Positive Spatial Correlation Research Articles

Identifying driving factors of ecosystem service trade-offs in mountainous region of southwestern China across geomorphic and climatic types

Mountainous areas have obvious spatial differences in topography and climate, which could further cause heterogeneity of ecosystem service (ES) trade-offs. The characteristics of ES trade-offs had been extensively studied, however, the driving mechanism of which is still unclear in mountainous areas. Focusing on the Hengduan Mountain region (HDM) in southwest China, this study quantified the spatial aggregation effects of ESs and their trade-offs using a spatial autocorrelation analysis, and identified the dominant drives for each ES trade-off across various geomorphological and climatic zones. In terms of the spatial distribution, ESs and their trade-offs have a significant positive spatial correlation, which was mainly manifested as high-high (H-H) and low-low (L-L) value aggregations. The dominant factors for some trade-offs differed across geomorphological and climatic zones. Land use type was the main factor in flat areas for paired water yield (WY) with soil conservation (SC) and carbon storage (C). In plateau (PLA) and mid-subtropical (MS) climate zones, the main factors were land use type and soil types for paired WY and C, respectively. Temperature had a higher contribution for paired C and SC in flat and plateau areas. For the other trade-offs, the dominant factor was constant for different zones. The normalized difference vegetation index (NDVI) and soil type were the main factors for paired net primary productivity (NPP) with SC and C respectively. For trade-offs between habitat quality (HQ) and other ESs, and those among multiple ESs, land use type was the dominant drive, and the influence decreased with the increase of topographic relief. Therefore, attention should be paid to the ecological effects of land use change in future urban planning and development. The study will help guide zoning regional spatial planning and achieve mountain sustainable development.

Correlations between soil properties and spectral index (healthy vegetation) in soybean crops

Precision agricultural technologies, such as the use of spatial variability of soil properties, have been extensively studied for soybean cultivation. The objective of this study was to analyze the spatial variability of soil properties cultivated with soybean and to correlate the healthy vegetation (HV) spectral index with the bands B8A (classifying vegetation - 865 nm), B11 (measuring the moisture content of soil and vegetation - 1610 nm), B02 blue (useful for soil and vegetation discrimination - 490 nm). A sampling grid was installed for data collection in an area of 2,126.02 ha, with 270 regular points and 98 random points, totaling 368 points. For the soil, the contents of P (resin), K+, Ca2+, Mg2+, H+, Al3+, pH values, sum of bases (SB), cation exchange capacity (CEC), and base saturation were determined at a depth of 0.0 to 0.20 m. Most of the soil properties had exponential and spherical dependence. Clay percentages and Ca, Mg, and P contents had positive spatial correlation with the healthy vegetation spectral index (HV) while no spatial correlation was observed for pH, B, K, silt, sand, S, H+Al, Al, SB, and CEC. The sensor image used in this study in relation to HV showed good application for observing the spatial variability of the soil properties and soybean yield.

Spatio-temporal evolutionary analysis of surface ecological quality in Pingshuo open-cast mine area, China.

The open-pit mining area is highly affected by human activities, which aggravate soil erosion and disturb surface ecology, bringing many problems and challenges to its environmental management and restoration, which has received widespread attention. The establishment of an objective, timely and quantitative remote sensing monitoring, and evaluation system for the spatio-temporal evolution of the surface ecological environment in the open-pit mining area is of great significance for its environmental protection, management decisions, and sustainable social development. Based on the Google Earth Engine (GEE) platform, this paper uses Landsat images to construct and calculate the remote sensing ecological index (RSEI) of the Pingshuo open-cast mine area (POMA) from 1990 to 2020 and monitor and evaluate its surface ecological environment. Combined with the Theil-Sen median, Mann-Kendall test, and Hurst index, the spatio-temporal process was analyzed. The results showed that the ecological environmental quality of the mining area first decreased and then increased from 1990 to 2020. 1990-2000 was a period of serious ecological degradation, followed by improvement. The overall improvement area reached 87.03%, and the degradation was concentrated in the coal mining area. Between 1990 and 2020, the Hurst index of the mining area was 0.452, indicating that the region has a fragile ecological environment and has difficult maintaining its stability. The global Moran's I mean value of the RSEI of the study area is 0.92, which combined with Moran's scatter plot to indicate that there is a strong positive spatial correlation rather than a random distribution of its ecological environment. During the study period, the impact on the climate of the ecological environmental change of POMA was weak, and human factors such as coal mining, land reclamation, and social construction were the main driving forces for the change in ecological quality. The results of this study reveal the changing trend of surface ecology in the mining area over the past 30 years, which is helpful for understanding its impact mechanism on ecological quality and provides support for the management of the region.

