Statistical analysis
All datasets to be analysed were firstly subjected to a
D’Agostino-Pearson normality test for a Gaussian distribution as well as
Spearman’s test to determine if variances between variables are
heteroscedastic. A two-way ANOVA was performed on datasets conforming to
a Gaussian distribution and which were homoscedastic. If an independent
variable ([CO2] or genotype) had a significant
effect on the response (P ≤ 0.05), Tukey’s multiple comparison test was
used to compare means. Datasets which were normally distributed, but
heteroscedastic were analysed with a Welch ANOVA test followed by
Dunnett’s T3 multiple comparisons test. Datasets which did not follow a
normal distribution were subjected to a Kruskal-Wallis test. Following a
significant p-value computed by the Kruskal-Wallis test, multiple
comparisons were performed using Dunn’s procedure. Different letters
indicate a statistically significant difference, p ≤ 0.05. Graphpad
Prism 8.2.1 was used to perform all statistical analysis.