Influence of predictors and assembly processes in the structure of microbial communities in disturbed soil ecosystems
Bibliographic record
Abstract
The environmental factors and assembly processes influencing microbial community structure and dynamics help with understanding the trajectories followed by these communities after disturbance or along restoration projects. This study analyzed the predictors associated with variability in microbial communities of soils that were stockpiled for later use as a reclamation substrate for post-mining sites in Alberta, Canada. We applied a null model operational framework to shed light on the assembly processes influencing β-diversity in the microbial communities of stockpiled soil in a chronosequence of 0.5 to 28 years and from 0 to 300 cm depth.. Microbial communities of disturbed and undisturbed soils were significantly different. Some of the conditions that characterized the disturbed soils (i.e., Increase in non-native plant groups and soil nutrients), were positively correlated with microbial diversity and with the microbial taxa that accounted for the difference between stockpiled and reference soils. However, only ∼1/5 of microbial community variability was explained by the environmental predictors assessed in our study. Overall, stochastic factors exerted the most important influence over community assembly processes in microbes (Bacteria, Archaea, and fungi). Homogenizing dispersal and dispersal limitation were the most important processes influencing the structure of bacterial communities, whereas the fungi were mainly governed by drift. Nevertheless, the relative influence of specific stochastic processesvaried depending on soil depth, storage time, and taxa abundance. Our results provide insights into microbial groups that may be indicators of soil disturbance and reveal that selective pressures promoted by environmental filters or legacy effects may not be as important as usually described in the literature for the structuring and variability of the microbial communities in stockpiled soils.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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 teacher head, 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".