REGIONAL LEGACIES OF LOGGING: DEPARTURE FROM PRESETTLEMENT FOREST CONDITIONS IN NORTHERN MINNESOTA
Bibliographic record
Abstract
Forests in the Great Lakes region of Canada and the United States have been important timber producing resources for more than 100 years. Logging and fire suppression have caused major, but unquantified change in those forests, which includes both the magnitude of compositional change and its spatial patterns. Hence, a spatially explicit regional‐scale change analysis was conducted using General Land Office Survey records from the late 1800s and the 1990 U.S. Forest Service Inventory and Analysis Survey, for a 3.2 million hectare study area in northeastern Minnesota, USA. These data document altered species abundance, proportional basal area, and spatial distribution patterns. Regionally, the proportionally most abundant species shifted from the presettlement period (spruce, 21%; larch, 15%; and paper birch, 15%) to aspen (30%), spruce (16%), and balsam fir (16%) in 1990. In terms of proportional basal area dominance, white pine declined from 20% to 5%, birch from 16% to 13%, spruce from 14% to 9%, and larch from 12% to 2%, while aspen increased from 8% to 35%. Based on ordination of species abundance and proportional basal area, physiographic zones varying in geology and hydrology were characterized by different species composition in the 19th century and experienced largely parallel rather than convergent shifts in community composition since that time. Maps were developed for the regional study area using a 10 × 10 km spatial resolution to document spatial patterns of species proportional basal area. White pine co‐dominated (was ranked first or second in proportion of basal area) 45% of the 253 100‐km2 presettlement zones, but none of the 1990 zones. Forest zones co‐dominated by red pine, jack pine, and larch also largely disappeared. These forests were largely supplanted by aspen co‐dominated communities, which accounted for 82% of the 1990 forest zones and represent diminished regional landscape diversity. Although the same 11 species made up the 1990 as well as the 19th century forest, change in their relative abundance and dominance was profound such that 85% of the 253 zones now contain community types (i.e., dominant species pairs) that did not dominate anywhere in the presettlement era.
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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 | 0.000 |
| 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".