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The purpose of this study is to reveal the spatial-temporal change and driving factors of green space in coastal cities of southeast China over the past 20 years. A supervised classification method combining support vector machines (SVMs) and visual interpretation was used to extract the green space from Landsat TM/OLI imageries from 2000–2020. The landscape pattern index was used to calculate geospatial information of green space and analyze their spatial-temporal changes. The hierarchical partitioning analysis was then used to determine the influences of anthropogenic and geographic environmental factors on the spatial-temporal changes in green space. The results indicated that the total area of green space remained constant over the past 20 years in coastal cities of southeast China (1% reduction). The spatial change of green space mainly occurred in the area near the ocean and the southern region. 41.37% of forest land was transferred from cultivated land, while 44.56%, 41.83%, 43.20%, 46.31%, 41.98% and 40.20% of shrub land, sparse woodland, other woodland, high-coverage grassland, moderate-coverage grassland and low-coverage grassland were transferred from forest land. The number of patches, patch density, edge density, landscape shape index and Shannon’s diversity index increased from 2000–2015, and then decreased to the minimum in 2020, while largest patch index continued to decline from 2000–2020. The contribution of anthropogenic factors (0.53–0.61) on the spatial-temporal changes of green space continually increased over the past 20 years, which was also higher than geographical environment factors (0.39–0.41). Our study provides a new perspective to distinguish the impact of anthropogenic activities and geographical environmental factors on the change of green space area, thereby providing a theoretical support for the construction and ecological management of green space.
Huayan Weng; Yongchao Gao; Xinyi Su; Xiaodong Yang; Fangyan Cheng; Renfeng Ma; Yanju Liu; Wen Zhang; Liwen Zheng. Spatial-Temporal Changes and Driving Force Analysis of Green Space in Coastal Cities of Southeast China over the Past 20 Years. Land 2021, 10, 537 .
AMA StyleHuayan Weng, Yongchao Gao, Xinyi Su, Xiaodong Yang, Fangyan Cheng, Renfeng Ma, Yanju Liu, Wen Zhang, Liwen Zheng. Spatial-Temporal Changes and Driving Force Analysis of Green Space in Coastal Cities of Southeast China over the Past 20 Years. Land. 2021; 10 (5):537.
Chicago/Turabian StyleHuayan Weng; Yongchao Gao; Xinyi Su; Xiaodong Yang; Fangyan Cheng; Renfeng Ma; Yanju Liu; Wen Zhang; Liwen Zheng. 2021. "Spatial-Temporal Changes and Driving Force Analysis of Green Space in Coastal Cities of Southeast China over the Past 20 Years." Land 10, no. 5: 537.
Nitrogen amendment is known to effectively enhance the bioremediation of hydrocarbon-contaminated soil, but the nitrogen metabolism in this process is not well understood. To unravel the nitrogen metabolic pathway(s) of diesel contaminated soil, six types of nitrogen sources were added to the diesel contaminated soil. Changes in microbial community and soil enzyme genes were investigated by metagenomics analysis and chemical analysis through a 30-day incubation study. The results showed that ammonium based nitrogen sources significantly accelerated the degradation of total petroleum hydrocarbon (TPH) (79–81%) compared to the control treatment (38%) and other non-ammonium based nitrogen amendments (43–57%). Different types of nitrogen sources could dramatically change the microbial community structure and soil enzyme gene abundance. Proteobacteria and Actinobacteria were identified as the two dominant phyla in the remediation of diesel contaminated soil. Metagenomics analysis revealed that the preferred metabolic pathway of nitrogen was from ammonium to glutamate via glutamine, and the enzymes governing this transformation were glutamine synthetase and glutamate synthetase; while in nitrate based amendment, the conversion from nitrite to ammonium was restrained by the low abundance of nitrite reductase enzyme and therefore retarded the TPH degradation rate. It is concluded that during the process of nitrogen enhanced bioremediation, the most efficient nitrogen cycling direction was from ammonium to glutamine, then to glutamate, and finally joined with carbon metabolism after transforming to 2-oxoglutarate.
Yongchao Gao; Jianhua Du; Mezbaul Bahar; Hui Wang; Suresh Subashchandrabose; Luchun Duan; Xiaodong Yang; Mallavarapu Megharaj; Qingqing Zhao; Wen Zhang; Yanju Liu; Jianing Wang; Ravi Naidu. Metagenomics analysis identifies nitrogen metabolic pathway in bioremediation of diesel contaminated soil. Chemosphere 2021, 271, 129566 .
AMA StyleYongchao Gao, Jianhua Du, Mezbaul Bahar, Hui Wang, Suresh Subashchandrabose, Luchun Duan, Xiaodong Yang, Mallavarapu Megharaj, Qingqing Zhao, Wen Zhang, Yanju Liu, Jianing Wang, Ravi Naidu. Metagenomics analysis identifies nitrogen metabolic pathway in bioremediation of diesel contaminated soil. Chemosphere. 2021; 271 ():129566.
Chicago/Turabian StyleYongchao Gao; Jianhua Du; Mezbaul Bahar; Hui Wang; Suresh Subashchandrabose; Luchun Duan; Xiaodong Yang; Mallavarapu Megharaj; Qingqing Zhao; Wen Zhang; Yanju Liu; Jianing Wang; Ravi Naidu. 2021. "Metagenomics analysis identifies nitrogen metabolic pathway in bioremediation of diesel contaminated soil." Chemosphere 271, no. : 129566.