Differential structure and function of phosphorus‐mineralizing microbial communities in organic and upper mineral soil horizons across a temperate rainforest chronosequence
Bibliographic record
Abstract
Microbial community structure and function were assessed in the organic and upper mineral soil across a ~4000-year dune-based chronosequence at Big Bay, New Zealand, where total P declined and the proportional contribution of organic soil in the profile increased with time. We hypothesized that the organic and mineral soils would show divergent community evolution over time with a greater dependency on the functionality of phosphatase genes in the organic soil layer as it developed. The structure of bacterial, fungal, and phosphatase-harbouring communities was examined in both horizons across 3 dunes using amplicon sequencing, network analysis, and qPCR. The soils showed a decline in pH and total phosphorus (P) over time with an increase in phosphatase activity. The organic horizon had a wider diversity of Class A (phoN/phoC) and phoD-harbouring communities and a more complex microbiome, with hub taxa that correlated with P. Bacterial diversity declined in both horizons over time, with enrichment of Planctomycetes and Acidobacteria. More complex fungal communities were evident in the youngest dune, transitioning to a dominance of Ascomycota in both soil horizons. Higher phosphatase activity in older dunes was driven by less diverse P-mineralizing communities, especially in the organic horizon.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".