Article(id=1241408721604112826, tenantId=1146029695717560320, journalId=1234093305789726721, issueId=1241408710791189399, articleNumber=null, orderNo=null, doi=null, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1728921600000, receivedDateStr=2024-10-15, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1773904503489, onlineDateStr=2026-03-19, pubDate=1745078400000, pubDateStr=2025-04-20, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773904503489, onlineIssueDateStr=2026-03-19, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773904503489, creator=13701087609, updateTime=1773904503489, updator=13701087609, issue=Issue{id=1241408710791189399, tenantId=1146029695717560320, journalId=1234093305789726721, year='2025', volume='45', issue='4', pageStart='1777', pageEnd='2368', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773904500911, creator=13701087609, updateTime=1773904624658, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1241409229878259747, tenantId=1146029695717560320, journalId=1234093305789726721, issueId=1241408710791189399, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1241409229878259748, tenantId=1146029695717560320, journalId=1234093305789726721, issueId=1241408710791189399, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=2240, endPage=2250, ext={EN=ArticleExt(id=1241408722099040737, articleId=1241408721604112826, tenantId=1146029695717560320, journalId=1234093305789726721, language=EN, title=Production rates and key influencing factors of CH4 and CO2 of freshwater and saltwater Phragmites australis marshes in major estuaries of China, columnId=1234106390126588740, journalTitle=China Environmental Science, columnName=Carbon Emission Control, runingTitle=null, highlight=null, articleAbstract=

This study collected the surface soil samples (0~10cm) from the freshwater (salinity: 0) and mesohaline (salinity:10~15) P. australis marshes in the six main estuaries in China, which are the Liao River Estuary, Yellow River Estuary, Yangtze River Estuary, Oujiang River Estuary, Minjiang River Estuary, and Pearl River Estuary. The production rates of soil CH4 and CO2 were measured using laboratory anaerobic slurry incubation method, and the extracellular enzyme activity and abundance of methanogen functional genes (mcrA) were also measured. Mean CH4 production rate in the freshwater and saltwater P. australis marshes was (2.69±1.63) and (2.97±1.71) ng CH4/(g·d), respectively. Mean CO2 production rate was (7.64±4.94)and (10.28±6.84)µg CO2/(g·d), respectively. CO2 production rate in the freshwater P. australis marshes was significantly lower than that in mesohaline P. australis marshes, but no significant difference in CH4 production rate was observed between freshwater and mesohaline marshes. Soil pH and soil organic carbon (SOC) content were identified as the main factors influencing extracellular enzyme activity and methanogen abundance. A decrease in pH led to a significant reduction in the production rates of CH4 and CO2. Total carbon, total nitrogen, SOC, activity of five extracellular enzymes, and abundance of mcrA were identified as the key factors influencing CH4 and CO2 production. Our research results suggest that across the Chinese coastal estuarine freshwater and mesohaline P. australis marshes, salinity is not a main factor controlling CH4 production, however, the increase in salinity perhaps raise soil anaerobic mineralization rates, which indicates that sea level rise and saltwater intrusion will cause carbon emission increase from estuarine P. australis marshes.

, correspAuthors=Chuan TONG, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, authorCompany=null, fund=null, authors=null, authorsList=Zhi-hua FENG, Fang HU, Peng-fei ZHAN, Jia-fang HUANG, Chuan TONG), CN=ArticleExt(id=1241408725982966649, articleId=1241408721604112826, tenantId=1146029695717560320, journalId=1234093305789726721, language=CN, title=中国主要河口淡水和咸水芦苇湿地CH4和CO2产生速率及影响因子, columnId=1234106391661704058, journalTitle=中国环境科学, columnName=碳排放控制, runingTitle=null, highlight=null, articleAbstract=

采集辽河口、黄河口、长江口、瓯江口、闽江口、珠江口6个河口分布的淡水(盐度:0)和咸水(盐度:10~15)芦苇湿地的表层土样,室内运用泥浆厌氧培养法测定土壤CH4、CO2产生速率,并测定土壤胞外酶活性以及产甲烷菌功能基因(mcrA)丰度.6个河口淡水和咸水芦苇湿地土壤CH4产生速率平均值分别为(2.69±1.63)和(2.97±1.71)ng CH4/(g·d);CO2产生速率平均值分别为(7.64±4.94)和(10.28±6.84)µg CO2/(g·d).淡水芦苇湿地土壤CO2产生速率显著低于咸水芦苇湿地,然而,淡水芦苇湿地土壤CH4产生速率与咸水芦苇湿地无显著差异.土壤pH值、有机碳(SOC)含量是影响芦苇湿地土壤胞外酶活性以及产甲烷菌功能基因(mcrA)丰度的主要因子.土壤pH值、TC、TN、SOC以及5种胞外酶活性、产甲烷菌功能基因丰度是CH4和CO2产生的主要影响因子,pH值降低导致CH4与CO2产生速率显著下降,.本研究结果表明:中国沿海主要河口尺度淡水到中咸水生境,盐度不是芦苇湿地土壤CH4产生速率的调控因子,但是盐度增加显著提升芦苇湿地土壤厌氧矿化速率,上述结果表明:,海平面上升-盐水入侵将导致河口区芦苇湿地土壤碳排放量增加.

, correspAuthors=仝川, authorNote=null, correspAuthorsNote=
* 责任作者,教授,
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冯智桦(2001-),男,广东佛山人,福建师范大学硕士研究生,主要从事河口湿地生物地球化学循环的研究..

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冯智桦(2001-),男,广东佛山人,福建师范大学硕士研究生,主要从事河口湿地生物地球化学循环的研究..

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冯智桦(2001-),男,广东佛山人,福建师范大学硕士研究生,主要从事河口湿地生物地球化学循环的研究..

