Toward a common methodological framework for the sampling, extraction, and isotopic analysis of water in the Critical Zone to study vegetation water use
Bibliographic record
Abstract
Abstract The analysis of the stable isotopic composition of hydrogen and oxygen in water samples from soils and plants can help to identify sources of vegetation water uptake. This approach requires that the heterogeneous nature of plant and soil matrices is carefully accounted for during experimental design, sample collection, water extraction and analyses. The comparability and shortcomings of the different methods for extracting water and analyzing isotopic composition have been discussed in specialized literature. Yet, despite insightful comparisons of extraction methods and benchmarking methodologies of laboratories worldwide, the community still lacks a roadmap to guide sample collection, extraction, and isotopic analyses, and many practical issues for potential users remain unresolved: for example, which (soil or plant) water pool(s) does the extracted water represent? These constitute a hurdle for the implementation of the approach by newcomers. Here, we summarize discussions led in the framework of the COST Action WATSON (“WATer isotopeS in the critical zONe: from groundwater recharge to plant transpiration”—CA19120). We provide guidelines for (1) sampling soil and plant material for isotopic analysis, (2) methods for laboratory or in situ water extraction, and (3) measurements of isotopic composition. We highlight the importance of considering the process chain as a whole, from experimental design to isotopic analysis to minimize biased estimates of the relative contribution of different water sources to plant water uptake. We conclude by acknowledging some of the limitations of this methodology and advice on the collection of key environmental parameters prior to sample collection for isotopic analyses. This article is categorized under: Science of Water > Hydrological Processes Science of Water > Water and Environmental Change Science of Water > Water Extremes
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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 | 0.201 | 0.098 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.015 | 0.008 |
| Science and technology studies | 0.005 | 0.013 |
| Scholarly communication | 0.011 | 0.009 |
| Open science | 0.014 | 0.013 |
| Research integrity | 0.006 | 0.015 |
| Insufficient payload (model declined to judge) | 0.002 | 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".