Drought weakens the positive effects of defoliation on native rhizomatous grasses but enhances the drought‐tolerance traits of native caespitose grasses
Bibliographic record
Abstract
Abstract The objective of this study was to evaluate the drought tolerance, compensatory growth, and different plant traits between two native perennial caespitose grasses and two native rhizomatous grasses in response to drought and defoliation. A randomized complete block design at the Swift Current Research and Development Centre ( SCRDC ) of Agriculture and Agri‐Food Canada ( AAFC ) examined the effects of water stress and clipping on the plant biomass, plant morphological traits, and relative leaf chlorophyll content ( SPAD value) of four native grasses (caespitose grass: Hesperostipa comata and H. curtiseta ; rhizomatous grass: Pascopyrum smithii and Elymus lanceolatus ). Drought drastically decreased the shoot and root biomass, plant height, number of tillers and leaf growth of P. smithii and E. lanceolatus , as well as the rhizome biomass and R/S ratio of P. smithii . Defoliation had a positive effect on the shoot biomass of P. smithii and E. lanceolatus under well water treatments (100% and 85% of field capacity). However, the compensatory growth of P. smithii and E. lanceolatus significantly declined with increased water stress. In addition, there are no significant changes in plant biomass, plant height, number of tillers and leaves, and SPAD value of H. comata and H. curtiseta under relative dry condition (70% of field capacity). Consequently, these results demonstrated that the rhizomatous grasses possessed a stronger compensation in response to defoliation under wet conditions, but the positive effects of defoliation can be weakened by drought. The caespitose grasses ( Hesperostipa species) exhibited a greater drought tolerance than rhizomatous grasses due to the relatively stable plant traits in response to water stress.
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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".