Article(id=1309575127935841116, tenantId=1146029695717560320, journalId=1308397196074385509, issueId=1309575113855562513, articleNumber=null, orderNo=null, doi=10.11733/j.issn.1007-0435.2026.09.026, pmid=null, cstr=null, oa=null, hot=0, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1763568000000, receivedDateStr=2025-11-20, revisedDate=1772035200000, revisedDateStr=2026-02-26, acceptedDate=null, acceptedDateStr=null, onlineDate=1790156641229, onlineDateStr=2026-09-23, pubDate=null, pubDateStr=null, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1790156641229, onlineIssueDateStr=2026-09-23, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1790156641229, creator=13701087609, updateTime=1790156641229, updator=13701087609, issue=Issue{id=1309575113855562513, tenantId=1146029695717560320, journalId=1308397196074385509, year='2026', volume='34', issue='9', pageStart='3141', pageEnd='3524', issueExtLink='null', onlineDate='null', pubDate='1789401600000', pubDateStr='2026-09-15', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=1, specialIssue=null, createTime=1790156637871, creator='13701087609', updateTime=1790156973247, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1309576520587374966, tenantId=1146029695717560320, journalId=1308397196074385509, issueId=1309575113855562513, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1309576520587374967, tenantId=1146029695717560320, journalId=1308397196074385509, issueId=1309575113855562513, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=3426, endPage=3433, ext={EN=ArticleExt(id=1309575129986855775, articleId=1309575127935841116, tenantId=1146029695717560320, journalId=1308397196074385509, language=EN, title=Soil Microbial Biomass Carbon, Nitrogen, Phosphorus and Their Driving Factors in Inner Mongolia Grassland Ecosystems, columnId=null, journalTitle=Acta Agrestia Sinica, columnName=null, runingTitle=null, highlight=null, articleAbstract=To reveal the spatial distribution characteristics and driving mechanisms of soil microbial biomass carbon (MBC), nitrogen (MBN), and phosphorus (MBP) stoichiometry under precipitation gradients, this study collected 57 sampling points of three grassland types along a 3000 km transect in Inner Mongolia. The spatial distribution characteristics of microbial biomass and its stoichiometry were analyzed, and their relationship with climate and soil physicochemical factors was explored. The results showed that MBC content was significantly higher than that of MBN and MBP. Microbial biomass was positively correlated with available carbon, nitrogen, and phosphorus in the soil. MBN was negatively correlated with aridity, mean annual temperature (MAT), and soil bulk density (SBD). MBP was negatively correlated with aridity, MAT, and soil pH. The microbial biomass carbon-nitrogen ratio (Mcn) was significantly negatively correlated with mean annual precipitation (MAP), the microbial biomass carbon-phosphorus ratio (Mcp) was significantly positively correlated with aridity, and the microbial biomass nitrogen-phosphorus ratio (Mnp) was significantly positively correlated with soil pH. Random forest analysis indicated that MAP, aridity, and soil pH were the main driving factors of microbial biomass. This study deepened our understanding of the response of soil microorganisms to climate change and provided theoretical support for protecting the nutrient cycling function of grassland ecosystems., authors=LEI Lei1, LI Shao-yu1, ZHENG Jia-hua1, ZHANG Feng1, ZHANG Bin1, YANG Li-shan1, XING Jia-qing1, CHEN Xin-li2, ZHAO Meng-li1, HAN Guo-dong1, authorsList=LEI Lei, LI Shao-yu, ZHENG Jia-hua, ZHANG Feng, ZHANG Bin, YANG Li-shan, XING Jia-qing, CHEN Xin-li, ZHAO Meng-li, HAN Guo-dong, authorCompany=1 College of Grassland, Inner Mongolia Agricultural University, Hohhot, Inner Mongolia 010000, China; 2. Zhejiang Agriculture and Forestry University, Hangzhou, Zhejiang Province 310000, China, correspAuthors=null, 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, fund=null), CN=ArticleExt(id=1309575128606929757, articleId=1309575127935841116, tenantId=1146029695717560320, journalId=1308397196074385509, language=CN, title=内蒙古草地生态系统土壤微生物生物量碳氮磷及其驱动因素, columnId=1309565024058835950, journalTitle=草地学报, columnName=研究论文, runingTitle=null, highlight=null, articleAbstract=为揭示降水梯度下土壤微生物量碳氮磷(Microbial carbon, MBC;Microbial nitrogen, MBN; Microbial phosphorus,MBP)化学计量比的空间分布特征及驱动机制,本研究在内蒙古境内沿约3000 km样线采集了3种草地类型共57个样点,分析了微生物量及其化学计量比的空间分布特征,并探讨其与气候及土壤理化因子的关系。