Large herbivores control the invasive potential of nonnative Austrian black pine in a mixed deciduous Mediterranean forest
Bibliographic record
Abstract
The invasive potential of the nonnative Austrian black pine (Pinus nigra subsp. nigra Arn.) was analyzed in a 100-year-old Mediterranean mixed deciduous forest in the Massane Nature Reserve, eastern Pyrenees (France). The reserve holds approximately 120150 semiferal cattle (Bos taurus L.) that browse and trample the woody regeneration. Tree age structure was assessed by dendrochronology to reconstruct the pine population dynamics in grazed and nongrazed (fenced in 1954) portions of the forested reserve. The age structure of the pine population regenerating before 1960 was similar between the inside and outside of the enclosed reserve area. Since 1960, pine recruitment has occurred only in the nongrazed area. The diameter variability with age changed since the 19th century. For pines less than 20 years old, the diameter variability is low, whereas it is very high for individuals older than 100 years. Diverse forest structural changes (composition, canopy height, density, etc.) likely explain the variability in diameter at a given age. Cattle do not appear to affect tree growth as it is similar inside and outside the fenced area, but they control the regeneration of nonnative Austrian black pines, which can spread in the absence of cattle. If nonnative black pine poses a risk for forest conservation, large herbivores may play a useful role in maintaining this species at low abundance.
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), 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".