Different adaptive responses of leaf physiological and biochemical aspects to drought in two contrasting populations of seabuckthorn
Bibliographic record
Abstract
Two contrasting populations of seabuckthorn ( Hippophae rhamnoides L.) from western China were employed to study their differences in adaptive responses to drought. The Daofu population was from a wetter upland climate region, whereas the Dingxi populations was from a drier lowland climate region. A completely randomized design with two factors, two populations and two watering regimes (100% and 25% of the soil water holding capacity), was used. In both populations, drought significantly decreased growth and the net photosynthesis rate (A), and significantly increased the root/shoot ratio (RS), catalase (CAT), peroxidase (POD), glutathione peroxidase (GPX) and ascorbate peroxidase (APX) activities, and abscisic acid (ABA) and proline contents. Compared with the Daofu population, drought induced a greater RS value, higher CAT, GPX, and APX activities, and a higher ABA content in the Dingxi population, whereas the gas exchange traits, for example, the stomatal limitation value (LS) and intercellular CO2 concentration (Ci), were less responsive to drought in the Dingxi population. The two populations may have developed different strategies to tolerate drought, such as different pathways to dissipate excess absorbed light energy, to resist oxidative stress, and to keep water status. Such factors enable the Dingxi population to tolerate drought better than the Daofu population.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".