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Ecology letters200811(11):1252-1264., articleTitle=Stoichiometry of soil enzyme activity at global scale, refAbstract=null), Reference(id=1241408746849628641, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241408721604112826, doi=null, pmid=null, pmcid=null, year=2020, volume=53, issue=14, pageStart=2897, pageEnd=2906, url=null, language=null, rfNumber=[44], rfOrder=54, authorNames=袁武, 靳振江, 程跃扬, journalName=中国农业科学, refType=null, unstructuredReference=袁武,靳振江,程跃扬,等.岩溶湿地和稻田的土壤酶活性与CO2和CH4排放特征[J]. 中国农业科学202053(14):2897-2906., articleTitle=岩溶湿地和稻田的土壤酶活性与CO2和CH4排放特征, refAbstract=null), Reference(id=1241408746967069161, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241408721604112826, doi=null, pmid=null, pmcid=null, year=2020, volume=53, issue=14, pageStart=2897, pageEnd=2906, url=null, language=null, rfNumber=[44], rfOrder=55, authorNames=Yuan W, Jin Z J, Cheng Y Y, journalName=Scientia Agricultura Sinica, refType=null, unstructuredReference=Yuan WJin Z JCheng Y Y,et al. Characteristics of soil enzyme activities and CO2 and CH4 emissions from natural wetland and paddy field in Karst Areas [J]. Scientia Agricultura Sinica202053(14):2897-2906., articleTitle=Characteristics of soil enzyme activities and CO2 and CH4 emissions from natural wetland and paddy field in Karst Areas, refAbstract=null), Reference(id=1241408747369722357, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241408721604112826, doi=null, pmid=null, pmcid=null, year=2000, volume=33, issue=null, pageStart=181, pageEnd=189, url=null, language=null, rfNumber=[45], rfOrder=56, authorNames=Bergman I, Klarqvist M, Nilsson M, journalName=Federation of European Microbiological Societies Microbiology Ecology, refType=null, unstructuredReference=Bergman IKlarqvist MNilsson M. Seasonal variation in rates of methane production from peat of various botanical origins: effects of temperature and substrate quality [J]. 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language=EN, label=Fig.4, caption=Results of random forest model analysis on relative importance of soil factors in CH4 and CO2 production rates of estuarine P.australis marshes, figureFileSmall=s5hEFn42gtj7iwuvp2PWPw==, figureFileBig=bUuisoBeojBf5mra1LmBsg==, tableContent=null), ArticleFig(id=1241408733587239632, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241408721604112826, language=CN, label=图4, caption=土壤因子对芦苇湿地CH4和CO2产生速率影响的相对重要性的随机森林模型分析结果

*表示P<0.05,**表示P<0.01

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*表示P<0.05,**表示P<0.01

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Information of the sampling sites of freshwater and saltwater P.australis marshes in six main estuaries of China

, figureFileSmall=null, figureFileBig=null, tableContent=
采样河口生境潮汐状况经纬度坐标
辽河口咸水湿地不规则半日潮121°41′37″E40°53′37″N
淡水湿地121°56′31″E41°08′46″N
黄河口咸水湿地不规则半日潮119°12′42″E37°43′35″N
淡水湿地119°09′13″E37°45′43″N
长江口咸水湿地不规则半日潮121°58′12″E30°53′07″N
淡水湿地121°17′56″E31°31′01″N
瓯江口咸水湿地典型的半日潮120°07′42″E27°58′16″N
淡水湿地120°39′54″E28°02′41″N
闽江口咸水湿地典型的半日潮119°37′51″E26°08′26″N
淡水湿地119°24′24″E25°57′21″N
珠江口咸水湿地不规则半日潮113°49′45″E22°25′42″N
淡水湿地113°31′01″E22°53′05″N
), ArticleFig(id=1241408734975554372, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241408721604112826, language=CN, label=表1, caption=

中国6个河口淡水和咸水芦苇湿地土壤采样点信息

, figureFileSmall=null, figureFileBig=null, tableContent=
采样河口生境潮汐状况经纬度坐标
辽河口咸水湿地不规则半日潮121°41′37″E40°53′37″N
淡水湿地121°56′31″E41°08′46″N
黄河口咸水湿地不规则半日潮119°12′42″E37°43′35″N
淡水湿地119°09′13″E37°45′43″N
长江口咸水湿地不规则半日潮121°58′12″E30°53′07″N
淡水湿地121°17′56″E31°31′01″N
瓯江口咸水湿地典型的半日潮120°07′42″E27°58′16″N
淡水湿地120°39′54″E28°02′41″N
闽江口咸水湿地典型的半日潮119°37′51″E26°08′26″N
淡水湿地119°24′24″E25°57′21″N
珠江口咸水湿地不规则半日潮113°49′45″E22°25′42″N
淡水湿地113°31′01″E22°53′05″N
), ArticleFig(id=1241408735130743633, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241408721604112826, language=EN, label=Table 2, caption=

Soil physical and chemical properties of the sampling sites of freshwater (denoted by F) and saltwater (denoted by S) P.australis marshes in six estuaries in China

, figureFileSmall=null, figureFileBig=null, tableContent=
河口采样点盐度含水率(%)容重(g/cm3)pH值TC(g/kg)TN(g/kg)C:NSOC(g/kg)
辽河口淡水(LHF)0.00±0.0034±41.26±0.037.69±0.128.25±1.410.49±0.1411.92±0.626.83±0.63
(LH)咸水(LHS)14.50±0.5645±61.17±0.048.79±0.067.57±0.250.27±0.0311.72±0.096.78±0.56
黄河口淡水(HHF)0.42±0.7227±11.34±0.088.63±0.1414.33±0.320.17±0.0216.92±0.2912.06±0.57
(HH)咸水(HHS)14.46±0.6749±171.22±0.098.30±0.2219.02±1.960.26±0.1018.17±0.9415.26±0.11
长江口淡水(CJF)0.00±0.0055±100.88±0.037.41±0.1119.81±0.631.17±0.0314.82±0.1316.06±0.09
(CJ)咸水(CJS)12.70±0.1049±200.92±0.028.19±0.0216.99±1.290.71±0.1517.71±0.4413.44±0.26
瓯江口淡水(OJF)0.00±0.0051±21.1±0.047.68±0.049.37±1.290.55±0.229.22±0.118.56±0.19
(OJ)咸水(OJS)14.56±0.7882±20.8±0.027.79±0.0410.25±1.100.65±0.0910.74±0.079.19±0.84
闽江口淡水(MJF)0.00±0.0067±170.81±0.046.12±0.1226.15±1.112.04±0.0211.69±0.4623.09±2.18
(MJ)咸水(MJS)14.80±0.2059±190.78±0.046.2±0.2717.06±0.81.38±0.1310.19±0.114.25±0.69
珠江口(ZJ)淡水(ZJF)0.00±0.00103±50.66±0.027.66±0.1419.00±1.511.23±0.169.56±0.1916.44±1.24
咸水(ZJS)9.99±1.7564±71.06±0.056.33±0.3122.26±0.111.46±0.038.99±0.0918.01±0.53
), ArticleFig(id=1241408735273349987, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241408721604112826, language=CN, label=表2, caption=

