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Apportioning Human-Induced and Climate-Induced Land Degradation: A Case of the Greater Sekhukhune District Municipality
Land degradation (LD) is a global issue that affects sustainability and livelihoods of approximately 1.5 billion people, especially in arid/semi-arid regions. Hence, identifying and assessing LD and its driving forces (natural and anthropogenic) is important in order to design and adopt appropriate...
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Published in: | Applied sciences 2023-03, Vol.13 (6), p.3644 |
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description | Land degradation (LD) is a global issue that affects sustainability and livelihoods of approximately 1.5 billion people, especially in arid/semi-arid regions. Hence, identifying and assessing LD and its driving forces (natural and anthropogenic) is important in order to design and adopt appropriate sustainable land management interventions. Therefore, using vegetation as a proxy for LD, this study aimed to distinguish anthropogenic from rainfall-driven LD in the Greater Sekhukhune District Municipality from 1990 to 2019. It is widely established that rainfall highly correlates with vegetation productivity. A linear regression was performed between the Normalized Difference Vegetation Index (NDVI) and rainfall. The human-induced LD was then distinguished from that of rainfall using the spatial residual trend (RESTREND) method and the Mann–Kendall (MK) trend. RESTREND results showed that 11.59% of the district was degraded due to human activities such as overgrazing and injudicious rangeland management. While about 41.41% was degraded due to seasonal rainfall variability and an increasing frequency of droughts. Climate variability affected vegetation cover and contributed to different forms of soil erosion and gully formation. These findings provide relevant spatial information on rainfall or human-induced LD, which is useful for policy formulation and the design of LD mitigation measures in semi-arid regions. |
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Hence, identifying and assessing LD and its driving forces (natural and anthropogenic) is important in order to design and adopt appropriate sustainable land management interventions. Therefore, using vegetation as a proxy for LD, this study aimed to distinguish anthropogenic from rainfall-driven LD in the Greater Sekhukhune District Municipality from 1990 to 2019. It is widely established that rainfall highly correlates with vegetation productivity. A linear regression was performed between the Normalized Difference Vegetation Index (NDVI) and rainfall. The human-induced LD was then distinguished from that of rainfall using the spatial residual trend (RESTREND) method and the Mann–Kendall (MK) trend. RESTREND results showed that 11.59% of the district was degraded due to human activities such as overgrazing and injudicious rangeland management. While about 41.41% was degraded due to seasonal rainfall variability and an increasing frequency of droughts. Climate variability affected vegetation cover and contributed to different forms of soil erosion and gully formation. These findings provide relevant spatial information on rainfall or human-induced LD, which is useful for policy formulation and the design of LD mitigation measures in semi-arid regions.</description><identifier>ISSN: 2076-3417</identifier><identifier>EISSN: 2076-3417</identifier><identifier>DOI: 10.3390/app13063644</identifier><language>eng</language><publisher>Basel: MDPI AG</publisher><subject>Agriculture ; Anthropogenic factors ; Arid regions ; Arid zones ; Climate ; Climate change ; Climate variability ; Drought ; Environmental economics ; Gullies ; Gully erosion ; Human influences ; Land degradation ; Land management ; land use and land cover change ; Land use planning ; Mann–Kendall trend ; Mitigation ; Monitoring systems ; NDVI ; Normalized difference vegetative index ; Precipitation ; Precipitation variability ; Productivity ; Rain ; Rain and rainfall ; Rainfall ; Range management ; Rangelands ; Regions ; residual trend (RESTREND) ; Satellites ; Semi arid areas ; Semiarid lands ; Soil erosion ; Spatial data ; Sustainability management ; Trends ; Vegetation ; Vegetation cover</subject><ispartof>Applied sciences, 2023-03, Vol.13 (6), p.3644</ispartof><rights>COPYRIGHT 2023 MDPI AG</rights><rights>2023 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-c361t-373b410dfa20e2bf5e6e59b5859d4da5bfdff95891627033496fb16761d218173</cites><orcidid>0000-0002-9917-9754 ; 0000-0002-1737-7213</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/2791592485/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2791592485?