Diversity Patterns in Iberian <I>Calathus</I> (Coleoptera, Carabidae: Harpalinae): Species Turnover Shows a Story Overlooked by Species Richness
Bibliographic record
Abstract
We assessed the relationships between diversity patterns of Iberian Calathus and current environmental gradients or broad-scale spatial constraints, using 50-km grid cells as sampling units. We assessed the completeness of the inventories using nonparametric estimators to avoid spurious results based on sampling biases. We modeled species richness and beta diversity, using spatial position, and 23 topographical, climatic, and geological variables as predictors in regression and constrained analysis of principal coordinates modeling. Geographical situation does not seem to affect Calathus species richness, because no spatial pattern was detected. The environmental variables only explained 23% of the variation in richness. Spatial and environmental predictors explained a large part of the variation in species composition (58%). The fraction shared by both groups of variables was relatively large, but the pure effect of each model was still important. Our results show that it is necessary to assess the completeness of inventories to avoid drawing false conclusions. Also, Iberian Calathus represent a clear example of the need for combined analyses of species richness and beta diversity patterns, because the lack of patterns in the former does not imply the invariance of biotic communities.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.025 | 0.001 |
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; both teacher heads agree on what is shown here.
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".