Photochemical responses of the diatom Skeletonema costatum grown under elevated CO2 concentrations to short-term changes in pH


Autoria(s): Zheng, Y; Giordano, Mario; Gao, Kunshan; Yang, Yan
Data(s)

15/06/2015

Resumo

Variability in pH is a common occurrence in many aquatic environments, due to physical, chemical and biological processes. In coastal waters, lagoons, estuaries and inland waters, pH can change very rapidly (within seconds or hours) in addition to daily and seasonal changes. At the same time, progressive ocean acidification caused by anthropogenic CO2 emissions is superimposed on these spatial and temporal pH changes. Photosynthetic organisms are therefore unavoidably subject to significant pH variations at the cell surface. Whether this will affect their response to long-term ocean acidification is still unknown, nor is it known whether the short-term sensitivity to pH change is affected by the pCO2 to which the cells are acclimated. We posed the latter open question as our experimental hypothesis: Does acclimation to seawater acidification affect the response of phytoplankton to acute pH variations? The diatom Skeletonema costatum, commonly found in coastal and estuarine waters where short-term acute changes in pH frequently occur, was selected to test the hypothesis. Diatoms were grown at both 390 (pH 8.2, low CO2; LC) and 1000 (pH 7.9, high CO2; HC) µatm CO2 for at least 20 generations, and photosynthetic responses to short-term and acute changes in pH (between 8.2 and 7.6) were investigated. The effective quantum yield of LC-grown cells decreased by ca. 70% only when exposed to pH 7.6; this was not observed when exposed to pH 7.9 or 8.2. HC-grown cells did not show significant responses in any pH treatment. Non-photochemical quenching showed opposite trends. In general, our results indicate that while LC-grown cells are rather sensitive to acidification, HC-grown cells are relatively unresponsive in terms of photochemical performance.

Formato

text/tab-separated-values, 36048 data points

Identificador

https://doi.pangaea.de/10.1594/PANGAEA.846975

doi:10.1594/PANGAEA.846975

Idioma(s)

en

Publicador

PANGAEA

Relação

Gattuso, Jean-Pierre; Epitalon, Jean-Marie; Lavigne, Héloise (2015): seacarb: seawater carbonate chemistry with R. R package version 3.0.6. https://cran.r-project.org/package=seacarb

Direitos

CC-BY: Creative Commons Attribution 3.0 Unported

Access constraints: unrestricted

Fonte

Supplement to: Zheng, Y; Giordano, Mario; Gao, Kunshan (2015): Photochemical responses of the diatom Skeletonema costatum grown under elevated CO2 concentrations to short-term changes in pH. Aquatic Biology, 23(2), 109-118, doi:10.3354/ab00619

Palavras-Chave #Alkalinity, total; Alkalinity, total, standard deviation; Aragonite saturation state; Bicarbonate ion; Bicarbonate ion, standard deviation; Calcite saturation state; Calculated using CO2SYS; Calculated using seacarb after Nisumaa et al. (2010); Carbon, inorganic, dissolved; Carbon, inorganic, dissolved, standard deviation; Carbonate ion; Carbonate ion, standard deviation; Carbonate system computation flag; Carbon dioxide; Carbon dioxide, standard deviation; Coulometric titration; Effective quantum yield; Effective quantum yield, standard deviation; Electron transport rate, relative; Electron transport rate, relative, standard deviation; Figure; Fugacity of carbon dioxide (water) at sea surface temperature (wet air); Initial slope of rapid light curve; Initial slope of rapid light curve, standard deviation; Irradiance; Maximum photochemical quantum yield of photosystem II; Maximum photochemical quantum yield of photosystem II, standard deviation; Non photochemical quenching; Non photochemical quenching, standard deviation; OA-ICC; Ocean Acidification International Coordination Centre; Partial pressure of carbon dioxide, standard deviation; Partial pressure of carbon dioxide (water) at sea surface temperature (wet air); pH; pH, standard deviation; Potentiometric; Salinity; Species; Temperature, water; Time in minutes; Time point, descriptive; Treatment
Tipo

Dataset