Phylogenomic Analysis of Wide‐Ranging Least Shrews Refines Conservation Priorities and Supports a Paradigm for Evolution of Biota Spanning Eastern North America and Mesoamerica
Bibliographic record
Abstract
ABSTRACT Anthropogenic global change is impacting the evolutionary potential of biodiversity in ways that have been difficult to predict. Distinct evolutionary units within species may respond differently to the same environmental trends, reflecting unique geography, ecology, adaptation, or drift. Least shrews (Cryptotis parvus group) have a widespread distribution across North America, yet systematic relationships and ongoing evolutionary processes remain unresolved. Westernmost peripheral populations have been prioritized for conservation, but little is known of their evolutionary histories or population trajectories. The broad range of this group of species is coincident with many other temperate taxa, presenting a hypothesis that diversification of least shrews follows a repeated process through the Pleistocene, leading to regionally diagnosable conservation units. We use genomic data and niche modeling to delimit species and conservation units of least shrews. Our results show that least shrews warrant recognition as multiple distinct species, along with geographically discrete infraspecific lineages of C. parvus (sensu stricto). Western peripheral populations are evolutionarily distinct based on nuclear, but not mitochondrial data, possibly reflecting mitochondrial capture during the last glacial phase. This population represents a relict conservation unit, consistent with both an “adaptive unit” and “management unit” based on non‐neutral and neutral divergence, respectively. Hindcast niche modeling supports growing evidence for a shared process of diversification among co‐distributed biota, and forecast modeling suggests continued future loss of suitable environmental niche in peripheral regions. Given mito‐nuclear discordance among samples of parapatric lineages, future environmental perturbation may continue to impact the genomic integrity of important conservation units, making ecological and genomic monitoring a critical need.
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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 | 0.001 | 0.001 |
| 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) | 0.001 | 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".