The role of salal in forest regeneration problems in coastal British Columbia: problem or symptom?
Bibliographic record
Abstract
The ericaceous shrub, salal (Gaultheria shallon Pursch) is associated with forest regeneration problems on a variety of site types along the west coast of North America. On dry sites, salal is a serious competitor for water; on wet (cedar-salal) sites, salal is thought to limit nutrient availability to trees by competing, interfering with mycorrhizae and "short-circuiting" the nitrogen cycle through production of phenolic compounds. Short-term field experiments and laboratory and greenhouse studies provided some evidence of each of these effects. However, long-term results from a suite of silvicultural trials and associated ecological studies indicated that salal is not the fundamental problem for regenerating conifers on cedar-salal sites. Fertilization of cedar-salal sites caused a large and sustained response in tree growth regardless of the presence of salal, and growth responses to salal removal were much smaller than fertilization responses. Greenhouse experiments indicated that salal does not have allelopathic effects on germination or growth of conifer seedlings. In laboratory studies, salal did not demonstrate a greater capacity to take up organic N forms than the conifers, and molecular studies uncovered a vast diversity of mycorrhizal fungi associated with salal and hemlock roots. Together these findings indicate that the nutrient "short-circuiting" hypothesis, based on assumptions about ericoid versus non-ericoid mycorrhizal plants does not adequately describe the nutrition of plants in these ecosystems. We conclude that salal should be viewed as a symptom of the underlying problem of poor nutrient supply on cedar-salal sites, and that fertilization, rather than salal control, is the optimal solution for improving forest regeneration on these sites. Key words: ericaceous shrubs, fertilization, scarification, allelopathy,mycorrhizae, Gaultheria shallon, nitrogen
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".