Existing studies on the performance of green innovation in the Yangtze River Economic Belt mostly treat it as a "black box" for analysis, but often ignore the different stages of its innovation process. Based on the innovation value chain perspective, the green innovation activities were divided into two stages: research and development of science and technology and transformation of achievement. A network SBM model was constructed to measure the total green innovation performance and sub-stage performance of 108 cities at prefecture level and above along the Yangtze River Economic Belt from 2010 to 2019. The spatial and temporal divergence and dynamic evolution characteristics were explored using natural break points, Theil index, and kernel density estimation. The panel Tobit model was used to examine the influencing factors. The results showed that: (1) in general, the total green innovation performance, science and technology R&D performance and achievement conversion performance in Yangtze River Economic Belt all showed a fluctuating upward trend, and the total performance of green innovation and R&D performance showed a distribution pattern of "high at both ends and low in the middle", while the performance of results transformation showed a decreasing spatial pattern of "down-middle-up". The spatial layout of "down-middle-upstream" decreased. (2) In terms of spatial differences, the regional differences of total green innovation performance and sub-stage performance showed a fluctuating downward trend, and the differences showed the structural characteristics of total green innovation performance < achievement conversion performance < science and technology R&D performance. (3) In terms of dynamic evolution, the total performance and sub-stage performance of green innovation were polarized, and the degree of polarization was that science and technology R&D performance < total green innovation performance < achievement conversion performance. (4) Factor analysis showed that innovation support, industrial structure, and environmental regulation had significant effects on green innovation and sub-stage performance, and there were obvious stage differences in the effects of intellectual property protection, enterprise scale, human capital, and urbanization on green innovation performance. These results provide a reference for decision making to promote green innovation performance enhancement and regional synergistic development in the Yangtze River Economic Belt.

Taking the Yangtze River Delta as a research area, this paper investigated the spatial effect and influencing mechanism of digital finance on high-quality development from the theoretical and empirical aspects. The findings were as follows: (1) Digital finance could promote the high-quality development of local and neighboring areas, and there were characteristics of dimensional heterogeneity, temporal heterogeneity and spatial heterogeneity. In terms of dimensional heterogeneity, the coverage breadth and use depth of digital finance had a significantly positive effect on local and neighboring high-quality development, while the digitalization degree had a significantly negative effect on local and neighboring high-quality development. In terms of temporal heterogeneity, the long-term impact of digital finance on local and neighboring high-quality development was greater than the short-term impact, indicating that the network effect and “Metcalfe’s law” of digital finance were significantly established in high-quality development system. In terms of spatial heterogeneity, the spatial spillover effect of digital finance and its subdivision dimension gradually decreased with the increase of geographical distance, and 215 km was found to be the effective spillover boundary. (2) The collaborative agglomeration of manufacturing and producer services (hereinafter referred to as “industrial collaborative agglomeration”), local government behavior (official replacement, fiscal expenditure bias, environmental regulation) were the important ways for digital finance to affect high-quality development, and could form collaborative forces with digital finance construction. (3) In the low-value region of high-quality development and the high-value region of Internet development, the dividend release of digital finance on high-quality development was more obvious.

Innovation is the primary driving force of economic development. As the carrier of innovation activities, the spatial configuration distortion of industrial land and the impacts were the major issues related to the high-quality development of the regional economy. Based on the panel data of 41 cities in the Yangtze River Delta region from 2008 to 2019, this paper used the spatial econometric model and the intermediary effect model to investigate the impacts and mechanism of industrial land spatial mismatch on urban innovation. The results showed that: (1) From the perspective of industrial land misallocation types, most of the central cities in the Yangtze River Delta region were identified as deficient misallocation, while most of the peripheral cities were identified as excess misallocation. (2) During the study period, the innovation level in the Yangtze River Delta region was generally improved, and the improvement rate of peripheral cities was greater than that of central cities; In terms of space, the level of urban innovation decreased from east to west, and gradually formed a continuous innovation zone centered on Shanghai, Nanjing and Hangzhou. (3) The spatial mismatching of industrial land had a significant negative impact on urban innovation, and this negative impact was more obvious in areas with deficient mismatching, industries with high land dependence and for periods with strong land constraints; In excess mismatched areas, there existed a negative spillover effect of industrial land spatial mismatching. (4) For the excess mismatching area, the spatial mismatching of industrial land obstructed the improvement of the innovation level through the innovation capital extrusion mechanism and the innovation environment destruction mechanism; For the deficient mismatched areas, the spatial misallocation of industrial land mainly hindered the improvement of innovation level through the mechanism of innovation capital extrusion. This study implied that promoting the correction of industrial land spatial mismatch was an effective measure to break the barriers to urban innovation and help the high-quality development of the Yangtze River Delta region.

