Spatial analysis of response of trembling aspen patches to clearcutting in black spruce-dominated stands
Bibliographic record
Abstract
While expansion of intolerant hardwoods, including trembling aspen, has been recognized as a problem by boreal forestmanagers in eastern Canada, the problem has mostly been associated with the boreal mixedwood and, with a few exceptions,the spatial aspects of the phenomenon have not been well documented in the scientific literature. The objective ofthis study is to evaluate how the density and size of aspen patches influence the change in density, size and persistence ofpatches following clearcutting of black spruce forests in the claybelt region of northwestern Quebec. To do this, we finelyinterpreted: 1) aerial photos taken between 1970 and 1979 of 12 mature black spruce-dominated stands containing varyingsizes and densities of aspen patches prior to being clearcut harvested and 2) aerial photos taken between 1992 and1995 of the 12 resulting clearcuts, 11 to 18 years after harvesting. Sketch maps of pre- and post-harvest aspen presencewere rasterized and changes in aspen patch size and cover were determined. As well, the probabilities of aspen colonizationwith increasing distance from pre-harvest patches were calculated for each site. Black spruce forests of the claybeltcontaining no aspen prior to harvesting are relatively resistant to aspen invasion. However, when forests do contain aspenpatches with cover values ≤25%, almost 60% of these patches increase to a higher density class. Aspen patches less than 2ha in area had about a 50% probability of disappearing following clearcutting whereas larger patches had about a 96%chance of persisting as a result of clearcutting. In the black spruce forest of the claybelt, thick organic layers appear to havea negative effect on aspen recruitment. Distances of regenerating aspen from pre-harvest patches suggest that recruitmentfrom seed is more important than previously thought. Key words: encroachment, trembling aspen, clearcutting, black spruce, claybelt, aerial photography
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".