MétaCan
Menu
Back to cohort
Record W7135009618 · doi:10.5376/ijmec.2025.15.0008

Population Structure and Genetic Adaptation of Domestic and Wild Ducks Across Different Climatic Regions

2025· article· W7135009618 on OpenAlexvenueno aff
Xian Li, Qibin Xu

Bibliographic record

VenueInternational Journal of Molecular Ecology and Conservation · 2025
Typearticle
Language
FieldAgricultural and Biological Sciences
TopicLivestock and Poultry Management
Canadian institutionsnot available
Fundersnot available
KeywordsAdaptation (eye)PopulationGenetic diversityLineage (genetic)Genetic structureWaterfowlBiodiversityLocal adaptationDomestication

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.044
Threshold uncertainty score0.336

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.012
GPT teacher head0.262
Teacher spread0.251 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Molecular Ecology and ConservationSame topicLivestock and Poultry ManagementFrench-language works237,207