The Relationship Between Erect Deciduous Shrub Growth and Spectral Greening on the Bathurst Caribou Range
Bibliographic record
Abstract
The Canadian Arctic has simultaneously experienced rapid climate warming, increases in plant productivity (“greening”), and barren-ground caribou population declines in recent decades. Across the tundra biome, remotely sensed greening has been attributed to an expansion of erect deciduous shrubs, although the patterns and processes of shrub growth are heterogeneous. I applied field investigation and dendrochronology at different levels of the ecological hierarchy to examine recent patterns of growth of trees, erect deciduous shrubs, and other plant functional types in relation to climate. My research sought changes inferred from remote sensing within the relatively understudied treeline ecotone of central Canada on the late summer range of the Bathurst caribou herd. Consistent with previous studies, a high degree of heterogeneity manifested across sites that had greened and those whose productivity had remained stable according to remotely sensed time series trends. Overall, however, there was no significant difference in annual radial growth of trees and shrubs; in composition, establishment, height, or growth rate of shrubs; or in plant community composition between the two site types. However, subtle patterns of change and small differences were evident at all levels of the ecological hierarchy to suggest that dwarf birch is gaining dominance across the landscape and within plant communities, driven by increased secondary growth and a healthier, more productive canopy. Like birch, spruce growth has also been increasing, with both woody plant types responding to warmer temperatures. Greater birch importance at greening sites contrasted strongly with a greater importance of lichen and more bare ground cover at stable sites. A shifting dominance of shrubs can alter range condition and available forage for caribou, thereby also impacting the people who rely on caribou. In addition to improving our understanding of greening in relation to shrub expansion and climate sensitivity of woody plants at latitudinal treeline, my characterization of plant community change in recent decades can help identify areas for protection and monitoring on the Bathurst range, ultimately supporting recovery efforts for this ecologically and culturally important caribou herd.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".