Pan trapping in habitats supporting <i>Platanthera</i> (Orchidaceae) shows little difference in insect family-level diversity
Bibliographic record
Abstract
Abstract The role of insects as pollinators within plant communities is well established, yet our knowledge of insect biodiversity in many habitats is lacking. Given the growing concern that insect biodiversity is declining, it is increasingly important to document insect assemblages from a wide range of geographic locations and habitats. Pan trapping is a common means of sampling local insect diversity. Many studies have found different insects associated with different-coloured pan traps. Here, eight different-coloured pan traps were used to sample local insect diversity in habitats supporting Platanthera (bog and rein) orchids on Vancouver Island, British Columbia, Canada. A total of 16 sites supporting seven orchid species resulted in 435 insects from 53 families being caught over 64.9 hours of pan trapping. Both Shannon and Simpson diversity index values were low despite sampling in markedly different habitats. Yellow traps caught higher numbers of insects, but no statistical difference was found among colours overall. No activity indicating pollination was recorded from a total of 254 insect observations over 21.5 hours. Our results contribute important baseline data on the diversity and behaviour of insect communities in orchid habitats of Vancouver Island and on the use of pan traps to characterise insect communities.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".