Environmental Determinants of Tree Species Distributions in Central Ontario, Canada
Bibliographic record
Abstract
The ability to model forest distributions in light of anthropogenic disturbance requires a thorough understanding of how trees respond to their physical and climatic environment. The primary objective of this study is to determine how four environmental variables (elevation, latitude, slope angle, and slope aspect) affect the distribution of seven common tree species (Acer saccharum, Betula alleghaniensis, Betula papyifera, Abies balsamea, Picea glauca, Thuja occidentalis, and Acer spicatum) using both regression tree analysis (RTA) and canonical correspondence analysis (CCA) techniques. In general, within the study area, Acer saccharum, Abies balsamea, and Thuja occidentalis abundance was controlled by elevation and latitude, whereas the other species showed limited response to the measured environmental variables. While CCA and RTA showed similar patterns, RTA allows for a more nuanced evaluation of species-environment interactions. Given that the study area encompasses Acer saccharum's northern limit, there were differences in the response of Abies balsamea to environmental conditions in the absence of Acer saccharum.
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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 | 0.002 |
| Science and technology studies | 0.002 | 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) | 0.002 | 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".