Detrimental effects of white-tailed deer browsing on balsam fir growth and recruitment in a second-growth stand on Anticosti Island, Québec
Bibliographic record
Abstract
White-tailed deer (Odocoileus virginianus Zimmermann) was introduced on Anticosti Island in the late 1890s. The current population, estimated at 120 000 (15 animals/km2), jeopardizes balsam fir (Abies balsamea [L.] Mill.) growth and recruitment to the canopy. Balsam fir is a preferred browsed species of white-tailed deer during winter. In a second-growth stand resulting from a clearcut and a fire in 1959, we investigated the stand structure and developmental patterns of fir stems using dendroecological methods. White spruce (Picea glauca [Moench] Voss), a less palatable, occasionally browsed species, was used as a control to evaluate the influence of repeated browsing on fir and to differentiate it from the possible effects of other factors. Our data showed that deer browsing delayed vertical and radial growth and altered the stand structure in favor of white spruce. Browsing resulted in a semi-open stand with a tree layer dominated by white spruce and a scattered understory of predominantly small balsam fir (< 3 m) of approximately the same age as spruce. Stem analysis showed that growth patterns varied among the fir sampled. The few stems that had escaped deer browsing showed faster stem development, punctuated by short periods of minimal growth. Above the mean maximum level of browsing (ca. 110 cm from ground level), mean vertical growth was twice (17 cm year-1) that calculated for the lower part (9.3 cm year-1). The fir tree-ring series showed a major growth depression between 1985 and 1989, possibly associated with increased deer browsing pressure and spruce budworm activity. Incomplete rings were also frequent after 1984. Browsing intensity on fir may increase in years to come because of an expected higher site attendance. This could favor white spruce at the expense of balsam fir.
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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 | 0.001 | 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".