The allocation of water resources has a profound impact on the regional economic development pattern. The South-to-North Water Diversion Project (SNWTP) provides strong support for optimizing water resource allocation and alleviating the serious water shortage in northern China. However, whether the operation of the SNWTP can promote the economic growth of the water-receiving areas and water-source areas still remains unclear. This article took the Central Line Project of the SNWTP as an example and used the synthetic control method to analyze the impact and mechanism of water supply on the economic growth of water-receiving areas and water-source areas. The research results showed that: (1) From the overall effect, the water transfer had a significant positive effect on the per capita GDP and nighttime light brightness of the water-receiving area and water-source area, indicating that the engineering water supply had effectively promoted the economic growth and activity of the two areas. From the perspective of dynamic effects, the promotion effect of engineering water supply on the economic growth of the water-receiving was hysteretic. In the first two years of water supply, a slight impact was shown on the economic development of the water-source area, and a positive promoting effect was shown thereafter. (2) The engineering water supply had a significant positive impact on the rationalization of industrial structure in water-receiving areas and water-source areas, and the rationalization degree of industrial structure promoted economic growth in the two areas. (3) The engineering water supply improved industrial structure sophistication in water-receiving areas, but the impact on the industrial structure sophistication in the water-source areas was hysteretic; The effects on industrial structure sophistication could significantly promote economic growth in the two areas. (4) From different dimensions of economic growth, the growth of per capita GDP in water-receiving areas and water-source areas mainly depended on the rationalization effect of industrial structure; The improvement of economic activity depended on the effect of industrial structure sophistication. Finally, this study provided policy recommendations for promoting the high-quality development of the follow-up project of the SNWTP to fully leverage its strategic and fundamental functions.

Improving green total factor productivity (GTFP) is an important initiative to promote high-quality economic and social development in the Qinghai-Tibet Plateau region. Based on the panel data of cities in the Qinghai-Tibet Plateau from 2000 to 2019, the spatial-temporal evolution characteristics of GTFP and its driving mechanism were analyzed by applying global Malmquist-Luenberger index, non-parametric Kernel density estimation, spatial Markov chain and panel quantile regression. The results showed that: (1) During the study period, the evolution trend of GTFP was relatively stable, with fluctuation at the provincial and city levels, showing a "multi-peak" wave-shaped agglomeration pattern. (2) The spatial differentiation of GTFP had good continuity and stability. There was a possibility of leapfrog transfer in space, and the "Matthew effect" existed in the process of continuous transfer. (3) The level of economic development, industrial structure and population size all promoted the improvement of GTFP in the Qinghai-Tibet Plateau at different levels, while the acceleration of urbanization was not conducive to the growth of GTFP.

