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Since reform and opening up in 1978, with the rapid development of China's economy, the problem of ecological environment has become increasingly serious. In order to ensure the ecological security of the countries and regions, it is necessary to simulate and predict the future ecological space. Under the background of the Yangtze River protection strategy and the green development of the Yangtze River Economic Belt, this paper takes Hubei province as the research area. Based on the data of land use in 2010 and 2015 and the data of 15 driving factors including natural and human factors, the FLUS model was used to simulate and predict the ecological space of Hubei province in 2035. Based on the current situation of land use in 2010, the results show that the overall accuracy of land use change in Hubei in 2015 is 0.976, and the Kappa coefficient is 0.961, which are of high accuracy. The four scenarios of production space priority, living space priority, ecological space priority and comprehensive space optimization basically meet the needs of different development orientations in this province in the future. From the perspective of geomorphic unit, under different scenarios, the ecological space of Hubei is mainly distributed in the four major mountainous areas on the border of Hubei province, and the ecological space in the central Jianghan Plain is scattered. In terms of quantity scale, the difference in the size and scale of each land use type in different scenarios is more obvious. The area of cultivated land increased by 1216 km2 under the priority of production space, and the scale of urban land use increased by 5959 km2 under the priority of living space. The ecological space used in the ecological space priority scenario increased by 722 km2, while that used in the integrated space optimization scenario became moderate. From the distribution of ecological space change, the ecological space of the four mountainous areas has not changed much, but the ecological space of the central Jianghan Plain is more obvious. From the perspective of administrative divisions, the scope of change is mainly distributed in Wuhan City Circle, Xiangyang city, the central- west of Yichang city and the central part of Suizhou city. All in all, the FLUS model has good applicability to the ecological spatial simulation in Hubei. The results of multi- scenario simulation can provide a multi- angle and multi- directional policy decision reference for the future territorial spatial planning and ecological spatial control in this province [ABSTRACT FROM AUTHOR]

Energy and water are highly correlated. In order to break through the limitations of the previous single-resource management policy and improve the effectiveness of related policies, it is urgent to carry out research on energy-water coupling relationship and collaborative management. Based on the system input-output analysis and ecological network analysis, this paper built an energy-water nexus network of Hubei Province in 2007 and 2012. The results are as follows: 1) In 2012, the energy consumption and water use caused by urban final demand were 14 304.93×104 tce and 346.66×108 m3, respectively. Compared with those in 2007, energy consumption and water use induced by urban final demand increased by 52.26% and 7.98%, respectively. About 50% of energy consumption and water use caused by urban final demand were contributed by manufacturing. 2) In 2007, the recycling rates of water networks and energy networks in Hubei Province were all around 2.71%. The recycling rate of water network increased to 4.23%-4.40% in 2012, and the recycling rate of energy network had small variation. 3) The robustness analysis showed that both energy and the water networks are less efficient and more redundant. 4) After taking nexus effect into consideration, the control of production and supply sectors of electric power and heat over most other sectors in the energy and water networks becomes stronger during 2007- 2012. The proposed nexus network approach may help bridge the gap between nexus modeling and regional resource management by identifying the regulating pathways for each sector to coordinate with their nexus management. [ABSTRACT FROM AUTHOR]