中国6个河口淡水(F)和咸水(S)芦苇湿地土壤理化特征

, figureFileSmall=null, figureFileBig=null, tableContent=
河口采样点盐度含水率(%)容重(g/cm3)pH值TC(g/kg)TN(g/kg)C:NSOC(g/kg)
辽河口淡水(LHF)0.00±0.0034±41.26±0.037.69±0.128.25±1.410.49±0.1411.92±0.626.83±0.63
(LH)咸水(LHS)14.50±0.5645±61.17±0.048.79±0.067.57±0.250.27±0.0311.72±0.096.78±0.56
黄河口淡水(HHF)0.42±0.7227±11.34±0.088.63±0.1414.33±0.320.17±0.0216.92±0.2912.06±0.57
(HH)咸水(HHS)14.46±0.6749±171.22±0.098.30±0.2219.02±1.960.26±0.1018.17±0.9415.26±0.11
长江口淡水(CJF)0.00±0.0055±100.88±0.037.41±0.1119.81±0.631.17±0.0314.82±0.1316.06±0.09
(CJ)咸水(CJS)12.70±0.1049±200.92±0.028.19±0.0216.99±1.290.71±0.1517.71±0.4413.44±0.26
瓯江口淡水(OJF)0.00±0.0051±21.1±0.047.68±0.049.37±1.290.55±0.229.22±0.118.56±0.19
(OJ)咸水(OJS)14.56±0.7882±20.8±0.027.79±0.0410.25±1.100.65±0.0910.74±0.079.19±0.84
闽江口淡水(MJF)0.00±0.0067±170.81±0.046.12±0.1226.15±1.112.04±0.0211.69±0.4623.09±2.18
(MJ)咸水(MJS)14.80±0.2059±190.78±0.046.2±0.2717.06±0.81.38±0.1310.19±0.114.25±0.69
珠江口(ZJ)淡水(ZJF)0.00±0.00103±50.66±0.027.66±0.1419.00±1.511.23±0.169.56±0.1916.44±1.24
咸水(ZJS)9.99±1.7564±71.06±0.056.33±0.3122.26±0.111.46±0.038.99±0.0918.01±0.53
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中国主要河口淡水和咸水芦苇湿地CH4和CO2产生速率及影响因子
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冯智桦 1 , 胡芳 1 , 展鹏飞 1 , 黄佳芳 1, 2 , 仝川 1, 2, *
中国环境科学 | 碳排放控制 2025,45(4): 2240-2250
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中国环境科学 | 碳排放控制 2025, 45(4): 2240-2250
中国主要河口淡水和咸水芦苇湿地CH4和CO2产生速率及影响因子
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冯智桦1 , 胡芳1, 展鹏飞1, 黄佳芳1, 2, 仝川1, 2, *
作者信息
  • 1.福建师范大学地理科学学院,湿润亚热带生态-地理过程教育部重点实验室,福建 福州 350117
  • 2.福建闽江河口湿地生态系统国家定位观测研究站(国家林草局),福建 福州 350215
  • 冯智桦(2001-),男,广东佛山人,福建师范大学硕士研究生,主要从事河口湿地生物地球化学循环的研究..

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* 责任作者,教授,
Production rates and key influencing factors of CH4 and CO2 of freshwater and saltwater Phragmites australis marshes in major estuaries of China
Zhi-hua FENG1 , Fang HU1, Peng-fei ZHAN1, Jia-fang HUANG1, 2, Chuan TONG1, 2, *
Affiliations
  • 1.Key Laboratory for Humid Subtropical Eco-Geographical Processes of the Ministry of Education, School of Geographical Sciences, Fujian Normal University, Fuzhou 350117, China
  • 2.Wetland Ecosystem Research Station of Minjiang Estuary, National Forestry and Grassland Administration, Fuzhou 350215, China
出版时间: 2025-04-20
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采集辽河口、黄河口、长江口、瓯江口、闽江口、珠江口6个河口分布的淡水(盐度:0)和咸水(盐度:10~15)芦苇湿地的表层土样,室内运用泥浆厌氧培养法测定土壤CH4、CO2产生速率,并测定土壤胞外酶活性以及产甲烷菌功能基因(mcrA)丰度.6个河口淡水和咸水芦苇湿地土壤CH4产生速率平均值分别为(2.69±1.63)和(2.97±1.71)ng CH4/(g·d);CO2产生速率平均值分别为(7.64±4.94)和(10.28±6.84)µg CO2/(g·d).淡水芦苇湿地土壤CO2产生速率显著低于咸水芦苇湿地,然而,淡水芦苇湿地土壤CH4产生速率与咸水芦苇湿地无显著差异.土壤pH值、有机碳(SOC)含量是影响芦苇湿地土壤胞外酶活性以及产甲烷菌功能基因(mcrA)丰度的主要因子.土壤pH值、TC、TN、SOC以及5种胞外酶活性、产甲烷菌功能基因丰度是CH4和CO2产生的主要影响因子,pH值降低导致CH4与CO2产生速率显著下降,.本研究结果表明:中国沿海主要河口尺度淡水到中咸水生境,盐度不是芦苇湿地土壤CH4产生速率的调控因子,但是盐度增加显著提升芦苇湿地土壤厌氧矿化速率,上述结果表明:,海平面上升-盐水入侵将导致河口区芦苇湿地土壤碳排放量增加.