Transportation serves as the vanguard of China's modernization, with high-speed rail standing as a significant emblem of transportation modernization. The spatial flow of high-speed rail has emerged as a crucial perspective for investigating urban and regional spatial structures. Utilizing GIS spatial analysis and social network analysis methods based on national railway passenger train schedule data from 2009 to 2020, focusing on 369 administrative units in China, this study explored the spatiotemporal evolution characteristics of urban network intensity and structure, and examined the developmental disparities within and between regions. The following were the primary conclusions: (1) The intensity of urban network associations in China hadexperienced a rapid surge, with the hierarchical structure transitioning from quantity-oriented to quality-driven. Moreover, cities in central and western China were consistently ascending to the highest echelon of urban centers. (2) The network density and core-periphery structure of the urban network were in spatiotemporal heterogeneity. The urban network in coastal areas had higher correlation strength and a more hierarchical structure, and the urban network in the central region exhibited moderate correlation intensity, but operated on a larger scale. The southwest and northwest regions experienced a delayed period of high-speed rail (HSR) operation; however, their urban networks developed rapidly. Conversely, the northeastern region was the earliest HSR operation but witnessed a slower development of urban network. (3) The number of city pairs with cross-regional connections was increasing, and the intensity of cross-regional city network connections continued to increase, however was still dominated by low-level connections. The region with the highest concentration of cross-regional connections had shifted from the eastern coastal area to the middle reaches of the Yangtze River. (4) The centrality index exhibited an upward trajectory. Cities with higher degrees of centrality were predominantly concentrated along the Beijing-Shanghai, Beijing-Harbin-Beijing-Hong Kong-Macao Road and Bridge, as well as the Shanghai-Kunming passageways. Conversely, cities with higher centrality primarily consisted of regional central cities with elevated administrative levels.

The coupling relationship between carbon and water cycles in terrestrial ecosystems is one of the hot spots of global change research. However, the current research is mainly in arid and semi-arid areas, and the coupling mechanism of terrestrial carbon and water in humid regions is still unclear. Based on Remote Sensing and GIS, the coupling relationship between vegetation net primary productivity (NPP), soil moisture and evapotranspiration in Taihu Lake Basin was analyzed at different spatial and temporal scales. The results showed that the coupling relationships between NPP and hydrological elements were significantly different at different spatial and temporal scales: Based on all monthly data during the study period, evapotranspiration and NPP were significantly positively correlated, while soil moisture in 99.86% regions was negatively correlated with NPP. In the interannual scale, the correlation between the three was weakened. At the seasonal scale, soil moisture and NPP were negatively correlated in 82% of regions in spring, summer and autumn, among which spring was the most significant, which was mainly related to the difference of land cover and plant growth period. The study further found that the correlation between the three was closely related to topographic factors, which was manifested as a trend of weakening with the increase of slope or altitude. Finally, it was found that the Random forest model (RF_All model) based on the whole period monthly scale hydro-meteorological elements could estimate and predict the NPP of the basin well (R2 = 0.97，RMSE = 4.16 gC m-2 a-1，Bias = 0.37 gC m-2 a-1). The conclusion of this study has important theoretical significance for formulating the policy of ecological construction and sustainable development of Taihu basin under the background of global change.

The loss and fragmentation of suitable habitat in the wild is the biggest challenge for the protection of Chinese alligator. Building and maintaining the ecological corridor between habitats is an important protection strategy. Taking 8 blocks of the Chinese Alligator Nature Reserve as the ecological sources, this study aimed to build a comprehensive resistance surface, to simulate the ecological corridors between blocks, to identify the ecological “pinch points” and “barriers”, and to propose targeted protection and repair strategies. The Linkage Mapper tool and the Circuitscape program were used in this study. The research results were as follows: (1) There were 14 identified ecological corridors with a total length of 391.06 km, which were in the state of “long in the east and short in the west”. Seven key ecological corridors effectively connected Changle, Zhongqiao, Shuangkeng and Hongxing areas in the southwest of the study area; (2)12 ecological pinch points were identified, with an area of 82.35 km2. The protection strategy of giving priority to natural protection, supplemented by the creation of suitable habitat for Chinese alligator was put forward. At the same time, attention should be paid to the risk of certain pinch points that was disturbed by human activities; (3)19 ecological barriers were identified, with an area of 92.49 km2. It was mainly located in traffic trunk lines, urban land or surrounding radiation areas. Suggestions such as setting up animal migration channels, promoting ecological agriculture, optimizing the layout of residential areas, and resolving the conflicts between people and alligators were put forward.

