Excision increases branch water potential but reduces leaf gas exchange
Bibliographic record
Abstract
Measurement of leaf gas exchange is often complicated by the difficulty of sampling leaves from tall or otherwise inaccessible plants.Branch excision is widely used to enable such measurements, but the magnitude, variability, and mechanisms of its effects on water potential and gas exchange are not well characterized across species and contexts.We quantified the effects of excision on branch water potential, stomatal conductance, photosynthesis, and stomatal behaviour (parameter g1) in four angiosperm and one gymnosperm tree species differing in hydraulic traits and water-use strategies.To assess generality, we also conducted a meta-analysis of 26 species spanning a broad range of hydraulic traits, water-use strategies, and biomes.Excision consistently increased branch water potential in all species.In angiosperms, excision reduced stomatal conductance and photosynthesis, with decreases in g1 for some species, whereas in the gymnosperm, excision increased stomatal conductance, photosynthesis, and g1.The meta-analysis showed that excision generally decreased stomatal conductance and photosynthesis, with effect sizes varying by species, water-use strategy, and hydraulic traits.These results demonstrate that the effects of excision are strongly species-and trait-dependent.Careful consideration and study-specific corrections are needed when interpreting gas exchange data from excised branches.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".