Groundwater Depth Affects Phosphorus But Not Carbon and Nitrogen Concentrations of a Desert Phreatophyte in Northwest China
Bibliographic record
Abstract
Ecological stoichiometry is an important aspect in the analysis of the changes in ecological system composition, structure, and function and understanding of plant adaptation in habitats. Leaf carbon (C), nitrogen (N), and phosphorus (P) concentrations in desert phreatophytes can be affected by different depths of groundwater through its effect on the adsorption and utilization of nutrient and plant biomass. We examined the biomass, soil organic C, available (mineral) N, and available P, and leaf C, N, and P concentrations of Alhagi sparsifolia grown at varying groundwater depths of 2.5, 4.5, and 11.0 m in 2015 and 2016 growing seasons in a desert-oasis ecotone in northwest China. The biomass of A. sparsifolia and the C, N, and P concentrations in soil and A. sparsifolia showed different responses to various groundwater depths. The leaf P concentration of A. sparsifolia was lower at 4.5 m than at 2.5 and 11.0 m likely because of a biomass dilution effect. By contrast, leaf C and N concentrations were generally unaffected by groundwater depth, thereby confirming that C and N accumulations in A. sparsifolia were predominantly determined by C fixation through the photosynthesis and biological fixation of atmospheric N2, respectively. Soil C, N, and P concentrations at 4.5 m were significantly lower than those at 11.0 m. Leaf P concentration was significantly and positively correlated with soil N concentration at all of the groundwater depths. The C:N and C:P mass ratios of A. sparsifolia at 4.5 m were higher than those at the other groundwater depths, suggesting a defensive life history strategy. Conversely, A. sparsifolia likely adopted a competitive strategy at 2.5 and 11.0 m as indicated by the low C:N and C:P mass ratios. To our knowledge, this study is the first to elucidate the variation in the C, N, and P stoichiometry of a desert phreatophyte at different groundwater depths in an arid ecosystem.
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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 | 0.000 |
| 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".