Diet of two insectivorous bats, Myotis lucifugus and Myotis keenii, in relation to arthropod abundance in a temperate Pacific Northwest rainforest environment
Bibliographic record
Abstract
We assessed the diet of two morphologically similar bats ( Myotis lucifugus (LeConte, 1831) and Myotis keenii (Merriam, 1895)), which both used hydrothermally heated nursery roosts at Gandll K’in Gwaayaay (Hotspring Island), Haida Gwaii (Queen Charlotte Islands), British Columbia, in 1998 and 1999. Our purpose was to determine if they fed opportunistically or actively selected prey, and whether they partitioned prey resources. We determined diet by analyzing feces collected from captured bats and compared it with the relative abundance of insects captured in light traps. Myotis lucifugus fed mainly on lepidopterans, medium-sized to large dipterans, neuropterans, and hymenopterans, while M. keenii fed on lepidopterans, arachnids, medium-sized to large dipterans, and neuropterans. We found that both species were selecting prey, although selection may have been more a function of prey size than particular taxa. Arachnids occurred in feces of both species, implying that both were capable of gleaning prey from surfaces, although only M. keenii regularly fed on spiders. We concluded from the preponderance of flying insects in the diet of M. lucifugus that it was primarily aerial hawking prey, while we took the frequent occurrence of both flying insects and spiders in the diet of M. keenii to indicate that it was both aerial hawking and gleaning prey. Weather conditions between years affected relative abundance of insects and bat diet, with species diversity being lower in light-trap samples and diet of M. lucifugus in 1999, which was cooler and wetter than in 1998. Species diversity in the diet of M. keenii was higher in 1999. Similarities in diet indicated that some interspecific competition was occurring, although this competition was likely minimized by their different foraging strategies.
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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 | 0.000 |
| Science and technology studies | 0.001 | 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".