Meta-analysis shows plant diversity enhances grassland carbon and nitrogen cycles
Bibliographic record
Abstract
This study is a global meta-analysis of the effects of grassland plant species richness on aboveground and belowground carbon and nitrogen dynamics. Observations from 73 studies in grasslands totaling 1385 paired observations of plant mixtures and monocultures were compiled. Response variables included nine carbon and six nitrogen processes to plant diversity, examined the effects of experimental types and age on the responses, and predicted the carbon and nitrogen balance following different biodiversity loss scenario in grasslands. We found that carbon and nitrogen functions significantly enhanced in plant mixtures, but varied with experimental types. Most of the attributes was significantly correlated with species richness and experimental age, the relationship between species richness and carbon and nitrogen processes was interacted with experimental duration in the field experiments, except for soil respiration, fungal biomass, and soil nitrate nitrogen. Importantly, our results showed that the declines in soil carbon and nitrogen pool accelerated following plant diversity loss. Our meta-analysis revealed that the plant diversity has ubiquitous impacts on carbon and nitrogen cycles in grasslands, likely driven by complementarity effects of plant diversity on plant productivity and biomass, underlined interactive effects of plant diversity, experimental types and age, and climate on carbon and nitrogen processes, and suggested that the reduction in carbon and nitrogen stocks in grasslands will be larger following biodiversity loss in the future.
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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 | 0.011 | 0.011 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.010 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".