation and service protection, we developed the first prioritization scheme for protecting ecosystem services in the world's watersheds and compared our results with global conservation schemes. We found that by explicitly incorporating human need into prioritization strategies, service‐protection priorities were squarely focused on the world's poorest, most densely populated regions. We identified watersheds in Southeast Asia and East Africa as the most crucial priorities for service protection and biodiversity conservation, including Irrawaddy—recently devastated by cyclone Nargis. Emphasizing human need is a substantial improvement over dollar‐based, ecosystem‐service valuations that undervalue the requirements of the world's poor, and our approach offers great hope for reconciling conservation and human development goals.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it