期刊
WATER RESEARCH
卷 164, 期 -, 页码 -出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.watres.2019.114936
关键词
Wetlands management; Metagenomics; Alkaline wetland; Greenhouse gases
资金
- National Natural Science Foundation of China [31870471]
- Heilongjiang Natural Science Foundation [C2017003]
- State Key Laboratory of Urban Water Resource and Environment, Harbin Institute of Technology [20181DX07]
Reed (Phragmites australis) is dominant vegetation in alkaline wetlands that is harvested annually due to its economic value. To reveal the effects of harvesting reeds on the emission of greenhouse gases (GHG), the annual soil physicochemical characteristics and flux of GHGs in a reed wetland without harvesting (NHRW) and with harvesting (HRW) were measured. The results showed that after the harvesting of reeds, the total organic carbon (TOC) and total nitrogen (TN) significantly decreased, and soil temperature significantly increased. The annual cumulative N2O emissions decreased from 0.73 +/- 0.20 kg ha(-1) to 0.57 +/- 0.49 kg ha(-1) with the harvesting of reeds. The annual cumulative CH4 emissions also decreased from 561.88 +/- 18.61 kg ha(-1) to 183.13 +/- 18.77 kg ha(-1) with the harvesting of reeds. However, harvesting of reeds had only a limited influence on the annual cumulative CO2 emissions. A Pearson correlation analysis revealed that the CO2 and N2O emissions were more sensitive to temperature than the CH4 emissions. Both structural equation modeling (SEM) analysis and slurry incubation confirmed that higher temperatures offset the reduction of CO2 emissions after reed harvesting. Metagenomics showed that the abundance of functional genes involved in both GHG sink and source decreased with reed harvesting. This study presents a comprehensive view of reed harvesting on GHG emissions in alkaline wetlands, yielding new insight into the microbial response and offering a novel perspective on the potential impacts of wetland management. (C) 2019 Elsevier Ltd. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据