Aboveground dry matter partitioning responses of black spruce to directional-specific indices of local competition
Bibliographic record
Abstract
This study assessed the effects of directional-specific indices of local competition on the partitioning of aboveground dry matter of individual black spruce (Picea mariana (Mill.) BSP) trees. Historical tree reconstruction sampling techniques were used to estimate stem, branch, and foliage ovendry masses by year of formation (cohort age-class) of 125 subject trees situated within 15 density-stressed stands. Component-specific modular mass proportion calculated on an individual and cumulative cohort age-class basis was employed as an index of dry matter partitioning. Analytically, local competitors were stratified into one of four competition classes based on their relative size differential with respect to the subject tree. Sequential competition analysis was used to assess directional-specific partitioning responses to competition accumulating upwards from below and downwards from above. Furthermore, within the sequential competition analysis framework, the effects of the individual competition strata on partitioning were assessed employing stepwise multivariate analysis of variance. The results supported the presence of an asymmetric relationship dominated by competition from above in which branch partitioning was the most affected. Specifically, competition from larger-sized competitors resulted in decreased branch mass proportions whereas competition from smaller-sized competitors had no appreciable effect. These results are in accord with the hypothesis that black spruce responds to competition via an adaptive phenotypic plastic response in which branch growth declines and (or) branch abscission rates increase with increasing competition from above.
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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".