The effects of long-term in situ CO(2) enrichment on tropical seagrass communities at volcanic vents

• Published in: ICES Journal of Marine Science
• Main Authors: Takahashi, M., Noonan, S.H.C., Fabricius, K.E., Collier, C.J.
• Format: Article in Journal/Newspaper
• Language: unknown
• Published: Oxford University Press 2016
• Subjects: Ocean acidification
• Online Access: https://researchonline.jcu.edu.au/40741/6/40741%20Takahashi%20et%20al%202016.pdf

The effects of long-term exposure to elevated levels of carbon dioxide (CO(2)) on seagrass communities are still poorly understood. This study investigates the tropical subtidal seagrass communities at three shallow volcanic CO(2) vents in Papua New Guinea. Seagrass cover and biomass increased threefold and fivefold, respectively, from control to medium and high pCO(2) sites (average pH = 7.9, 7.7, and 7.5, respectively). The seagrass community composition differed significantly between the pCO(2) sites: Cymodocea serrulata, Cymodocea rotundata, and Halodule uninervis were more abundant at high pCO(2) sites, whereas Halophila ovalis, Thalassia hemprichii, and Syringodium isoetifolium occurred only at low and mid pCO(2) sites. Cymodocea rotundata was the only species common among all pCO(2) sites and locations. The δ13C in its leaves significantly declined with increasing pCO(2), indicating that additional CO(2) influenced seagrass carbon uptake, and specifically, that there was discrimination against the heavier isotope (13C) when carbon was more abundant. Size-specific leaf growth rates (i.e. leaf turnover) also significantly declined with increasing pCO(2); however, leaf growth rates showed no consistent difference in response to elevated pCO(2) in two of four surveys. Our study suggests that progressive ocean acidification may lead to higher cover and above- and below-ground biomass, but lower size-specific growth and altered species composition in tropical seagrass communities. The effects of co-limiting factors, such as light and nutrient availability, on early-responding parameters, such as growth rates, require further attention to improve projections.