Logging-induced change (1930-2002) of a preindustrial landscape at the northern range limit of northern hardwoods, eastern Canada
Bibliographic record
Abstract
Logging-induced changes from preindustrial (1930) to current conditions (2002) were studied in a landscape covering 13 550 ha in eastern Quebec. Age and types of forest cover were compared between 1930 and 2002 forest maps. In addition, we compared relative species abundance between living stems and coarse woody debris to study these changes at the stand scale. More than 90% of the 1930 preindustrial landscape was composed of forest stands older than 100 years. A balsam fir (Abies balsamea (L.) Mill.) white spruce (Picea glauca (Moench) Voss) dominated conifer cover (77% of the landscape area) formed the landscape matrix across the lowlands and was intermingled with mixed stands of sugar maple (Acer saccharum Marsh.) and conifers on the highlands. As a result of recurrent logging, stands less than 70 years old accounted for 93% of the 2002 landscape. From 1930 to 2002, 37% of the landscape was converted from coniferous to mixed forest, and 19% evolved towards a deciduous cover. The total number of cover patches doubled to 193, whereas mean patch size decreased twofold to 65 ha. Sugar maple, red maple (Acer rubrum L.), striped maple (Acer pennsylvanicum L.), and white birch (Betula papyrifera Marsh.) probably experienced a greater increase in abundance, whereas balsam fir, white spruce, and eastern white-cedar (Thuja occidentalis L.) experienced a more pronounced decrease. Because it does not consider preindustrial landscape patterns, the system of ecological land classification currently in use in this area suggests that potential late-successional cover types should be more similar to present-day than to preindustrial conditions.
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 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".