Genetic variation and cryptic lineage diversity of the Nigerian red-headed rock agama Agama agama associate with eco-geographic zones
Bibliographic record
Abstract
Abstract Nigeria is an Afrotropical region with considerable ecological heterogeneity and levels of biotic endemism. Among its vertebrate fauna, reptiles have broad distributions, thus, they constitute a compelling system for assessing the impact of ecological variation and geographic isolation on species diversification. The red-headed rock agama, Agama agama, lives in a wide range of habitats and, thus, it may show genetic structuring and diversification. Herein, we tested the hypothesis that ecology affects its genetic structure and population divergence. Bayesian inference phylogenetic analysis of a mitochondrial DNA (mtDNA) gene recovered four well-supported matrilines with strong evidence of genetic structuring consistent with eco-geographic regions. Genetic differences among populations based on the mtDNA also correlated with geographic distance. The ecological niche model for the matrilines had a good fit and robust performance. Population divergence along the environmental axes was associated with climatic conditions, and temperature ranked highest among all environmental variables for forest specialists, while precipitation ranked highest for the forest/derived savanna, and savanna specialists. Our results cannot reject the hypothesis that niche conservatism promotes geographic isolation of the western populations of Nigerian A. agama. Thus, ecological gradients and geographic isolation impact the genetic structure and population divergence of the lizards. This species might be facing threats due to recent habitat fragmentation, especially in western Nigeria. Conservation actions appear necessary.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".