Pedigree-Based Estimation of Reproductive Value
Author(s) -
Darren C. Hunter,
Josephine M. Pemberton,
Jill G. Pilkington,
Michael B. Morrissey
Publication year - 2019
Publication title -
journal of heredity
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 92
eISSN - 1471-8505
pISSN - 0022-1503
DOI - 10.1093/jhered/esz033
Subject(s) - biology , reproductive value , estimation , population , selection (genetic algorithm) , inference , ovis , population genetics , reproductive success , value (mathematics) , cohort , evolutionary biology , statistics , demography , ecology , genetics , offspring , computer science , mathematics , management , artificial intelligence , sociology , economics , pregnancy
How successful an individual or cohort is, in terms of their genetic contribution to the future population, is encapsulated in the concept of reproductive value, and is crucial for understanding selection and evolution. Long-term studies of pedigreed populations offer the opportunity to estimate reproductive values directly. However, the degree to which genetic contributions, as defined by a pedigree, may converge on their long-run values within the time frames of available data sets, such that they may be interpreted as estimates of reproductive value, is unclear. We develop a system for pedigree-based calculation of the expected genetic representation that both individuals and cohorts make to the population in the years following their birth. We apply this system to inference of individual and cohort reproductive values in Soay sheep (Ovis aries) from St Kilda, Outer Hebrides. We observe that these genetic contributions appear to become relatively stable within modest time frames. As such, it may be reasonable to consider pedigree-based calculations of genetic contributions to future generations as estimates of reproductive value. This approach and the knowledge that the estimates can stabilize within decades should offer new opportunities to analyze data from pedigreed wild populations, which will be of value to many fields within evolutionary biology and demography.
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