An evaluation of methods for sampling ants (Hymenoptera: Formicidae) in British Columbia, Canada
Bibliographic record
Abstract
Abstract Ants (Hymenoptera: Formicidae) are ubiquitous and of considerable ecological interest, yet poorly studied in Canada. Given their natural history attributes and relatively low density and diversity in cool boreal forests, there is a need to evaluate the applicability of commonly used approaches to sampling and analysis. We examined the relative utility of two pitfall trap designs, mini-Winkler litter extractions, and colony versus forager sampling for ecological studies. First, we found that Laurent (conventional) and Nordlander (modified to exclude larger nontarget organisms) pitfall traps were equally efficacious for estimating total species richness. Second, pitfall trapping yielded marginally higher total species richness than mini-Winkler litter sampling, by the incidence-based estimator (Chao2). Third, two studies considering the relationship between captures of individual ants in pitfall traps and identified ant colonies argued for caution in how pitfall captures are interpreted. In the first study, Nordlander traps placed in a grid surrounding nests ofFormica obscuripesForel revealed unique and highly patchy captures of individuals, with no patterns relating to proximity to the nest. In the second study, abundance estimates to compare ant assemblage structure in a simple grassland ecosystem by pitfall trapping (relative) and area-based hand sampling (absolute) for colonies, revealed that relative sampling does not reflect the absolute ant assemblage structure. Our results support, equivocally, the use of pitfall traps (Nordlander) over mini-Winklers in the cool moist forests of west-central British Columbia, but individual specimen counts should not be used when analysing the data.
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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 | 0.008 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".