Temporal and Spatial Characteristics and Influencing Factors of Carbon Storage in Black Soil Area Under Topographic Gradient
Exploring the characteristics and driving factors of carbon storage change in different terrain gradient variations can provide important insights for formulating the agricultural ecological protection policy for regional development. Previous studies have used the fixed value of carbon density to e...
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description | Exploring the characteristics and driving factors of carbon storage change in different terrain gradient variations can provide important insights for formulating the agricultural ecological protection policy for regional development. Previous studies have used the fixed value of carbon density to evaluate the change characteristics of carbon storage but ignored the spatio-temporal heterogeneity of carbon storage at the block scale and the impact of policy factors. Thus, this paper takes Sanjiang Plain, Heilongjiang Province, China, as a study area, and the spatio-temporal variation of carbon storage at different topographic gradients was revealed using hot and cold spot analysis and zonal statistics. Through the geographic detector and estimation of the soil carbon density model, the driving factors and intensity of carbon storage spatial distribution are revealed from 1990 to 2020. We conducted analyses on aboveground biomass, underground biomass, and soil carbon storage across three elevation levels (0–200 m, 200–500 m, 500–999 m) to reveal the quantitative distribution features of carbon storage. The study analysis finds that carbon storage indicates a sawtooth evolution during the study period. Carbon storage was dominant at elevation I (range is 0–200 m), slope I (range is 0–2°), and relief amplitude I (range is 0–30 m). Additionally, the carbon storage losses were severe at elevation II (range is 200–500 m), slope II (2–6°), and relief amplitude II (30–70 m). In contrast, the carbon storage losses at elevation III (500–999 m), slope III (6–15°), and relief amplitude III (70–186 m) were insignificant. The spatial pattern of carbon storage varies significantly under different topographic gradients from 1990 to 2020. The most critical driving factors influencing the spatial distribution pattern of carbon storage were land use and annual average temperature. Distance to urban centers and soil texture also moderately influence the distribution of carbon storage. As the topographic gradient increases, the dominant factors of carbon storage gradually change from annual mean temperature and the extent of land use to policy factors and other socio-economic factors. Therefore, this study emphasizes the importance of implementing policies that convert farmland to forests and wetlands and promote the green transformation of agriculture. |
doi_str_mv | 10.3390/land14010016 |
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Previous studies have used the fixed value of carbon density to evaluate the change characteristics of carbon storage but ignored the spatio-temporal heterogeneity of carbon storage at the block scale and the impact of policy factors. Thus, this paper takes Sanjiang Plain, Heilongjiang Province, China, as a study area, and the spatio-temporal variation of carbon storage at different topographic gradients was revealed using hot and cold spot analysis and zonal statistics. Through the geographic detector and estimation of the soil carbon density model, the driving factors and intensity of carbon storage spatial distribution are revealed from 1990 to 2020. We conducted analyses on aboveground biomass, underground biomass, and soil carbon storage across three elevation levels (0–200 m, 200–500 m, 500–999 m) to reveal the quantitative distribution features of carbon storage. The study analysis finds that carbon storage indicates a sawtooth evolution during the study period. Carbon storage was dominant at elevation I (range is 0–200 m), slope I (range is 0–2°), and relief amplitude I (range is 0–30 m). Additionally, the carbon storage losses were severe at elevation II (range is 200–500 m), slope II (2–6°), and relief amplitude II (30–70 m). In contrast, the carbon storage losses at elevation III (500–999 m), slope III (6–15°), and relief amplitude III (70–186 m) were insignificant. The spatial pattern of carbon storage varies significantly under different topographic gradients from 1990 to 2020. The most critical driving factors influencing the spatial distribution pattern of carbon storage were land use and annual average temperature. Distance to urban centers and soil texture also moderately influence the distribution of carbon storage. As the topographic gradient increases, the dominant factors of carbon storage gradually change from annual mean temperature and the extent of land use to policy factors and other socio-economic factors. Therefore, this study emphasizes the importance of implementing policies that convert farmland to forests and wetlands and promote the green transformation of agriculture.