结果表明,MBC含量显著高于MBN、MBP;微生物量与土壤速效碳氮磷呈正相关,MBN与干旱度(Aridity)、年均温(Mean annual temperature,MAT)、土壤容重(Soil bulk density, SBD)呈负相关,MBP与Aridity、MAT、土壤pH值呈负相关;微生物量碳氮比(Mcn)与年平均降水量(Mean annual precipitation, MAP)呈显著负相关,微生物量碳磷比(Mcp)与Aridity呈显著正相关,微生物量氮磷比(Mnp)与土壤pH值呈显著正相关。随机森林分析表明,MAP、Aridity、土壤pH值是微生物量的主要驱动因子。本研究加深了土壤微生物碳氮磷对气候变化的响应的认知,为保护草地生态系统养分循环功能提供了理论支撑。, authors=雷蕾1, 李邵宇1, 郑佳华1, 张峰1, 张彬1, 杨立山1, 邢佳庆1, 陈信力2, 赵萌莉1, 韩国栋1, authorsList=雷蕾, 李邵宇, 郑佳华, 张峰, 张彬, 杨立山, 邢佳庆, 陈信力, 赵萌莉, 韩国栋, authorCompany=1 内蒙古农业大学草业学院, 内蒙古 呼和浩特 010010; 2 浙江农林大学, 浙江 杭州 310000, correspAuthors=null, authorNote=雷蕾(1996-),女,汉族,内蒙古鄂尔多斯人,博士研究生,主要从事草地生态经济学研究,E-mail:ivyleiben@163.com, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=MVO5oa9ctFKc1Ow5hmYqdw==, pdfFileSize=2091720, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, 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interPubPlatform=, interPubPlatformUrl=null), detailUrlCn=https://castjournals.cast.org.cn/joweb/cdxb/CN/10.11733/j.issn.1007-0435.2026.09.026, detailUrlEn=https://castjournals.cast.org.cn/joweb/cdxb/EN/10.11733/j.issn.1007-0435.2026.09.026, pdfUrlCn=https://castjournals.cast.org.cn/joweb/cdxb/CN/PDF/10.11733/j.issn.1007-0435.2026.09.026, pdfUrlEn=https://castjournals.cast.org.cn/joweb/cdxb/EN/PDF/10.11733/j.issn.1007-0435.2026.09.026, aliStartDate=null, aliEndDate=null, collectionFlag=false, citedCount=null, citedUrl=null, previewStatus=0, delFlag=0, hasFullText=0, orderTime=1789401600000, fullTextJson=null, articleText=null, reference=LIU Y Q. 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Soil Microbial Biomass Carbon, Nitrogen, Phosphorus and Their Driving Factors in Inner Mongolia Grassland Ecosystems
LEI Lei1, LI Shao-yu1, ZHENG Jia-hua1, ZHANG Feng1, ZHANG Bin1, YANG Li-shan1, XING Jia-qing1, CHEN Xin-li2, ZHAO Meng-li1, HAN Guo-dong1
Affiliations
1 College of Grassland, Inner Mongolia Agricultural University, Hohhot, Inner Mongolia 010000, China; 2. Zhejiang Agriculture and Forestry University, Hangzhou, Zhejiang Province 310000, China
To reveal the spatial distribution characteristics and driving mechanisms of soil microbial biomass carbon (MBC), nitrogen (MBN), and phosphorus (MBP) stoichiometry under precipitation gradients, this study collected 57 sampling points of three grassland types along a 3000 km transect in Inner Mongolia. The spatial distribution characteristics of microbial biomass and its stoichiometry were analyzed, and their relationship with climate and soil physicochemical factors was explored. The results showed that MBC content was significantly higher than that of MBN and MBP. Microbial biomass was positively correlated with available carbon, nitrogen, and phosphorus in the soil. MBN was negatively correlated with aridity, mean annual temperature (MAT), and soil bulk density (SBD). MBP was negatively correlated with aridity, MAT, and soil pH. The microbial biomass carbon-nitrogen ratio (Mcn) was significantly negatively correlated with mean annual precipitation (MAP), the microbial biomass carbon-phosphorus ratio (Mcp) was significantly positively correlated with aridity, and the microbial biomass nitrogen-phosphorus ratio (Mnp) was significantly positively correlated with soil pH. Random forest analysis indicated that MAP, aridity, and soil pH were the main driving factors of microbial biomass. This study deepened our understanding of the response of soil microorganisms to climate change and provided theoretical support for protecting the nutrient cycling function of grassland ecosystems.
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