甲烷产生速率  /  二氧化碳产生速率  /  胞外酶  /  盐度  /  芦苇沼泽  /  河口  /  中国

This study collected the surface soil samples (0~10cm) from the freshwater (salinity: 0) and mesohaline (salinity:10~15) P. australis marshes in the six main estuaries in China, which are the Liao River Estuary, Yellow River Estuary, Yangtze River Estuary, Oujiang River Estuary, Minjiang River Estuary, and Pearl River Estuary. The production rates of soil CH4 and CO2 were measured using laboratory anaerobic slurry incubation method, and the extracellular enzyme activity and abundance of methanogen functional genes (mcrA) were also measured. Mean CH4 production rate in the freshwater and saltwater P. australis marshes was (2.69±1.63) and (2.97±1.71) ng CH4/(g·d), respectively. Mean CO2 production rate was (7.64±4.94)and (10.28±6.84)µg CO2/(g·d), respectively. CO2 production rate in the freshwater P. australis marshes was significantly lower than that in mesohaline P. australis marshes, but no significant difference in CH4 production rate was observed between freshwater and mesohaline marshes. Soil pH and soil organic carbon (SOC) content were identified as the main factors influencing extracellular enzyme activity and methanogen abundance. A decrease in pH led to a significant reduction in the production rates of CH4 and CO2. Total carbon, total nitrogen, SOC, activity of five extracellular enzymes, and abundance of mcrA were identified as the key factors influencing CH4 and CO2 production. Our research results suggest that across the Chinese coastal estuarine freshwater and mesohaline P. australis marshes, salinity is not a main factor controlling CH4 production, however, the increase in salinity perhaps raise soil anaerobic mineralization rates, which indicates that sea level rise and saltwater intrusion will cause carbon emission increase from estuarine P. australis marshes.

