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Based on the ArcGIS geostatistical analysis method, this study offers a visualization of the spatial distribution pattern and spatial trend of vegetable production in China. The research also examines the degree of spatial agglomeration patterns of vegetable production by using the standard deviation ellipse technique and exploratory spatial data analysis method. In addition, we employ the spatial regression model partial differential method to explore the driving factors leading to the changing layout of vegetable production. The findings unveil that vegetable production in China exhibit strong spatial non-equilibrium characteristics, with "high-high" and "low-low" types as the main agglomeration patterns. Furthermore, the location distribution shows a northeast–southwest orientation with the center of gravity of distribution gradually directed toward the southwest. Regarding driving factors, the results show that the effective irrigated area of natural factors had a facilitating effect on the layout of vegetable production, while the affected area had an inhibiting effect on it. Climate indicators such as temperature, precipitation and light show different degrees of influence on the layout of vegetable production. The level of urbanization and transportation conditions have a negative impact on the layout of production in the region. Market demand has a positive spillover effect on the layout of local vegetable production, while it has a negative spillover effect on other regions. Technological progress shows positive spillover effects on the layout of vegetable production in the region and other regions. Financial support policy also shows positive effects from an overall perspective. [ABSTRACT FROM AUTHOR]

Simple Summary: In recent years, the damage inflicted upon vegetation by the fall webworm (FWW), Hyphantria cunea (Drury) (Lepidoptera: Erebidae: Arctiidae), has escalated globally. The black-headed fall webworm has extensively invaded regions in Europe and Asia. In China, scholars have conducted extensive research on the fall webworm. However, there has been limited research on the dynamics of invasion by the black-headed form of the fall webworm and the comprehensive interplay of various factors affecting its spread. Therefore, this study focuses on the dynamics of invasion by the black-headed form of the fall webworm and the combined influence of various factors affecting its spread. The plan is to map the invasion road map of Autumn Dictyophora melanocephala since its introduction into China and summarize the effects of terrain, vegetation, and human factors on the temporal and spatial changes of the species. The fall webworm (FWW), H. cunea (Drury) (Lepidoptera: Erebidae: Arctiidae), is an extremely high-risk globally invasive pest. Understanding the invasion dynamics of invasive pests and identifying the critical factors that promote their spread is essential for devising practical and efficient strategies for their control and management. The invasion dynamics of the FWW and its influencing factors were analyzed using standard deviation ellipse and spatial autocorrelation methods. The analysis was based on statistical data on the occurrence of the FWW in China. The dissemination pattern of the FWW between 1979 and 2022 followed a sequence of "invasion-occurrence-transmission-outbreak", spreading progressively from coastal to inland regions. Furthermore, areas with high nighttime light values, abundant ports, and non-forested areas with low vegetation cover at altitudes below 500 m were more likely to be inhabited by the black-headed FWW. The dynamic invasion pattern and the driving factors associated with the fall webworm (FWW) provide critical insights for future FWW management strategies. These strategies serve not only to regulate the dissemination of insects and diminish migratory tendencies but also to guarantee the implementation of efficient early detection systems and prompt response measures. [ABSTRACT FROM AUTHOR]

The Tarim River Basin in China has predominantly assumed the task of commodity cotton and other high water-intensive crop production in recent years. The spatial matching status of agricultural water and land resources is a prerequisite for local economic development. This paper provides an insight into the spatiotemporal variation trends of agricultural production water footprint and oasis farmland in the Tarim River Basin. The degree of spatial mismatching between oasis farmland and crop production water footprints studied in this paper found how the crop water footprint affected the change in oasis farmland area by sensitivity analysis. Time series data covering the period of 1990–2015 were used for the study. The results showed that the annual variation of crop production water footprint and oasis farmland area have experienced upward trends in Tarim River Basin. The blue water makes the largest contribution to the components of the crop production water footprint in each district (all exceeded 77%). The crop production water footprint and oasis farmland area tend to aggregate towards the eastern region. The level of spatial mismatch between the blue water footprint and farmland area fluctuated during the study period, but it was gradually remedied after 2000, while the spatial mismatch between green water footprint and farmland area gradually worsened. The number of districts with mid and high sensitivity to changes in blue water footprint continuously increased during 1990–2005, which revealed that the change in blue water footprint has an increasing influence on oasis farmland. The results can provide operable recommendations for efficient use of water resources, maintaining oasis suitable farmland scale and agricultural sustainable development in the Tarim River Basin. [ABSTRACT FROM AUTHOR]

