How do leaf and ecosystem measures of water‐use efficiency compare?
Bibliographic record
Abstract
Summary The terrestrial carbon and water cycles are intimately linked: the carbon cycle is driven by photosynthesis, while the water balance is dominated by transpiration, and both fluxes are controlled by plant stomatal conductance. The ratio between these fluxes, the plant water‐use efficiency (WUE), is a useful indicator of vegetation function. WUE can be estimated using several techniques, including leaf gas exchange, stable isotope discrimination, and eddy covariance. Here we compare global compilations of data for each of these three techniques. We show that patterns of variation in WUE across plant functional types (PFTs) are not consistent among the three datasets. Key discrepancies include the following: leaf‐scale data indicate differences between needleleaf and broadleaf forests, but ecosystem‐scale data do not; leaf‐scale data indicate differences between C 3 and C 4 species, whereas at ecosystem scale there is a difference between C 3 and C 4 crops but not grasslands; and isotope‐based estimates of WUE are higher than estimates based on gas exchange for most PFTs. Our study quantifies the uncertainty associated with different methods of measuring WUE, indicates potential for bias when using WUE measures to parameterize or validate models, and indicates key research directions needed to reconcile alternative measures of WUE.
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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 | 0.000 |
| 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 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".