Investigating the impacts of biochar on water fluxes in tropical agriculture using stable isotopes
Bibliographic record
Abstract
Abstract. Amending soils with biochar, a pyrolyzed organic material, is an emerging practice to potentially increase plant available water. However, it is not clear (1) to what extent biochar amendments increase soil water storage relative to non-amended soils and (2) whether plants grown in biochar amended soils access different pools of water compared to those grown in non-amended soils. To investigate these questions, we set up an upland rice field experiment in a tropical seasonally dry region in Costa Rica, with plots treated with two different biochar amendments and control plots, from where we collected hydrometric and isotopic data (δ18O and δ2H from rain, soil, groundwater and rice plants). Our results show that the soil water retention curves for biochar treated soils shifted, indicating that rice plants had 2 % to 7 % more water available throughout the growing season relative to the control plots. In addition, we observed a within treatment variability in the soil water retention curves which was in the same order of magnitude as one would expect from responses due to differences in biochar application rates or due to differences in biochar typologies. The stable water isotope composition of plant water showed that the rice plants across all plots preferentially utilized the more variable soil water from the top 20 cm of the soil instead of using the deeper and less variable sources of water. Our results indicated that rice plants in biochar amended soils could access larger stores of water more consistently and thus could withstand dry spells of seven extra days relative to rice grown in non-treated soils. Though supplemental irrigation was required to facilitate plant growth during extended dry periods. Therefore, biochar amendments can complement, but not necessarily replace, other water management strategies.
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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".