Temporal Trends in Soil Health and Productivity on Reclaimed Natural Gas Pipeline Rights‐of‐Way on Cropland
Bibliographic record
Abstract
ABSTRACT The construction of underground pipelines negatively impacts soil productivity in various ecosystems. However, the temporal progression in the recovery of soil productivity following the reclamation of cropland impacted by natural gas pipeline rights‐of‐way (ROWs) construction remains unclear. This study examined temporal, post‐reclamation changes in selected soil health indicators and productivity on reclaimed underground natural gas pipeline ROWs on cropland. Soil and crop samples were collected from ROWs ranging in time elapsed since reclamation (TSR) from 6 to 12 years and from adjacent undisturbed locations (off‐ROW) in the same field. The soil samples were analyzed for soil health indicators (permanganate‐oxidizable carbon (POXC), soil respiration, and autoclaved citrate‐extractable (ACE) protein) and selected chemical properties. Crop samples were assessed for grain and total biomass yields as well as grain protein content. Compared to the off‐ROW, soil organic C on the ROWs was 29% (6‐year ROW) and 33% (9‐year ROW) lower than on the off‐ROWs. Soil respiration recovered within 6 years of ROW reclamation, whereas it took 12 years for POXC and ACE protein to recover to off‐ROW levels. Grain and biomass yields 12 years post‐reclamation were still 42% and 36%, respectively, lower on the ROWs than on the off‐ROWs. However, measured soil attributes recovered faster than crop variables, indicating that pipeline construction on cropland has longer‐term impacts on crop yields than on soil attributes. These results indicate that, although underground pipeline construction has detrimental impacts on soil and crop attributes, these attributes would slowly recover to pre‐construction levels with increasing TSR.
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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".