Nonlinear Interactions and Dynamic Analysis of Ecosystem Resilience and Human Activities in China’s Potential Urban Agglomerations
Understanding the nonlinear relationship between human activity intensity (HAI) and ecosystem resilience (ER) is crucial for sustainability, yet underdeveloped areas are often overlooked. This study examines the Xuzhou Urban Agglomeration (XZUA) from 2012 to 2022, creating a framework to assess both...
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2025-06-01
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| author | Xinyu Wang Shidong Ge Yaqiong Xu László Kollányi Tian Bai |
| author_facet | Xinyu Wang Shidong Ge Yaqiong Xu László Kollányi Tian Bai |
| author_sort | Xinyu Wang |
| collection | DOAJ |
| description | Understanding the nonlinear relationship between human activity intensity (HAI) and ecosystem resilience (ER) is crucial for sustainability, yet underdeveloped areas are often overlooked. This study examines the Xuzhou Urban Agglomeration (XZUA) from 2012 to 2022, creating a framework to assess both ER and HAI. Both frameworks utilize multi-source datasets, such as remote sensing, statistical yearbooks, and geospatial data. The ER framework uniquely combines dynamic and static indicators, while the HAI framework differentiates explicit and implicit human activity dimensions. We used spatial analysis, the Optimal Parameter Geodetector (OPGD), and Multi-Scale Geographically Weighted Regression (MGWR) to examine the nonlinear spatiotemporal interaction between HAI and ER. Results show the following: (1) ER exhibited a “shock-recovery” pattern with a net decline of 3.202%, while HAI followed a nonlinear “rise-fall” trend with a net decrease of 0.800%. (2) Spatial mismatches between HAI and ER intensified over time. (3) The negative correlation in high-HAI regions remained stable, whereas neighboring low-HAI areas deteriorated, indicating a spillover effect. (4) OPGD identified the change in HAI (Sen’s slope) as the primary driver of ER change (q = 0.512), with the strongest interaction observed between HAI Sen’s slope and precipitation (q = 0.802). (5) Compared to HAI intensity (mean), its temporal variation had a more spatially stable influence on ER. These findings offer insights for ecological management and sustainable planning in underdeveloped regions, highlighting the need for targeted HAI and ER interventions. |
| format | Article |
| id | doaj-art-4e2f0e515fee4e20a3f2e0ee882d21a1 |
| institution | Kabale University |
| issn | 2072-4292 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | MDPI AG |
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| series | Remote Sensing |
| spelling | doaj-art-4e2f0e515fee4e20a3f2e0ee882d21a12025-08-20T03:46:50ZengMDPI AGRemote Sensing2072-42922025-06-011711195510.3390/rs17111955Nonlinear Interactions and Dynamic Analysis of Ecosystem Resilience and Human Activities in China’s Potential Urban AgglomerationsXinyu Wang0Shidong Ge1Yaqiong Xu2László Kollányi3Tian Bai4College of Landscape and Horticulture, Yunnan Agricultural University, Kunming 650201, ChinaCollege of Landscape Architecture and Art, Henan Agricultural University, Zhengzhou 450002, ChinaCollege of Environmental Science and Forestry, The State University of New York, New York, NY 13210, USAInstitute of Landscape Architecture, Urban Planning and Garden Art, Hungarian University of Agriculture and Life Sciences, 1118 Budapest, HungaryCollege of Landscape and Horticulture, Yunnan Agricultural University, Kunming 650201, ChinaUnderstanding the nonlinear relationship between human activity intensity (HAI) and ecosystem resilience (ER) is crucial for sustainability, yet underdeveloped areas are often overlooked. This study examines the Xuzhou Urban Agglomeration (XZUA) from 2012 to 2022, creating a framework to assess both ER and HAI. Both frameworks utilize multi-source datasets, such as remote sensing, statistical yearbooks, and geospatial data. The ER framework uniquely combines dynamic and static indicators, while the HAI framework differentiates explicit and implicit human activity dimensions. We used spatial analysis, the Optimal Parameter Geodetector (OPGD), and Multi-Scale Geographically Weighted Regression (MGWR) to examine the nonlinear spatiotemporal interaction between HAI and ER. Results show the following: (1) ER exhibited a “shock-recovery” pattern with a net decline of 3.202%, while HAI followed a nonlinear “rise-fall” trend with a net decrease of 0.800%. (2) Spatial mismatches between HAI and ER intensified over time. (3) The negative correlation in high-HAI regions remained stable, whereas neighboring low-HAI areas deteriorated, indicating a spillover effect. (4) OPGD identified the change in HAI (Sen’s slope) as the primary driver of ER change (q = 0.512), with the strongest interaction observed between HAI Sen’s slope and precipitation (q = 0.802). (5) Compared to HAI intensity (mean), its temporal variation had a more spatially stable influence on ER. These findings offer insights for ecological management and sustainable planning in underdeveloped regions, highlighting the need for targeted HAI and ER interventions.https://www.mdpi.com/2072-4292/17/11/1955ecosystem resiliencehuman activity intensityOPGDMGWRspatiotemporal analysisXuzhou Urban Agglomeration |
| spellingShingle | Xinyu Wang Shidong Ge Yaqiong Xu László Kollányi Tian Bai Nonlinear Interactions and Dynamic Analysis of Ecosystem Resilience and Human Activities in China’s Potential Urban Agglomerations Remote Sensing ecosystem resilience human activity intensity OPGD MGWR spatiotemporal analysis Xuzhou Urban Agglomeration |
| title | Nonlinear Interactions and Dynamic Analysis of Ecosystem Resilience and Human Activities in China’s Potential Urban Agglomerations |
| title_full | Nonlinear Interactions and Dynamic Analysis of Ecosystem Resilience and Human Activities in China’s Potential Urban Agglomerations |
| title_fullStr | Nonlinear Interactions and Dynamic Analysis of Ecosystem Resilience and Human Activities in China’s Potential Urban Agglomerations |
| title_full_unstemmed | Nonlinear Interactions and Dynamic Analysis of Ecosystem Resilience and Human Activities in China’s Potential Urban Agglomerations |
| title_short | Nonlinear Interactions and Dynamic Analysis of Ecosystem Resilience and Human Activities in China’s Potential Urban Agglomerations |
| title_sort | nonlinear interactions and dynamic analysis of ecosystem resilience and human activities in china s potential urban agglomerations |
| topic | ecosystem resilience human activity intensity OPGD MGWR spatiotemporal analysis Xuzhou Urban Agglomeration |
| url | https://www.mdpi.com/2072-4292/17/11/1955 |
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