POPULATION STRUCTURE OF A DOMINANT HALOXYLON SPECIES, ACROSS A HABITAT GRADIENT IN THE SOUTHERN GURBANTUNGGUT DESERT, CENTRAL ASIA
Bibliographic record
Abstract
In the context of habitat change, widely distributed vegetation can serve as relevant barometers of ecosystems' sensitivity or resilience to disturbances.This study analyzed morphological variations in trees and recruits density, individual size and their spatial structure through Haloxylon population's field experiment in each sampling location.Our results showed a significant decrease in tree density from the south (4445 trees/ ha) to the central desert (481 trees/ ha), whereas basal diameter, crown radius and height showed different tendency.Tree basal diameter and height structure of populations had positively skewed asymmetric distributions with"reverse J" shape.Tree density in the valleys between dunes (6133 trees/ha) was greatest.Few recruits were found in the central desert, but their density increased from central to south of the Gurbantunggut desert ,perhaps owing to seed rain patterns and availability of soil moisture and nutrients.Trees had a spatially clustered distribution in all study plots.Haloxylon spp.can tolerate wide climatic and habitat fluctuations, however recruitment can be unpredictable in harsh desert conditions.Soil physicochemical properties were the main ecological factor influencing spatial patterns.With increasing altitude, soil moisture and nutrient contents decreased significantly.In different dune habitats, Haloxylon population had different characteristics.
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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".