Growth and physiological responses of isohydric and anisohydric poplars to drought
Bibliographic record
Abstract
Understanding how different plants prioritize carbon gain and drought vulnerability under a variable water supply is important for predicting which trees will maximize woody biomass production under different environmental conditions. Here, Populus balsamifera (BS, isohydric genotype), P. simonii (SI, previously uncharacterized stomatal behaviour), and their cross, P. balsamifera x simonii (BSxSI, anisohydric genotype) were studied to assess the physiological basis for biomass accumulation and water-use efficiency across a range of water availabilities. Under ample water, whole plant stomatal conductance (gs), transpiration (E), and growth rates were higher in anisohydric genotypes (SI and BSxSI) than in isohydric poplars (BS). Under drought, all genotypes regulated the leaf to stem water potential gradient via changes in gs, synchronizing leaf hydraulic conductance (Kleaf) and E: isohydric plants reduced Kleaf, gs, and E, whereas anisohydric genotypes maintained high Kleaf and E, which reduced both leaf and stem water potentials. Nevertheless, SI poplars reduced their plant hydraulic conductance (Kplant) during water stress and, unlike, BSxSI plants, recovered rapidly from drought. Low gs of the isohydric BS under drought reduced CO2 assimilation rates and biomass potential under moderate water stress. While anisohydric genotypes had the fastest growth under ample water and higher photosynthetic rates under increasing water stress, isohydric poplars had higher water-use efficiency. Overall, the results indicate three strategies for how closely related biomass species deal with water stress: survival-isohydric (BS), sensitive-anisohydric (BSxSI), and resilience-anisohydric (SI). Implications for woody biomass growth, water-use efficiency, and survival under variable environmental conditions are discussed.
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 | 0.001 |
| 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".