Voegtlin‐style suction traps measure insect diversity and community heterogeneity
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Comparing ecologically relevant communities of insects in heterogeneous environments requires methods capable of sampling a sufficient number of individuals and diversity of species to measure β diversity. A battery‐operated computer fan powers a 1.5 m high Voegtlin suction trap. These traps are efficient at capturing small, weakly flying insects, and can be used to sample the α and β diversity of Microhymenoptera in discrete habitats within a temperate forest ecosystem. During a preliminary study comparing Voegtlin‐style suction and Townes‐style Malaise traps, we found that the suction traps caught a greater number and a greater diversity of Hymenoptera than the Malaise traps, especially of those OTUs smaller than 1.5 mm. Placed along a transect at 50 m intervals, the suction traps also yielded more heterogeneous samples than the Malaise traps, suggesting they may be particularly useful for quantifying β diversity at small spatial scales. The same analyses with brachyceran Diptera were more nuanced. Malaise traps outperformed suction traps in terms of measuring α diversity, but suction traps resolved a higher degree of brachyceran community heterogeneity using β diversity. Insofar as Hymenoptera are amongst the most diverse of insect orders and the vast majority of species are specialist parasitoids of other insects, suction trapped Hymenoptera diversity may be a useful proxy for measuring α and β insect diversity in general.
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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 | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 it