Historical and contemporary demography of leaf-toed geckos (Phyllodactylidae: Phyllodactylus) in the Mexican dry forest
Bibliographic record
Abstract
Disentangling the relative influence of historical versus contemporary processes shaping the spatial distribution of genetic variation is critical if we are to effectively mitigate key biodiversity issues. We utilize a comprehensive approach based on different molecular marker types and analytical methods to understand the demographic consequences of recent habitat fragmentation in a spatially explicit context. We focus our efforts on native leaf-toed geckos (Phyllodactylus tuberculosus saxatilis) throughout fragmented habitat in the tropical dry forest of northern Mexico as recent evidence suggests that geographic ranges for these geckos may be much smaller than currently realized. However, no data are available regarding recent shifts in demographic trends and how these trends may correspond with recent fragmentation and introductions of non-native gecko species (Hemidactylus). Mitochondrial DNA sequences reveal substantial historical genetic divergence over a small geographic area (<40 km). We find evidence for an increase in contemporary versus historical migration rates based on 10 microsatellite loci, but evidence that many populations suffer from recent reductions in effective population sizes. Landscape genetic analyses find that contemporary migration rates are significantly more correlated with the landscape versus historical migration rates or mtDNA divergence, suggesting that individuals have altered their dispersal routes in response to recent habitat changes. Taken together, this study suggests that long-term female philopatry, recent habitat fragmentation, and possibly introductions of non-native gecko species all contribute to the demographic patterns and the high degree of differentiation observed over fine-spatial scales in Mexican leaf-toed geckos.
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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 | 0.001 | 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".