Elevational changes in the composition of insects and other terrestrial arthropods at tropical latitudes: a comparison of multiple sampling methods and social spider diets
Bibliographic record
Abstract
Abstract. We explored the extent to which differences between elevations in arthropod composition – insects and arachnids – are reflected by different sampling methods and in the diet of local social and subsocial spiders. We surveyed two low‐elevation tropical rainforest and two upper montane cloud forest sites in eastern Ecuador using blacklighting, sweeping, malaise traps, beating, and visual search. We also observed the prey captured by social (lowland rainforest) and subsocial (upper montane cloud forest) spider colonies in each habitat and related their diets to the insect composition yielded by the individual and combined set of techniques. The most notable differences between high‐ and low‐elevation sites in eastern Ecuador were an increase in the relative abundance of Hymenoptera, in particular ants, and a concomitant reduction in the representation of homopterans, dipterans and coleopterans at lower elevations. Differences between elevations, however, were only detected by three of the techniques employed (beating, sweeping and blacklighting). The proportions of major taxa categories in the spider diets were only significantly different from samples from their respective environments for the upper elevation subsocial spider against blacklighting and the combined set of all techniques, excluding blacklighting. Nonetheless, only sweeping had similarity indices greater than 75% for both species, with beating and malaise being the next most similar. The more advanced level of sociality and larger nests of the social species may facilitate exploitation of a more representative range of insect types from its environment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| 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".