The best watering hole in town: Characteristics of ponds used by an endangered bat in an urbanizing boreal landscape
Bibliographic record
Abstract
Small waterbodies, or ‘ponds’, have an important role in maintaining biodiversity and ecosystem services, particularly where freshwater sources are limited, such as arid or some urban environments. However, studies that examine the use of ponds by terrestrial wildlife are limited. In the boreal forest, aquatic habitats are important drinking and feeding habitat for endangered little brown bats (Myotis lucifugus), and their relative value likely varies based on their characteristics, such as size, adjacent land cover type, anthropogenic disturbance, and proximity to other water bodies. We examined the characteristics of ponds used by little brown bats along an urban-rural gradient in Yukon, Canada. We used ultrasonic detectors to sample 99 ponds and generalized linear mixed models to determine whether ponds with certain characteristics received more bat activity than others. We found that ponds are important habitat for little brown bats, as 98% of the ponds we sampled were used. Bats selected ponds based on local rather than landscape level factors, and there was less bat activity at ponds surrounded by additional open water/wetland habitat, which was contrary to our prediction. Ponds that were surrounded by additional open water/wetland habitat may have been too exposed for bats at high latitudes, where nights are short and not completely dark. Isolated ponds that are darker, such as those surrounded by mature forest, may be particularly valuable for little brown bats at high latitudes that exhibit risk-sensitive foraging. We suggest that ponds of comparatively high value for endangered little brown bats be further identified and that these ponds be protected from development, draining, and degradation, and the surrounding mature forest remains intact. More broadly, recognition and conservation of ponds and their surroundings as key habitat for species of bats requires further attention. Understanding the characteristics of ponds selected by threatened bats can help inform conservation priorities and measures that ensure the aquatic habitats they require are maintained in developing landscapes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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 teacher head, 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".