The seeds of ecological recovery in urbanization – Spatiotemporal evolution of ecological resiliency of Dianchi Lake Basin, China

Li, Donghui; Yang, Jia; Hu, Tao; Wang, Guifang; Cushman, Samuel A.; Wang, Xinyu; Kursinszki, L.; Su, Rui; Li, Yuan; Li, B.; Wu, Yanjun; Tian, Bin

doi:10.1016/j.ecolind.2023.110431

Cited by 5 publications

(4 citation statements)

References 67 publications

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“…The low and low-medium ecological resilience areas in the Wuling Mountains area are shifted to the east, and the medium-high and high ecological resilience areas are shifted to the west and south. However, the very low ecological resilience and very high ecological resilience areas in the Dianchi Basin moved to the northeast, the light ecological resilience areas to the northwest, and the high ecological resilience areas to the southeast [31].…”

Section: Discussionmentioning

confidence: 98%

“…This research introduces novel methods for assessing ecological resilience in the Wuling Mountains and similar ecologically vulnerable regions, offering useful insights for ecological conservation and rehabilitation. Most of the existing findings measure ecological resilience by constructing a comprehensive indicator system [31,32,47,48,56,57], which requires more data and is less operational for ecological resilience studies at long time scales. In this paper, NDVI is used as a proxy for ecological resilience, and the ecological resilience index is measured using NDVI data from 2000 to 2020, which enriches the case of ecological resilience research in ecologically fragile areas and expands the scope of ecological resilience proxy selection.…”

Section: Discussionmentioning

confidence: 99%

“…The NDVI is highly sensitive to vegetation cover and dynamics and can capture subtle changes in vegetation conditions over time, reflecting changes in the regional ecological environment. NDVI has been applied to identify ecologically sensitive areas [29], to track ecosystem dynamics and environmental management [30], or as one of the indicators to evaluate ecological resilience [31,32]. Previous research often assessed ecological resilience by creating a whole assessment index system.…”

Section: Introductionmentioning

confidence: 99%

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Spatio-Temporal Evolution of Ecological Resilience in Ecologically Fragile Areas and Its Influencing Factors: A Case Study of the Wuling Mountains Area, China

Wu,

Yang,

Zuo

et al. 2024

Sustainability

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The ecological environment of the Wuling Mountains region has been impacted by climate change and economic development, necessitating immediate reinforcement of ecological protection and restoration measures. The study utilized the normalized vegetation index (NDVI) as a proxy for ecological resilience. NDVI data from 2000 to 2020 were employed to compute the ecological resilience index of the Wuling Mountains area and to examine its spatial and temporal evolution as well as the factors influencing it. The findings indicate that: (1) The ecological resilience index increased in the Wuling Mountains area and Guizhou, Chongqing, and Hunan sub-areas but decreased in the Hubei sub-area. (2) The ecological resilience varies significantly in the Wuling Mountains area and the Guizhou, Hubei, and Hunan sub-regions, whereas it varies less in the Chongqing sub-region. (3) The primary elements influencing the ecological resilience capability of the Wuling Mountains area and its four sub-areas are climate conditions and socio-economic factors, respectively. The study can offer a scientific foundation for ecological conservation and restoration efforts in the Wuling Mountains area, as well as serve as a benchmark for measuring ecological resilience in other environmentally vulnerable regions.

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Section: Discussionmentioning

confidence: 98%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Spatio-Temporal Evolution of Ecological Resilience in Ecologically Fragile Areas and Its Influencing Factors: A Case Study of the Wuling Mountains Area, China

Wu,

Yang,

Zuo

et al. 2024

Sustainability

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“…This study employs the entropy method [76,77] to systematically evaluate the UGHQD levels of China's five major urban agglomerations, the Yangtze River Delta (YRD), the Pearl River Delta (PRD), Beijing-Tianjin-Hebei (BTH), the Middle Reaches of the Yangtze River (MYR), and Chengdu-Chongqing (CC), from 2003 to 2020. The study performs meanization processing on the urban sample data and, based on this, depicts the evolutionary trends of the UGHQD levels for these urban agglomerations, as shown in Figure 2.…”

Section: Level Measurementmentioning

confidence: 99%

Unveiling the Spatio-Temporal Evolution and Key Drivers for Urban Green High-Quality Development: A Comparative Analysis of China’s Five Major Urban Agglomerations

Yu,

Huang,

Jia

et al. 2023

Land

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Faced with the dual challenges of ecological degradation and economic deceleration, promoting urban green high-quality development (UGHQD) is pivotal for achieving economic transformation, ecological restoration, and regional sustainable development. While the existing literature has delved into the theoretical dimensions of UGHQD, there remains a notable dearth of empirical studies that quantitatively assess its developmental levels, spatio-temporal evolution, and driving factors. This study examines 107 cities of China’s five major urban agglomerations from 2003 to 2020, constructing a comprehensive evaluation indicator system for UGHQD. By employing methodologies, including the Dagum Gini coefficient, Kernel density estimation, Markov chain, and geographical detector, this study extensively assesses the spatial difference, dynamic evolution, and underlying driving forces of UGHQD in these urban agglomerations. The findings indicate: (1) The UGHQD level of the five major urban agglomerations has witnessed a consistent year-over-year growth trend, with coastal agglomerations like the Pearl River Delta (PRD) and Yangtze River Delta (YRD) outperforming others. (2) Pronounced regional differences exist in UGHQD levels across the urban agglomerations, with inter-regional differences primarily contributing to these differences. (3) The dynamic evolution of UGHQD distribution generally transitions from a centralized to a decentralized pattern, with a marked “club convergence” characteristic hindering cross-type leaps. (4) While a range of factors drive UGHQD in these agglomerations, technological innovation stands out as the principal factor inducing spatial differentiation. The comprehensive analysis and findings presented in this research not only contribute to academic knowledge but also hold practical implications for policymakers and practitioners striving for environmentally conscious land use planning and urban management.

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Research on the coupling coordination of land use and eco-resilience based on entropy weight method: a case study on Dianchi Lake Basin

Deng,

Xie,

Jiang

et al. 2024

Landscape Ecol Eng

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The seeds of ecological recovery in urbanization – Spatiotemporal evolution of ecological resiliency of Dianchi Lake Basin, China

Cited by 5 publications

References 67 publications

Spatio-Temporal Evolution of Ecological Resilience in Ecologically Fragile Areas and Its Influencing Factors: A Case Study of the Wuling Mountains Area, China

Spatio-Temporal Evolution of Ecological Resilience in Ecologically Fragile Areas and Its Influencing Factors: A Case Study of the Wuling Mountains Area, China

Unveiling the Spatio-Temporal Evolution and Key Drivers for Urban Green High-Quality Development: A Comparative Analysis of China’s Five Major Urban Agglomerations

Research on the coupling coordination of land use and eco-resilience based on entropy weight method: a case study on Dianchi Lake Basin

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