To systematically understand the seasonal dynamics and assembly mechanism of macroinvertebrate community in Huishui River, an investigation was carried out in October (autumn) and December (winter) 2021, April (spring) and August (summer) 2022. The Huishui River supports a high array of macroinvertebrate diversity. A total of 168 taxa were identified, belonging to 8 classes and 73 families. The numbers of macroinvertebrate species in spring, summer, autumn and winter were 85, 77, 82 and 82, respectively. Analysis of similarities (ANOSIM) and nonmetric multidimensional scaling analysis (NMDS) showed that the macroinvertebrate community structure in Huishui River differed significantly among seasons. Canonical correspondence analysis (CCA) showed that the environmental factors affecting the macroinvertebrate community structure were different in the four seasons. Environmental filtering appeared to be key process in structuring macroinvertebrate assemblages in spring, autumn and winter, while the spatial processes played a leading role in summer. This study provides an important scientific reference for the seasonal dynamics of the macroinvertebrate community structure, biodiversity assessment and environmental monitoring in the mountainous streams of southern Anhui Province.

In order to study the temporal and spatial evolution characteristics of bottomland in Dongting Lake since the middle of the Republic of China, this paper used the historical maps and aerospace remote sensing data of 15 periods since the middle of the Republic of China, used remote sensing interpretation and historical comparison methods to study subzone of bottomland development in modern Dongting Lake. The evolution characteristics and change reasons of main bottomland from 1938 to 2021 were analyzed. The results showed that the bottomland of Dongting Lake was dominated by terrigenous detritus, accompanied by biogenic sedimentation. The sedimentary types included lacustrine deposits, river alluvial deposits, floodplain and river delta deposits, and river lake interactive deposits. Furthermore, different sediment characteristics were displayed due to the different water and sediment conditions in different seasons. The modern bottomland of Dongting Lake was divided into 20 sub regions, including 9 sub regions in the east of Dongting Lake, 8 sub regions in the south of Dongting Lake, and 3 sub regions in the west of Dongting Lake. In the East Dongting Lake, Piaowei Island was the largest beach of Dongting Lake, with an area of 466.89 km2 during dry seasons. The estuary delta of the east branch of the Ouchi River was the fastest growing bottomland in the last century, which was located at the junction of Zhuzi bleeder in 1938, and estuary delta had extended 12.13 km2 eastward to the current shoreline, and then the river channel advanced 26.42 km2 toward the lake. The bottomland of South Dongting Lake mainly developed along the Songzhu River and the north of Wanzi Lake. The Xiangjiang River floodplain, the ancient Xiangjiang River and the Zishui Delta were eroded and silted, but their outlines were clear in dry seasons. In West Dongting Lake, Qili Lake had become a component of Songli floodway due to sedimentation, and the northern part of Muping Lake was the Songli Delta, while the southern part was the Yuanshui Delta. The sediment was severely silted up, and the main lakes were basically dried up during dry seasons. The research results provided objective data for the rational development and utilization of Dongting Lake bottomland resources and the adjustment of the Dongting Lake region's lake management strategy in the post-Three Gorges era.

Accurate water level prediction can provide scientific basis for flood control and disaster reduction and water resource management in lake area. In this paper, the IPSO improved particle swarm optimization algorithm and EGA elite genetic algorithm were introduced to optimize the LSTM long short term memory neural network structure. The improved IPSO-EGA-LSTM model was used to predict the water level of the gauging stations in Dongting Lake area under the 1d forecast period. The accuracy of the model was compared with the LSTM, GRU and BP neural network models. The prediction accuracy of the model was evaluated under the longer forecast period (3d, 5d and 7d). Three kinds of model input conditions were further set, corresponding water level prediction schemes were put forward, and the prediction accuracy of each forecasting scheme (direct forecasting, synchronous forecasting, rolling forecasting) under different forecast periods was explored. The results showed that the IPSO-EGA-LSTM model was better than the traditional neural network model in predicting the water level of Dongting Lake. It effectively captured the variation characteristics of water level of Dongting Lake in different forecast periods. The Nash efficiency coefficient (NSE) in 1d forecast period was greater than 0.998, and the NSE was still greater than 0.9 in long forecast period. The three prediction schemes under different input conditions demonstrated better prediction effects, among which the synchronous prediction scheme had better performance than the direct prediction and rolling prediction under the long prediction periods.

