title: Estimating Trait Heritability in Highly Fecund Species.
abstract: Increasingly, researchers are interested in estimating the heritability of traits for nonmodel organisms. However, estimating the heritability of these traits presents both experimental and statistical challenges, which typically arise from logistical difficulties associated with rearing large numbers of families independently in the field, a lack of known pedigree, the need to account for group or batch effects, etc. Here we develop both an empirical and computational methodology for estimating the narrow-sense heritability of traits for highly fecund species. Our experimental approach controls for undesirable culturing effects while minimizing culture numbers, increasing feasibility in the field. Our statistical approach accounts for known issues with model-selection by using a permutation test to calculate significance values and includes both fitting and power calculation methods. We further demonstrate that even with moderately high sample-sizes, the p-values derived from asymptotic properties of the likelihood ratio test are overly conservative, thus reducing statistical power. We illustrate our methodology by estimating the narrow-sense heritability for larval settlement, a key life-history trait, in the reef-building coral Orbicella faveolata. The experimental, statistical, and computational methods, along with all of the data from this study, are available in the R package multiDimBio.
authors.affiliation: Department of Integrative Biology, The University of Texas at Austin, Texas 78712 daviessw@gmail.com scarpino@santafe.edu matz@utexas.edu.
authors.forename: Sarah W
authors.initials: SW
authors.lastname: Davies
authors.affiliation: Santa Fe Institute, Santa Fe, New Mexico 87501 daviessw@gmail.com scarpino@santafe.edu matz@utexas.edu.
authors.forename: Samuel V
authors.initials: SV
authors.lastname: Scarpino
authors.affiliation: Department of Integrative Biology, The University of Texas at Austin, Texas 78712.
authors.forename: Thanapat
authors.initials: T
authors.lastname: Pongwarin
authors.affiliation: Department of Statistics and Data Sciences, The University of Texas at Austin, Texas 78712 Department of Information, Risk, and Operations Management, The University of Texas at Austin, Texas 78712.
authors.forename: James
authors.initials: J
authors.lastname: Scott
authors.affiliation: Department of Integrative Biology, The University of Texas at Austin, Texas 78712 daviessw@gmail.com scarpino@santafe.edu matz@utexas.edu.
authors.forename: Mikhail V
authors.initials: MV
authors.lastname: Matz
mesh_terms: D000465:Algorithms; D000818:Animals; D003198:Computer Simulation; D005298:Fertility / Q000235:genetics*; D014644:Genetic Variation; D040582:Inheritance Patterns; D007814:Larva / Q000235:genetics; D008957:Models, Genetic; D015233:Models, Statistical; D009010:Monte Carlo Method; D010641:Phenotype; D040641:Quantitative Trait Loci; D019655:Quantitative Trait, Heritable
keywords: binary variable traits; common garden; coral settlement; heritability; nonmodel organisms