Spatial relationship between δ<sup>15</sup>N and elevation in agricultural landscapes
Bibliographic record
Abstract
Understanding of the nitrogen (N) cycle and its spatial variability is important for managing ecosystems. Soil δ<sup>15</sup>N, as an important indicator of different soil nitrogen cycling processes, may provide critical information about the spatial variability in soil N cycling. The objective of this study was to examine the dominant landscape scale variability of δ<sup>15</sup>N, the location of the variability and its spatial relationship with elevation. Soil δ<sup>15</sup>N and elevation were measured along two transects (Davidson and Elstow, Saskatchewan, Canada). Each transect had 128 points with 3 m sampling intervals. Higher δ<sup>15</sup>N values typically occurred in topographic depressions as compared to knolls. The coefficient of determination revealed a significant linear relationship between δ<sup>15</sup>N and elevation (<i>r</i><sup>2</sup>=0.27) at Davidson whereas no relationship (<i>r</i><sup>2</sup>=0.00) was detected for the Elstow transect. However, wavelet spectra, cross wavelet, and squared wavelet coherency analysis revealed spatial relationships between δ<sup>15</sup>N and elevation at both sites. A strong coherency between δ<sup>15</sup>N and elevation at large scales (96 m or more) was detected for both transects. The Davidson transect showed an out of phase coherency at a topographically elevated area at the beginning and the end of the transect. The Elstow transect had a strong out of phase correlation (negative relationship) at the middle of the transect (corresponding to a depressions) indicating a location dependent relationship between δ<sup>15</sup>N and elevation. The relationship between δ<sup>15</sup>N and elevation reflects the effects of hydrology and soil water content over the landscape on N cycling processes.
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How this classification was reachedexpand
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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 teacher head, 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".