Despite the important roles of assortative mating for understanding evolutionary processes, our knowledge on the variation in assortative mating across populations and breeding periods has been overshadowed by the greater attention given to general patterns. Obtaining data on mating pairs are difficult for most species; therefore, researchers often group data from different populations or breeding periods, which can increase positive biases in detecting and estimating assortative mating. We used a meta-analytic approach to investigate the biases caused by spatially or temporally pooling data and the assortative mating consistency across populations and breeding periods. We describe assortative mating patterns across and within animal taxa. We performed a systematic review to search studies reporting measures of size-assortative mating (SAM). Grouping data from multiple populations and seasons incurred positive biases. Overall, assortative mating moderately exhibited low repeatability in space and time, but it was inconsistent for most taxa. After excluding pooled measures, the average estimate for assortative mating was moderate and positive. Thus, our findings demonstrate that pooling data can produce misleading results. We also highlight the importance of further investigation of hypotheses that explain spatial and temporal variation in assortative mating, after its detection. Our study reinforces the significance of investigating mating patterns at various spatial and temporal scales before drawing broad conclusions.
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http://dx.doi.org/10.1111/ele.13690 | DOI Listing |
Nat Hum Behav
December 2024
Leverhulme Centre for Demographic Science, Nuffield Department of Population Health and Nuffield College, University of Oxford, Oxford, UK.
Socioeconomic status (SES) impacts health and life-course outcomes. This genome-wide association study (GWAS) of sociologically informed occupational status measures (ISEI, SIOPS, CAMSIS) using the UK Biobank (N = 273,157) identified 106 independent single-nucleotide polymorphisms of which 8 are novel to the study of SES. Genetic correlations with educational attainment (r = 0.
View Article and Find Full Text PDFG3 (Bethesda)
December 2024
Animal Ecology, Department of Ecology and Genetics, Uppsala University, 752 36 Uppsala, Sweden.
Species-specific sexual traits facilitate species-assortative mating by reducing mating across species and reducing hybrid sexual attractiveness. For learned sexual traits, such as song in oscine birds, species distinctiveness can be eroded when species co-occur. Transcriptional regulatory divergence in brain regions involved in sensory learning are hypothesized to maintain species distinctiveness, but relatively few studies have compared gene expression in relevant brain regions between closely related species.
View Article and Find Full Text PDFJ Evol Biol
December 2024
Department of Theoretical Biology, Faculty of Biology, Bielefeld University, Universit ätsstraÿe 25, 33615 Bielefeld, Germany.
Behav Ecol
November 2024
Department of Zoology, Stockholm University, Svante Arrhenius väg, 106 91 Stockholm, Sweden.
J Dairy Sci
December 2024
Irish Cattle Breeding Federation, Carrigrohane, Ballincollig, Co. Cork, P31 D452, Ireland.
A decision support tool or system is a computerized information system used to support decision-making in a business; one central component to profitable dairy cattle production systems is the appropriate mating of bulls and females. While tools have been described to aid mating decisions between dairy bulls and dairy females, or between beef bulls and beef females, there is a void of such tools that recommend which beef bull to mate to individual dairy females. The objective of the present study was to develop and validate a framework, founded on linear programming, to aid herd-level mating decisions where the bull-female mating is tailored based on complementarity and compatibility of both mates; consideration in the process was given to the genetic merit of both mates for a series of traits as well as the life history of the female herself.
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