methane production rate  /  carbon dioxide production rate  /  extracellular enzymes  /  salinity  /  reed marsh  /  estuary  /  China
冯智桦, 胡芳, 展鹏飞, 黄佳芳, 仝川. 中国主要河口淡水和咸水芦苇湿地CH4和CO2产生速率及影响因子. 中国环境科学, 2025 , 45 (4) : 2240 -2250 .
Zhi-hua FENG, Fang HU, Peng-fei ZHAN, Jia-fang HUANG, Chuan TONG. Production rates and key influencing factors of CH4 and CO2 of freshwater and saltwater Phragmites australis marshes in major estuaries of China[J]. China Environmental Science, 2025 , 45 (4) : 2240 -2250 .
甲烷(CH4)具有高热辐射吸收潜力,是最重要的温室气体之一.CH4单位质量全球增温潜势远高于二氧化碳(CO2[1].非化石能源(non-fossil) CH4排放百年尺度全球变暖潜势是CO2的27倍[2].滨海/河口沼泽湿地是主要的滨海蓝碳生态系统之一,也是全球生产力极高的植物群落类型之一,其单位面积固碳能力远超其他生态系统[3],在缓解全球气候变暖方面发挥着重要的作用.但同时,滨海/河口沼泽湿地又是大气CH4不可忽视的自然排放源.
河口沼泽湿地受河流径流和海洋潮汐作用共同影响,土壤盐度存在着明显的变化.考虑到盐度是河口湿地最重要的环境因子之一,盐度变化对于河口沼泽湿地CH4和CO2排放的影响受到科学界的关注[4-7].一项对1983~2010年发表文献的综述研究发现:沼泽湿地CH4排放通量大致上表现为随盐度的增加而降低,一个关键的盐度阈值为18,盐度高于该阈值的沼泽湿地CH4排放通量显著低于小于该阈值的沼泽,淡水(盐度<0.5)和中咸水(0.5<盐度<18)沼泽湿地CH4排放通量无显著差异,在盐度范围为0.5~5之间CH4排放通量明显增加[8].湿地CH4产生是CH4代谢过程重要的一环,直接影响着湿地CH4排放.目前研究已表明盐水入侵或盐度增加导致河口湿地土壤中电子受体SO42-浓度提升,硫酸盐异化还原较CH4产生的能量更高,因此增加的SO42−浓度造成淡水湿地CH4产生过程向硫酸盐还原过程转变,CH4产生速率降低[9-12],但这种变化是否与盐度增加的幅度有关?通过文献综述分析发现的淡水沼泽湿地CH4排放通量与中咸水湿地无显著差异的结论,是否有相应的CH4产生速率方面规律的研究结果支持,目前还未见文献报道.此外,盐度对于河口沼泽湿地CO2产生速率的影响较为复杂[13],影响的结果尚不清晰.基于我国主要河口区分布的芦苇(Phragmites australis)沼泽湿地的盐度范围为淡水到中咸水(盐度<18)[14],本研究以我国沿海6个主要河口分布的淡水(盐度:~0)和咸水(盐度:10~15)芦苇湿地为研究对象,通过采集以上沼泽湿地表层土壤样品,运用室内泥浆厌氧培养法测定土壤CH4、CO2产生速率,土壤胞外酶活性以及产甲烷功能基因(mcrA)丰度,以期回答河口淡水和咸水(盐度:10~15)沼泽湿地土壤CH4和CO2产生速率是否具有显著差异这一科学问题,进而更深入地认识盐度变化对河口沼泽湿地土壤CH4和CO2产生的影响.
本研究的6个采样河口分别为辽河口(LH)、黄河口(HH)、长江口(CJ)、瓯江口(OJ)、闽江口(MJ)、珠江口(ZJ).辽河口位于辽宁省盘锦市,属于暖温带大陆性季风气候区[15].黄河口位于渤海湾与莱州湾的交界处,属于暖温带大陆性季风气候区[16],其潮汐特性主要表现为不规则的半日潮型态.长江口位于中国上海市北部,属于副热带季风气候区[17].瓯江口位于浙江省温州市,属于中亚热带海洋性季风气候区[18].闽江河口位于福州市,属于亚热带海洋性季风气候区[19].珠江口位于中国南亚热带季风气候区[20].各河口淡水芦苇湿地和咸水芦苇湿地采样点的经纬度等信息见表1.
2021年夏季分别在辽河口、黄河口、长江口、瓯江口、闽江口、珠江口分布的淡水(盐度:~0)及咸水(盐度:10~15)芦苇湿地采集表层(0~10cm)土样.对于每个河口选定的淡水、咸水芦苇湿地,随机选取3个具有一定距离的芦苇湿地样地(plot),在每个样地使用土钻(内径10cm)随机采集3个表层土壤样品并混合为1个土壤样品,迅速装入冷藏箱运回实验室.在实验室将土样过筛以剔除细根等杂物,并分为两份,一份于4℃的冰箱中储存,另一份室内风干后碾磨过筛以待理化指标的分析.
测定采集土样的盐度、含水率、容重、pH值、TC(总碳含量)、TN(总氮含量)和SOC(土壤有机碳)含量等指标,此外,在厌氧培养实验结束时(第15d)收集各培养瓶内泥浆土样.测定pH值、盐度、NO3-、NH4+、SO42-、Cl-、TC、TN和SOC含量等指标.运用pH值400便携式土壤pH值计(Spectrum Technologies Inc,美国)测定土壤pH值;运用失重法在105℃烘干至恒重测定土壤含水率[21];使用便携式Salt6+盐度计(Thermo Fisher Scientific,美国)测定土壤盐度.土壤NO3和NH4+浓度测定:土样用2mol/L KCl浸提,运用SAN++连续流动注射分析仪测定(Skalar Analytical SAN++,荷兰);土壤SO42−和Cl浓度用离子色谱仪测定(赛默飞ICS-2100型,美国).全碳(TC)和全氮(TN)采用碳氮元素分析仪(Elementar Vario MAX CN,德国)测定;土壤有机碳(SOC)使用碳氮元素分析仪器(Elementar Vario MAX,德国,碳素检测限为0.01mg)测定,测定前先用浓度为0.5mol/L HCl去除土壤/沉积物中的无机碳,后用蒸馏水洗至中性并风干研磨,过0.15mm筛.
实验室厌氧培养法是目前最为普遍的测定湿地CH4产生速率和厌氧CO2产生速率的方法.厌氧环境主要通过氮气置换实现,土壤样品多用鲜土配置为泥浆[22].本研究称取25g鲜土放入150mL玻璃培养瓶内,分别加入25mL去离子,震荡30min使其充分混合均匀后将瓶口密封,使用两根注射针分别注入高纯氮气(N2)以排出瓶内气体,洗气过程持续6~10min使瓶内形成厌氧状态[12],并立即测定瓶内CO2和CH4浓度作为初始浓度.培养箱温度设置为25℃,连续培养15d,分别在第1,3,7,15d测定CH4和CO2浓度.每次抽气前将培养瓶放入震荡器设置200r/min震荡30min,使瓶内CH4或CO2浓度均衡,抽取瓶内5mL气体,使用气相色谱仪(Shimadzu,GC−2010,Japan)测定CO2和CH4浓度,在气体采集后立即补充等量氮气保持瓶内气压平衡,根据公式(1)[23]计算CO2和CH4产生速率:
