Relation of soil-, surface-, and ground-water distributions of inorganic nitrogen with topographic position in harvested and unharvested portions of an aspen-dominated catchment in the Boreal Plain
Bibliographic record
Abstract
Spatial distributions of soil extractable nitrate (NO3) and ammonium (NH+4) concentrations were related to surface- and ground-water NO3and NH+4concentrations in harvested and forested sections of a catchment dominated by trembling aspen (Populus tremuloides Michx.) in the subhumid boreal forest of Alberta, Canada. NO3and NH+4concentrations in soils varied spatially throughout the catchment and were larger in surface soils than in subsurface soils. Spatial distributions of soil inorganic nitrogen (N) concentrations were not explained by the harvested versus the unharvested condition; heterogeneity was instead related to topographic position. NO3concentrations in both surface and subsurface soils were largest in ephemeral draws and wetlands. NH+4concentrations in subsurface soils were largest in ephemeral draws and wetlands, but this pattern was not apparent for surface soils. Soil NO3and NH+4availability and surface- and ground-water NO3and NH+4concentrations reflected soil NO3and H+4concentrations. N-rich surface soils in both forested and harvested areas have a large potential for releasing N to surface waters. This study indicates that even though topography is subtle in this catchment, topographic position and its soil moisture relations, along with vegetation demand, can influence N transformation and transport in both forested and harvested portions of the Boreal Plain landscape.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 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".