Vegetation patterns influence on soil microbial biomass and functional diversity in a hilly area of the Loess Plateau, China
Purpose Shifts of microbial biomass and functional diversity under different vegetation patterns can impact the soil processes, and the specific knowledge about this can be used to develop sound vegetation restoration strategies. This study was devoted to examine the effects of different vegetation...
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creator | Hu, Chanjuan Fu, Bojie Liu, Guohua Jin, Tiantian Guo, Lei |
description | Purpose
Shifts of microbial biomass and functional diversity under different vegetation patterns can impact the soil processes, and the specific knowledge about this can be used to develop sound vegetation restoration strategies. This study was devoted to examine the effects of different vegetation patterns on microbial biomass and functional diversity and explore the relationship between soil erosion and soil microbial properties under typical erosion conditions of the semiarid hilly area of the Loess Plateau, China.
Materials and methods
Soil samples were collected from the Yangjuangou catchment near Yan’an City, northern Shaanxi province, China. Four types of slopes, each with different vegetation pattern, were sampled, including F (forest planted by human), G (grass), G–F–G (grass on the upper and lower slopes and forest on the middle slope), and F–G–F (forest on the upper and lower slopes and grass on the middle slope). Top soil samples (0–10 cm) from each of the four slopes were analyzed for their physicochemical properties, microbial biomass, and functional diversity. The microbial biomass was analyzed using the fumigation–extraction method and microbial functional diversity using the community-level physiological profile method.
Results and discussion
The analysis of variance revealed a trend of increasing nutrient concentrations and soil microbial biomass nitrogen in the G–F–G soil samples. However, the F–G–F slope had the highest microbial biomass carbon, with an average of 289 mg kg
−1
and had the highest average well color development values (up to 120 h of incubation), which is used as an indicator of microbial activity. Mean values of Shannon diversity (H′), which are indicative of soil microbial functional diversity, ranged from only 2.75 for F to 2.82 for F–G–F. Principal component analysis showed that the four vegetation patterns had differences that are consistent with different carbon substrate utilization patterns. The greatest differences in single-carbon substrate utilization were between F–G–F and F and between F–G–F and G–F–G.
Conclusions
The F–G–F vegetation pattern was the best pattern for restoring soils on sloping land in terms of improving soil microbial biomass carbon, soil microbial functional diversity, and activity. Soil erosion processes might have an indirect effect on soil microbial biomass through its influence on soil physicochemical properties in the typical erosion-prone region of the Loess Plateau, China. |
doi_str_mv | 10.1007/s11368-010-0209-3 |
format | Article |
fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_856754464</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>856754464</sourcerecordid><originalsourceid>FETCH-LOGICAL-a413t-e5b54fc177359682fffddde83a96634e430246b9a24dcf4fe21c0276240d7e3f3</originalsourceid><addsrcrecordid>eNp1kU1rGzEQhkVpoKmTH9Cb6CWXbCqttNLuMZh-gaE5JLmK8e7IVpAlR9IWDPnxlXGgEMhphpn3GWbmJeQLZzecMf0tcy5U3zDOGtayoREfyDlXXDZa9uxjzaUYjt3-E_mc8xNjQtf2OXl5xA0WKC4GuodSMIVMXbB-xjAirdUcnac7N6a4duDp2sUd5EwhTNTOYTyStTy5v5iyK4cKU6Bb5_2BQkKg0dKyRbqKWKk7DwVhvqbLrQtwQc4s-IyXr3FBHn58v1_-alZ_fv5e3q4akFyUBrt1J-3ItRbdoPrWWjtNE_YCBqWERClYK9V6gFZOo5UWWz6yVqtWskmjsGJBrk5z9yk-z5iL2bk8ovcQMM7Z9J3SnZRKVuXXN8qnOKd6YDZaKqGGoW60IPwkqj_JOaE1--R2kA6GM3N0w5zcMPXf5uiGEZVpT0yu2rDB9H_w-9A_hJCNtg</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>746369941</pqid></control><display><type>article</type><title>Vegetation patterns influence on soil microbial biomass and functional diversity in a hilly area of the Loess Plateau, China</title><source>SpringerNature Journals</source><creator>Hu, Chanjuan ; Fu, Bojie ; Liu, Guohua ; Jin, Tiantian ; Guo, Lei</creator><creatorcontrib>Hu, Chanjuan ; Fu, Bojie ; Liu, Guohua ; Jin, Tiantian ; Guo, Lei</creatorcontrib><description>Purpose
Shifts of microbial biomass and functional diversity under different vegetation patterns can impact the soil processes, and the specific knowledge about this can be used to develop sound vegetation restoration strategies. This study was devoted to examine the effects of different vegetation patterns on microbial biomass and functional diversity and explore the relationship between soil erosion and soil microbial properties under typical erosion conditions of the semiarid hilly area of the Loess Plateau, China.
