A bioassay of crop response to fertilizer nutrients in soils from a chronosequence of reclaimed natural gas pipeline rights‐of‐way
Bibliographic record
Abstract
Abstract Construction of underground pipelines on cropland impacts the soil ecosystem, resulting in crop yield losses persisting for several years after right‐of‐way (ROW) reclamation. Information on whether higher than recommended fertilizer application rates could improve productivity of reclaimed ROWs is scarce. The objective of this growth room bioassay was to determine the productivity response of a chronosequence of reclaimed ROW soils to differential fertilizer rates. Bulk soil samples were collected from the 0 to 20 cm soil layer on two ROWs of different ages (i.e., time since reclamation, TSR). The experiment was laid out in a completely randomized design with a 3 × 3 factorial treatment structure with three replications per treatment. The factors were TSR (4 and 10 year plus undisturbed (off‐ROW) sites) and fertilizer application rates (no fertilizer (Check); recommended rate (100%) of nitrogen (N), phosphorus (P), potassium (K), and sulphur (S); and 150% of the recommended N, P, K, and S rates). The recommended nutrient rates produced 66% lower canola dry matter yield (DMY) and 45% lower wheat DMY in the 4‐year ROW soil relative to the off‐ROW soil. Increasing the rate to 150% of the recommended rate significantly increased canola and wheat DMY in the 4‐year ROW soil to levels similar to those in the off‐ROW soil receiving the recommended rate. Nitrogen uptake by canola and wheat was 30%–45% lower, while P uptake was 40%–55% lower in the ROW soils than in the off‐ROW soil. These results indicate incomplete recovery of the ROW soils within at least the first 4 year following completion of reclamation. However, crop yields were not significantly different between the 10 year ROW and the off‐ROW at 100% fertilizer rate suggesting that productivity had been restored to off‐ROW levels by year 10 following reclamation. Findings from this study will contribute towards the formulation of strategies for improving the productivity of reclaimed ROWs on cropland.
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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) | 0.001 | 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".