Nitrogen fertilization weakens the linkage between soil carbon and microbial diversity: A global meta‐analysis
Bibliographic record
Abstract
Soil microbes make up a significant portion of the genetic diversity and play a critical role in belowground carbon (C) cycling in terrestrial ecosystems. Soil microbial diversity and organic C are often tightly coupled in C cycling processes; however, this coupling can be weakened or broken by rapid global change. A global meta-analysis was performed with 1148 paired comparisons extracted from 229 articles published between January 1998 and December 2021 to determine how nitrogen (N) fertilization affects the relationship between soil C content and microbial diversity in terrestrial ecosystems. We found that N fertilization decreased soil bacterial (-11%) and fungal diversity (-17%), but increased soil organic C (SOC) (+19%), microbial biomass C (MBC) (+17%), and dissolved organic C (DOC) (+25%) across different ecosystems. Organic N (urea) fertilization had a greater effect on SOC, MBC, DOC, and bacterial and fungal diversity than inorganic N fertilization. Most importantly, soil microbial diversity decreased with increasing SOC, MBC, and DOC, and the absolute values of the correlation coefficients decreased with increasing N fertilization rate and duration, suggesting that N fertilization weakened the linkage between soil C and microbial diversity. The weakened linkage might negatively impact essential ecosystem services under high rates of N fertilization; this understanding is important for mitigating the negative impact of global N enrichment on soil C cycling.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".