Materials and methods
Soil samples were collected from the Yangjuangou catchment near Yan’an City, northern Shaanxi province, China. Four types of slopes, each with different vegetation pattern, were sampled, including F (forest planted by human), G (grass), G–F–G (grass on the upper and lower slopes and forest on the middle slope), and F–G–F (forest on the upper and lower slopes and grass on the middle slope). Top soil samples (0–10 cm) from each of the four slopes were analyzed for their physicochemical properties, microbial biomass, and functional diversity. The microbial biomass was analyzed using the fumigation–extraction method and microbial functional diversity using the community-level physiological profile method.
Results and discussion
The analysis of variance revealed a trend of increasing nutrient concentrations and soil microbial biomass nitrogen in the G–F–G soil samples. However, the F–G–F slope had the highest microbial biomass carbon, with an average of 289 mg kg
−1
and had the highest average well color development values (up to 120 h of incubation), which is used as an indicator of microbial activity. Mean values of Shannon diversity (H′), which are indicative of soil microbial functional diversity, ranged from only 2.75 for F to 2.82 for F–G–F. Principal component analysis showed that the four vegetation patterns had differences that are consistent with different carbon substrate utilization patterns. The greatest differences in single-carbon substrate utilization were between F–G–F and F and between F–G–F and G–F–G.
Conclusions
The F–G–F vegetation pattern was the best pattern for restoring soils on sloping land in terms of improving soil microbial biomass carbon, soil microbial functional diversity, and activity. Soil erosion processes might have an indirect effect on soil microbial biomass through its influence on soil physicochemical properties in the typical erosion-prone region of the Loess Plateau, China.</description><identifier>ISSN: 1439-0108</identifier><identifier>EISSN: 1614-7480</identifier><identifier>DOI: 10.1007/s11368-010-0209-3</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer-Verlag</publisher><subject>Biomass ; Carbon ; Earth and Environmental Science ; Environ Risk Assess ; Environment ; Environmental Physics ; Environmental restoration ; Fumigation ; Grasses ; Microbial activity ; Nutrient concentrations ; Physicochemical properties ; Principal components analysis ; Sec 2 • Global Change ; Slopes ; Soil erosion ; Soil microorganisms ; Soil properties ; Soil Science & Conservation ; Soil sciences ; Soils ; Sustainable Land Use • Research Article ; Variance analysis ; Vegetation patterns</subject><ispartof>Journal of soils and sediments, 2010-09, Vol.10 (6), p.1082-1091</ispartof><rights>Springer-Verlag 2010</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-a413t-e5b54fc177359682fffddde83a96634e430246b9a24dcf4fe21c0276240d7e3f3</citedby><cites>FETCH-LOGICAL-a413t-e5b54fc177359682fffddde83a96634e430246b9a24dcf4fe21c0276240d7e3f3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s11368-010-0209-3$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s11368-010-0209-3$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>315,781,785,27928,27929,41492,42561,51323</link.rule.ids></links><search><creatorcontrib>Hu, Chanjuan</creatorcontrib><creatorcontrib>Fu, Bojie</creatorcontrib><creatorcontrib>Liu, Guohua</creatorcontrib><creatorcontrib>Jin, Tiantian</creatorcontrib><creatorcontrib>Guo, Lei</creatorcontrib><title>Vegetation patterns influence on soil microbial biomass and functional diversity in a hilly area of the Loess Plateau, China</title><title>Journal of soils and sediments</title><addtitle>J Soils Sediments</addtitle><description>Purpose
Shifts of microbial biomass and functional diversity under different vegetation patterns can impact the soil processes, and the specific knowledge about this can be used to develop sound vegetation restoration strategies. This study was devoted to examine the effects of different vegetation patterns on microbial biomass and functional diversity and explore the relationship between soil erosion and soil microbial properties under typical erosion conditions of the semiarid hilly area of the Loess Plateau, China.
Materials and methods
Soil samples were collected from the Yangjuangou catchment near Yan’an City, northern Shaanxi province, China. Four types of slopes, each with different vegetation pattern, were sampled, including F (forest planted by human), G (grass), G–F–G (grass on the upper and lower slopes and forest on the middle slope), and F–G–F (forest on the upper and lower slopes and grass on the middle slope). Top soil samples (0–10 cm) from each of the four slopes were analyzed for their physicochemical properties, microbial biomass, and functional diversity. The microbial biomass was analyzed using the fumigation–extraction method and microbial functional diversity using the community-level physiological profile method.
