Evidence for the widespread occurrence of ancient forests on cliffs
Bibliographic record
Abstract
Abstract AimThe objective of this work was to determine if the existence of ancient forests on cliffs was specific to the Niagara Escarpment, Canada, or part of a globally widespread pattern. LocationSixty‐five cliff sites were visited in five countries in the temperate climatic zone, and trees were sampled for age and growth rate on forty‐six of these. MethodsTwo hundred and twenty‐four core samples or cross‐sections were taken from trees on cliffs that varied in height, aspect, rock‐type, and exposure. General observations were also made of regeneration of the tree species forming the mature canopy, and other habitat conditions. ResultsThe evidence shows that ancient slow‐growing forest occurs on most cliffs. Age and growth rate distributions were similar at all treed sites. Small‐staturedThuja, Juniperus, orTaxusstems with age estimates in excess of 1000 years were found in the United States, the United Kingdom and France, and smallPinus and Quercusstems nearly 400 years in Germany. There was a high rate of recurrence of plants in the generaPolypodium,Asplenium,Cystopteris,Campanula,Rosa,Prunus,Hedera, andSorbus. Most of the sites appear to be habitats of completely natural origin. ConclusionsWe conclude that ancient natural forest is a normal feature of cliffs, at least in the temperate zone.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".