Growth change of young Picea sitchensis in response to deer browsing
Bibliographic record
Abstract
Taking advantage of the introduction of the black-tailed deer to the Queen Charlotte Islands (British Columbia, Canada), we used dendrochronological analyses to understand the consequences of deer browsing on Sitka spruce growth. We compared shape, radial growth, height growth and age of young spruce in three sites. We identified two types of trees growing side by side: (1) stunted and heavily browsed spruce, smaller than the browsing limit and (2) escaped spruce that were taller than the browsing limit but still browsed in their lower part. The compact and heavily ramified shape in stunted spruce was the result of repeated and intense browsing. In escaped spruce this was also the case below the browsing limit (1:16 m 0:07 m), in sharp contrast with the normal shape that escaped spruce resumed above the browsing limit. We show that the release of browsing pressure, once the tree reaches the browsing limit, is characterised by an abrupt increase in radial growth. Before release, trees show a growth stagnation characterized by narrow rings (0.5 mm per year) and small annual height increments (<5 cm per year). After release, trees show a growth stabilisation characterised by wider rings (3 mm per year) and larger annual height increments (20 cm per year). We use this pattern to estimate frequency and age at release and their possible variation over time. Age differences between stunted and escaped spruce are highly significant and indicate that, despite of browsing, most if not all trees will ultimately reach the browsing limit and escape. Heavy deer pressure (30 deer per km2) delays spruce sapling recruitment by about 8 years. This delay varies in relation to site quality and seems to have increased over time, suggesting an increase in
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".