Owl pellets: a more effective alternative to conventional trapping for broad‐scale studies of small mammal communities
Bibliographic record
Abstract
Summary Small mammal community composition is almost universally estimated from conventional trapping, which is logistically difficult to scale up for landscape‐level assessments. Owl pellets may be a more effective alternative for measuring small mammal community composition over large geographic areas due to the relative ease and low cost of field collections. However, owl pellets may introduce sampling biases that differ from those associated with conventional trapping. A thorough comparison to conventional traps is required before owl pellets can be widely adopted as an alternative research tool for small mammal studies. We conducted a literature review of owl diet‐prey availability studies to: (i) compare small mammal community composition between owl pellets and trapping when the two methods were used simultaneously and (ii) assess the influence of owl genus and habitat type on community composition estimated by these two methods. We used data from 27 published studies, which allowed for 32 comparisons between owl pellets and trapping conducted simultaneously. These studies included 15 owl species from five common genera from different major habitats. Rarefied estimates showed that owls consistently sampled identical or higher species richness compared to conventional trapping. Richness estimates rarefied to the lowest sample size per study were not statistically identical (μ Δrichness = 0·20 ± 0·09 SE , P = 0·30); on average, 0·95 ± 0·13 SE additional species were identified from pellets compared to trapping. Measures of species dominance and evenness estimated from both methods were statistically identical (μ Δ1‐D = 0·02 ± 0·03 SE ; μ Δ PIE = 0·004 ± 0·04 SE ). Species lists, relative species composition and species rank‐order abundance were in moderate agreement between sampling methods (Jaccard = 0·62 ± 0·04 SE ; Bray–Curtis = 0·53 ± 0·04 SE ; Spearman rho = 0·41 ± 0·07 SE ). Linear regression and AIC model selection showed that the performance of pellets versus traps did not differ based on owl genus or habitat type. Small mammal community composition estimated via pellets was better represented compared to estimates from conventional trapping. Composition metrics from the two methods were consistent and not affected by owl genera or habitat type. Thus, owls are an effective alternative for landscape‐level assessments of small mammal communities.
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 | 0.016 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".