Recent advance of forest–grassland ecotones in southwestern Yukon
Bibliographic record
Abstract
We investigated recent ecotone dynamics in the forest–grassland mosaics of southwestern Yukon. Our objectives were to determine (i) if forests are encroaching into grasslands, (ii) if rate and extent of encroachment varies by region or with topographic setting, and (iii) if encroachment is related to climate change and variability. Dendroecological techniques were used to obtain dates of establishment for 1847 trees (trembling aspen (Populus tremuloides Michx.) and white spruce (Picea glauca (Moench) Voss)) sampled from 28 sites divided between two different regions and three topographic settings. Generalized linear modeling was used to identify relationships between climate and tree establishment. Results show that encroachment of forest, particularly aspen trees, into grasslands has been nearly ubiquitous on flat terrain and on south-facing slopes in both regions over the last 60–80 years. In contrast, spruce-dominated ecotones on north-facing slopes experienced little change. Aspen establishment was positively associated with spring temperatures and precipitation, although evidence suggests that other factors such as soil moisture interact with climate to mediate the timing and rate of tree encroachment. These results indicate that transformation of grasslands to aspen-dominated forest is an additional, but previously unexplored, element of the widespread ecosystem changes currently being experienced in northwestern North America.
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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 | 0.000 | 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".