Exploring the long-term impact of organic amendments on restored quarry soil microbial communities by shotgun metagenome sequencing.
Bibliographic record
Abstract
Abstract In quarries, human extractive activities degrade the soil’s physical and chemical qualities, affecting microbial communities. The application of organic amendments is known to improve the soil’s physical, chemical and biochemical properties, causing short-term changes in taxonomic composition and function of bacterial communities. The objective of this study is to determine the long-term effects of organic amendments applied to degraded quarry soils on the taxonomic composition and function of bacterial communities by shotgun metagenome sequencing (MGS). The study site is located in a limestone quarry in the Sierra de Gádor (SE, Spain). In 2018, five different organic amendments were applied to 15 experimental plots (three replicates per treatment): greenhouse waste compost (COHort), garden waste compost (COVG), WWTP sludge (SS), COHort+SS mixture, COVG+SS mixture and three unamended control plots (CON). Forty Stipa tenacissima L. Kunth plants were planted per plot. Five years after the amendments were applied, rhizosphere soil samples were collected for DNA extraction. Sequencing was performed on an Illumina platform and data analyzed using a custom Kraken2+MMseqs2 pipeline. Differential abundance tests were performed for important taxa/EC numbers/pathways and comparisons of richness and diversity (Kruskal-Wallis). The most abundant bacterial phyla in all samples were Proteobacteria, Actinobacteria, and Firmicutes. Five years after the incorporation of organic amendments, although clustering patterns were observed in the taxonomic distribution, no significant differences in richness and diversity were observed between treatments. This lack of significant differences suggests that after five years the bacterial composition could be influenced by factors such as bacterial dormancy and dispersal, “soil memory” or the influence of the plant on the rhizosphere microbiota. The restoration process seems to lead to a situation where soils present similar composition and diversity in terms of taxonomy, functions and metabolic pathways. This finding has important implications for the understanding of the long-term effects of soil management practices, highlighting the need to investigate the in-depth mechanisms behind this homogenization process.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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".