Evidence for competition and facilitation trade-offs: effects of Sitka alder density on pine regeneration and soil productivity
Bibliographic record
Abstract
We suggest that the net outcome of interactions between regenerating conifers and early seral deciduous species depends on trade-offs between competition and facilitation over time. Vegetation management treatments that dramatically reduce competitive effects of deciduous species may constrain the ability of conifers to optimize resource trade-offs (e.g., increased growth response to light at the expense of increased drought mortality), potentially affecting long-term productivity. In a 15-year study in southern interior British Columbia, we investigated whether lodgepole pine (Pinus contorta Dougl. ex Loud. var. latifolia Engelm.) survival, growth, and resource availability differed among manipulated stand compositions, from pure pine stands to mixtures with native N2-fixing Sitka alder (Alnus viridis subsp. sinuata (Regel) Á. Löve & D. Löve) or herbs. We found that pine growth increases were sustained only in pure stands, where alder and herbs were completely removed, corresponding with short-term increases in light, soil and air temperature, and soil nitrate. However, this came at a significant cost to survival (through loss of protection from browsing, desiccation, and sun scald), as well as dramatic depletions in soil nitrogen mineralization over the longer term. Our results support a competitionfacilitation trade-off hypothesis, suggesting that treatment-imposed shifts in resource availability over time could negatively affect forest productivity.
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 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 | 0.001 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".