Aspect and slope influence plant community composition more than elevation across forest–tundra ecotones in subarctic Canada
Bibliographic record
Abstract
Abstract Questions How does tree line community composition vary between elevations, aspects and slope angles in the alpine subarctic and what are the specific abiotic factors governing this variability? How do species richness and rates of community turnover vary from low to high elevation across the forest–tundra ecotone? What do the results indicate about future vegetation change? Location Kluane Region, southwest Yukon, Canada. Methods We surveyed plant communities and measured key abiotic variables across forest–tundra ecotones in six alpine valleys, each with a north‐ and a south‐facing slope, in two mountain ranges of southwest Yukon. We usedNMSto identify patterns in plant community composition and infer which abiotic variables drive these patterns. We calculated species richness and community dissimilarity at regular elevational intervals to assess trends in richness and rates of community turnover within the ecotone. Results Plant communities varied more with aspect and slope angle than they did with elevation. Aspect‐related differences were driven by warmer soil temperatures and deeper active layers on south‐ compared to north‐facing slopes, while differences related to slope angle occurred only on north‐facing slopes and were driven by soil moisture. Species richness increased with elevation on north‐facing slopes and showed no trend with elevation on south‐facing slopes. Rates of community turnover were higher on south‐facing than north‐facing slopes. Conclusions Plant community composition within the forest–tundra ecotone is driven primarily by soil temperature and, to a lesser extent, soil moisture, both of which vary more in relation to aspect and slope angle than they do between forest and tundra elevations. We recommend that models of vegetation change in subarctic alpine regions address the possibility of change occurring at different rates and in different directions depending on the topographic characteristics of each slope.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".