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>314,780,784,25753,27924,27925,37012,44590,74998</link.rule.ids></links><search><creatorcontrib>Kgaphola, Motsoko Juniet</creatorcontrib><creatorcontrib>Ramoelo, Abel</creatorcontrib><creatorcontrib>Odindi, John</creatorcontrib><creatorcontrib>Mwenge Kahinda, Jean-Marc</creatorcontrib><creatorcontrib>Seetal, Ashwin</creatorcontrib><title>Apportioning Human-Induced and Climate-Induced Land Degradation: A Case of the Greater Sekhukhune District Municipality</title><title>Applied sciences</title><description>Land degradation (LD) is a global issue that affects sustainability and livelihoods of approximately 1.5 billion people, especially in arid/semi-arid regions. Hence, identifying and assessing LD and its driving forces (natural and anthropogenic) is important in order to design and adopt appropriate sustainable land management interventions. Therefore, using vegetation as a proxy for LD, this study aimed to distinguish anthropogenic from rainfall-driven LD in the Greater Sekhukhune District Municipality from 1990 to 2019. It is widely established that rainfall highly correlates with vegetation productivity. A linear regression was performed between the Normalized Difference Vegetation Index (NDVI) and rainfall. The human-induced LD was then distinguished from that of rainfall using the spatial residual trend (RESTREND) method and the Mann–Kendall (MK) trend. RESTREND results showed that 11.59% of the district was degraded due to human activities such as overgrazing and injudicious rangeland management. While about 41.41% was degraded due to seasonal rainfall variability and an increasing frequency of droughts. Climate variability affected vegetation cover and contributed to different forms of soil erosion and gully formation. These findings provide relevant spatial information on rainfall or human-induced LD, which is useful for policy formulation and the design of LD mitigation measures in semi-arid regions.</description><subject>Agriculture</subject><subject>Anthropogenic factors</subject><subject>Arid regions</subject><subject>Arid zones</subject><subject>Climate</subject><subject>Climate change</subject><subject>Climate variability</subject><subject>Drought</subject><subject>Environmental economics</subject><subject>Gullies</subject><subject>Gully erosion</subject><subject>Human influences</subject><subject>Land degradation</subject><subject>Land management</subject><subject>land use and land cover change</subject><subject>Land use planning</subject><subject>Mann–Kendall trend</subject><subject>Mitigation</subject><subject>Monitoring systems</subject><subject>NDVI</subject><subject>Normalized difference vegetative index</subject><subject>Precipitation</subject><subject>Precipitation variability</subject><subject>Productivity</subject><subject>Rain</subject><subject>Rain and rainfall</subject><subject>Rainfall</subject><subject>Range management</subject><subject>Rangelands</subject><subject>Regions</subject><subject>residual trend (RESTREND)</subject><subject>Satellites</subject><subject>Semi arid areas</subject><subject>Semiarid lands</subject><subject>Soil erosion</subject><subject>Spatial data</subject><subject>Sustainability management</subject><subject>Trends</subject><subject>Vegetation</subject><subject>Vegetation cover</subject><issn>2076-3417</issn><issn>2076-3417</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNpNUU1rG0EMXUoLDUlO_QMDPZZN5_ujN-O0icGlh7bnRbujcca1Z7azu4T8-47rECIJJB7vPSTUNB8YvRHC0c8wjkxQLbSUb5oLTo1uhWTm7av5fXM9TXtawzFhGb1oHlfjmMscc4ppR-6XI6R2k_wyoCeQPFkf4hFmfMG2J_AWdwU8nFRfyIqsYUKSA5kfkNwVrPRCfuKfh6VWQnIbp7nEYSbflxSHOMIhzk9XzbsAhwmvn_tl8_vb11_r-3b7426zXm3bQWg2t8KIXjLqA3CKvA8KNSrXK6uclx5UH3wITlnHNDdUCOl06Jk2mnnOLDPistmcfX2GfTeWek156jLE7j-Qy66Dev5wwK6nhnsKylrNpJHSoqWm1xyACgzIq9fHs9dY8t8Fp7nb56Wkun7HjWPKcWlVZd2cWTuopjGFPBcYano8xiEnDLHiK6OYs45rWQWfzoKh5GkqGF7WZLQ7fbZ79VnxDzs6lIE</recordid><startdate>20230301</startdate><enddate>20230301</enddate><creator>Kgaphola, Motsoko Juniet</creator><creator>Ramoelo, Abel</creator><creator>Odindi, John</creator><creator>Mwenge Kahinda, Jean-Marc</creator><creator>Seetal, Ashwin</creator><general>MDPI AG</general><scope>AAYXX</scope><scope>CITATION</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0002-9917-9754</orcidid><orcidid>https://orcid.org/0000-0002-1737-7213</orcidid></search><sort><creationdate>20230301</creationdate><title>Apportioning Human-Induced and Climate-Induced Land Degradation: A Case of the Greater Sekhukhune District Municipality</title><author>Kgaphola, Motsoko