Wolf, Klara K E; Romanelli, Elisa; Rost, Björn; John, Uwe; Collins, Sinéad; Weigand, Hannah; Hoppe, Clara Jule Marie (2019): Seawater carbonate chemistry and growth, production rates, and cellular composition of Arctic diatom [dataset]. PANGAEA, https://doi.org/10.1594/PANGAEA.913498

Arctic phytoplankton and their response to future conditions shape one of the most rapidly changing ecosystems on the planet. We tested how much the phenotypic responses of strains from the same Arctic diatom population diverge and whether the physiology and intraspecific composition of multistrain populations differs from expectations based on single strain traits. To this end, we conducted incubation experiments with the diatom Thalassiosira hyalina under present‐day and future temperature and pCO2 treatments. Six fresh isolates from the same Svalbard population were incubated as mono‐ and multistrain cultures. For the first time, we were able to closely follow intraspecific selection within an artificial population using microsatellites and allele‐specific quantitative PCR. Our results showed not only that there is substantial variation in how strains of the same species cope with the tested environments but also that changes in genotype composition, production rates, and cellular quotas in the multistrain cultures are not predictable from monoculture performance. Nevertheless, the physiological responses as well as strain composition of the artificial populations were highly reproducible within each environment. Interestingly, we only detected significant strain sorting in those populations exposed to the future treatment. This study illustrates that the genetic composition of populations can change on very short timescales through selection from the intraspecific standing stock, indicating the potential for rapid population level adaptation to climate change. We further show that individuals adjust their phenotype not only in response to their physicochemical but also to their biological surroundings. Such intraspecific interactions need to be understood in order to realistically predict ecosystem responses to global change.

In order to allow full comparability with other ocean acidification data sets, the R package seacarb (Gattuso et al, 2019) 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 2020-03-06.