Brine-induced soil gradients drive microbial community assembly and ecological partitioning
Bibliographic record
Abstract
Brine (produced water) releases from oil and gas infrastructure alter soil physicochemical properties, disrupt vegetation, and affect microbial communities vital for soil function. We evaluated long-term brine disturbance effects on soil microbiota at a 25-hectare boreal site in northern Alberta, Canada. Soils, including both topsoil (A horizon) and subsoil (B horizon) layers, were sampled along four 300 m transects spanning undisturbed forest to brine-impacted areas. Soil gradients intensified toward brine-impacted zones, with electrical conductivity (EC) increasing from 0.1 to 40 dS m -1 , sodium adsorption ratio (SAR) from 0.1 to 41, and pH from 4 to 8. Microbial diversity declined with rising EC, SAR, and pH, however, even in very strongly saline soils (EC > 16 dS m -1 ), Shannon diversity indices remained above 7. Approximately one-third of the microbial genera shifted in abundance along these gradients, with salinity-adapted taxa enriched and key oligotrophic groups declining. We identified tipping points in salinity, sodicity, and pH gradients—at EC 1.9 and 4.2 dS m -1 , SAR 3.5 and 6.4, and pH ∼5.5—coinciding with major shifts in community composition. Habitat partitioning was evident, with 27% and 39% of taxa specialized to unimpacted and brine-impacted soils, respectively, while 20% were generalists. Network analysis revealed denser community assembly but reduced robustness in brine-impacted soils, indicating greater vulnerability to environmental perturbations. These findings highlight how soil microbiota reflect both the detrimental effects of brine disturbance and adaptive responses, underscoring their value as bioindicators for soil health assessment in salt-impacted landscapes.
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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 | 0.001 | 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".