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Data and code from: Estimating minimum sample size for detecting phenotypic imorphism using computational simulations

Zhou, Yibo1; Hou, Xudong1; Pan, Yanhong1

Published Jul 22, 2026 on Dryad. https://doi.org/10.5061/dryad.08kprr5f9

Data files

Jul 22, 2026 version files 4.96 GB

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Abstract

Polymorphism, a phenomenon in nature, is the occurrence of different morphs of a trait within the population of a single species. Polymorphism can play a crucial role in species diversification, genetic variation, and adaptation. Detecting polymorphism in a single character helps to understand population dynamics, particularly in species that inhabit diverse environments. However, detecting polymorphism in fossil taxa presents methodological and interpretative challenges due to the fragmentary and incomplete nature of fossil taxa. Dimorphism, defined as the occurrence of different morphs of a trait within the population of a single species, represents the simplest and most common form of polymorphism. In this study, we focus on dimorphism instead of polymorphism, which allows for a more streamlined analysis. We used computational simulation experiments to estimate the minimum sample size required to detect a bimodal distribution in univariate morphological variables. First, we describe the morphological diversity of a measured variable (e.g., body mass or skeletal length) as a probability density function with specific parameter sets. Subsequently, we simulated the diversity of the measured variable with varying sample sizes and conducted resampling procedures to ensure robustness. Four key parameters that characterize the probability distribution are identified as having significant influence on the minimum sample size for dimorphism recognition. According to the simulation experiments, a model was built to estimate the minimum sample size for dimorphism recognition based on these parameters. A dataset from extant avian species was used to test the model. Furthermore, we calculated a reference for the minimal sample size required for assessing phenotypic dimorphism in fossil avian taxa by applying parameters derived from extant avian species.