Effects of leaf length and development stage on the triple oxygen isotope signature of grass leaf water and phytoliths: insights for a proxy of continental atmospheric humidity
Bibliographic record
Abstract
Abstract. Continental relative humidity (RH) is a key climate parameter, but there is a lack of quantitative RH proxies suitable for climate model–data comparisons. Recently, a combination of climate chamber and natural transect calibrations have laid the groundwork for examining the robustness of the triple oxygen isotope composition (δ′18O and 17O-excess) of phytoliths, that can preserve in sediments, as a new proxy for past changes in RH. However, it was recommended that besides RH, additional factors that may impact δ′18O and 17O-excess of plant water and phytoliths be examined. Here, the effects of grass leaf length, leaf development stage and day–night alternations are addressed from growth chamber experiments. The triple oxygen isotope compositions of leaf water and phytoliths of the grass species F. arundinacea are analysed. Evolution of the leaf water δ′18O and 17O-excess along the leaf length can be modelled using a string-of-lakes approach to which an unevaporated–evaporated mixing equation must be added. We show that for phytoliths to record this evolution, a kinetic fractionation between leaf water and silica, increasing from the base to the apex, must be assumed. Despite the isotope heterogeneity of leaf water along the leaf length, the bulk leaf phytolith δ′18O and 17O-excess values can be estimated from the Craig and Gordon model and a mean leaf water–phytolith fractionation exponent (λPhyto-LW) of 0.521. In addition to not being leaf length dependent, δ′18O and 17O-excess of grass phytoliths are expected to be impacted only very slightly by the stem vs. leaf biomass ratio. Our experiment additionally shows that because a lot of silica polymerises in grasses when the leaf reaches senescence (58 % of leaf phytoliths in mass), RH prevailing during the start of senescence should be considered in addition to RH prevailing during leaf growth when interpreting the 17O-excess of grass bulk phytoliths. Although under the study conditions 17O-excessPhyto do not vary significantly from constant day to day–night conditions, additional monitoring at low RH conditions should be done before drawing any generalisable conclusions. Overall, this study strengthens the reliability of the 17O-excess of phytoliths to be used as a proxy of RH. If future studies show that the mean value of 0.521 used for the grass leaf water–phytolith fractionation exponent λPhyto-LW is not climate dependent, then grassland leaf water 17O-excess obtained from grassland phytolith 17O-excess would inform on isotope signals of several soil–plant-atmosphere processes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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 teacher head, 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".