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.