School of Environment and Energy, South China University of Technology, Guangzhou 510006, China.
School of Environment and Energy, South China University of Technology, Guangzhou 510006, China; State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China; The Key Lab of Pollution Control and Ecosystem Restoration in Industry Clusters, Ministry of Education, Guangzhou 510006, China; Guangdong Provincial Key Laboratory of Atmospheric Environment and Pollution Control, Guangzhou 510640, China.
Sci Total Environ. 2017 Dec 1;599-600:952-959. doi: 10.1016/j.scitotenv.2017.04.228. Epub 2017 May 11.
Phosphine (PH), as a gaseous phosphide, plays an important role in the phosphorus cycle in ecosystems. In this study, the emission and distribution of phosphine, carbon dioxide (CO) and methane (CH) in paddy fields were investigated to speculate the future potential impacts of enhanced greenhouse effect on phosphorus cycle involved in phosphine by the method of Pearson correlation analysis and multiple linear regression analysis. During the whole period of rice growth, there was a significant positive correlation between CO emission flux and PH emission flux (r=0.592, p=0.026, n=14). Similarly, a significant positive correlation of emission flux was also observed between CH and PH (r=0.563, p=0.036, n=14). The linear regression relationship was determined as [PH]=0.007[CO]+0.063[CH]-4.638. No significant differences were observed for all values of matrix-bound phosphine (MBP), soil carbon dioxide (SCO), and soil methane (SCH) in paddy soils. However, there was a significant positive correlation between MBP and SCO at heading, flowering and ripening stage. The correlation coefficients were 0.909, 0.890 and 0.827, respectively. In vertical distribution, MBP had the analogical variation trend with SCO and SCH. Through Pearson correlation analysis and multiple stepwise linear regression analysis, pH, redox potential (Eh), total phosphorus (TP) and acid phosphatase (ACP) were identified as the principal factors affecting MBP levels, with correlative rankings of Eh>pH>TP>ACP. The multiple stepwise regression model ([MBP]=0.456∗[ACP]+0.235∗[TP]-1.458∗[Eh]-36.547∗[pH]+352.298) was obtained. The findings in this study hold great reference values to the global biogeochemical cycling of phosphorus in the future.
磷化氢(PH)作为一种气态磷化物,在生态系统的磷循环中起着重要作用。本研究通过 Pearson 相关分析和多元线性回归分析的方法,调查了稻田中磷化氢、二氧化碳(CO)和甲烷(CH)的排放和分布,以推测未来增强的温室效应对磷循环中磷化氢的潜在影响。在整个水稻生长期间,CO 排放通量与 PH 排放通量之间存在显著正相关(r=0.592,p=0.026,n=14)。同样,CH 和 PH 之间也观察到显著的排放通量正相关(r=0.563,p=0.036,n=14)。线性回归关系为 [PH]=0.007[CO]+0.063[CH]-4.638。稻田土壤中的基质结合态磷(MBP)、土壤二氧化碳(SCO)和土壤甲烷(SCH)的所有值均无显著差异。然而,在抽穗期、开花期和成熟期,MBP 与 SCO 之间存在显著的正相关。相关系数分别为 0.909、0.890 和 0.827。在垂直分布方面,MBP 与 SCO 和 SCH 具有类似的变化趋势。通过 Pearson 相关分析和多元逐步线性回归分析,pH 值、氧化还原电位(Eh)、总磷(TP)和酸性磷酸酶(ACP)被确定为影响 MBP 水平的主要因素,相关顺序为 Eh>pH>TP>ACP。获得了多元逐步回归模型 ([MBP]=0.456∗[ACP]+0.235∗[TP]-1.458∗[Eh]-36.547∗[pH]+352.298)。本研究的结果对未来全球磷的生物地球化学循环具有重要的参考价值。