Evaluation of a new battery of toxicity tests for boreal forest soils: Assessment of the impact of hydrocarbons and salts
Bibliographic record
Abstract
The ability to assess the toxic potential of soil contamination within boreal regions is currently limited to test species representative of arable lands. This study evaluated the use of six boreal plant species (Pinus banksiana, Picea glauca, Picea mariana, Populus tremuloides, Calamagrostis Canadensis, and Solidago canadensis) and four invertebrate species (Dendrodrilus rubidus, Folsomia nivalis, Proisotoma minuta, and Oppia nitens) and compared their performance to a suite of standard agronomic soil test species using site soils impacted by petroleum hydrocarbon (PHC) and salt contamination. To maintain horizon-specific differences, individual soil horizons were collected from impacted sites and relayered within the test vessels. Use of the boreal species was directly applicable to the assessment of the contaminated forest soils and, in the case of the hydrocarbon-impacted soil, demonstrated greater overall sensitivity (25th percentile of estimated species sensitivity distribution [ESSD25] = 5.6% contamination: 10,600 mg/kg fraction 3 [F3; equivalent hydrocarbon range of >C16 to C34] Of/Oh horizon, and 270 mg/kg F3 Ahg horizon) relative to the standard test species (ESSD25 = 23% contamination: 44,000 mg/kg F3 Of/Oh horizon, and 1,100 mg/kg F3 Ahg horizon). For salinity, there was no difference between boreal and standard species with a combined ESSD25 = 2.3%, equating to 0.24 and 0.25 dS/m for the Ah and Ck horizons. The unequal distribution of soil invertebrates within the layered test vessels can confound test results and the interpretation of the toxic potential of a site. The use of test species relevant to boreal eco-zones strengthens the applicability of the data in support of realistic ecological risk assessments applicable to the boreal regions.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".