Long-term compositional changes following partial disturbance revealed by the resurvey of logging concession limits in the northern temperate forest of eastern Canada
Bibliographic record
Abstract
Land use changes that are linked to European settlement of North America have transformed northeastern temperate forest landscapes. Many studies report a regional increase of young early-successional forests due to high disturbance rates since the preindustrial era (fire, land clearing, and clear-cuts). In this study, we document specific compositional changes to present-day mature forest landscapes, which have only been managed with partial cutting (high-grading and diameter-limit cuts) since the preindustrial era in southwestern Quebec. We resurveyed 108 forest observations that were extracted from logbooks of former logging concession limits (surveyed between 1870 and 1890). Results highlight an increase in mid- to late-successional shade-tolerant taxa (Betula alleghaniensis Britton, Thuja occidentalis L., Acer saccharum Marsh.) at the expense of preindustrial dominant conifers (Abies balsamea (L.) Mill., Pinus strobus L.). Former logging activities and spruce budworm (Choristoneura fumiferana Clemens) outbreaks appear to be the main drivers of these changes, which were also strongly structured across the topographic gradient. To some extent, these results highlight the relevance of partial cutting management, as it has allowed long-term maintenance of a mid- to late-successional forest composition, while also pointing the need for P. strobus restoration. We conclude that by allowing site-specific comparisons, the resurvey of historical observations greatly improve the analytical strengths of historical reconstruction.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| 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".