Drought stress ecophysiology of shrub and grass functional groups on opposing slope aspects of a temperate grassland valley
Bibliographic record
Abstract
Plant functional groups with contrasting growth strategies co-occur in semiarid ecosystems. In the northern Great Plains, woody shrubs and grasses interact competitively, with shrubs prevalent on mesic hillslopes. To understand topographic influences on physiological drought acclimation, we measured seasonal photosynthetic water use in C3 shrubs ( Artemisia cana Pursh and Rhus trilobata Nutt.) and grasses ( Agropyron cristatum (L.) Gaertn. and Stipa viridula Trin.) on north- and south-facing slopes. Relationships between abiotic controls and photosynthesis were similar on both aspects, indicating an absence of long-term photosynthetic acclimation to xeric, south-facing conditions. Acclimatory differences were observed between functional groups. Soil moisture depletion lowered intercellular:atmospheric CO2 ratio (Ci/Ca) and increased intrinsic water-use efficiency (WUEi = Amax/gs) in shrubs, but not grasses. Consequently, between-slope differences in net photosynthesis (Amax) and stomatal conductance (gs) occurred only in shrubs, with lower values on the south-facing slope. Shrubs also exhibited between-slope differences in the photochemical reflectance index, suggesting drought-related photoprotection. The deuterium:hydrogen ratios of stem water showed that deep water use facilitated late summer growth in shrubs. Consistent with plant distribution, cumulative water use and photosynthesis were higher in shrubs than in grasses on the north-facing slope, but higher in grasses than in shrubs on the south-facing slope. This shows that topographic effects on leaf photosynthetic gas exchange are mediated by physiological acclimation strategy and water source use.
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".