Two Measurement Methods of Leaf Dry Matter Content Produce Similar Results in a Broad Range of Species
Bibliographic record
Abstract
BACKGROUND AND AIMS: Leaf dry matter content (LDMC) is widely used as an indicator of plant resource use in plant functional trait databases. Two main methods have been proposed to measure LDMC, which basically differ in the rehydration procedure to which leaves are subjected after harvesting. These are the 'complete rehydration' protocol of Garnier et al. (2001, Functional Ecology 15: 688-695) and the 'partial rehydration' protocol of Vendramini et al. (2002, New Phytologist 154: 147-157). METHODS: To test differences in LDMC due to the use of different methods, LDMC was measured on 51 native and cultivated species representing a wide range of plant families and growth forms from central-western Argentina, following the complete rehydration and partial rehydration protocols. KEY RESULTS AND CONCLUSIONS: The LDMC values obtained by both methods were strongly and positively correlated, clearly showing that LDMC is highly conserved between the two procedures. These trends were not altered by the exclusion of plants with non-laminar leaves. Although the complete rehydration method is the safest to measure LDMC, the partial rehydration procedure produces similar results and is faster. It therefore appears as an acceptable option for those situations in which the complete rehydration method cannot be applied. Two notes of caution are given for cases in which different datasets are compared or combined: (1) the discrepancy between the two rehydration protocols is greatest in the case of high-LDMC (succulent or tender) leaves; (2) the results suggest that, when comparing many studies across unrelated datasets, differences in the measurement protocol may be less important than differences among seasons, years and the quality of local habitats.
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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 | 0.003 | 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".