Temporal dynamics of oxygen isotope compositions of soil and canopy CO<sub>2</sub> fluxes in a temperate deciduous forest
Bibliographic record
Abstract
Abstract Partitioning of CO2 exchange into canopy (FA) and soil (FR) flux components is essential to improve our understanding of ecosystem processes. The stable isotope C18OO can be used for flux partitioning, but this approach depends on the magnitude and consistency of the isotope disequilibrium (Deq), i.e., the difference between the isotope compositions of FR (δA) and FA (δR). In this study, high temporal resolution isotopic data were used (1) to test the suitability of existing steady state and nonsteady models to estimate H218O enrichment in a mixed forest canopy, (2) to investigate the temporal dynamics of δA using a big‐leaf parameterization, and (3) to quantify the magnitude of the C18OO disequilibrium (Deq) in a temperate deciduous forest throughout the growing season and to determine the sensitivity of this variable to the CO2 hydration efficiency (θeq). A departure from steady state conditions was observed even at midday in this study, so the nonsteady state formulation provided better estimates of leaf water isotope composition. The dynamics of δR was mainly driven by changes in soil water isotope composition, caused by precipitation events. Large Deq values (up to 11‰) were predicted; however, the magnitude of the disequilibrium was variable throughout the season. The magnitude of Deq was also very sensitive to the hydration efficiencies in the canopy. For this temperate forest during most of the growing season, the magnitude of Deq was inversely proportional to θeq, due to the very negative δR signal, which is contrary to observations for other ecosystems investigated in previous studies.
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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 | 0.000 | 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 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".