Data and code for study entitled "Do environmental fluctuations during development affect trait variation? An experimental test with salinity"

We tested how developmental environments (freshwater, stable-saline, fluctuating-saline) influence variation in life-history traits (age at maturity, size at maturity, relative gut length, immunity) and reproductive traits in both sexes – females (egg number, egg size) and males (relative gonopodium length, sperm count, sperm velocity) at both young and old adult stages (before and after 12 weeks of mating). We have attached the raw data spreadsheet (Raw data.xlsx). For young males, life-history and reproductive traits were measured in different individuals and are provided in separate sheets. For young females, old females, and old males, all traits were measured on the same individuals and are combined in a single sheet for each group. We analysed mean egg size in our models; individual egg size data for young females are also included in the raw data file. The R code (Trait variability.R) was run using R v1.3.1093. Analyses used data from female.csv and male.csv. ----- Analytical approach ----- We used Bayesian multivariate mixed-effects models to estimate trait covariances and test whether developmental environment affected both trait means and variances, run separately for each age–sex group. Separate models were used for young males' life-history and reproductive traits. Environment (3 levels) was included as a fixed effect, with brood identity as a random effect. Traits including age at maturity, immunity, egg number (young females), and sperm count were power transformed to improve normality. Each model used four MCMC chains (5000 iterations, 1000 burn-in), with convergence confirmed (Rhat = 1) and effective sample sizes >1480. To test environmental effects on trait variance, we modelled both trait means and standard deviations (SDs) on a log scale. We calculated: lnVR = ln(SD1/SD2), to assess changes in raw variance lnCVR = ln(CV1/CV2), to assess changes in relative variance (accounting for trait means) We compared specific environment pairs to assess: Effect of salinity: stable salinity vs freshwater Effect of fluctuations: fluctuating salinity vs stable salinity本研究探究了发育环境（淡水、稳定盐水、波动盐水）对雌雄两性在成年早期与成年晚期（交配12周前后）的生活史性状与繁殖性状变异程度的影响。其中，生活史性状包括成熟年龄、成熟体型、相对肠长与免疫能力；雌性繁殖性状为产卵量、卵大小，雄性繁殖性状为相对生殖肢长度、精子数量及精子运动速度。 本研究已附原始数据电子表格（Raw data.xlsx）。其中，成年早期雄性的生活史与繁殖性状取自不同个体，分别存储于单独的工作表中；成年早期雌性、成年晚期雌性与成年晚期雄性的所有性状均来自同一批个体，每组对应一个整合了全部性状的工作表。本研究的模型采用卵大小均值进行分析，成年早期雌性的单枚卵大小数据也包含于原始数据文件内。 本研究使用R v1.3.1093版本运行了R脚本（Trait variability.R），分析所用数据来源于female.csv与male.csv文件。 ----- 分析方法 ----- 本研究采用贝叶斯多变量混合效应模型估计性状协方差，并检验发育环境是否同时影响性状均值与方差，针对每个年龄-性别组别分别构建模型。针对成年早期雄性的生活史与繁殖性状，我们分别采用了独立模型进行分析。环境因子（共3个水平）被设定为固定效应，窝别身份作为随机效应。包括成熟年龄、免疫能力、成年早期雌性产卵量以及精子数量在内的多个性状均经过幂变换以提升正态性。每个模型均设置4条马尔可夫链蒙特卡洛（Markov Chain Monte Carlo, MCMC）链，迭代次数为5000，预烧期为1000，通过Rhat值为1确认模型收敛，且有效样本量大于1480。 为检验环境对性状方差的影响，我们以对数尺度分别对性状均值与标准差（SD）进行建模。本研究计算了两类指标： 1. lnVR = ln(SD1/SD2)，用于评估原始方差的变化； 2. lnCVR = ln(CV1/CV2)，用于评估相对方差的变化（已校正性状均值的影响）。 本研究通过对比特定环境组间的差异，以评估两类效应： ① 盐度效应：稳定盐水组与淡水组的对比； ② 波动效应：波动盐水组与稳定盐水组的对比。