Genetic divergence correlates with the contemporary landscape in populations of Slimy Salamander (<i>Plethodon glutinosus</i>) species complex across the lower Piedmont and Coastal Plain of the southeastern United States
Bibliographic record
Abstract
A primary goal of landscape genetics is to elucidate factors associated with genetic structure among populations. Among the important patterns identified have been isolation by distance (IBD), isolation by barrier (IBB), and isolation by environment (IBE). We tested hypotheses relating each of these possible patterns to genetic divergence in the Slimy Salamander (Plethodon glutinosus (Green, 1818)) species complex across the lower Piedmont and Coastal Plain of Georgia, USA, and adjacent areas of South Carolina, USA. We sequenced 2148 total bp, including three regions of the mitochondrial genome and a nuclear intron, and related genetic distance to GIS-derived surrogate variables representing possible IBD (geographic distance), IBE (principal components of 19 climate variables, watershed, and normalized difference vegetation index (NDVI)), and IBB (streams of fourth order and higher). Multiple matrix regression with randomization analysis indicated significant relationships between genetic distance and two principal components of climate, as well as NDVI. These results support roles for environment (IBE) in helping to drive genetic divergence in this group of salamanders. The absence of a significant influence of IBD and IBB was surprising. It is possible that the signal effects of geographic distance and barriers on genetic divergence may have been erased by more recent responses to the environment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".