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 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) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".