</description><identifier>ISSN: 2073-445X</identifier><identifier>EISSN: 2073-445X</identifier><identifier>DOI: 10.3390/land14010016</identifier><language>eng</language><publisher>Basel: MDPI AG</publisher><subject>Accuracy ; Agricultural land ; Altitude ; Amplitudes ; Biomass ; black soil area ; Carbon ; Carbon sequestration ; carbon storage ; Climate change ; Cold storage ; Density ; Distribution patterns ; driving factors ; Economic factors ; Ecosystems ; Elevation ; Forest management ; Geographical distribution ; Greenhouse gases ; Heterogeneity ; Land area ; Land use ; Methods ; Quantitative distribution ; Regional development ; Regional planning ; Regression analysis ; Socioeconomic factors ; Socioeconomics ; Soil analysis ; Soil density ; Soil properties ; Soil temperature ; Soil texture ; Spatial distribution ; spatio-temporal characteristics ; Statistical analysis ; Temperature ; Temporal variations ; terrain gradient ; Texture ; Underground storage ; Urban areas ; Urban environments</subject><ispartof>Land (Basel), 2025-01, Vol.14 (1), p.16</ispartof><rights>2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c1696-7e3c9f041f0b4a049f7cf62cb8bc1d485d407df09b32fe0dae7b9f3453cef42e3</cites><orcidid>0000-0003-4465-6792 ; 0009-0005-4490-0152 ; 0009-0004-7028-8852</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,860,2096,27901,27902</link.rule.ids></links><search><creatorcontrib>Gai, Zhaoxue</creatorcontrib><creatorcontrib>Zheng, Wenlu</creatorcontrib><creatorcontrib>Faye, Bonoua</creatorcontrib><creatorcontrib>Wang, Hongyan</creatorcontrib><creatorcontrib>Du, Guoming</creatorcontrib><title>Temporal and Spatial Characteristics and Influencing Factors of Carbon Storage in Black Soil Area Under Topographic Gradient</title><title>Land (Basel)</title><description>Exploring the characteristics and driving factors of carbon storage change in different terrain gradient variations can provide important insights for formulating the agricultural ecological protection policy for regional development. Previous studies have used the fixed value of carbon density to evaluate the change characteristics of carbon storage but ignored the spatio-temporal heterogeneity of carbon storage at the block scale and the impact of policy factors. Thus, this paper takes Sanjiang Plain, Heilongjiang Province, China, as a study area, and the spatio-temporal variation of carbon storage at different topographic gradients was revealed using hot and cold spot analysis and zonal statistics. Through the geographic detector and estimation of the soil carbon density model, the driving factors and intensity of carbon storage spatial distribution are revealed from 1990 to 2020. We conducted analyses on aboveground biomass, underground biomass, and soil carbon storage across three elevation levels (0–200 m, 200–500 m, 500–999 m) to reveal the quantitative distribution features of carbon storage. The study analysis finds that carbon storage indicates a sawtooth evolution during the study period. Carbon storage was dominant at elevation I (range is 0–200 m), slope I (range is 0–2°), and relief amplitude I (range is 0–30 m). Additionally, the carbon storage losses were severe at elevation II (range is 200–500 m), slope II (2–6°), and relief amplitude II (30–70 m). In contrast, the carbon storage losses at elevation III (500–999 m), slope III (6–15°), and relief amplitude III (70–186 m) were insignificant. The spatial pattern of carbon storage varies significantly under different topographic gradients from 1990 to 2020. The most critical driving factors influencing the spatial distribution pattern of carbon storage were land use and annual average temperature. Distance to urban centers and soil texture also moderately influence the distribution of carbon storage. As the topographic gradient increases, the dominant factors of carbon storage gradually change from annual mean temperature and the extent of land use to policy factors and other socio-economic factors. Therefore, this study emphasizes the importance of implementing policies that convert farmland to forests and wetlands and promote the green transformation of agriculture.