Salinity, a climate-change factor affecting growth, domoic acid and isodomoic acid C content in the diatomPseudo-nitzschia seriata(Bacillariophyceae)

Abstract

Freshening of the oceans is a predicted outcome of climate change. Marine phytoplankton organisms are in general affected by salinity changes and, given their key role in oceanic food webs and geochemical cycles, it is important to investigate the response of phytoplankton species to salinity changes. Diatom species of the genus Pseudo-nitzschia can form massive and, at times, toxic blooms, because several Pseudo-nitzschia species produce the neurotoxin domoic acid. Domoic acid can cause amnesic shellfish poisoning in humans and harm animals in the marine food web. The species Pseudonitzschia seriata can produce domoic acid in cold-water areas, like the Arctic. Hence, it is relevant to investigate the response of P. seriata to different salinity levels. Three strains of P. seriata were exposed to four different salinity levels (15, 20, 30 and 40). None of the strains grew at salinity 15, and maximum growth rates were found at salinity 30. All three strains contained toxins at salinities 20-40, with the highest cellular content occurring at salinity 20. The peak in toxin content was related to a significantly lower growth rate. However, the higher toxin content overrode the lower growth rate, ultimately resulting in a higher toxin potential at salinity 20. In addition to domoic acid, all strains contained isodomoic acid C in surprisingly high amounts, similar to the domoic acid content.

Harmful Algal Blooms in the Alaskan Arctic: An Emerging Threat as the Ocean Warms

“…Data on the diversity and distribution of Pseudo-nitzschia assemblages in the Alaskan Arctic are limited, but at least six species of predominantly polar, subpolar, or temperate origin have been reported, many of which occur in sea ice (Figure 4; Poulin et al, 2011;Percopo et al, 2016). Several produce DA in culture, including P. seriata and P. obtusa, although few Arctic strains have been cultivated and tested (Bates et al, 2018;Weber et al, 2021).…”

Probabilistic models for harmful algae: application to the Norwegian coast

“…These inputs are chosen for two reasons: (i) they have enough time span and spatial coverage matching the algae observations in the shellfish farms and (ii) algae growth is mostly driven by these factors. Algae show distinct temperature-related traits that cause them to grow or diminish in different temperature ranges (Basti et al, 2018; Fehling et al, 2004; Guerrini et al, 2007; Nagai et al, 2004; Rial et al, 2023; Röder et al, 2012; Thomas et al, 2012); PAR corresponds to the light available for photosynthesis and therefore strongly influences algae growth (Bill et al, 2012; García-Portela et al, 2018; Jauffrais et al, 2013); salinity variations affect algae by inducing osmotic stress, creating ion stress through the unavoidable absorption or loss of ions, and altering the cellular ionic ratios due to selective mechanisms (Jauffrais et al, 2013; Kirst, 1990; Klemm et al, 2022; Nagai et al, 2004; Rial et al, 2023; Weber et al, 2021); shallower MLD—a common proxy to well-stratified waters—is commonly associated with HABs (Klemm et al, 2022; Reguera et al, 2012). Note that other important variables, such as nutrients, are not included as no product available matches the farms in a long time series.…”