STRUCTURE AND COMPOSITION OF RIPARIAN BOREAL FOREST: NEW METHODS FOR ANALYZING EDGE INFLUENCE
Bibliographic record
Abstract
Riparian ecotones at lakeshore edges are prominent features on the heterogeneous boreal forest landscape. We introduce a new method (the critical values approach), which incorporates inherent variability in interior forest, to quantify distance of edge influence at lakeshore forest edges. We use this method to examine the variation in forest structure and composition along the lakeshore forest edge-to-interior gradient in the mixedwood boreal forest. Our objectives were: (1) to quantify distance of edge influence for forest structure and composition at lakeshore forest edges; and (2) to investigate spatial pattern in vegetation along the edge-to-interior gradient. Trees, coarse woody material, saplings, shrubs, and herbs were sampled in plots at varying distances along 200-m transects established perpendicular to lakeshore forest edges. Distance of edge influence was determined by comparing mean values at different positions along the transect to critical values established from a randomization test of interior forest data. The spatial pattern of four selected species along the edge-to-interior gradient was assessed using split moving window analysis and wavelet analysis. The results suggest that a distinct lakeshore forest edge community exists. This community was ∼40 m wide and was characterized by greater structural diversity, larger amounts of coarse woody material, and more saplings and mid-canopy trees than interior forest. Distance of edge influence for understory composition was generally greater than for forest structure. Patterns of response for different species along the edge-to-interior gradient were related to shade tolerance. Lakeshore forest edges are distinct landscape elements, but their prominence depends on the reference forest, species, and scale.
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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 | 0.000 | 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 | 0.000 | 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) | 0.000 | 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".