Ten‐year assessment of the 100 priority questions for global biodiversity conservation
Bibliographic record
Abstract
In 2008, a group of conservation scientists compiled a list of 100 priority questions for the conservation of the world's biodiversity. However, now almost a decade later, no one has yet published a study gauging how much progress has been made in addressing these 100 high-priority questions in the peer-reviewed literature. We took a first step toward reexamining the 100 questions to identify key knowledge gaps that remain. Through a combination of a questionnaire and a literature review, we evaluated each question on the basis of 2 criteria: relevance and effort. We defined highly relevant questions as those that - if answered - would have the greatest impact on global biodiversity conservation and quantified effort based on the number of review publications addressing a particular question, which we used as a proxy for research effort. Using this approach, we identified a set of questions that, despite being perceived as highly relevant, have been the focus of relatively few review publications over the past 10 years. These questions covered a broad range of topics but predominantly tackled 3 major themes: conservation and management of freshwater ecosystems, role of societal structures in shaping interactions between people and the environment, and impacts of conservation interventions. We believe these questions represent important knowledge gaps that have received insufficient attention and may need to be prioritized in future research.
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How this classification was reachedexpand
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 | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".