A hybrid correlative‐mechanistic approach for modeling winter distributions of North American bat species
Bibliographic record
Abstract
Abstract Aim The fungal pathogen Pseudogymnoascus destructans and resultant white‐nose syndrome (WNS) continues to advance across North America, infecting new bat hibernacula. Western North America hosts the highest bat diversity in the United States and Canada, yet little is known about hibernacula and hibernation behaviour in this region. An improved understanding of the distribution of suitable hibernacula is critical for land managers to anticipate conservation needs of WNS‐susceptible species in currently uninfected regions. Location United States, Canada. Taxon Bats. Methods We estimated suitability of potential winter hibernaculum sites across five bat species' ranges. We estimated winter survival capacity from a mechanistic survivorship model based on bat bioenergetics and climate conditions. We then used boosted regression trees to relate these estimates, along with key landscape attributes, to bat occurrence data in a hybrid correlative‐mechanistic approach. Results Winter survival capacity, topography, land cover and access to subterranean features were important predictors of winter hibernaculum selection, but the shape and relative importance of these relationships varied amongst species. This suggests that the occurrence of bat hibernacula can, in part, be predicted from readily mapped above‐ground features, not just below‐ground characteristics for which spatial data are lacking. Furthermore, our mechanistic estimate of winter survivorship was, on average, the third strongest predictor of winter occurrence probability across focal species. Main conclusions Winter distributions of North American bat species were driven by their physiological capacity to survive winter conditions and duration in a given location, as well as selection for topographic and other landscape features but in species‐specific ways. The influence of winter survivorship on several species' distributions, the underlying influence of climate conditions on winter survivorship and the anticipated influence of WNS on bats' hibernation physiology and survivorship together suggest that North American bat distributions may undergo future shifts as these species are exposed not only to WNS but also to climate change.
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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".