Intercomparison of soil pore water extraction methods for stable isotope analysis
Bibliographic record
Abstract
Abstract Measurements of δ2H and δ18O composition of pore waters in saturated and unsaturated soil samples are routinely performed in hydrological studies. A variety of in‐situ and lab‐based pore water extraction methods for the analysis of the stable isotopes of water now exist. While some have been used for decades (e.g. cryogenic vacuum extraction) others are relatively new, such as direct vapour equilibration or the microwave extraction technique. Despite their broad range of application, a formal and comprehensive intercomparison of soil water extraction methods for stable isotope analysis is lacking and long overdue. Here we present an intercomparison among five commonly used lab‐based pore water extraction techniques (high pressure mechanical squeezing, centrifugation, direct vapour equilibration, microwave extraction, and cryogenic extraction). We applied these extraction methods to two physicochemically different soil types that were dried and rewetted with water of known isotopic composition at three different water contents. Our results showed that the extraction approach can have a significant effect on pore water isotopic composition as all methods exhibited significant deviations from the spiked reference water, depending secondarily on the soil type and soil water content. Most pronounced, cryogenic water extraction showed large deviations from the spiked reference water, whereas mechanical squeezing and centrifugation provided results closest to the spiked water for both soil types. We also compared results for each extraction method – where liquid water was obtained – on both an OA‐ICOS and IRMS. Differences between these two analytical instruments were negligible for these organic compound‐free waters. We suggest that users of soil water extraction approaches carefully choose an extraction technique that is suitable for the specific research question, adapted to the dominant soil type and water content of the study. Copyright © 2016 John Wiley & Sons, Ltd.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".