Exploring the spatial distribution characteristics of ethnic villages and revealing its influencing factors will help to protect and develop resources in ethnic areas and promote the economic and social development. In this paper, 65 ethnic villages in southwest Hubei were selected as the research objects. The spatial distribution characteristics and influencing factors were analyzed by using GIS spatial analysis and geographical detector research methods. The results showed that: （1） the spatial differentiation of ethnic villages in southwest Hubei was remarkable, showing a "three areas-multiple scattered points" nuclear density distribution trend, forming a "V-shaped" high-density distribution belt composed of Enshi City, Xuanen County, Xianfeng County and Hefeng County. The number of villages in the region was obviously polarized between the west and the east, showing the spatial distribution trend of cold hotspots of "hot in the west and cold in the east, high in the northwest and high in the northeast"; （2）Dominated by natural factors, ethnic villages in southwest Hubei were mostly distributed in strips on the sunny slope of the mountain within 2km from the river, with small relief and an altitude of 600-900 m; （3）Restricted by socio-economic factors, there was a positive correlation between the ethnic population and the number of ethnic  villages, and a negative correlation between the distance from the central town and the level of economic development and the number of ethnic villages.

The provinces and cities located in the Yangtze River Economic Belt are confronted with unbalanced and uncoordinated developments in the fields of ecology, innovation, and the economy sectors. An examination of the coordination relationships within these three areas may have significant importance for both theoretical and practical purposes. Using multiple empirical analysis methods, including the Super-Efficiency SBM-DEA model, the Entropy Weight Linear Weighting method, and the Entropy Weight TOPSIS method, this study respectively evaluated the haze governance efficiency, the green technology innovation index, and the low-carbon high-quality development index of the provinces and cities along the Yangtze River Economic Belt from 2009 to 2020. The coordination between these three aspects was also explored, based on the coupling coordination degree model. The results indicated that: (1) The haze governance efficiency significantly differed from the green technology innovation index and the low-carbon high-quality development index at both the provincial and regional levels. (2) The coupling coordination of the ternary system displayed an overall increasing trend, with a positive spatial spillover effect and a spatial differentiation identified as "higher in the eastern region and lower in the central region". (3) The gap in coordination among the provinces and cities exhibited heterogeneity, but the divergences between regions were reducing over time. Based on these findings, this article put forward several proposals for enhancing the coordinated growth of the Yangtze River Economic Belt. These proposals included the optimization of resource and factor allocation, the design of tailored and targeted improvement strategies, and the implementation of cross-regional collaboration mechanisms.

The financial sector plays a crucial role in supporting a low-carbon economy, and the development of green finance is an indispensable pathway. It is of great significance to explore the effect of green finance on carbon reduction. The Yangtze River Economic Belt (YREB), as a driving force for leading high-quality economic development, serves as the primary battleground for achieving the "dual carbon" goals. A variety of spatial econometric models were used to analyze the panel data of 11 provinces and municipalities in the YREB from 2013 to 2020. The impact of green finance on CO₂ emissions and its spillover effects were explored from a spatial perspective. The results showed that: (1) The development level of green finance showed an obvious spatial correlation in various regions of the YREB, with significant spatial aggregation characteristics. There were spatial spillovers of the impact of green finance, environmental investment, economic development and other factors on the level of CO₂ emissions. (2) The relationship between green finance and CO₂ emission level showed a significant inverted "U" curve. The impact of green finance development level on CO₂ emission level was first promoted and then suppressed. The environmental investment and economic development level negatively regulated the effect of green finance. Furthermore, the dynamic SDM model was used to verify the positive feedback effect of the time dimension of CO2 emissions. (3) Due to different geographical locations and economic developments, green finance demonstrated different impacts on CO₂ emissions in the Yangtze River Delta region and other regions. The impact relationship of the inverted "U" curve was more obvious in other regions outside the Yangtze River Delta. (3) Different geographical location and economic development led to the heterogeneity in the results. Green finance had different impacts on CO₂ emissions in the Yangtze River Delta region and other regions, and the influence of green finance on the inverted "U" curve of CO₂ emissions was more obvious in other regions outside the Yangtze River Delta.

