The effects of NPK fertilization for nine years on boreal forest vegetation in northwestern Canada
Bibliographic record
Abstract
Plant productivity is limited by mineral nutrient availability in many boreal forest ecosystems. This study is an analysis of the growth responses of components of a boreal plant community (cryptogams, herbaceous and woody perenni- als, the dominant shrubs Salix glauca (grey willow) and Betula glandulosa (bog birch) and the dominant tree Picea glauca (white spruce), to the addition of an NPK fertilizer over a nine- year period. The study was carried out in a low-nutrient boreal forest ecosystem in the Yukon territory in northwestern Canada. The following predictions were tested: (1) that there would be an overall increase in abundance (measured either as cover, density, or dry mass) of all components of the vegetation, (2) that vegetation composition would change as more competitive species increased in abundance and (3) that initial community changes in response to fertilization would be transient. In gen- eral, all predictions were found to be true. Species composition changed rapidly in response to fertilizer. Graminoids (e.g. Festuca altaica) and some dicots (e.g. Mertensia paniculata and Achil- lea millefolium) increased in cover, while other dicots (e.g. Anemone parviflora), dwarf shrubs (e.g. Arctostaphylos uva- ursi), bryophytes and lichens declined. There was a significant increase in the growth rate of the two dominant shrubs and of Picea, but not in the cone crop or seed production by Picea. Surveys after 1 or 2 years showed responses by the vegetation but more stable patterns of response did not emerge until after 5 or 6 years. There were consistent and directional changes in the percent cover of some of the herbaceous species on control plots. Growth rates of Salix and Betula varied considerably from year to year, independently of treatment. Long-term studies are essential if we are to understand the role of nutrient limitation in this ecosystem.
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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 | 0.000 |
| Science and technology studies | 0.001 | 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 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".