Population Structure and Genetic Adaptation of Domestic and Wild Ducks Across Different Climatic Regions
Bibliographic record
Abstract
Having a perception of how domestic and wild ducks (Anas genus) adapt to climatic zones is extremely significant to evolutionary biology as well as conservation of species. In the present work, the study examines systematically the population structure and genetic adaptation of ducks common in tropical, temperate, and cold regions. By integrating mitochondrial and nuclear DNA data, we reconstructed phylogenetic relationships, estimated the times of lineage divergence, and compared genetic lineage diversity in domestic duck breeds and their wild relatives. The findings revealed clear genetic structuring across populations from different geographic regions, which reflects previous domestication events as well as ongoing gene flow. In addition, we identified genomic signatures of environmental adaptation, which comprised functional genes known to play roles in thermoregulation, metabolism, and immune response. Ecological niche modeling and spatial analysis based on GIS also evidenced that the genetic differentiation patterns are influenced by geographical discontinuity and climatic heterogeneity. The study bears witness to the evolutionary flexibility of ducks and establishes the value of molecular ecology for biodiversity conservation and adaptive management, and offers a scientific basis for the sustainable use and conservation of waterfowl resources under global climate change.
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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) | 0.000 | 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".