Interactive effects of water and nitrogen addition on soil microbial communities in a semiarid steppe
Bibliographic record
Abstract
Better understanding of microbial compositional and physiological acclimation mechanisms is critical for predicting terrestrial ecosystem responses to global change. The aim is to assess variations in soil microbial communities under future scenarios of changing precipitation and N deposition in a semiarid grassland of northern China. In order to explicitly estimate microbial responses, a field experiment with water and N addition was established in April 2005 and continuously conducted for 4 years. Specifically, soil microbial community composition and microbial C utilization potential were determined by phospholipid fatty acid (PLFA) and community-level physiological profiles, respectively. Water addition had no effects on the PLFA concentrations of gram-positive (GP) and negative bacteria (GN), total bacteria and fungi. However, N addition caused significant reductions in the PLFA concentrations of GP, GN, total bacteria and fungi and thus decreased total PLFA of microbial communities. Moreover, there were interactive effects of water and N addition on GN/GP and the ratio of fungal to bacterial PLFA (F/B). In addition, synergistic effects were found between water and nitrogen in affecting microbial C utilization potentials, which implies that microbial C utilization potentials tend to be enhanced when both N and water availability are sufficient. Overall, the microbial responses to water and N addition support our hypothesis that water and N addition may be combined together to affect microbial communities in the semiarid grassland.
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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 | 0.000 |
| 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".