Geographical CO₂ sensitivity of phytoplankton correlates with ocean buffer capacity

Abstract

Accumulation of anthropogenic CO is significantly altering ocean chemistry. A range of biological impacts resulting from this oceanic CO accumulation are emerging, however, the mechanisms responsible for observed differential susceptibility between organisms and across environmental settings remain obscure. A primary consequence of increased oceanic CO uptake is a decrease in the carbonate system buffer capacity, which characterizes the system's chemical resilience to changes in CO , generating the potential for enhanced variability in pCO and the concentration of carbonate [CO32-], bicarbonate [HCO3-], and protons [H ] in the future ocean. We conducted a meta-analysis of 17 shipboard manipulation experiments performed across three distinct geographical regions that encompassed a wide range of environmental conditions from European temperate seas to Arctic and Southern oceans. These data demonstrated a correlation between the magnitude of natural phytoplankton community biological responses to short-term CO changes and variability in the local buffer capacity across ocean basin scales. Specifically, short-term suppression of small phytoplankton (<10 μm) net growth rates were consistently observed under enhanced pCO within experiments performed in regions with higher ambient buffer capacity. The results further highlight the relevance of phytoplankton cell size for the impacts of enhanced pCO in both the modern and future ocean. Specifically, cell size-related acclimation and adaptation to regional environmental variability, as characterized by buffer capacity, likely influences interactions between primary producers and carbonate chemistry over a range of spatio-temporal scales.

Ocean Alkalinity, Buffering and Biogeochemical Processes

“…These and other seawater sensitivities have many applications, ranging from propagating uncertainties in the carbonic acid system (Orr et al, 2018), attributing changes in pCO 2 to temperature, salinity, and other factors (Middelburg, 2019; Sarmiento & Gruber, 2006; Takahashi et al, 1993, 2014), understanding factors governing pH seasonality (Hagens & Middelburg, 2016b), and how these factors will change because of global warming and ocean acidification (Hagens & Middelburg, 2016a). For instance, Richier et al (2018) showed that the CO 2 sensitivity of phytoplankton correlates with the sensitivity of seawater. This quantification of sensitivities is pivotal to understanding earth system functioning and the magnitude of climate feedbacks during times of global change.…”

Ocean alkalinity, buffering and biogeochemical processes

“…factors (Middelburg, 2019;Sarmiento & Gruber, 2006;Takahashi et al, 1993Takahashi et al, , 2014, understanding factors governing pH seasonality (Hagens & Middelburg, 2016b), and how these factors will change because of global warming and ocean acidification (Hagens & Middelburg, 2016a). For instance, Richier et al (2018) showed that the CO 2 sensitivity of phytoplankton correlates with the sensitivity ∂pH ∂DIC of seawater. This quantification of sensitivities is pivotal to understanding earth system functioning and the magnitude of climate feedbacks during times of global change.…”

A meta-analysis of microcosm experiments shows that dimethyl sulfide (DMS) production in polar waters is insensitive to ocean acidification

“…The response of DMS cycling to elevated CO 2 is generally driven by changes to the microbial community structure (Brussaard et al, 2013;Archer et al, 2013;Hopkins et al, 2010;Engel et al, 2008). The pseudo-natural conditions of mesocosm experiments offer the benefit of the in-clusion of community dynamics of three or more trophic levels, providing the opportunity to investigate the influence of ecosystem dynamics on biogeochemical processes under experimental conditions (Riebesell et al, 2013a). Furthermore, physical processes such as particle export , which would be excluded by smaller-scale experiments, can be considered within the holistic mesocosm framework and make the results relevant for use within Earth system models (Six et al, 2013).…”