Edge effects at clearcut, fire and riparian buffers in the boreal forest of Northwestern Ontario / by Katherine J. Stewart. --
Bibliographic record
Abstract
In the boreal forest o f northwestern Ontario clearcutting and 6re are two common edge-creating disturbances.Fundamental knowledge regarding the ability of fire and clearcut edges to minimize edge effects, preserve interior habitat, and provide sources o f vegetative growth is lacking.Development o f sustainable forest management strategies that emulate natural disturbance relies upon such information.This thesis examines edge effects in the boreal forest of northwestern Ontario at conifer clearcut, deciduous clearcut, and conifer 6re edges.Riparian buSers with an upland clearcut edge and an uplandriparian ecotone were also studied.Edge effects were explored on a number o f scales ranging &om landscape-level to stand-level to small-scale bryophyte response.Residual patch, core area and edge were assessed in 1000 ha and 250 ha windows in both clearcut and fire disturbance.At the stand-level canopy and understory conditions were sampled along transects (60 m) placed across edges and buffers, in comparison to transects in the interior forest or at undisturbed stream edges.Edge characteristics and the depth of edge influence (DEI) were determined using the critical values approach, multiple response permutation procedure, analysis o f covariance and other nonparametric tests.Conifer and deciduous clearcut edges had many similarities.Species response across conifer fire edges was different 6om clearcut edges due to shading provided by standing dead trees and a pre-existing moisture gradient at burnt edges.Most buffers maintained a similar species composition to undisturbed stream edges, but changes in species abundance were detected at the stream edge.The DEI was greatly decreased for most response variables 10 m past the edge; however, a significant DEI was found for some response variables at 40 m or up to the stream edge, which was the greatest distance measured.11
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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 | 0.000 | 0.001 |
| 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) | 0.008 | 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".