Department of Bioresources Engineering, Okinawa National College of Technology, 905 Henoko, Nago-City, Okinawa 905-2192, Japan.
Center for Environmental Biology and Ecosystem Studies, National Institute for Environmental Studies, Tsukuba, Ibaraki 305-8506, Japan.
Mar Pollut Bull. 2014 Dec 15;89(1-2):348-355. doi: 10.1016/j.marpolbul.2014.09.037. Epub 2014 Oct 17.
In this study, we report the acidification impact mimicking the pre-industrial, the present, and near-future oceans on calcification of two coral species (Porites australiensis, Isopora palifera) by using precise pCO2 control system which can produce acidified seawater under stable pCO2 values with low variations. In the analyses, we performed Bayesian modeling approaches incorporating the variations of pCO2 and compared the results between our modeling approach and classical statistical one. The results showed highest calcification rates in pre-industrial pCO2 level and gradual decreases of calcification in the near-future ocean acidification level, which suggests that ongoing and near-future ocean acidification would negatively impact coral calcification. In addition, it was expected that the variations of parameters of carbon chemistry may affect the inference of the best model on calcification responses to these parameters between Bayesian modeling approach and classical statistical one even under stable pCO2 values with low variations.
在这项研究中，我们报告了使用精确的 pCO2 控制系统模拟工业化前、现在和近未来海洋对两种珊瑚物种（Porites australiensis、Isopora palifera）钙化作用的酸化影响，该系统可以在稳定的 pCO2 值下产生酸化海水，且变化很小。在分析中，我们采用贝叶斯建模方法，纳入了 pCO2 的变化，并比较了我们的建模方法和经典统计学方法的结果。结果表明，工业化前 pCO2 水平下的钙化率最高，而在近未来海洋酸化水平下逐渐降低，这表明正在进行的和近未来的海洋酸化将对珊瑚钙化产生负面影响。此外，即使在稳定的低变化 pCO2 值下，碳化学参数的变化也可能影响贝叶斯建模方法和经典统计学方法对钙化对这些参数的响应的最佳模型推断。
