Effects of warming and oxalic acid addition on plant–microbial competition in <i>Picea brachytyla</i>
Bibliographic record
Abstract
The importance of oxalic acid for tree seedling growth and the competition for inorganic nitrogen (N) by plants and soil microorganisms under warming was investigated using 15N tracer techniques in Picea brachytyla (Franch.) E. Pritz. Results showed that warming combined with oxalic acid application induced growth enhancements in seedlings primarily through increases in fine root length and fine root surface area. Moreover, soil NH4 +, NO3 –, PO4 3–, N mineralization, microbial biomass carbon (MBC), and microbial biomass nitrogen (MBN) were significantly higher or tended to be higher with oxalic acid application. However, warming with oxalic acid application altered the partitioning of N between plants and soil microorganisms by increasing microbial 15N recovery to a lesser extent than it increased plant 15N recovery. While plants showed no specific preferences between N forms under normal conditions or warming alone, under warming and oxalic acid, plants showed a preference for 15NO3. Microorganisms showed a stronger preference for 15NH4 especially under warming and oxalic acid treatments. These findings suggest that plasticity in resource use could be an important mechanism in alleviating competition for soil N between plants and microbes under warming and oxalic acid addition.
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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 | 0.000 | 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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".