Photosynthetic and growth responses of the C<sub>3</sub> <i>Bromus inermis</i> and the C<sub>4</sub> <i>Andropogon gerardii</i> to tree canopy cover
Bibliographic record
Abstract
Agroforestry systems are designed to improve the efficiency of use of available resources and to increase potential site productivity. The capability of a plant to acclimate to shade when cultivated beneath trees is important in determining the success of agroforestry projects. The objectives of this study were to determine the morphological, physiological and growth responses of C4big bluestem ( Andropogon gerardii Vitman.) and C3smooth bromegrass ( Bromus inermis Leyss) to various canopy levels of green ash ( Fraxinus pennsylvanica Marsh) in the field, and to examine the impacts of these responses on grass yield. Net photosynthesis (Anet), stomatal conductance (gs), and dark respiration (Rd) declined in response to shade in both species, but the decline was steeper in big bluestem than in smooth bromegrass. Total chlorophyll content (Tchl), specific leaf area (SLA), and N content of the leaves increased with shade in both species. In addition, Tchl, SLA, N, and gs were significantly greater in smooth bromeg r ass than in big bluestem at all canopy levels. Lower gs and N, and higher Anet in big bluestem resulted in a higher water and N use efficiencies in this species than in smooth bromegrass. Yield of big bluestem sharply declined with increased canopy cover, whereas yield of smooth bromegrass was not affected by canopy cover. Our results indicate that while both species were productive under various levels of green ash canopy, and showed similar ecophysiological responses to shade, smooth bromegrass acclimate d better to shade than big bluestem. Key words:
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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) | 0.001 | 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".