Results and discussion
The analysis of variance revealed a trend of increasing nutrient concentrations and soil microbial biomass nitrogen in the G–F–G soil samples. However, the F–G–F slope had the highest microbial biomass carbon, with an average of 289 mg kg
−1
and had the highest average well color development values (up to 120 h of incubation), which is used as an indicator of microbial activity. Mean values of Shannon diversity (H′), which are indicative of soil microbial functional diversity, ranged from only 2.75 for F to 2.82 for F–G–F. Principal component analysis showed that the four vegetation patterns had differences that are consistent with different carbon substrate utilization patterns. The greatest differences in single-carbon substrate utilization were between F–G–F and F and between F–G–F and G–F–G.
Conclusions
The F–G–F vegetation pattern was the best pattern for restoring soils on sloping land in terms of improving soil microbial biomass carbon, soil microbial functional diversity, and activity. Soil erosion processes might have an indirect effect on soil microbial biomass through its influence on soil physicochemical properties in the typical erosion-prone region of the Loess Plateau, China.</description><subject>Biomass</subject><subject>Carbon</subject><subject>Earth and Environmental Science</subject><subject>Environ Risk Assess</subject><subject>Environment</subject><subject>Environmental Physics</subject><subject>Environmental restoration</subject><subject>Fumigation</subject><subject>Grasses</subject><subject>Microbial activity</subject><subject>Nutrient concentrations</subject><subject>Physicochemical properties</subject><subject>Principal components analysis</subject><subject>Sec 2 • Global Change</subject><subject>Slopes</subject><subject>Soil erosion</subject><subject>Soil microorganisms</subject><subject>Soil properties</subject><subject>Soil Science & Conservation</subject><subject>Soil sciences</subject><subject>Soils</subject><subject>Sustainable Land Use • Research Article</subject><subject>Variance analysis</subject><subject>Vegetation patterns</subject><issn>1439-0108</issn><issn>1614-7480</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2010</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp1kU1rGzEQhkVpoKmTH9Cb6CWXbCqttNLuMZh-gaE5JLmK8e7IVpAlR9IWDPnxlXGgEMhphpn3GWbmJeQLZzecMf0tcy5U3zDOGtayoREfyDlXXDZa9uxjzaUYjt3-E_mc8xNjQtf2OXl5xA0WKC4GuodSMIVMXbB-xjAirdUcnac7N6a4duDp2sUd5EwhTNTOYTyStTy5v5iyK4cKU6Bb5_2BQkKg0dKyRbqKWKk7DwVhvqbLrQtwQc4s-IyXr3FBHn58v1_-alZ_fv5e3q4akFyUBrt1J-3ItRbdoPrWWjtNE_YCBqWERClYK9V6gFZOo5UWWz6yVqtWskmjsGJBrk5z9yk-z5iL2bk8ovcQMM7Z9J3SnZRKVuXXN8qnOKd6YDZaKqGGoW60IPwkqj_JOaE1--R2kA6GM3N0w5zcMPXf5uiGEZVpT0yu2rDB9H_w-9A_hJCNtg</recordid><startdate>20100901</startdate><enddate>20100901</enddate><creator>Hu, Chanjuan</creator><creator>Fu, Bojie</creator><creator>Liu, Guohua</creator><creator>Jin, Tiantian</creator><creator>Guo, Lei</creator><general>Springer-Verlag</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7ST</scope><scope>7UA</scope><scope>7X2</scope><scope>7XB</scope><scope>88I</scope><scope>8FE</scope><scope>8FH</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>BKSAR</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>F1W</scope><scope>GNUQQ</scope><scope>H96</scope><scope>H97</scope><scope>HCIFZ</scope><scope>L.G</scope><scope>M0K</scope><scope>M2P</scope><scope>PATMY</scope><scope>PCBAR</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PYCSY</scope><scope>Q9U</scope><scope>SOI</scope><scope>7T7</scope><scope>8FD</scope><scope>FR3</scope><scope>P64</scope></search><sort><creationdate>20100901</creationdate><title>Vegetation patterns influence on soil microbial biomass and functional diversity in a hilly area of the Loess Plateau, China</title><author>Hu, Chanjuan ; Fu, Bojie ; Liu, Guohua ; Jin, Tiantian ; Guo, Lei</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a413t-e5b54fc177359682fffddde83a96634e430246b9a24dcf4fe21c0276240d7e3f3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2010</creationdate><topic>Biomass</topic><topic>Carbon</topic><topic>Earth and Environmental Science</topic><topic>Environ Risk Assess</topic><topic>Environment</topic><topic>Environmental Physics</topic><topic>Environmental restoration</topic><topic>Fumigation</topic><topic>Grasses</topic><topic>Microbial activity</topic><topic>Nutrient concentrations</topic><topic>Physicochemical properties</topic><topic>Principal components analysis</topic><topic>Sec 2 • Global Change</topic><topic>Slopes</topic><topic>Soil erosion</topic><topic>Soil microorganisms</topic><topic>Soil properties</topic><topic>Soil Science & Conservation</topic><topic>Soil sciences</topic><topic>Soils</topic><topic>Sustainable Land Use • Research Article</topic><topic>Variance analysis</topic><topic>Vegetation patterns</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Hu, Chanjuan</creatorcontrib><creatorcontrib>Fu, Bojie</creatorcontrib><creatorcontrib>Liu, Guohua</creatorcontrib><creatorcontrib>Jin, Tiantian</creatorcontrib><creatorcontrib>Guo, Lei</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Environment