Juniet ; Ramoelo, Abel ; Odindi, John ; Mwenge Kahinda, Jean-Marc ; Seetal, Ashwin</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c361t-373b410dfa20e2bf5e6e59b5859d4da5bfdff95891627033496fb16761d218173</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Agriculture</topic><topic>Anthropogenic factors</topic><topic>Arid regions</topic><topic>Arid zones</topic><topic>Climate</topic><topic>Climate change</topic><topic>Climate variability</topic><topic>Drought</topic><topic>Environmental economics</topic><topic>Gullies</topic><topic>Gully erosion</topic><topic>Human influences</topic><topic>Land degradation</topic><topic>Land management</topic><topic>land use and land cover change</topic><topic>Land use planning</topic><topic>Mann–Kendall trend</topic><topic>Mitigation</topic><topic>Monitoring systems</topic><topic>NDVI</topic><topic>Normalized difference vegetative index</topic><topic>Precipitation</topic><topic>Precipitation variability</topic><topic>Productivity</topic><topic>Rain</topic><topic>Rain and rainfall</topic><topic>Rainfall</topic><topic>Range management</topic><topic>Rangelands</topic><topic>Regions</topic><topic>residual trend (RESTREND)</topic><topic>Satellites</topic><topic>Semi arid areas</topic><topic>Semiarid lands</topic><topic>Soil erosion</topic><topic>Spatial data</topic><topic>Sustainability management</topic><topic>Trends</topic><topic>Vegetation</topic><topic>Vegetation cover</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Kgaphola, Motsoko Juniet</creatorcontrib><creatorcontrib>Ramoelo, Abel</creatorcontrib><creatorcontrib>Odindi, John</creatorcontrib><creatorcontrib>Mwenge Kahinda, Jean-Marc</creatorcontrib><creatorcontrib>Seetal, Ashwin</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>ProQuest Central Essentials</collection><collection>AUTh Library subscriptions: ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>Publicly Available Content Database (Proquest) (PQ_SDU_P3)</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>Directory of Open Access Journals(OpenAccess)</collection><jtitle>Applied sciences</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Kgaphola, Motsoko Juniet</au><au>Ramoelo, Abel</au><au>Odindi, John</au><au>Mwenge Kahinda, Jean-Marc</au><au>Seetal, Ashwin</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Apportioning Human-Induced and Climate-Induced Land Degradation: A Case of the Greater Sekhukhune District Municipality</atitle><jtitle>Applied sciences</jtitle><date>2023-03-01</date><risdate>2023</risdate><volume>13</volume><issue>6</issue><spage>3644</spage><pages>3644-</pages><issn>2076-3417</issn><eissn>2076-3417</eissn><abstract>Land degradation (LD) is a global issue that affects sustainability and livelihoods of approximately 1.5 billion people, especially in arid/semi-arid regions. Hence, identifying and assessing LD and its driving forces (natural and anthropogenic) is important in order to design and adopt appropriate sustainable land management interventions. Therefore, using vegetation as a proxy for LD, this study aimed to distinguish anthropogenic from rainfall-driven LD in the Greater Sekhukhune District Municipality from 1990 to 2019. It is widely established that rainfall highly correlates with vegetation productivity. A linear regression was performed between the Normalized Difference Vegetation Index (NDVI) and rainfall. The human-induced LD was then distinguished from that of rainfall using the spatial residual trend (RESTREND) method and the Mann–Kendall (MK) trend. RESTREND results showed that 11.59% of the district was degraded due to human activities such as overgrazing and injudicious rangeland management. While about 41.41% was degraded due to seasonal rainfall variability and an increasing frequency of droughts. 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subjects | Agriculture Anthropogenic factors Arid regions Arid zones Climate Climate change Climate variability Drought Environmental economics Gullies Gully erosion Human influences Land degradation Land management land use and land cover change Land use planning Mann–Kendall trend Mitigation Monitoring systems NDVI Normalized difference vegetative index Precipitation Precipitation variability Productivity Rain Rain and rainfall Rainfall Range management Rangelands Regions residual trend (RESTREND) Satellites Semi arid areas Semiarid lands Soil erosion Spatial data Sustainability management Trends Vegetation Vegetation cover |
title | Apportioning Human-Induced and Climate-Induced Land Degradation: A Case of the Greater Sekhukhune District Municipality |
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