</description><subject>Accuracy</subject><subject>Agricultural land</subject><subject>Altitude</subject><subject>Amplitudes</subject><subject>Biomass</subject><subject>black soil area</subject><subject>Carbon</subject><subject>Carbon sequestration</subject><subject>carbon storage</subject><subject>Climate change</subject><subject>Cold storage</subject><subject>Density</subject><subject>Distribution patterns</subject><subject>driving factors</subject><subject>Economic factors</subject><subject>Ecosystems</subject><subject>Elevation</subject><subject>Forest management</subject><subject>Geographical distribution</subject><subject>Greenhouse gases</subject><subject>Heterogeneity</subject><subject>Land area</subject><subject>Land use</subject><subject>Methods</subject><subject>Quantitative distribution</subject><subject>Regional development</subject><subject>Regional planning</subject><subject>Regression analysis</subject><subject>Socioeconomic factors</subject><subject>Socioeconomics</subject><subject>Soil analysis</subject><subject>Soil density</subject><subject>Soil properties</subject><subject>Soil temperature</subject><subject>Soil texture</subject><subject>Spatial distribution</subject><subject>spatio-temporal characteristics</subject><subject>Statistical analysis</subject><subject>Temperature</subject><subject>Temporal variations</subject><subject>terrain gradient</subject><subject>Texture</subject><subject>Underground storage</subject><subject>Urban areas</subject><subject>Urban environments</subject><issn>2073-445X</issn><issn>2073-445X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2025</creationdate><recordtype>article</recordtype><sourceid>BENPR</sourceid><sourceid>DOA</sourceid><recordid>eNpNUcFqHDEMHUILDWlu_QBDrt1GHtsz42O6NMlCoIfdQG9GY8sbbyf21J49FPrxcbOlRBc96UlPEmqaTxy-CKHhesLouAQOwLuz5ryFXqykVD_evcEfmstSDlBNczFIdd782dHznDJOrLaz7YxLqHj9hBntQjmUJdjyym2in44UbYh7dlvJlAtLnq0xjymybY1xTyxE9nVC-5NtU5jYTSZkj9FRZrs0p33G-SlYdpfRBYrLx-a9x6nQ5T9_0Tzeftut71cP3-8265uHleWd7lY9Cas9SO5hlAhS-976rrXjMFru5KCchN550KNoPYFD6kfthVTCkpctiYtmc9J1CQ9mzuEZ82-TMJjXRMp7g7keOpHxvaRBKdnrjkvV8qHnnIPsPPXgRmmr1tVJa87p15HKYg7pmGNd3wiutBJSANSqz6cqm1Mpmfz_qRzM33eZt-8SL3SxiBk</recordid><startdate>20250101</startdate><enddate>20250101</enddate><creator>Gai, Zhaoxue</creator><creator>Zheng, Wenlu</creator><creator>Faye, Bonoua</creator><creator>Wang, Hongyan</creator><creator>Du, Guoming</creator><general>MDPI AG</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SN</scope><scope>7ST</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>PATMY</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PYCSY</scope><scope>SOI</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0003-4465-6792</orcidid><orcidid>https://orcid.org/0009-0005-4490-0152</orcidid><orcidid>https://orcid.org/0009-0004-7028-8852</orcidid></search><sort><creationdate>20250101</creationdate><title>Temporal and Spatial Characteristics and Influencing Factors of Carbon Storage in Black Soil Area Under Topographic Gradient</title><author>Gai, Zhaoxue ; Zheng, Wenlu ; Faye, Bonoua ; Wang, Hongyan ; Du, Guoming</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c1696-7e3c9f041f0b4a049f7cf62cb8bc1d485d407df09b32fe0dae7b9f3453cef42e3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2025</creationdate><topic>Accuracy</topic><topic>Agricultural land</topic><topic>Altitude</topic><topic>Amplitudes</topic><topic>Biomass</topic><topic>black soil area</topic><topic>Carbon</topic><topic>Carbon sequestration</topic><topic>carbon storage</topic><topic>Climate change</topic><topic>Cold storage</topic><topic>Density</topic><topic>Distribution patterns</topic><topic>driving factors</topic><topic>Economic factors</topic><topic>Ecosystems</topic><topic>Elevation</topic><topic>Forest management</topic><topic>Geographical distribution</topic><topic>Greenhouse gases</topic><topic>Heterogeneity</topic><topic>Land area</topic><topic>Land use</topic><topic>Methods</topic><topic>Quantitative distribution</topic><topic>Regional development</topic><topic>Regional planning</topic><topic>Regression analysis</topic><topic>Socioeconomic factors</topic><topic>Socioeconomics</topic><topic>Soil analysis</topic><topic>Soil density</topic><topic>Soil properties</topic><topic>Soil temperature</topic><topic>Soil texture</topic><topic>Spatial distribution</topic><topic>spatio-temporal characteristics</topic><topic>Statistical analysis</topic><topic>Temperature</topic><topic>Temporal variations</topic><topic>terrain gradient</topic><topic>Texture</topic><topic>Underground storage</topic><topic>Urban areas</topic><topic>Urban environments</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Gai, Zhaoxue</creatorcontrib><creatorcontrib>Zheng, Wenlu</creatorcontrib><creatorcontrib>Faye, Bonoua</creatorcontrib><creatorcontrib>Wang, Hongyan</creatorcontrib><creatorcontrib>Du, Guoming</creatorcontrib><collection>CrossRef</collection><collection>Ecology