Effect of pipeline installation on crop yield and some biological properties of boreal soils
Bibliographic record
Abstract
Pipeline construction on the Grey soils of the Canadian boreal plains, which have a thin Ah horizon, could have considerable impact on their properties and productivity. This study was conducted because the effects of pipeline installation on crop yield and biological properties of these soils have not been well-documented. Soil was sampled from a Grey Luvisol and a Dark Grey Solod prior to pipeline construction in 1991, and in each of the following 3 yr. The right-of-way (RoW) was divided into three zones: a road (or work) area used for vehicular traffic; a trench where the pipeline was buried; and a pile (or spoil) area where soil was stockpiled during construction. The RoW was cropped to barley (Hordeum vulgare L.) in 1992 through 1994. Barley yield was low in 1992 (830–1120 kg ha−1), and near average (2050–3290 kg ha−1) in 1993 and 1994. Except for low shoot P concentration (1.1–1.3 mg g−1) in 1992, macronutrient concentrations (N, P and K) in barley tissues were within normal ranges. Soil organic carbon was reduced by 12–28% in all RoW areas in 1993 and 1994. Soil total N was reduced by 29–49% in all RoWs in 1992 and increased slightly from those levels in 1993 and 1994. Pipeline construction affected soil microbial biomass carbon (MBC) in the three RoW areas differently, and the effect was not consistent from year to year. However, the average level of MBC was not adversely impacted. In 1994, soil phosphatase activity in the RoW zones tended to be lower as compared to pre-pipeline installation, particularly in the pile area of the Dark Grey Solod. It is concluded that although some soil biological properties were degraded by pipeline construction, and barley yield was reduced in 1992, crop production in the following 2 yr was not significantly affected. Key words: Barley, carbon, microbial biomass, nitrogen, phosphatase, pipeline
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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 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".