R script and datasets - CCA

This folder contained a R script and datasets to perform a Canonical correspondence analysis (CCA) in R. CCA was used to infer the underlying relationship between the benthic harmful dinoflagellate assemblages and benthic substrate characteristics, depths and irradiances. CCA is a constrained multivariate ordination technique that extracts major gradients among combinations of explanatory variables in a dataset and requires samples to be both random and independent. Data for cell abundances were Hellinger-transformed prior to CCA to ensure the data met the statistical assumptions of normality and linearity. The analysis was performed using vegan. The significance of variation in benthic harmful dinoflagellates assemblages explained by the explanatory variables was tested using an ANOVA-like Monte Carlo permutation test as implemented in vegan.

本文件夹包含用于在R语言中开展典范对应分析（Canonical Correspondence Analysis，CCA）的R脚本与配套数据集。本研究借助CCA推断底栖有害甲藻群落与底栖基质特征、水深及辐照度之间的内在关联。CCA作为一种有约束的多元排序技术，可从数据集的解释变量组合中提取主要梯度，且要求样本需满足随机且独立的统计前提。细胞丰度数据在CCA分析前已完成赫尔利格转换（Hellinger transformation），以确保数据符合正态性与线性性的统计假设。本次分析借助vegan R包完成，并通过该包中实现的类方差分析蒙特卡洛置换检验，对解释变量所解释的底栖有害甲藻群落变异的显著性进行了检验。