Testing for Bottom—up Effects in an Overbrowsed Boreal Landscape
Bibliographic record
Abstract
On Anticosti Island (Quebec, Canada), overbrowsing by white‐tailed deer Odocoileus virginianus has substantially modified plant communities and reduced the recruitment of balsam fir Abies balsamea seedlings over most of the territory. An exception to this phenomenon has been observed in localised patches occurring on a single geological deposit named Chicotte, where the natural recruitment of balsam fir is occurring even in the presence of a large white‐tailed deer population. We hypothesized that edaphic properties within the Chicotte deposit could result in lower forage quality, which in turn could reduce browsing pressure and allow fir regeneration to occur (i.e. bottom—up effects). To test this hypothesis, we measured soil properties and foliage chemistry of four forage species (balsam fir, white spruce Picea glauca , Canada mayflower Maianthemum canadense and Canada bunchberry Cornus canadensis ) collected on each of three geological deposits on Anticosti Island: Chicotte, Becscie and Jupiter (the latter two considered as controls). Contrary to expectation, results from principal component analysis suggested that Chicotte was the most fertile, whereas Becsie was the least fertile, of the three deposits. Furthermore, balsam fir foliage chemistry did not respond to geological deposit. Conversely, Mantel et Procrustes tests revealed a significant correlation between soil properties and forage quality for white spruce, consistent with the carbon—nutrient balance hypothesis. Univariate tests confirmed that neutral detergent fiber concentrations in white spruce were higher on the Becscie than on the Chicotte deposit. Likewise, in vitro true digestibility of both white spruce and Canada bunchberry foliage were lower on the Becscie than on the Chicotte deposit. Although we failed to demonstrate why balsam fir recruitment occurs on the Chicotte deposit, our data demonstrate that edaphic properties may affect the quality of some forage types, which potentially affect foraging patterns in overbrowsed boreal landscapes.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".