Abstracts</collection><collection>Water Resources Abstracts</collection><collection>Agricultural Science Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Science Database (Alumni Edition)</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Natural Science Collection</collection><collection>Earth, Atmospheric & Aquatic Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>ProQuest Central Student</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 3: Aquatic Pollution & Environmental Quality</collection><collection>SciTech Premium Collection</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>Agricultural Science Database</collection><collection>Science Database</collection><collection>Environmental Science Database</collection><collection>Earth, Atmospheric & Aquatic Science Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Environmental Science Collection</collection><collection>ProQuest Central Basic</collection><collection>Environment Abstracts</collection><collection>Industrial and Applied Microbiology Abstracts (Microbiology A)</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Biotechnology and BioEngineering Abstracts</collection><jtitle>Journal of soils and sediments</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Hu, Chanjuan</au><au>Fu, Bojie</au><au>Liu, Guohua</au><au>Jin, Tiantian</au><au>Guo, Lei</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Vegetation patterns influence on soil microbial biomass and functional diversity in a hilly area of the Loess Plateau, China</atitle><jtitle>Journal of soils and sediments</jtitle><stitle>J Soils Sediments</stitle><date>2010-09-01</date><risdate>2010</risdate><volume>10</volume><issue>6</issue><spage>1082</spage><epage>1091</epage><pages>1082-1091</pages><issn>1439-0108</issn><eissn>1614-7480</eissn><abstract>Purpose
Shifts of microbial biomass and functional diversity under different vegetation patterns can impact the soil processes, and the specific knowledge about this can be used to develop sound vegetation restoration strategies. This study was devoted to examine the effects of different vegetation patterns on microbial biomass and functional diversity and explore the relationship between soil erosion and soil microbial properties under typical erosion conditions of the semiarid hilly area of the Loess Plateau, China.
Materials and methods
Soil samples were collected from the Yangjuangou catchment near Yan’an City, northern Shaanxi province, China. Four types of slopes, each with different vegetation pattern, were sampled, including F (forest planted by human), G (grass), G–F–G (grass on the upper and lower slopes and forest on the middle slope), and F–G–F (forest on the upper and lower slopes and grass on the middle slope). Top soil samples (0–10 cm) from each of the four slopes were analyzed for their physicochemical properties, microbial biomass, and functional diversity. The microbial biomass was analyzed using the fumigation–extraction method and microbial functional diversity using the community-level physiological profile method.
Results and discussion
The analysis of variance revealed a trend of increasing nutrient concentrations and soil microbial biomass nitrogen in the G–F–G soil samples. However, the F–G–F slope had the highest microbial biomass carbon, with an average of 289 mg kg
−1
and had the highest average well color development values (up to 120 h of incubation), which is used as an indicator of microbial activity. Mean values of Shannon diversity (H′), which are indicative of soil microbial functional diversity, ranged from only 2.75 for F to 2.82 for F–G–F. Principal component analysis showed that the four vegetation patterns had differences that are consistent with different carbon substrate utilization patterns. The greatest differences in single-carbon substrate utilization were between F–G–F and F and between F–G–F and G–F–G.
Conclusions
The F–G–F vegetation pattern was the best pattern for restoring soils on sloping land in terms of improving soil microbial biomass carbon, soil microbial functional diversity, and activity. Soil erosion processes might have an indirect effect on soil microbial biomass through its influence on soil physicochemical properties in the typical erosion-prone region of the Loess Plateau, China.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer-Verlag</pub><doi>10.1007/s11368-010-0209-3</doi><tpages>10</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Biomass Carbon Earth and Environmental Science Environ Risk Assess Environment Environmental Physics Environmental restoration Fumigation Grasses Microbial activity Nutrient concentrations Physicochemical properties Principal components analysis Sec 2 • Global Change Slopes Soil erosion Soil microorganisms Soil properties Soil Science & Conservation Soil sciences Soils Sustainable Land Use • Research Article Variance analysis Vegetation patterns |
title | Vegetation patterns influence on soil microbial biomass and functional diversity in a hilly area of the Loess Plateau, China |
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