Inconsistent Growth Response to Fertilization and Thinning of Lodgepole Pine in the Rocky Mountain Foothills Is Linked to Site Index
Bibliographic record
Abstract
Fertilization of conifers often results in highly variable growth responses across sites which are difficult to predict. The goal of this study was to predict the growth response of lodgepole pine (Pinus contorta var. latifolia) crop trees to thinning and fertilization using basic site and foliar characteristics. Fifteen harvest-origin stands along the foothills of the Rocky Mountains of Alberta were subjected to six treatments including two levels of thinning (thinning to 2500 stems per hectare and a control) and three types of fertilization (nitrogen-only fertilization, complete fertilization including nitrogen with added P, K, S, Mg, and B, and no fertilization). After three growing seasons, the growth response and foliar status of the crop trees were examined and this response was related to site and foliar characteristics. There was a small and highly variable additive response to fertilization and thinning; diameter growth of crop trees increased relative to the controls an average of 0.3 cm with thinning, 0.3 cm with either N-only or complete fertilization and 0.6 cm when thinned and fertilized. The increase in diameter growth with thinning and nitrogen-only fertilization was positively related to site index but not to any other site factors or pretreatment foliar variables such as nutrient concentrations, ratios, or thresholds.
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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 | 0.000 | 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 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".