Differential response of soil microbial and animal communities along the chronosequence of Cunninghamia lanceolata at different soil depth levels in subtropical forest ecosystem
Bibliographic record
Abstract
Introduction: Soil biota plays a crucial role in the terrestrial ecosystem. There is growing momentum to understand the community structure and diversity of total belowground soil biota across large ecological scales. Soil biota follow divergent trends with respect to soil physiochemical properties in different ecosystems; however, little is known about their response to stand development across multiple soil depths in Chinese fir plantations, which is the most important tree species across all over China, popular for its timber production. Objectives: Here, we investigated the community assembly of soil bacteria, fungi, archaea, protists and animals across three different vertical soil profiles (0-10, 10-20, 20-40 cm) using a chronosequence of Chinese fir representing five different stand ages (5, 8, 21, 27, 40 years) in South China. Methods: High throughput illumine Hiseq2500 sequencing. Results: Our results showed that soil biotic communities exhibited a decreasing trend in alpha diversity of bacteria, fungi, protists and animals with increasing soil depth; however, archaea showed an opposite trend. Most abundant soil bacterial, fungal, archaeal, protist and animal classes were Acidobacteriia, Agaricomycetes, Bathyarchaeia, Chlorophyceae and Clitellata, respectively. Correlation of vertical distribution of biotic communities and variations in soil physiochemical properties explained that total nitrogen (TN), available phosphorus (AP) and pH were the most influencing factors for changes in soil biotic communities. Although the stand age was a contributing factor for fungal and animal beta diversity, however, as compared to soil depth, it was not dominatingly influencing the structure of other biotic communities. Conclusions: Collectively, these results reveal a new perspective on the vertical variation and distinct response patterns of soil biotic communities at a fine scale across different stand ages of Chinese fir plantations.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".