Wood processing products can be used as a substitute for some high carbon emission materials, thus contributing significantly to climate change mitigation. China has significant importance in guaranteeing a stable global supply of wood products. However, China has experienced a decline in wood product exports recently, which could affect the world's progress toward sustainable development. This study focuses on the spatial agglomeration of China's wood-processing industry and explores the potential of integrating spatial agglomeration to address the diminishing export growth. We found that the spatial agglomeration of China's wood-processing industry generally increased rapidly between 1999 and 2004, but decreased after 2004. The centroid of China's wood-processing is shifting from the northeastern region toward the eastern coastal areas. The industry is more concentrated in the north–south direction and slightly dispersed in the east–west direction. Most sub-sectors of China's wood-processing industry operate at the primary agglomeration level, indicating significant potential for improvement and further development. The empirical results unveil the substantial positive influence of spatial agglomeration on exports within China's wood-processing industry, indicating the prospects for enhancing exports through the deliberate exploitation of agglomeration effects. The results advocate the view that spatial agglomeration acts as an essential accelerator for export growth and firms' international competitiveness. Therefore, spatial agglomeration can alleviate the export constraints of China's wood-processing industry. The results also show that exports are hampered by increased enterprise productivity. The 'productivity paradox' phenomenon has also surfaced in low-tech industries, like the wood-processing industry, as a result of issues with transaction costs, the development path, and policy orientation. Therefore, we should strategically leverage the spatial agglomeration effect, especially in the western region, and guide the moderate competition of enterprises to enhance the competitiveness of low-tech enterprises. China's wood-processing industry can provide advanced experience and lessons for other countries regarding industrial cluster allocation and sustainable development models. [ABSTRACT FROM AUTHOR]

Since the implementation of the great western development strategy in 2000, the ecological environment in the western region of China has been significantly improved. In order to explore the temporal and spatial characteristics of vegetation coverage in the western region, this paper adopted the method of Maximum Value Composite (MVC) to obtain the mean Normalized Difference Vegetation Index (NDVI) of vegetation on the basis of the Moderate-resolution Imaging Spector audiometer (MODIS) data of 2000/2005/2010/2015/2018. Thereafter, the spatio-temporal differentiation characteristics of vegetation in western China were analyzed. The results show that: (1) According to the time characteristics of vegetation coverage in the western region, the average annual NDVI value of vegetation coverage in the growing season in the western region fluctuated between 0.12 and 0.15, among which that of 2000 to 2010 fluctuated more greatly but did not show obvious change trend. (2) Based on Sen trend and Mann-Kendall test analysis, the area of vegetation coverage improvement in the western region from 2000 to 2018 was larger than that of significant vegetation degradation. (3) From the perspective of global autocorrelation coefficient, Moran's I values were all positive from 2000 to 2018, which indicates that the vegetation coverage in the west showed strong positive autocorrelation in each period. According to the average value and coefficient of variation of vegetation coverage, the vegetation coverage was lower in 2000, its internal variation was smaller, and the vegetation coverage increased with time. According to the local spatial autocorrelation analysis, the vegetation coverage levels in different regions varied greatly. (4) The standard deviation ellipse method was used to study the spatial distribution and directional transformation of vegetation. It makes the result more intuitive, and the three levels of gravity center shift, direction shift, and angle shift were considered: the vegetation growth condition in the spatial aggregation area improved in 2015; the standard deviation ellipses in 2000 and 2018 overlapped and shifted eastward, which indicates that the vegetation coverage conditions in the two years were similar and got ameliorated. [ABSTRACT FROM AUTHOR]