Immediate effects of chemical and mechanical soil preparation techniques on epigaeic arthropod assemblages during reclamation of in situ oil and gas sites in northern Alberta, Canada
Bibliographic record
Abstract
Epigaeic arthropods have been used worldwide as indicators of post-disturbance recovery in many different types of ecosystems. We used them to evaluate the merit of different reclamation prescriptions applied to areas disturbed by oil and gas exploration and extraction. We compared the short-term effects of different mechanical and chemical site preparation techniques on the epigaeic arthropod fauna of previously reclaimed borrow pits in arrested succession with results from plots in untreated disturbed sites and undisturbed adjacent forest. In general, arthropod diversity increased and abundance decreased with the severity of soil disturbance involved in the silvicultural prescription. We place arthropod communities into four discrete groups reflected in the treatments and the environmental characteristics of the sites: forest species, grassland species, species primarily found in herbicide plots, and species found in disturbed soil. Individual borrow pits accounted for a significant amount of variation in faunal assemblages, suggesting that site location, vagaries of colonization, or disturbance history play a significant role in how the fauna recovers post disturbance. Our study provides baseline data required to document the trajectory of recovery in these sites. Long-term monitoring is essential to evaluate the relative usefulness of reclamation prescriptions in meeting targets established by law.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".