In the new stage of historical development, there is an urgent need for low-carbon transformation in economic development. Energy conservation and emission reduction, green low carbon have become the top priorities of China's economic development. Improving carbon emission efficiency is the key to achieve the carbon peaking and carbon neutrality goals while maintaining high-quality economic development. This paper took 108 cities in the Yangtze River Economic Belt as the research objects and used the super-efficiency SBM model considering unexpected output and the Malmquist index method to calculate carbon emission efficiency. Natural segmentation method of ArcGIS10.7 and Theil index were used to analyze the spatio-temporal evolution characteristics and regional differences. Finally, spatial Durbin model was constructed to further explore the influencing factors of carbon emission efficiency. The results showed that: (1) From 2005 to 2020, the carbon emission efficiency showed a fluctuating trend, and the overall carbon emission efficiency of the Yangtze River Economic Belt was insufficient. The efficiency level was greatly affected by technology and scale. (2) Malmquist index showed that the key reason for the significant gap of carbon emission efficiency among regions lied in the complementarity and mutual promotion of various efficiency indexes and the imbalance of emission reduction technology development. (3) The number of cities with the highest and higher carbon emission efficiency zones increased, and the agglomeration status of the Yangtze River Economic Belt was gradually becoming apparent. (4) Except for the level of economic development, other factors demonstrated significant positive or negative direct effects on carbon emission efficiency. The spatial spillover effects of economic development level, industrial structure, green technology innovation, and government intervention on carbon emission efficiency were indicated as significant factors.

The Ganfu Plains irrigation area is the largest water diversion irrigation area in Jiangnan and the largest irrigation area in Jiangxi Province. It is considered a typical "human-society-nature" composite ecosystem. To evaluate the ecological environment quality change of Ganfu Plains irrigation area from 2002 to 2021, the remote sensing ecological index (RSEI) was constructed by integrating four indicators of NDVI, WET, NDBSI and LST with the principal component analysis method. The Landsat TM/OLI remote sensing image data in 2002, 2008, 2015 and 2021 were used. The results showed that the ecological environment of Ganfu Plains irrigation area continued to improve from 2002 to 2021. The mean value of RSEI increased from 0.477 to 0.552, with an increase of 15.71%. NDVI and LST were the most significant influencing factors on ecological quality. The RSEI level of the irrigation area was mainly at the medium level. In the past 20 years, the area of excellent and fine ecological quality grades continued to increase with a rate of 48.37%.The most prominent improvement was in the east bank of Fuhe River and Jinxian County. Because of urban expansion and hydrometeorological drought, areas with deteriorating ecological environment quality were mostly distributed in the main urban areas, agricultural areas and coastal areas of rivers and lakes. Therefore, whether to coordinate climate change and ecological environment protection while modernizing irrigation areas was the key to achieve sustainable development in irrigation areas. The research results reflected the changes in the ecological environment quality of the Ganfu Plains irrigation area, and provided theoretical reference and scientific basis for regional ecological environment governance and protection.

Optimizing the spatial layout of the production-living-ecological at the village scale and revealing the spatial and temporal changes in the functional coupling and coordination of the production-living-ecological in the countryside are the prerequisites for realizing the revitalization and sustainable development of the countryside. Based on the village scale, this paper took Changling Town, Guangshui City, located in the low hilly region of northern Hubei, as the research area. The spatial and temporal change characteristics of the tertiary space from 2000 to 2020 were analyzed, based on the land use transfer matrix. The tertiary space function was explored using the coupling coordination degree model. The main driving factors was studied using the geographic detector. The study was expected to provide an effective reference for the sustainable development of rural areas, territorial space governance and ecological environment protection at the subsequent village scale. The results showed that: (1) the living space and production space of Changling Town in Guangshui City expanded from west to north during 2000-2020; (2) The coupling coordination degree of the production-living-ecological space in Changling Town of Guangshui City was in a relatively stable trend, and the overall was in a moderate state of imbalance; (3)Land use intensity was the most important driving factor that affected the spatial differentiation of the coupling coordination degree, followed by the proportion of cultivated land area and population density and other secondary factors. In general, the spatial and temporal variation of the coupling coordination degree was greatly affected by human activities.