No evidence of a common pattern of taxon or phylogenetic diversity across elevation for beetle (Coleoptera) families
Bibliographic record
Abstract
Abstract Mountains are among the most diverse terrestrial habitats on Earth, and understanding how montane species are distributed is a first step towards predicting how these taxa will respond to changing thermal environmental conditions. While most reported patterns of diversity and elevation are negative or hump‐shaped relationships, syntheses of these patterns are mostly derived from vertebrates. Here, we explored over 270 studies from the literature (more than a third of which we could reanalyse their data) to test whether beetles (Coleoptera) displayed a uniform pattern predicted by these syntheses at the family level. We found that deriving a common diversity/elevation pattern for beetles was not possible as our search results contained a tremendous taxonomic bias towards two families out of 176 (ground beetles (Carabidae) and dung beetles (Scarabaeidae)), and for most families, we found no reported investigation of elevation and diversity. We also found that the two most diverse families of beetles (Staphylinidae and Curculionidae) were severely underrepresented in our data set. Within the two better‐sampled families, we examined the diversity/elevation relationship using two measures of diversity: taxonomic and phylogenetic. For each family, we found no common trend of diversity across elevation. In both phylogenetic diversity and genus richness, the Scarabaeidae showed a strong negative relationship with elevation, while the Carabidae showed a much weaker negative relationship (mainly due to intrafamilial variation in the patterns observed). We conclude that a generalised pattern of diversity and elevation for beetles is not yet possible given that (1) most known patterns are from only two families, (2) patterns within those families are not the same and (3) that the most diverse beetle families are relatively understudied.
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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".