scholarly journals Evaluation of wetland ecosystem services in green core of Changzhutan urban agglomeration, Hunan

2021 ◽  
Vol 859 (1) ◽  
pp. 012111
Author(s):  
Jia Luo ◽  
Xiaoling Zhou ◽  
Zhihao Zhang ◽  
Yuxin Tian ◽  
Xian Tang
2017 ◽  
Vol 53 (4) ◽  
pp. 3197-3223 ◽  
Author(s):  
Christina P. Wong ◽  
Bo Jiang ◽  
Theodore J. Bohn ◽  
Kai N. Lee ◽  
Dennis P. Lettenmaier ◽  
...  

2019 ◽  
Vol 11 (22) ◽  
pp. 6416 ◽  
Author(s):  
Ouyang ◽  
Wang ◽  
Zhu

Coordinating ecosystem service supply and demand equilibrium and utilizing machine learning to dynamically construct an ecological security pattern (ESP) can help better understand the impact of urban development on ecological processes, which can be used as a theoretical reference in coupling economic growth and environmental protection. Here, the ESP of the Changsha–Zhuzhou–Xiangtan urban agglomeration was constructed, which made use of the Bayesian network model to dynamically identify the ecological sources. The ecological corridor and ecological strategy points were identified using the minimum cumulative resistance model and circuit theory. The ESP was constructed by combining seven ecological sources, “two horizontal and three vertical” ecological corridors, and 37 ecological strategy points. Our results found spatial decoupling between the supply and demand of ecosystem services (ES) and the degradation in areas with high demand for ES. The ecological sources and ecological corridors of the urban agglomeration were mainly situated in forestlands and water areas. The terrestrial ecological corridor was distributed along the outer periphery of the urban agglomeration, while the aquatic ecological corridor ran from north to south throughout the entire region. The ecological strategic points were mainly concentrated along the boundaries of the built-up area and the intersection between construction land and ecological land. Finally, the ecological sources were found primarily on existing ecological protection zones, which supports the usefulness of machine learning in predicting ecological sources and may provide new insights in developing urban ESP.


2018 ◽  
Vol 200 ◽  
pp. 349-358 ◽  
Author(s):  
Baodi Sun ◽  
Lijuan Cui ◽  
Wei Li ◽  
Xiaoming Kang ◽  
Xu Pan ◽  
...  

2020 ◽  
Vol 12 (24) ◽  
pp. 10233
Author(s):  
Shan Liu ◽  
Mingxia Yang ◽  
Yuling Mou ◽  
Yanrong Meng ◽  
Xiaolu Zhou ◽  
...  

Rapid urbanization has led to the continuous deterioration of the surrounding natural ecosystem. It is important to identify the key urbanization factors that affect ecosystem services and analyze the potential effects of these factors on the ecosystem. We selected the Beijing, Tianjin, and Hebei (BTH) urban agglomeration to investigate these effects, and designed three indicators to map the urbanization level: Population density, gross domestic product (GDP) density, and the construction land proportion. Four indicators were chosen to quantify ecosystem services: Food production, carbon sequestration and oxygen production, water conservation, and soil conservation. To handle the nonlinear interactions, we used a random forest (RF) method to assess the effect of urbanization on ecosystem services in the BTH area from 2000 to 2014. Our study demonstrated that population density and economic growth were the internal driving forces affecting ecosystem services. We observed changing trends in the effect of urbanization: The effect of population density on ecosystem services increased, the effect of the proportion of construction land was consistent with population density, and the effect of GDP density on ecosystem services decreased. Our results suggest that controlling the population and GDP would significantly influence the sustainable development in large urban areas.


2020 ◽  
Vol 43 ◽  
pp. 101103 ◽  
Author(s):  
Jiashu Shen ◽  
Shuangcheng Li ◽  
Ze Liang ◽  
Laibao Liu ◽  
Delong Li ◽  
...  

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