Contrasting Nitrate Adsorption in Andisols of Two Coffee Plantations in Costa Rica
Bibliographic record
Abstract
Fertilizer use in coffee plantations is a suspected cause of rising ground water nitrate concentrations in the ground water-dependent Central Valley of Costa Rica. Nitrate adsorption was evaluated beneath two coffee (Coffea arabica L.) plantations in the Central Valley. Previous work at one site had identified unsaturated zone nitrate retardation relative to a tritium tracer. Differences in nitrate adsorption were assessed in cores to 4 m depth in Andisols at this and one other plantation using differences in KCl- and water-extractable nitrate as an index. Significant adsorption was confirmed at the site of the previous tracer test, but not at the second site. Anion exchange capacity, X-ray diffraction data, extractable Al and Si, and soil pH in NaF corroborated that differences in adsorption characteristics were related to subtle differences in clay mineralogy. Soils at the site with significant nitrate adsorption showed an Al-rich allophane clay content compared with a more weathered, Si-rich allophane and halloysite clay mineral content at the site with negligible adsorption. At the site with significant nitrate adsorption, nitrate occupied less than 10% of the total anion adsorption capacity, suggesting that adsorption may provide long-term potential for mitigation or delay of nitrate leaching. Evaluation of nitrate sorption potential of soil at local and landscape scales would be useful in development of nitrogen management practices to reduce nitrate leaching to ground water.
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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 | 0.001 | 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".