Quantifying Spatiotemporal Characteristics and Identifying Influential Factors of Ecosystem Fragmentation in Karst Landscapes: A Comprehensive Analytical Framework
Guanling-Zhenfeng County, a microcosm of the ecologically fragile karst area in southwest China, experiences rapid population growth and urban expansion which intensifies land use transformation and ecological landscape fragmentation. Exploring the spatiotemporal characteristics of landscape fragmen...
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| Format: | Article |
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MDPI AG
2024-02-01
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| Series: | Land |
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| Online Access: | https://www.mdpi.com/2073-445X/13/3/278 |
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| author | Xiaopiao Wu Zhongfa Zhou Meng Zhu Jiale Wang Rongping Liu Jiajia Zheng Jiaxue Wan |
| author_facet | Xiaopiao Wu Zhongfa Zhou Meng Zhu Jiale Wang Rongping Liu Jiajia Zheng Jiaxue Wan |
| author_sort | Xiaopiao Wu |
| collection | DOAJ |
| description | Guanling-Zhenfeng County, a microcosm of the ecologically fragile karst area in southwest China, experiences rapid population growth and urban expansion which intensifies land use transformation and ecological landscape fragmentation. Exploring the spatiotemporal characteristics of landscape fragmentation and its causes in Guanling-Zhenfeng County is of great significance in maintaining the stability of the ecosystem and ecological protection in karst areas. In this study, a comprehensive landscape fragmentation index (FI), geographic probe, multi-scale geographically weighted regression (MGWR), and PLUS model were used to quantitatively explore the spatiotemporal characteristic heterogeneity, causes, and future scenario projections of landscape fragmentation in Guanling-Zhenfeng County from 2000 to 2020. The results showed that: (1) the distribution of each landscape index was characterized by obvious spatial differentiation. Among them, the spatial distribution trends of patch density (PD) and largest patch index (LPI) were opposite and the distribution trends of Shannon diversity index (SHDI) and Shannon evenness index (SHEI) were similar. There were fewer heterogeneous patches in the study area from 2000 to 2020, and the landscape shape was more regular and less fragmented. (2) The overall landscape fragmentation in Guanling-Zhenfeng County from 2000 to 2020 was dominated by moderate fragmentation, with the smallest percentage of extreme fragmentation, and heavy fragmentation was mainly distributed in the north-central part of the study area. (3) Natural and social factors jointly affect the landscape fragmentation in Guanling-Zhenfeng County, and there is a significant interactive enhancement effect among the factors, with population density being the most important influence factor. In addition, the effects of the factors on landscape fragmentation showed significant spatial non-stationarity. (4) The characteristics of landscape fragmentation changes in Guanling-Zhenfeng County under different scenarios varied significantly, with the largest percentage of increase in heavy landscape fragmentation under the business-as-usual scenario (BAU), the next under the land use planning scenario (LUP), and the smallest under the ecological protection scenario (ESP). |
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| institution | Directory Open Access Journal |
| issn | 2073-445X |
| language | English |
| last_indexed | 2024-04-24T18:05:38Z |
| publishDate | 2024-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Land |
| spelling | doaj.art-1cfe9b0b24a94350bef427a5fd4d7b952024-03-27T13:50:32ZengMDPI AGLand2073-445X2024-02-0113327810.3390/land13030278Quantifying Spatiotemporal Characteristics and Identifying Influential Factors of Ecosystem Fragmentation in Karst Landscapes: A Comprehensive Analytical FrameworkXiaopiao Wu0Zhongfa Zhou1Meng Zhu2Jiale Wang3Rongping Liu4Jiajia Zheng5Jiaxue Wan6School of Geography and Environmental Science/School of Karst Science, Guizhou Normal University, Guiyang 550001, ChinaSchool of Geography and Environmental Science/School of Karst Science, Guizhou Normal University, Guiyang 550001, ChinaSchool of Geography and Environmental Science/School of Karst Science, Guizhou Normal University, Guiyang 550001, ChinaState Key Laboratory Incubation Base for Karst Mountain Ecology Environment of Guizhou Province, Guiyang 550025, ChinaSchool of Geography and