Variation in a Darwin Wasp (Hymenoptera: Ichneumonidae) Community along an Elevation Gradient in a Tropical Biodiversity Hotspot: Implications for Ecology and Conservation
Bibliographic record
Abstract
Understanding how biodiversity varies from place to place is a fundamental goal of ecology and an important tool for halting biodiversity loss. Parasitic wasps (Hymenoptera) are a diverse and functionally important animal group, but spatial variation in their diversity is poorly understood. We survey a community of parasitic wasps (Ichneumonidae: Pimplinae) using Malaise traps up a mountain in the Brazilian Atlantic Rainforest, and relate the catch to biotic and abiotic habitat characteristics. We find high species richness compared with previous similar studies, with abundance, richness, and diversity peaking at low to intermediate elevation. There is a marked change in community composition with elevation. Habitat factors strongly correlated with elevation also strongly predict changes in the pimpline community, including temperature as well as the density of bamboo, lianas, epiphytes, small trees, and herbs. These results identify several possible surrogates of pimpline communities in tropical forests, which could be used as a tool in conservation. They also contribute to the growing evidence for a typical latitudinal gradient in ichneumonid species richness, and suggest that low to medium elevations in tropical regions will sometimes conserve the greatest number of species locally, but to conserve maximal biodiversity, a wider range of elevations should also be targeted.
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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 | 0.001 | 0.001 |
| 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) | 0.001 | 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".