Bark water affects the isotopic composition of xylem water in tropical rainforest trees
Bibliographic record
Abstract
The movement of water between xylem and inner bark (phloem and associated tissues), mostly driven by water potential differences, forms a key part of the diel transpiration cycle. It is not known how the use of water stored in bark at the diel transpiration cycle may influence the isotopic composition of xylem water. Understanding these possible effects is a major challenge for the identification of tree water sources and the interpretation of water use patterns using isotopes. Here, we examined the variation in the isotopic composition of water in inner bark and xylem at the diel scale and assessed how this varied in relation to traits and water use strategies on nine tree species in a tropical rainforest at the end of the dry season. We measured δ2H and δ18O in bark and xylem at two shallow depths: ‘outer xylem’ and ‘inner xylem’ (up to ~0.5 cm and ~ 1 cm from inner bark, respectively) collected at predawn, morning and midday. Considering all species together, the average isotopic composition of water in bark and outer xylem was similar at predawn and midday, suggesting water exchange between these tissues was reflected at these times, but differed significantly in the morning during increased transpiration. Results suggest that bark-xylem water exchange throughout the diel transpiration cycle affects the isotopic composition of xylem water in tropical rainforest trees. Furthermore, variations in δ2H and δ18O between xylem and bark were more pronounced in a deep-rooted, more isohydric species with dense wood than in a shallow-rooted, more anisohydric species with low wood density. This may suggest differences related to traits and hydraulic strategies in the reliance of bark-stored water across the diel cycle to buffer changes in xylem water potential. We discuss implications for interpreting tropical tree water sources in relation to water use strategies.
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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) | 0.000 | 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".