Greening on the Bathurst caribou range in northern Canada: are erect shrubs responsible for remotely sensed trends?
Bibliographic record
Abstract
Remote sensing has detected recent trends of increased vegetation productivity on the Bathurst caribou herd’s range. The cause of this spectral greening is unknown but is hypothesized to be the result of a change in the composition, establishment, structure, and/or growth of erect deciduous shrubs. We combined field investigation and dendroecology to compare shrubs between areas where productivity has increased (Greening sites) and areas where productivity has remained stable (No Change sites) based on a Moderate Resolution Imaging Spectroradiometer time series for the period from 2000 to 2017. Contrary to expectations, species composition, timing of stem establishment, stem density, stem length, and vertical and diameter growth rates did not differ between the two site types. However, shrub cover was 13% greater at Greening sites and shrubs at No Change sites had 9% more dead stems regardless of the size of the shrub. This suggests that the differences observed remotely are due to a combination of increased foliage production or survival at Greening sites and a dimming of the vegetation index at No Change sites. Our findings offer a population-level validation of specific shrub characteristics contributing to trends in spectral greening in an understudied region of the southern Arctic tundra.
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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".