式中:P为CO2或CH4产生速率(CO2:μg/(g·d),CH4:ng/(g·d));M为CO2或CH4的摩尔质量,CO2: 44g/mol,CH4:16g/mol;V是大气标准状态气体摩尔体积,22.4L/mol;dc/dt是单位时间内气体浓度的变化率CO2:μL/(L·d);CH4:mL/(L·d),且只有在回归系数R2>0.9时视为有效数据;VH为培养瓶上部空间气体体积L;WS为培养瓶内干土重[鲜土重×(1−土壤含水量)],g;T为培养温度,ºC.
在培养结束时(第15d)收集培养瓶内土样,测定相关的土壤胞外酶活性.土壤胞外酶活性测定参考Saiya-Cork等[25]的实验方法.3种水解酶活性:β-葡萄糖苷酶(BG)、纤维素水解酶(CBH)、β-N-乙酰氨基葡萄糖苷酶(NAG)用伞形酮(MUB)作为标示底物来测定;2种氧化酶活性:酚氧化酶(PHO)、过氧化物酶(PEO)用L-羟苯丙氨酸(DOPA)作为标示底物来测定,最后水解酶与氧化酶分别通过荧光度进行测定.具体操作步骤为取3g过0.25mm筛的鲜土,加入125mL浓度为50mmol/L的醋酸盐缓冲液(pH值5.0),用磁力搅拌器搅拌5min使其均质化,随后静置.用移液枪吸取200μL上层清液,移入96孔微孔板(Perkin Elmer,Inc美国),按要求加完样后,测定水解酶将微孔板置于黑暗中20ºC静置4h后加入10μL的1mol/L NaOH停止反应,使用美国Synergy H4多功能酶标仪(设置为365nm激发光谱和450nm荧光扫描滤片)检测荧光度,单位为nmol/(g·h).测定氧化酶将微孔板置于黑暗中20ºC静置18h,使用配置450nm吸光度的美国Synergy H4多功能酶标仪来测定胞外酶活性,单位为μmol/(g·h).
培养结束时(第15d)收集培养瓶内土壤样品,使用土壤DNA提取试剂盒(天根生化科技,北京)对土壤样品进行DNA提取,选取产甲烷菌的mcrA功能基因(I型甲基辅酶M还原酶)进行实时荧光定量PCR分析,反应在定量PCR仪(iCycler iQ5BioRa,美国)上进行.定量PCR检测的前后引物分别为: F-mcrA(5′-GGTGGTGTMGGDTTCACMCARTA-3′)和R-mcrA(5′-CGTTCATBGCGTAGTTVGGRTAGT-3′)(Steinb erg and Regan,2009).反应体系为18μL,包括前后引物各0.5μL,2×Taq MasterMix 10μL,水7μL.反应程序为94℃预变性5min,94℃变性30s,95℃退火10s;55℃退火30s;72℃延伸30s;80℃延伸5s,共39个循环.将质粒标准品从101~105进行10倍梯度稀释,每个梯度取2uL做模板建立标准曲线,标准曲线方程R2=0.99.测试过程由北京奥维森基因科技有限公司完成.
数据分别运用Microsoft Excel 2019,IBM SPSS Statistics 27和R(4.3.3)统计分析软件进行整理与绘图.采用SPSS27.0统计软件,检验所有数据是否通过正态分布和方差齐次性检验,当检验未通过时,对原有原始数据进行转换处理,直至符合条件方进行方差分析.对于有显著差异的数据利用Tukey事后检验分析组间的差异性.图标和文本中所示数据均采用平均区间(Mean)±标准差(Standard deviation)的形式表达,当P<0.05时,视为达到显著性水平.
6个河口淡水和咸水芦苇湿地土壤含水率总体较高,平均值分别为(56%±6%)和(58%±11%),且不同河口间存在一定差异,其中珠江口淡水芦苇湿地土壤含水率高达(103%±5%),远大于其他河口芦苇湿地土壤含水率(P<0.01);淡水和咸水芦苇湿地土壤容重平均值分别为(1.01±0.04)g/cm3和(0.99±0.04)g/cm3,两者无显著差异(P>0.05);淡水和咸水芦苇湿地土壤pH值平均范围分别为(7.55±0.11)和(7.7±0.15),咸水芦苇湿地土壤pH值稍高于淡水芦苇湿地土壤,但两者差异不显著(P>0.05);淡水和咸水芦苇湿地土壤TC平均值分别为(16.16±1.05) g/kg和(15.52±1.05)g/kg;TN平均值分别为(0.94±0.1) g/kg和(0.79±0.09)g/kg,闽江口与珠江口芦苇湿地土壤TN高于其它4个河口芦苇湿地土壤TN,TC、TN在淡水与咸水芦苇湿地均无显著差异(P>0.05).珠江口芦苇湿地土壤C:N低于其它5个河口;淡水和咸水芦苇湿地土壤SOC平均值分别为平均值分别为(13.84±0.82) g/kg和(12.82±0.5)g/kg,不同盐度下芦苇湿地土壤SOC无显著差异(P>0.05),各河口间SOC表现出一定的差异,辽河口芦苇湿地土壤SOC仅为(6.80±0.6)g/kg,低于其它5个河口(表2).
6个河口淡水和咸水芦苇湿地土壤CH4产生速率范围分别为(0.96±0.03)~(5.45±0.11) ng CH4/(g·d),(0.76±0.03)~(5.01±0.07) ngCH4/(g·d),平均值分别为(2.69±1.63)和(2.97±1.71) ng CH4/(g·d).由图1可见,对于淡水芦苇湿地,辽河口CH4产生速率最低(0.96±0.04) ng·CH4/(g·d),闽江口最高(5.45±0.13) ng CH4/(g·d);对于咸水芦苇湿地,黄河口芦苇湿地最低(0.76±0.03) ng CH4/(g·d),闽江口最高(5.01±0.05) g CH4/(g·d) (图1(a)).
6个河口淡水和咸水芦苇湿地土壤CO2产生速率范围分别为(2.70±0.15)~(14.48±1.06)μg CO2/(g·d),(1.38±0.27)~(19.11±0.45)μg CO2/(g·d),平均值分别为(7.64±4.94)和(10.28±6.84) μg CO2/(g·d).对于淡水芦苇湿地,辽河口最低(1.38±0.03)μg CO2/(g·d),闽江口最高(14.48±1.30)μg CO2/(g·d),对于咸水芦苇湿地,辽河口最低(2.70±0.18)μg CO2/(g·d),长江口最高(19.11±0.55) μg CO2/(g·d)(图1(b)).6个河口数据整体分析结果表明:淡水与咸水芦苇湿地土壤CH4产生速率无显著差异(P>0.05),然而,淡水芦苇湿地土壤CO2产生速率显著低于咸水芦苇湿地(P<0.01)(图1(b)).
