Assessing the potential of restoration measures and management techniques in a post‐pastured Azorean peatland: two years tendencies
Bibliographic record
Abstract
During more than five centuries of human colonization, 50% of original peatlands in Azores have been destroyed or degraded, mainly due to pasture use, resulting in landscape changes and a loss of ecosystem biodiversity and services. This study aims to identify the most effective measures in the recovery and to detect initial responses (2 years). These are the first restoration experiments, carried out in a background of complete absence of strategies adapted for Azores pastured peatlands. In a post‐pastured peatland, 24 experiments were implemented, repeated in more degraded (northern) and more natural (southern) areas. The experiments were combinations of restoration measures, with the introduction of Juniperus brevifolia , Calluna vulgaris , and Sphagnum palustre and the use of management techniques to control herbaceous cover (alien‐rich herbaceous cover competing with Sphagnum or peatland natural shrubs): intensive and extensive grazing and grass cutting. Principal response curves and redundancy analyses were used to assess changes in the flora and the physicochemical parameters. Globally there was an increase in Sphagnum cover and a decrease in herbaceous species. This was accompanied by an increase in organic matter and a decrease in nitrogen. In more natural parcels (large artificially divided areas where different experiments were implemented), the most positive tendencies were associated with the combination of J. brevifolia planting and grass cutting. In more degraded areas, treatments had a lower impact, as the results tended to be similar to the control, pointing to an important natural regenerative succession dynamic that overlapped the response to the implemented treatments.
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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 | 0.001 | 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 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".