Can the missing understory in old-growth forests on Haïda Gwaii (British Columbia, Canada) recover after deer exclusion?
Bibliographic record
Abstract
Large herbivores and deer in particular can have dramatic effects on ecosystem functions and act as keystone species in many forest systems. At high densities, deer are assumed to determine the structure and composition of forest understory. The introduction in the late 19th century of the Sitka black-tailed deer (Odocoileus hemionus sitkensis) on Haïda Gwaii archipelago (British Columbia, Canada) gave us the opportunity to illustrate the effects of predator-free deer populations on previously unbrowsed old-growth forest understory vegetation and the potential for recovery after a prolonged reduction of deer density. We installed and monitored a network of twenty 25m² enclosures from 1997 to 2005. We compared changes in species richness, apparition events, and vegetation cover by height strata in plots that were fenced or not. Protection from deer had no effect on total species richness but created a stable situation that favoured species appearance and establishment. Species tended to appear first inside the enclosures. The exclusion of deer had a positive effect on overall vegetation cover in height strata directly accessible to deer, but not above the browse line (>1.5m). Deer limited maximum height reached by the species outside the enclosures. Analysis of the vegetation cover by species groups (trees, shrubs, herbs) did not reveal any effect of the exclusion of deer. However, some species as Cornus canadensis, Menziesia ferruginea, Blechnum spicant, Lysichiton americanus exhibited a positive response to the protection from deer whereas more dominant species like Gaultheria shallon and Vaccinium sp. were not influenced. As expected, deer exclusion did result in some recovery of understory in Haïda Gwaii forest understory. Furthermore, fenced plots may be considered as sources for surrounding patches. However the slow vegetation growth recorded associated to potential interspecific competition with browse resistant species could prevent the understory recovery if a significant reduction of deer abundance is not maintained over a long period of time.
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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 | 0.000 | 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".