Grouseberry (<em>Vaccinium scoparium</em> Leiberg ex Coville) fruit production in forest openings in Banff National Park, Alberta
Bibliographic record
Abstract
Grouseberry (Vaccinium scoparium Leiberg ex Coville) is an abundant dwarf shrub in the understory of many areas of subalpine forest in Banff National Park and has the potential to produce fruit important for wildlife. However, the suppression and prevention of wildfires, which began in the early 1900s in the park, have reduced fire-dependent shrubland and open forest and increased the extent of closed, mature forest. Because canopy closure is typically associated with decreased fruit production by understory shrubs, the decline in fire disturbance may be reducing Grouseberry fruit production. To quantify this effect, we measured Grouseberry fruit production under various forest canopies at 10 sites in Banff during 2004–2012. We measured site openness by modeling photosynthetically active direct solar radiation (dPAR) adjusted for overshadowing by topography and coniferous foliage. We found a positive relation between Grouseberry fruit production and dPAR in 2006 and 2010–2012, but not in 2008 or 2009, the 2 years of lowest fruit production; data were lacking for 2004, 2005, and 2007. We also recorded high Grouseberry fruit densities beginning 5 years after fire removed the forest canopy in four prescribed burns conducted during 2001: fruit production was 3.3 to more than 20 times that in adjacent mature forests in 5 of the 6 years analyzed. This study shows the potential ecological benefits of both prescribed burns and wildfire in upper subalpine forests where Grouseberry is widespread, but fruit production is low under the forest canopy.
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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 | 0.001 |
| 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".