Once upon a time in Mexico: Holocene phylogeography of the spotted bat ( <i>Euderma maculatum</i> )
Bibliographic record
Abstract
Abstract Holocene-era range expansions are relevant to understanding how a species might respond to the warming and drying climates of today. The harsh conditions of North American deserts have phylogenetically structured desert bat communities but differences in flight capabilities are expected to affect their ability to compete, locate, and use habitat in the face of modern climate change. A highly vagile but data-deficient bat species, the spotted bat ( Euderma maculatum ) is thought to have expanded its range from central Mexico to western Canada during the Holocene. With specimens spanning this latitudinal extent, we coupled phylogeography (mtDNA) with ecological niche modeling (ENM) to investigate the Holocene biogeography from the rear to leading edges. The ENM and phylogeny supported a Holocene range expansion from Mexico with increased expansion throughout the intermountain west within the last 6 kya. Long-term isolation at the southern-most margin of the range suggests one or more populations were left behind as climate space contracted and are currently of unknown status. The species appears historically suited to track shifts in climate space but differences in flight behaviors between leading edge and core-range lineages suggest that range expansions could be influenced by differences in habitat quality or climate (e.g., drought). Although its vagility could facilitate the tracking of environmental change and thereby extinction avoidance, anthropogenic pressures at the core range could still threaten the ability for beneficial alleles to expand into the leading edge.
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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 | 0.000 | 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".