Seagrass photo-physiological responses in natural high-CO2 environment

The atmospheric concentration of CO2 has been steeply increasing over the last 200 years, with an associated increase of total dissolved inorganic carbon (Ci) and a decrease of the oceans’ pH. Seagrasses are among the most productive marine ecosystems, but yet little is known on the effects of high-CO2/low pH on their photosynthetic physiology and the ecological consequences. Marine CO2 seepage areas have been used as natural laboratories to investigate the performance of marine organisms under long-term exposure to high-CO2 levels that mimic the future ocean. In this work we conducted a series of experiments comparing the photophysiology of the seagrasses Posidonia oceanica and Cymodocea nodosa, growing in the vicinity of submarine CO2 vents around the islands of Vulcano and Panarea (Aeolian Archipelago, Southern Tyrrhenian Sea, Italy). Plants growing close to CO2-seepage sites were compared with plants from control sites. Automated chlorophyll fluorometers were deployed for 24-hour periods to examine the changes in photosynthetic efficiency and energy quenching mechanisms. Samples were collected at predawn and noon and analyzed for pigment composition, antioxidant capacity, and soluble carbohydrates. Differences in gene and protein expression were evaluated as a function of Ci levels. Stable carbon isotopes (δ13C) were also analysed to investigate the contribution of volcanic CO2 to seagrass productivity. Both P. oceanica and C. nodosa plants growing in CO2-seepage sites showed lower allocation of PSII-absorbed energy to photochemistry (φII), while presenting higher proportions of energy dissipation by non-photochemical pathways (down-regulation, φNPQ and other energy losses, φNO). As well, diel photosynthesis-irradiance curves (ETRI), built with data acquired over the 24-hour deployments, showed lower photosynthetic rates in plants from CO2 seepage sites. This unexpected pattern of photosynthetic activity will be discussed in light of the complementary data