Rapid mixed forest encroachment and the expansion of red maple (<i>Acer rubrum</i>) in a peatland: a dendroecological and paleoecological approach
Bibliographic record
Abstract
Some ombrotrophic peatlands in temperate regions have been characterized by a process of rapid densification of their forest cover for several decades. This phenomenon is particularly marked in southern Québec (Canada), where a number of peatlands now contain mixed forest stands. The present study aimed to document the woody encroachment dynamics of a peatland colonized by Larix laricina (Du Roi) K. Koch and Acer rubrum L. The specific objectives were to characterize the contemporary dynamics of the forest cover through analysis of dendrometric, dendrochronological, and aerial photographs, and to reconstruct the evolution of tree species present in situ since the peatland’s origin through botanical identification of ligneous remains collected in excavations of the peat as well as macrofossil analysis of a sedimentary core. The vegetation cover underwent rapid transformation beginning in the 1970s, first by the densification of L. laricina, followed by the expansion of A. rubrum. This transformation followed several millennia during which the peatland continuously presented a shrub-dominated cover with a few scattered coniferous trees. The rapid expansion of a mixed forest cover is a unique event in the peatland’s history. Acer rubrum progressively replaced L. laricina and, in the more or less long-term, should become the dominant species.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".