Global soil microbial biomass decreases with aridity and land‐use intensification
Bibliographic record
Abstract
Abstract Aim Although global patterns are emerging for the soil total microbial biomass pool, our understanding of the distribution of the finer groups, especially bacterial and fungal biomass, remains limited. Moreover, we lack mechanistic insights into the global variation of soil microbial biomass. Location Global terrestrial ecosystems. Time period 1990–2019. Major taxa studied Bacteria and fungi. Methods By conducting a global synthesis of 4,472 observations from 577 sites published in 404 studies, we examined the global patterns and drivers of the soil total microbial biomass, bacterial and fungal biomass and fungi‐to‐bacteria ratio. Results We found that soil total microbial, bacterial and fungal biomass peaked concurrently in tundras, with lower values in deserts, and that intensification of land use reduced soil total microbial, bacterial and fungal biomass and the fungi‐to‐bacteria biomass ratio. Soil organic carbon was the most important driver for global distribution patterns of both bacterial and fungal biomass. Our structural equation models indicated that soil bacterial and fungal biomass increased with water availability through its positive effect on soil organic carbon on a global scale. In contrast, soil total, bacterial and fungal biomass decreased with mean annual temperature and intensification of land use via their negative effects on soil organic carbon. Main conclusions Our results suggest that decreasing water availability and land‐use intensification could reduce soil microbial biomass and the relative abundance of soil fungi to bacteria, impairing their functions and the services they provide.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".