Abstracts</collection><collection>Environment Abstracts</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>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>Environmental Science Database</collection><collection>Publicly Available Content 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>ProQuest Central China</collection><collection>Environmental Science Collection</collection><collection>Environment Abstracts</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>Land (Basel)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Gai, Zhaoxue</au><au>Zheng, Wenlu</au><au>Faye, Bonoua</au><au>Wang, Hongyan</au><au>Du, Guoming</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Temporal and Spatial Characteristics and Influencing Factors of Carbon Storage in Black Soil Area Under Topographic Gradient</atitle><jtitle>Land (Basel)</jtitle><date>2025-01-01</date><risdate>2025</risdate><volume>14</volume><issue>1</issue><spage>16</spage><pages>16-</pages><issn>2073-445X</issn><eissn>2073-445X</eissn><abstract>Exploring the characteristics and driving factors of carbon storage change in different terrain gradient variations can provide important insights for formulating the agricultural ecological protection policy for regional development. Previous studies have used the fixed value of carbon density to evaluate the change characteristics of carbon storage but ignored the spatio-temporal heterogeneity of carbon storage at the block scale and the impact of policy factors. Thus, this paper takes Sanjiang Plain, Heilongjiang Province, China, as a study area, and the spatio-temporal variation of carbon storage at different topographic gradients was revealed using hot and cold spot analysis and zonal statistics. Through the geographic detector and estimation of the soil carbon density model, the driving factors and intensity of carbon storage spatial distribution are revealed from 1990 to 2020. We conducted analyses on aboveground biomass, underground biomass, and soil carbon storage across three elevation levels (0–200 m, 200–500 m, 500–999 m) to reveal the quantitative distribution features of carbon storage. The study analysis finds that carbon storage indicates a sawtooth evolution during the study period. Carbon storage was dominant at elevation I (range is 0–200 m), slope I (range is 0–2°), and relief amplitude I (range is 0–30 m). Additionally, the carbon storage losses were severe at elevation II (range is 200–500 m), slope II (2–6°), and relief amplitude II (30–70 m). In contrast, the carbon storage losses at elevation III (500–999 m), slope III (6–15°), and relief amplitude III (70–186 m) were insignificant. The spatial pattern of carbon storage varies significantly under different topographic gradients from 1990 to 2020. The most critical driving factors influencing the spatial distribution pattern of carbon storage were land use and annual average temperature. Distance to urban centers and soil texture also moderately influence the distribution of carbon storage. As the topographic gradient increases, the dominant factors of carbon storage gradually change from annual mean temperature and the extent of land use to policy factors and other socio-economic factors. Therefore, this study emphasizes the importance of implementing policies that convert farmland to forests and wetlands and promote the green transformation of agriculture.</abstract><cop>Basel</cop><pub>MDPI AG</pub><doi>10.3390/land14010016</doi><orcidid>https://orcid.org/0000-0003-4465-6792</orcidid><orcidid>https://orcid.org/0009-0005-4490-0152</orcidid><orcidid>https://orcid.org/0009-0004-7028-8852</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Accuracy Agricultural land Altitude Amplitudes Biomass black soil area Carbon Carbon sequestration carbon storage Climate change Cold storage Density Distribution patterns driving factors Economic factors Ecosystems Elevation Forest management Geographical distribution Greenhouse gases Heterogeneity Land area Land use Methods Quantitative distribution Regional development Regional planning Regression analysis Socioeconomic factors Socioeconomics Soil analysis Soil density Soil properties Soil temperature Soil texture Spatial distribution spatio-temporal characteristics Statistical analysis Temperature Temporal variations terrain gradient Texture Underground storage Urban areas Urban environments |
title | Temporal and Spatial Characteristics and Influencing Factors of Carbon Storage in Black Soil Area Under Topographic Gradient |
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