This paper present the effects of ocean acidification on growth and domoic acid (DA) content of several strains of the toxic Pseudo-nitzschia australis and the non-toxic P. fraudulenta. Three strains of each species (plus two subclones of P. australis) were acclimated and grown in semi-continuous cultures at three pH levels: 8.07, 7.77, and 7.40, in order to simulate changes of seawater pH from present to plausible future levels. Our results showed that lowering pH from current level (8.07) to predicted pH level in 2100 (7.77) did not affect the mean growth rates of some of the P. australis strains (FR-PAU-17 and L3-100), but affected other strains either negatively (L3-30) or positively (L3.4). However, the growth rates significantly decreased with pH lowered to 7.40 (by 13% for L3-100, 43% for L3-30 and 16% for IFR-PAU-17 compared to the rates at pH 8.07). In contrast, growth rates of the non-toxic P. fraudulenta strains were not affected by pH changing from 8.07 to 7.40.The P. australis strains produced DA at all pH levels tested, and the highest particulate DA concentration normalized to cell abundance (pDA) was found at pH 8.07. Total DA content (pDA and dissolved DA) was significantly higher at current pH (8.07) compared to pH (7.77), exept for one strain (L 3.4) where no difference was found. At lower pH levels 7.77 – 7.40, total DA content was similar, except for strains IFR-PAU-17 and L3-100 which had the lowest content at the pH 7.77. The diversity in the responses in growth and DA content highlights the inter- and intra-specific variation in Pseudo-nitzschia species in response to ocean acidification. When exploring environmental responses of Pseudo-nitzschia using cultured cells, not only strain-specific variation but also culturing history should be taken into consideration, as the light levels under which the subclones were cultured, afterwards affected both maximum growth rates and DA content.

In order to allow full comparability with other ocean acidification data sets, the R package seacarb (Gattuso et al, 2021) was used to compute a complete and consistent set of carbonate system variables, as described by Nisumaa et al. (2010). In this dataset the original values were archived in addition with the recalculated parameters (see related PI). The date of carbonate chemistry calculation by seacarb is 2021-10-22.