Patterns of shrub abundance and relationships with other plant types within the forest–tundra ecotone in northern Canada
Bibliographic record
Abstract
Throughout the forest–tundra ecotone where trees and tall shrubs are becoming more abundant, knowledge of associations between shrubs and surrounding vegetation could inform predictions of their changing relationships. We assessed shrubs in 1 m × 1 m contiguous quadrats along two ∼450 m transects across tundra and ecotone landscapes near Churchill, Canada to determine patterns in relation to lakeshore edges, soil pH, microtopography, and other plant groups. We used wavelet analysis to assess patterns and generalized least squares for relationships with environmental variables. Shrubs were taller and more diverse at edges, particularly in tundra. The ecotone was more complex than tundra with greater variation in tall shrub and tree cover, shrub height, and microtopography. Shrub richness was positively correlated with microtopography but exhibited no relationship with pH. Bivariate relationships of shrubs with other plant groups varied for different scales. In tundra, shrub richness was negatively correlated with graminoids, forbs, and moss, but positively correlated with lichens within 1 m; opposite relationships were found at 4–60 m scales. Relationships in the ecotone were reversed and more complex at different scales. As trees encroach in the tundra, the spatial pattern of shrubs will become more complex at a variety of scales, likely with cascading effects on other plant types.
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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".