Tolerance of an Expanding Subarctic Shrub, Betula glandulosa, to Simulated Caribou Browsing
Bibliographic record
Abstract
Densification of the shrub layer has been reported in many subarctic regions, raising questions about the implication for large herbivores and their resources. Shrubs can tolerate browsing and their level of tolerance could be affected by browsing and soils productivity, eventually modifying resource availability for the caribou. Our objective was to assess the compensatory growth potential of a subarctic shrub, Betula glandulosa Michx., in relation with caribou browsing and nutriment availability for the plants. We used a simulated browsing (0, 25 and 75% of available shoots) and nitrogen-fertilisation (0 and 10 g m(-2)) experiment to test two main hypotheses linking tolerance to resource availability, the Compensatory Continuum Hypothesis and the Growth Rate Hypothesis as well as the predictions from the Limiting Resource Model. We seek to explicitly integrate the relative browsing pressure in our predictions since the amount of tissues removed could affect the capacity of long-lived plants to compensate. Birches fully compensated for moderate browsing with an overall leaf biomass similar to unbrowsed birches but undercompensated under heavy browsing pressure. The main mechanism explaining compensation appears to be the conversion of short shoots into long shoots. The leaf area increased under heavy browsing pressure but only led to undercompensation. Fertilisation for two consecutive years did not influence the response of birch, thus we conclude that our results support the LRM hypothesis of equal tolerance under both high and low nitrogen availability. Our results highlight that the potential for compensatory growth in dwarf birch is surpassed under heavy browsing pressure independently of the fertilisation regime. In the context of the worldwide decline in caribou herds, the reduction in browsing pressure could act synergistically with global climate change to promote the current shrub expansion reported in subarctic regions.
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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 | 0.000 |
| 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) | 0.001 | 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".