Environmental Science/School of Karst Science, Guizhou Normal University, Guiyang 550001, ChinaSchool of Geography and Environmental Science/School of Karst Science, Guizhou Normal University, Guiyang 550001, ChinaState Key Laboratory Incubation Base for Karst Mountain Ecology Environment of Guizhou Province, Guiyang 550025, ChinaGuanling-Zhenfeng County, a microcosm of the ecologically fragile karst area in southwest China, experiences rapid population growth and urban expansion which intensifies land use transformation and ecological landscape fragmentation. Exploring the spatiotemporal characteristics of landscape fragmentation and its causes in Guanling-Zhenfeng County is of great significance in maintaining the stability of the ecosystem and ecological protection in karst areas. In this study, a comprehensive landscape fragmentation index (FI), geographic probe, multi-scale geographically weighted regression (MGWR), and PLUS model were used to quantitatively explore the spatiotemporal characteristic heterogeneity, causes, and future scenario projections of landscape fragmentation in Guanling-Zhenfeng County from 2000 to 2020. The results showed that: (1) the distribution of each landscape index was characterized by obvious spatial differentiation. Among them, the spatial distribution trends of patch density (PD) and largest patch index (LPI) were opposite and the distribution trends of Shannon diversity index (SHDI) and Shannon evenness index (SHEI) were similar. There were fewer heterogeneous patches in the study area from 2000 to 2020, and the landscape shape was more regular and less fragmented. (2) The overall landscape fragmentation in Guanling-Zhenfeng County from 2000 to 2020 was dominated by moderate fragmentation, with the smallest percentage of extreme fragmentation, and heavy fragmentation was mainly distributed in the north-central part of the study area. (3) Natural and social factors jointly affect the landscape fragmentation in Guanling-Zhenfeng County, and there is a significant interactive enhancement effect among the factors, with population density being the most important influence factor. In addition, the effects of the factors on landscape fragmentation showed significant spatial non-stationarity. (4) The characteristics of landscape fragmentation changes in Guanling-Zhenfeng County under different scenarios varied significantly, with the largest percentage of increase in heavy landscape fragmentation under the business-as-usual scenario (BAU), the next under the land use planning scenario (LUP), and the smallest under the ecological protection scenario (ESP).https://www.mdpi.com/2073-445X/13/3/278ecologically fragile areasgeographically weighted regression model (MGWR)landscape fragmentationPLUS modelspatiotemporal heterogeneity |
| spellingShingle | Xiaopiao Wu Zhongfa Zhou Meng Zhu Jiale Wang Rongping Liu Jiajia Zheng Jiaxue Wan Quantifying Spatiotemporal Characteristics and Identifying Influential Factors of Ecosystem Fragmentation in Karst Landscapes: A Comprehensive Analytical Framework Land ecologically fragile areas geographically weighted regression model (MGWR) landscape fragmentation PLUS model spatiotemporal heterogeneity |
| title | Quantifying Spatiotemporal Characteristics and Identifying Influential Factors of Ecosystem Fragmentation in Karst Landscapes: A Comprehensive Analytical Framework |
| title_full | Quantifying Spatiotemporal Characteristics and Identifying Influential Factors of Ecosystem Fragmentation in Karst Landscapes: A Comprehensive Analytical Framework |
| title_fullStr | Quantifying Spatiotemporal Characteristics and Identifying Influential Factors of Ecosystem Fragmentation in Karst Landscapes: A Comprehensive Analytical Framework |
| title_full_unstemmed | Quantifying Spatiotemporal Characteristics and Identifying Influential Factors of Ecosystem Fragmentation in Karst Landscapes: A Comprehensive Analytical Framework |
| title_short | Quantifying Spatiotemporal Characteristics and Identifying Influential Factors of Ecosystem Fragmentation in Karst Landscapes: A Comprehensive Analytical Framework |
| title_sort | quantifying spatiotemporal characteristics and identifying influential factors of ecosystem fragmentation in karst landscapes a comprehensive analytical framework |
| topic | ecologically fragile areas geographically weighted regression model (MGWR) landscape fragmentation PLUS model spatiotemporal heterogeneity |
| url | https://www.mdpi.com/2073-445X/13/3/278 |
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