6个河口的淡水和咸水芦苇湿地土壤5种胞外酶活性见图2. 6个河口淡水和咸水芦苇湿地土壤BG活性范围分别为(2.90±0.24)~(8.35±0.15)nmol/(g·h),(2.39±0.09)~(9.13±0.02) nmol/(g·h),BG活性在6个河口间存在较大差异(P<0.01),闽江口、珠江口的BG活性较高.6个河口淡水和咸水芦苇湿地土壤CBH活性范围分别为(0.73±0.04)~(1.22±0.10)nmol/(g·h),(0.55±0.25)~(1.23±0.12)nmol/(g·h),各河口间CBH也存在较大差异(P<0.01).6个河口淡水和咸水芦苇湿地土壤NAG活性范围分别为(0.99±0.09)~(2.79±0.25)nmol/(g·h)和(1.57±0.69)~(7.66±0.26)nmol/(g·h),各河口NAG活性表现出较一致的水平,只有闽江口咸水芦苇湿地NAG活性显著高于其它河口(P<0.01),达到(7.66±0.26) nmol/(g·h).6个河口淡水和咸水芦苇湿地土壤PHO活性范围分别为(0.10±0.03)~(1.14±0.18) nmol/(g·h),(0.04±0.01)~(2.45±0.04) nmol/(g·h),闽江口咸水芦苇湿地土壤PHO活性远高于其它河口咸水芦苇湿地(P<0.01),高达(2.45±0.04)nmol/(g·h).闽江口淡水和咸水芦苇湿地土壤PEO酶活性均高于其它河口(P<0.01),分别为(5.99±2.73)和(11.00±1.52)nmol/(g·h),除闽江口外,其它5个河口淡水芦苇湿地土壤PEO活性均大于咸水芦苇湿地(P<0.01).对于5种土壤胞外酶,仅有NAG活性在淡水与咸水芦苇间呈现显著差异(P<0.01),其它4种土壤酶活性均未表现出显著差异(P>0.05).
6个河口淡水和咸水芦苇湿地土壤mcrA丰度的平均值分别为(1.92±1.08)和(2.08±1.12) copies·104/g,两者间无显著差异(P>0.05).辽河口、黄河口芦苇湿地土壤mcrA丰度较低,闽江口淡水、咸水芦苇湿地土壤mcrA丰度在6个河口中最大,分别达(3.55±1.17)和(3.30±0.6)copies·104/g(图3).
随机森林模型分析结果表明:土壤C:N、mcrA丰度和NH4+浓度是对CH4产生速率贡献率最高的前3个驱动因子(P<0.01),贡献率均大于15%,pH值、BG、PEO、CBH对CH4产生速率的贡献率范围为10% ~15%(P<0.01),SO42-、NO3-、TC、PHO、SOC、Cl-、NAG对CH4产生速率贡献率范围为5% ~10% (P>0.05).TN、BG是对CO2产生速率贡献最高的前2个驱动因子(P<0.01),贡献率接近20%,SO42-、pH值、盐度、Cl-对CO2产生速率贡献率范围为10%~15%(图4).
土壤CH4和CO2产生速率与土壤理化特征与生物因子的相关性如图5所示,芦苇湿地土壤CH4产生速率与土壤C:N、pH值具有显著负相关关系(P<0.01),与CBH、SOC、BG、TN、PHO、TC、NH4+、PEO具有显著正相关关系(P<0.01),土壤CO2产生速率与C:N、pH值具有显著负相关关系(P<0.01),与CBH、SOC、BG、TN、PHO、TC、PEO、CH4mcrA具有正显著相关关系(P<0.01).(图5
土壤CH4产生速率与土壤理化指标和土壤微生物指标的线性拟合关系见图6.土壤CH4产生速率与TN、TC、SOC、NH4+、BG、CBH、PHO、PEO、mcrA呈显著正相关线性拟合关系,与C:N、pH值呈显著负相关线性拟合关系.河口芦苇湿地土壤CO2产生速率与土壤环境指标和土壤微生物指标的线性拟合关系见图7.土壤CO2产生速率与TN、TC、SOC、BG、CBH、PHO、PEO、mcrA、CH4产生速率呈显著正相关线性拟合关系,与C:N、pH值呈负相关线性拟合关系.
本研究6个河口数据整体统计分析发现:河口淡水(盐度:~0)和咸水(盐度:10~15)芦苇湿地表层土壤CH4产生速率无显著差异(P>0.05).本研究中的咸水芦苇湿地土壤盐度范围为10~15,该盐度范围的河口湿地属于Odum划定的中盐水[26](5.0≤盐度<18.0,mesohaline)沼泽.本研究的结果可以很好地用于解释Poffenbarger等[8]通过对文献综述研究发现的一个重要结论:18.0是一个关键的盐度阈值,即淡水(盐度<0.5)和中咸水(5.0≤盐度<18.0)沼泽湿地CH4排放通量无显著差异(P>0.05).事实上,河口湿地CH4排放除了受盐度影响外,还受到植物群落类型、植物生物量、土壤微生物群落结构、土壤有机碳含量以及水淹条件等生物和非生物因子的综合调控,是一个多因子影响的生物地球化学过程.泥浆厌氧培养法是测定湿地土壤CH4产生速率的主要方法.泥浆培养法多是添加一定量的去离子水配置成水:土比为1:1的泥浆[22-24],用去离子水添加配置泥浆的主要出发点是防止用不同原位水可能造成添加水中其它离子和溶解性有机碳含量等条件的差异.本研究对采集的淡水和咸水芦苇湿地土样均添加去离子水配置泥浆进行厌氧培养实验,可能会造成咸水泥浆盐度的一定下降,无法很好地反映原位环境,这也可能是造成本研究中淡水和咸水芦苇湿地土壤CH4产生速率无显著差异的原因之一.今后的研究,对于河口盐沼湿地土壤厌氧培养实验测定土壤CH4和CO2产生速率应加入去除氧气的原位水可更好地反映湿地环境状况,并保证厌氧培养环境.此外,本研究厌氧培养实验的时长为15d,推测厌氧泥浆实验产生的CO2主要来自于微生物介导的土壤有机碳厌氧矿化分解,主要过程可能包括铁异化还原、硝酸盐异化还原,在咸水泥浆厌氧培养实验中还有硫酸盐异化还原产生的CO2气体.
盐度是影响滨海/河口湿地土壤CH4产生的一个重要环境因子,目前一些研究表明伴随着盐度的增加,河口湿地土壤中SO42-浓度提升,硫酸盐异化还原过程的能量比CH4产生过程高,因此造成随着盐度的增加湿地CH4产生速率降低[9-12].此外,硫酸盐还原过程的中间产物H2S,对产甲烷菌具有毒害作用,也会导致产甲烷菌活性下降.Cl-浓度的增加可通过渗透胁迫进而破坏酶和微生物的生理结构,降低产甲烷菌的活性[27].推测发生这一现象的条件可能是盐度增加的上限超过了中咸水范围,最终导致硫酸盐异化还原过程占优势,CH4产生速率降低.
本研究中6个河口淡水、咸水芦苇湿地土壤厌氧CO2产生速率平均值分别为(7.64±4.94)和(10.28±6.84)μg CO2/g(·d).6个河口数据整体统计分析发现:淡水芦苇湿地土壤厌氧CO2产生速率显著低于咸水芦苇湿地(P<0.01).目前鲜见关于盐度变化对于河口湿地土壤厌氧CO2产生速率影响的文献报道.从理论上讲,河口湿地盐度增加提升硫酸盐异化还原过程,硫酸盐异化还原过程的主要产物包括CO2气体,这将导致河口湿地土壤厌氧CO2产生量增多.
