C:N:P stoichiometry of rhizosphere soils differed significantly among overstory trees and understory shrubs in plantations in subtropical China
Bibliographic record
Abstract
Rhizosphere soil C:N:P stoichiometry is useful for identifying the linkage of plant species and soil nutrients, which can be particularly helpful for understory vegetation management of forest ecosystems. There has been limited research on rhizosphere soil stoichiometry, especially for co-existing overstory and understory plant species. We investigated the bulk and rhizosphere soil C:N:P stoichiometry of dominant overstory trees and understory shrubs (Adinandra millettii, Eurya muricata, and Loropetalum chinense) in Pinus massoniana Lamb., Pinus elliottii Engelm., and Cunninghamia lanceolata (Lamb.) Hook. plantations in subtropical China. Rhizosphere soil C, N, and P concentrations and ratios increased significantly compared with bulk soil, and those of overstory trees were higher than those of understory shrubs with the exception of L. chinense. Rhizosphere soil C:N, C:P, and N:P of L. chinense were not significantly different with those of overstory trees but were higher than those of A. millettii and E. muricata. Soil pH significantly influenced the profiles produced by soil C, N, and P concentrations and their stoichiometries. This study indicated that the difference in nutrient status between overstory trees and understory shrubs was related to shrub species, in which soil pH was the dominant driving factor. Understory shrub species should be considered in plantation management to reduce resource competition among species.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| 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 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".