Photosynthesis, nitrogen-use efficiency, and water-use efficiency of jack pine seedlings in competition with four boreal forest plant species
Bibliographic record
Abstract
The objective of this study was to understand the mechanism underlying nitrogen (N) and water competition between jack pine (Pinus banksiana Lamb.) and four boreal forest species. Large-leaved aster (Aster macrophyllus L.), Canada blue-joint grass (Calamagrostis canadensis (Michx.) Beauv.), trembling aspen (Populus tremuloides (Michx.), and red raspberry (Rubus idaeus L.) were planted at a range of densities (0-8 plants/m2) with jack pine seedlings. Net photosynthesis (Pn), nitrogen-use efficiency (NUE), water-use efficiency (WUE) of each species were monitored over three consecutive growing seasons. Changes in available soil N and water were also measured. Jack pine Pn, NUE, and WUE decreased as competitor density increased, but these effects varied among species (p < 0.001) and over time (p < 0.001). The influence of density on jack pine Pn decreased over time for aster and blue-joint grass and increased over time for aspen and raspberry (p < 0.001). At most sample times, jack pine Pn correlated with available soil N. In contrast, the correlation between jack pine Pn and soil water was rarely significant.
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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".