South American and African Grass Species Cope Differently With Soil Water Availability
Bibliographic record
Abstract
African grasses pose a serious threat to the integrity and conservation of the Cerrado biome (Brazilian savanna). This study evaluated the responses of an invasive (Melinis minutiflora) and a native (Schizachyrium microstachyum) grass species to water availability, simulating natural situations. Individuals of the two species were submitted to different soil moisture levels, simulating from drought to flood, for four weeks in a climate-control chamber. Several morphological and physiological parameters were assessed: shoot height, biomass, number of leaves, tillers, leaf area, leaf gas exchange and chlorophylla fluorescence parameters, photosynthetic pigments and MDA concentration and GST, G-POX, APX and CAT activities. Significant differences were observed between species and among soil moisture levels, being drought more detrimental to both. Although both species were able to cope with water stress conditions and performed best at 80% soil moisture, the invasive species grew more rapidly, showed higher net photosynthetic rates in all circumstances and showed less evidence of stress. Variations in soil moisture levels promoted a stronger response in the native species, reducing biomass accumulation and triggering a stronger biochemical response than in the invasive species.
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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".