Statistical Analysis

All experiments were performed in triplicate. The three replicates were used for the measurement of chlorophyll fluorescence and inhibitor treatment, and the results of lipid peroxidation, H₂O₂ content, antioxidant content, antioxidant enzyme activity, and qRT-PCR data were obtained by analyzing the three biological replicates of the thalli. The results were tested in a one-way ANOVA using SPSS 22.0 statistical software (IBM Corp., Armonk, NY, United States), and Bivariate Pearson’s correlation analysis was performed to assess the relationships of the parameters for photosynthetic and antioxidant systems in U. prolifera. The figures related to this study were generated using SigmaPlot^TM 12.5 software (Systat Software Inc., United States).

Principal components analysis (PCA) was used as an exploratory tool to obtain an overall measure of the thalli of U. prolifera on the basis of the simultaneous analysis of 18 responses to abiotic factors on the sea surface. Correlations are removed by PCA and attributes are converted into new, combined variables. This multivariate approach is considered to be particularly suitable for datasets with possible correlations among attributes (Manly and Alberto, 2017). The resulting independent principal components (PCs) are ranked by PCA according to their importance in explaining the variation in the dataset, and the resulting correlation coefficients facilitate the distinction of key traits characterizing the environmental response in each dimension. The thalli samples that cluster close to either end of a particular axis can then be related to responses that are positively or negatively correlated with a particular PC axis. Another aim for using PCA was to identity constitutive thalli attributes that are correlated with the principle environmental response (PC1). The PCA analysis was conducted using SPSS 22.0.