Year-to-year Reuse of Tree-roosts by California Bats (Myotis californicus) in Southern British Columbia
Bibliographic record
Abstract
(Uploaded by Plazi for the Bat Literature Project) To document year-to-year reuse of roost trees by forest-dwelling bats we monitored trees in southern British Columbia that we first identified as maternity roosts of California bats (Myotis californicus) in 1995. Initially we identified roost trees by tracking radiotagged individuals. Then we revisited each tree in subsequent years up to 2000. At the start of the study the bats roosted under loose bark or in cavities in dead trees. Seven of eight trees were still standing in 2000, although all had lost bark since 1995, particularly ponderosa pines (Pinus ponderosa). In 1995, after radio-tagged bats had moved and the tags had fallen off, trees either were occupied by colonies of 5 to 52 M. californicus or they were unoccupied. In contrast, roost counts in subsequent years indicated that colonies rarely used the same trees and most observations were of one or two bats. Thus, while bats continued to use most of the trees over the 5 y period, the numbers of individuals declined and much of the use may have been by males or non-reproductive females. Although our study is preliminary, the results suggest that the suitability of roosts of tree-dwelling bats declines relatively rapidly compared to the loss of the snags themselves. More intensive studies are required given the current focus on preserving roosting habitat for forest-dwelling bats.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| 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) | 0.002 | 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".