Spatial pattern of male and female Oedaleus asiaticus in the upper reaches of Heihe River,western China
Bibliographic record
Abstract
It is important to study how male and female grasshoppers respond to topography-induced environmental changes and to identify dominant topographic factors that affect the spatial distribution. The spatial heterogeneity pattern of male and female grasshoppers responding to terrain reflects the resource co-evolution mechanism that grasshoppers adapt to the diversity of habitats. Through field survey from July to August,2009,by using the GIS and S-PLUS,we developed a GAM model for Oedaleus asiaticus in the upper reaches of Heihe River on the northern slope of Qilian Mountain. The topographic indices included elevation,direction,slope,position,profile and plane. The results showed that the structure and D2values of models were different for male and female,so was the model stability in modeling,indicating their differences in response to the gradients of topographic indices. The gradient analysis in this model showed that male and female were distributed in a wide range of environments,in different gradients of elevation,direction,slope,position,profile and plan,in all land positions. However,this did not mean that the distribution of male and female was equally affected by each factor,or had a uniform distribution probability in the whole environmental range. The GAM modeling results indicated that the distribution of male and female were mainly controlled by the elevation,but the upper limit of elevation for distribution of the female grasshopper was higher than that of the male. On the regional distribution,there was higher abundance of the female in the whole region,but they were mainly located in the region with profile less than 0,and the male mainly concentrated in the south and southwest slopes. The heterogeneity attribute of O. asiaticus in selecting habitats made the spatial pattern of male and female in the same terrain obviously different.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".