Physiological responses of Caulerpa spp. (with different dissolved inorganic carbon physiologies) to ocean acidification

NEW ZEALAND JOURNAL OF BOTANY(2023)

引用 0|浏览2
暂无评分
摘要
Caulerpa is a widely distributed genus of chlorophytes (green macroalgae) which are important for their dietary, social and coastal ecosystem value. Ocean acidification (OA) threatens the future of marine ecosystems, favouring macroalgal species that could benefit from increased seawater carbon dioxide (CO2) concentrations. Most macroalgae species possess CO2 concentrating mechanisms (CCMs) that allow active uptake of bicarbonate (HCO3-). Those species without CCMs are restricted to using CO2, which is currently the least abundant species of dissolved inorganic carbon (DIC) in seawater. Thus, macroalgae without CCMs are predicted to be likely benefit from OA. Caulerpa is one of the rare few genera that have species both with and without CCMs. The two most common Caulerpa species in New Zealand are C. geminata (possesses a CCM) and C. brownii (non-CCM). We investigated the responses of growth, photo-physiology and DIC utilisation of C. geminata and C. brownii to four mean seawater pH treatments (8.03, 7.93, 7.83 and 7.63) that correspond to changes in pH driven by increases in pCO(2) simulating future OA. There was a tendency for the mean growth rates for C. brownii (non-CCM) to increase under lower pH, and the growth rates of C. geminata (CCM) to decline with lower pH, although this was not statistically significant. However, this is likely because variability in growth rates also increased as seawater pH declined. There were few other differences in physiology of both species with pH, although there was tendency for greater preference for CO2 over HCO3- uptake in the CCM species with declining seawater pH. This study demonstrates that DIC-use alone does not predict macroalgal responses to OA.
更多
查看译文
关键词
Chlorophyte,ocean acidification,dissolved inorganic carbon,physiology,macroalgae,CO2 concentrating mechanism
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要