Temperate marine reserves: global ecological effects and guidelines for future networks
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 Marine reserves, areas closed to all fishing and other extractive activities, provide a refuge for species of commercial and conservation importance. Given the considerable resources committed to designing temperate reserve networks, we synthesized data from temperate reserves worldwide to determine their ecological effects. In common with other studies, we found higher density, biomass, and species richness in temperate marine reserves compared to adjacent exploited areas. However, there was considerable heterogeneity in magnitude of effect among reserves, variability which was largely unexplained by species or reserve characteristics. Our analytical approach allowed for formal power analyses, indicating that detection of large reserve effects in temperate systems globally requires monitoring at least 37 reserves. These results must be qualified by the limitations of data available and will undoubtedly vary at different spatio‐temporal scales and for different focal species, but provide guidance for the design and monitoring of future marine conservations plans. International commitments toward establishment of multiple reserves offer a unique opportunity to assess reserve effectiveness; this opportunity can only be realized if reserves are designed to achieve clear and quantifiable objectives and are adequately monitored before and after establishment, based on appropriate power analyses, to assess how well those objectives are achieved.
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