The contribution of rewetting to vegetation restoration of degraded peat meadows
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 Question: What is the contribution of a rise in groundwater level to vegetation restoration of degraded peat meadows compared to abandonment only? Location: Abandoned peat meadows in the central part of The Netherlands. Methods: Comparison of species composition and species abundance of vegetation and seed banks of reference and rewetted peat meadows, using plant trait and seed bank analysis. Results: Vegetation of rewetted meadows shared on average only 27% of their species with the reference meadow, while this was 50% on average for species in the seed bank. Rewetted meadows had a lower total number of species and a lower number of wet grassland and fen species present in the vegetation, but had higher species richness per m 2 , although evenness was not affected. Rewetting increased the dominance of species of fertile and near neutral habitats, but did not result in an increase of species of wet or waterlogged habitats. Re‐wetted meadows were dominated by species relying mainly on vegetative reproduction and species with a low average seed longevity compared to the reference meadow. Conclusion: Rewetting was not effective as a restoration measure to increase plant species diversity or the number of wet grassland and fen species in the vegetation. If no additional restoration management is applied, the seed bank will be depleted of seeds of species of wet grassland or fen habitats, further reducing the chances of successful vegetation restoration.
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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