Emergence, survival and growth of selected plant species in petroleum-impacted flare pit soils
Bibliographic record
Abstract
One of the prerequisites to phytoremediation of hydrocarbon-contaminated soils is that plants be able to germinate and become established in the presence of contaminants. This 5-wk growth chamber study examined the tolerance of five grasses and one legume to petroleum hydrocarbons (PHCs) and associated salts in three weathered, fine-textured, flare pit soils obtained from NE British Columbia. Plant tolerance to these soils was measured by percent seedling emergence (PSE), percent seedling survival (PSS) and 5-wk dry shoot biomass; a non-contaminated control soil was included in the study. The contaminated soils showed a wide range in total PHC concentrations (Soil A: 0.1 %, Soil B: 1.8 %, Soil C: 16 % PHC by mass) and in the recently established Canadian Council of Ministers of the Environment (CCME) PHC Tier 1 fractions 1–4. Electrical conductivity in contaminated soils ranged from 3.00 (Soil B) to 5.16 (Soil A) dS m-1. Medicago sativa (alfalfa, cv. Peace) was sensitive (low PSS, PSE and shoot biomass) to high salinity of Soil A but flourished in Soil B, a soil with F3 a nd F4 (gravimetric) concentrations that exceeded CCME PHC Tier 1 Eco Contact standards for agricultural, residential and parkland soils. When considering the combined effects of PHC and salts, Bromus inermis (smooth brome, cv. Carlton) was the grass most tolerant of contaminants in the weathered industrial soils. Compared to other plants, it consistently produced relatively high PSS, PSE and shoot biomass. Soil C was slightly hydrophobic and all plants showed reduced shoot biomass compared to other soils; however, average shoot biomass for Bromus inermis was almost twice as great as any other plant species growing in this soil. More research on the properties and remediation of historic flare pit soils is warranted. Key words: Hydrocarbons, phytoremediation, soil contamination, soil remediation, CCME, soil toxicity
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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) | 0.000 | 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".