土壤胞外酶是由土壤植物根系、动物和微生物等合成分泌而成,其对土壤生物地球化学循环过程起到重要的作用.本研究中5种土壤胞外酶活性及产甲烷菌均与pH值呈显著负相关关系(P<0.01),mcrA丰度与土壤C:N呈显著负相关关系,与土壤NO3-、SOC、TN、TC、NH4+呈显著正相关关系.本研究中6个河口数据整体分析发现:河口淡水芦苇湿地NAG活性显著低于咸水芦苇湿地(P<0.01).NAG是土壤中的氮分解酶,其主要的功能是降解土壤中几丁质和肽聚糖等,并作为重要氮源物质[28],NAG活性的增减与微生物对氮源的需求有关,当微生物对氮需求增多的时候,土壤中NAG的活性也会随之增加.盐度对河口湿地土壤胞外酶活性的影响较为复杂.盐度作为酶活性的环境胁迫因子之一,可以通过影响微生物的群落结构、湿地植物生长等因素间接影响土壤胞外酶的活性[29].有研究提出,NAG在一定的盐度环境中表现出较高的活性,但并未明确指出其活性与盐度有直接关系[30]. Morrissey等[29]指出盐度增加可增强离子强度,提高酶及有机底物的吸附性与稳定性,进而提高酶活性.美国路易斯安纳州沼泽湿地土壤盐度从0.3增加至35时,BG活性会降低15%[31],与之类似的,孟加拉湾潮汐沼泽湿地围垦的水稻田土壤盐度从0增加至16,BG活性降低46%[32],中国长江河口潮汐沼泽湿地土壤施加盐水,也发现施加10以上的盐水,CBH活性降低[33].本研究对6个河口湿地数据整体分析发现,河口芦苇湿地土壤产甲烷菌丰度与土壤C:N、pH值具有显著负相关关系(P<0.01),与TC、TN、CBH、BG、PHO、NH4+具有显著正相关关系(P<0.01),然而盐度与SO42-含量无显著相关性(P>0.05)(图5).但也有研究表明:从淡水到微咸水沼泽(盐度:0~5.0),产甲烷菌丰度随盐度的增加而降低,即较低幅度的盐度增加同样对产甲烷菌丰度具有抑制作用[34].
河口沼泽湿地土壤CH4与CO2的产生是微生物介导的生物地球化学过程.本研究随机森林模型分析结果表明:土壤C:N、mcrA丰度和NH4+浓度对中国主要河口芦苇湿地CH4产生速率的贡献率最高,是3个最主要的驱动因子.土壤TN、BG活性对CO2产生速率贡献最高,是2个最主要的驱动因子.本研究相关性分析结果显示:河口沼泽湿地土壤CH4和CO2的产生速率与土壤TC、TN和SOC含量呈显著正相关关系.TC、TN和SOC含量越高,碳的可利用性就越高,增加了CH4和CO2产生底物的可利用性[35].此外,本研究中,河口沼泽湿地土壤CH4和CO2产生速率与C:N呈显著负相关关系,这也表明:对于河口沼泽湿地CH4和CO2产生,氮是一个限制因素.氮限制环境下土壤呼吸速率往往会较低,氮输入可提高氮的可利用性且会降低C:N,这导致底物氮限制得到改变,进而通过激发效应促进了微生物的活性,加快土壤有机碳的分解.
本研究相关分析结果表明:CH4与CO2的产生速率与土壤pH值呈显著负相关关系,随着pH值的增加,CH4、CO2的产生速率均显著下降.有研究表明,产甲烷菌代谢最适的pH值范围为6.5~7.5,超出此范围抑制CH4产生[36].曹琼等[37]发现土壤pH值增加,电导率显著上升,推测沉积物间隙水中SO42-、Cl-等浓度增加,导致硫酸盐还原过程增强,从而降低产甲烷菌对底物的利用效率[38].CH4产生速率与NH4+浓度呈显著正相关,可能由于NH4+浓度的增加提升了氮的可利用性,缓解了河口区沼泽湿地土壤的氮限制,为CH4与CO2的产生提供了良好的环境条件.
本研究发现,河口沼泽湿地土壤CH4和CO2产生与土壤胞外酶活性以及mcrA丰度呈显著正相关关系(P<0.01).产甲烷古菌是影响CH4产生速率的主要生物贡献因子,该结果与以往研究一致.Yuan等[39]发现外来植物入侵滨海湿地后CH4产生速率的增加与土壤中mcrA基因丰度的增加同步; Qi等[40]研究发现水稻田土壤CH4产生速率下降与mcrA的丰度降低相互关联.土壤胞外酶在湿地生态系统物质循环中具有关键作用[41],与湿地碳循环相关的胞外酶活性的增加,如BG、CBH、PHO和PEO的增加促进土壤有机碳分解[42].河口沼泽湿地植被茂密,生物量大,植物丰富的纤维素与根系的分泌物会为土壤胞外酶提供充足的底物,进一步导致CBH、PEO等胞外酶在河口沼泽湿地土壤的有机碳分解与转化过程中发挥重要作用.BG与河口芦苇湿地CO2产生速率具有显著相关性(P<0.001),可能是由于BG将二糖底物降解为葡萄糖[43],从而为土壤微生物提供了底物,促进了土壤的呼吸作用.河口芦苇湿地土壤CH4和CO2产生速率与土壤胞外酶活性、mcrA丰度存在显著正相关关系也支持了土壤胞外酶活性与mcrA丰度是CH4和CO2产生的主要驱动因子的结论.但是也有研究发现湿地CO2产生速率与土壤胞外酶活性呈现出相反的变化趋势[44],其具体关系仍需更为深入的研究加以明晰.有机碳输入以及SOC含量的差异也对产甲烷菌丰度和CH4产生具有重要的影响.本研究结果表明:CH4产生速率与SOC含量具有显著正相关关系,Bergman等[45]对瑞士泥炭沼泽湿地的研究发现,SOC含量的差异是造成不同湿地CH4产生速率差异的主要因素.
4.1 河口淡水芦苇湿地土壤表层CO2产生速率显著低于咸水(盐度:10~15)芦苇湿地,但是两者的CH4产生速率均无显著差异.
4.2 河口芦苇湿地土壤CH4及CO2产生速率受土壤理化特性与微生物功能因子的双重影响.土壤SOC、TC和TN含量是芦苇湿地土壤CH4及CO2产生速率的关键驱动因子,它们为土壤微生物代谢活动提供了丰富的底物资源.土壤CH4产生速率随着C:N、pH值的增加而降低.土壤mcrA丰度、BG、CBH、PEO、PHO酶活性对芦苇湿地土壤CH4及CO2的产生具有显著促进作用.
  • 国家自然科学基金资助项目(42177213)
  • 国家重点研发计划项目(2022YFC3105401)
  • 中央专项财政支持项目([350182]FJYHZB[GK]2024001)
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  • 接收时间:2024-10-15
  • 首发时间:2026-03-19
  • 出版时间:2025-04-20
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  • 收稿日期:2024-10-15
基金
国家自然科学基金资助项目(42177213)
国家重点研发计划项目(2022YFC3105401)
中央专项财政支持项目([350182]FJYHZB[GK]2024001)
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    1.福建师范大学地理科学学院,湿润亚热带生态-地理过程教育部重点实验室,福建 福州 350117
    2.福建闽江河口湿地生态系统国家定位观测研究站(国家林草局),福建 福州 350215

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2种不同金属材料的力学参数

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属数
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genus
种数
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species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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