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王文静,韩宝龙,郑华,欧阳志云.粤港澳大湾区生态系统格局变化与模拟.生态学报,2020,40(10):3364~3374 本文二维码信息
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粤港澳大湾区生态系统格局变化与模拟
Evolution and simulation of ecosystem patterns in Guangdong-Hong Kong-Macau Bay Area
投稿时间:2019-06-10  修订日期:2020-01-04
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基金项目国家自然科学青年科学基金项目(71804180)
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摘要:
快速城市化是导致粤港澳大湾区生态系统时空格局变化的主要驱动力之一,模拟生态系统变化趋势对于优化区域土地利用格局、防控城市化的生态风险具有重要意义。以2000、2005、2010、2015、2018年5期土地利用数据,分析该区域生态系统格局演变,并运用CA-Markov模型模拟2025年的生态系统格局。研究结果表明:(1)2018年大湾区的森林、农田和城镇为主要生态系统类型,分别占区域总面积的53.99%、22.67%和14.51%。(2)2000-2018年农田、森林、湿地面积分别下降了1983、740、278 km2,城镇和草地面积分别上升了2896、103 km2,城镇面积增长的主要途径是对周围农田、林地和湿地的侵占,草地面积增长是因为管理经营不善导致部分林地退化为草地。(3)大湾区的景观多样性和均匀度下降,景观正在向小斑块趋势发展,空间连通性下降,破碎度增加。(4)模拟2025年的生态系统格局发现,与2018年相比,城镇面积增长了609 km2,农田和森林分别减少了309 km2和316 km2。基于大湾区生态系统格局变化与模拟发现,快速城市化区域中,落实耕地保护红线和生态保护红线制度、保护重要生态空间完整性,对于降低城市化的生态风险具有重要作用。
Abstract:
Rapid urbanization has been one of the primary drivers of ecosystems change in the Guangdong-Hong Kong-Macau Bay Area (the Great Bay Area). To understand these spatio-temporal dynamics, it is important to simulate ecosystem trend and patterns during regional land use optimization, preventing and controlling the ecological risks of urbanization. Based on land use-land cover (LULC) data for the years 2000, 2005, 2010, 2015 and 2018, this paper analyzed the evolution of ecosystem types and landscape patterns in this region. A CA-Markov model was used to simulate ecosystem pattern in 2025. The results showed that: (1) the forests, farmland and urban land were the main ecosystem types in the Greater Bay Area in 2018, accounting for 53.99%, 22.67% and 14.51% of the total area, respectively. (2) From 2000 to 2018, the area of farmland, forest, and wetland decreased by 1983 km2, 740 km2 and 278 km2 respectively, and the area of urban and grassland increased by 2896 km2 and 103 km2, respectively. The growth in urban areas came from the conversion of surrounding farmland, woodland and wetland. Due to poor management, portions of woodland degraded to grassland, leading to the growth of the latter. The change rate of ecosystem types in the Greater Bay Area had obvious periodical characteristics. The fastest period of urban expansion was from 2000 to 2005, leading to a rapid decline in farmland. The rate of urban expansion and farmland reduction slowed after 2005.The speed of forest reduction accelerated in 2000-2015 and slowed down in 2015-2018. The grassland area increased from 2000 to 2015, with a slow growth rate from 2000 to 2010 and a rapid growth rate from 2010 to 2015, then decreased from 2015 to 2018. From 2000 to 2018, the wetland area continued declining with the same speed. (3) Under the effects of demographic urbanization and LULC urbanization, the landscape pattern changed significantly. Fragmentation and separation increased, and the diversity and evenness of the landscape decreased. The Contagion index (CONTAG) increased and the Division index (DIVISION) increased, indicating that the fragmentation and heterogeneity of the landscape increased. The largest patches of farmland and forestland were destroyed, and the Number of Patches index (NP) increased. Urban patches showed a spreading growth, while the urban landscape's degree of fragmentation and separation fell. (4) The ecosystem pattern in 2025 was simulated based on a CA-Markov model, and the accuracy test was carried out by comparison with the actual data in 2015; the Kappa coefficient was 0.94. Compared with 2018, the urban area is projected to increase by 609 km2, extending outward along the larger urban patches, mainly in Guangzhou, Dongguan and Foshan prefectures. The area of farmland and forest ecosystem is projected to decrease by 309 km2 and 316 km2, respectively. The areas of grassland ecosystem and wetland ecosystem are projected to remain unchanged. Based on the change and simulation of ecosystem patterns in the Greater Bay Area, it was found that the farmland protection red line, ecological protection red line and the protection of important ecological space integrity (all national policies) played important roles in reducing the ecological risk of urbanization in a rapidly urbanizing region.
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