Spatiotemporal Heterogeneity of Soil Available Nitrogen During Crop Growth Stages on Mollisol Slopes of Northeast China
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Bibliographic record
Abstract
Abstract Spatiotemporal heterogeneity of soil available nitrogen (AN) (sum of NO 3 − –N and NH 4 + –N) is the essential basis for soil management and highly correlates to crop yield. Both geostatistical and traditional analyses were used to describe the spatiotemporal distribution of AN in the 0–20‐cm soil depth on typical Mollisol slopes (S1 and S2) in Northeast China. The concentration of NO 3 − –N dynamics at slope positions was typically opposite to NH 4 + –N. The peak values of AN typically moved from the summit of the slope to the bottom from spring to autumn and were mainly influenced by the content of NO 3 − –N (S1, 7·9–18·9 mg kg −1 ; S2, 1·2–103·6 mg kg −1 ), both of NO 3 − –N (S1, 3·9–8·3 mg kg −1 ; S2, 2·2–28·0 mg kg −1 ) and NH 4 + –N (S1, 21·4–30·5 mg kg −1 ; S2, 2·1–23·3 mg kg −1 ), and NH 4 + –N (S1, 10·5–28·9 mg kg −1 ; S2, 5·0–39·0 mg kg −1 ) in the seedling stage, vegetative growth stage, and reproductive growth stage, respectively. The spatial autocorrelation of AN was strong and was mainly influenced by structural factors during crop growth stages. This was mainly determined by soil erosion–deposition (SED) and soil temperature–moisture (STM) in the seedling stage; this was also mainly influenced by SED, STM, crop type, and crop growth in the vegetative growth stage and by early STM and early SED in the reproductive growth stage. Generally, the content of AN, NO 3 − –N, and NH 4 + –N on the whole slope was mainly determined by the early SED and local fertilizer application, while their spatiotemporal heterogeneity, especially the evenness, was mainly changed by SED, STM, crop growth, and crop types on the slope scale. In order to increase more crop yields, additional N fertilizer application on both the summit and the bottom during the vegetative growth stage and conservation tillage systems or additional soil amendments on the back slopes was necessary. Copyright © 2016 John Wiley & Sons, Ltd.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 it