The relationship between altitudinal gradients, diversity, and body size in a dung beetle (Coleoptera: Scarabaeinae: <i>Onthophagus</i>) model system
Bibliographic record
Abstract
Mountainous regions represent an excellent model to test ecological hypotheses encompassing assemblage diversity and body traits of species. Among insects, there is no uniform body size pattern across temperature gradients, suggesting that processes controlling body size may differ among species. The aim of this study was to explore diversity and body size patterns of dung beetle species of the genus Onthophagus Latreille, 1802 across altitudinal gradients at two mountains in Mexico. Tropical mountain species were sampled from 2200 to 3400 m a.s.l. In both mountains, there was a decrease of richness and abundance of Onthophagus with increasing altitude. There were contrasting relationships between beetle body size and altitude, which varied depending on the data set analyzed. Furthermore, interspecific variations of body size were not related to the number of altitudinal bands recorded by each species. Species from high altitudes were also recorded at lower mountain altitudes, suggesting that diversity at the highest altitudes represents a subgroup of lowland diversity. This may indicate that the fauna inhabiting higher elevations could be the most eurytopic one. Here we present an example of an assemblage that partially contradicts Bergmann’s rule, with contrasting effects of altitude on dung beetle body size.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".