Distribution patterns of desert plant diversity and relationship to soil properties in the Heihe River Basin, China
Bibliographic record
Abstract
Abstract The study on the patterns of plant species diversity and the factors influencing these patterns forms the basis of ecology and is fundamental to conservation biology. In this paper, desert plant species diversity and soil properties (nutrient and texture) were investigated along desert region of the Heihe River Basin (HRB) to determine whether soil environmental factors influenced desert plant species diversity. We found a total of 44 shrub and herb species belonging to 40 genera of 17 families. The largest family was the Compositae, accounting for 25.0% of the total. Twenty‐four survey plots were clustered into eight plant community types. The Margalef richness (D), Simpson dominance (C), Pielou evenness (Jsw), and Shannon‐wiener (H) index differed significantly among community types. Redundancy analysis (RDA) revealed a relatively strong relationship between the species diversity and soil environmental factors. The first RDA axis accounted for 80.5% and 81.8% of the variation in soil nutrient and texture properties, respectively, but was not statistically significant. RDA suggested that total phosphorus (TP) and medium sand (0.25–0.5 mm) content were the only two statistically significant factors in the study area. Both classification and ordination resulted in a clear demonstration of the spatial variability of community and soil properties. In general, the distribution pattern of desert plant community was mainly related to soil nutrient and texture properties factors, but the relation was not strong. This study provides insights into desert plant diversity and community conservation of Inland HRB in arid desert ecosystems.
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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 | 0.001 | 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) | 0.001 | 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".