Study on the Spatial Correlation Characteristics of Residential Land Prices in Counties of the Urban Agglomeration in the Middle Reaches of the Yangtze River and Their Influencing Factors

The role of residential land price in regulating local economic development and optimizing urban land spatial layout is becoming more and more prominent. This paper takes the residential land price of 229 counties (districts, cities) of urban agglomeration in the middle reaches of the Yangtze River in 2017 as the research object, and establishes a theoretical model of the influencing factors of county residential land price based on equilibrium price and regional economic theory; and uses methods of spatial autocorrelation analysis and spatial lag model to explore the spatial distribution characteristics and influencing factors of residential land price in the research area and the influencing factors. The research results indicate that: (1) There are significant overall differences in residential land price among different counties within the urban agglomeration in the middle reaches of the Yangtze River, and the overall distribution of residential land price shows a "pyramid" pattern from low to high. (2) The spatial distribution pattern of residential land price in counties within urban agglomerations is greatly influenced by the location conditions and the administrative level of higher-level cities. The residential land price shows an inverted "U" distribution in the east-west direction, with the eastern part being higher than the western part as a whole; There is a gradual downward trend from north to south in the north-south direction. (3) The Global Moran’s I of residential land prices in the research area is 0. 603, with a significant spatial positive correlation and agglomeration phenomenon. and the obvious local spatial agglomeration characteristics. (4) There is a significant positive spillover effect between county-level residential land price in the urban agglomeration of the middle reaches of the Yangtze River. The residential land price in the study area is strongly influenced by both land supply and demand factors, policy systems, and government regulatory capabilities. The relevant conclusions can provide reference for urban agglomeration to optimize urban resource allocation through land price regulation, narrow regional development gaps, and promote the integrated development of the region.

Epidemiological characteristics and spatio-temporal aggregation of severe fever with thrombocytopenia syndrome in Jinan City, China, 2018-2022.

Severe fever with thrombocytopenia syndrome (SFTS) has become a significant public health issue in Jinan City. However, the analysis of epidemiological characteristics and spatio-temporal clustering of SFTS in Jinan has not been studied yet. SFTS data from 2018-2022 in Jinan City were obtained from the China Information System for Disease Control and Prevention. Global spatial autocorrelation and local spatial autocorrelation analyses were performed using ArcGIS 10.2 software, and spatiotemporal hotspot area detection was carried out using SatScan 9.6 software. Between 2018 and 2022, 680 SFTS cases were reported in Jinan City, resulting in 53 deaths and an average case fatality rate of 7.8%. 99.0% of cases occurred between April and October, 91.9% individuals were over 50 years old, and 87.79% were primarily farmers. A positive spatial correlation of SFTS in Jinan was observed (Moran's I value between 0.135-0.197, P<0.001), indicating spatial aggregation, primarily in Licheng, Zhangqiu, Laiwu, and Gangcheng districts in southeastern Jinan. Spatiotemporal scanning detected one class I and two class II aggregation areas, with the class I aggregation area (RR = 5.66, LLR = 192.547, P<0.001) locating in southeastern Jinan City, comprising 31 towns/streets, and an aggregation time from 13 May 2020 to 13 October 2022. Spatial and temporal aggregation of SFTS is evident in Jinan. Based on the spatial and temporal distribution and epidemiological characteristics, prevention and control measures such as public education, monitoring, and training should target key populations in high-incidence epidemic areas.

The spatiotemporal distribution and prognostic factors of Japanese encephalitis in Shanxi Province, China, 2005-2022.

Japanese encephalitis (JE) is a naturally occurring localized disease caused by the Japanese encephalitis virus, which is spread by the Culex tritaeniorhynchus. China has a high rate of JE. Shanxi, located in North China, has a high prevalence of adult JE. Adult JE has more severe complications, mortality, and a higher disease burden, making it a public health issue. This retrospective study examined the dynamic epidemic changes, high-risk areas of JE, and clinical characteristics and prognostic factors of adult JE in Shanxi Province. The findings revealed that July to September was the primary epidemic season of JE and that JE cases were mainly in individuals over the age of 40. The incidence of JE from 2005 to 2022 demonstrated a positive spatial correlation with significant clustering characteristics, with high-incidence clusters in the south and southeast. Multivariate logistic regression analysis revealed that higher cerebrospinal fluid pressure, higher white blood cell counts, higher neutrophil percentage, deep coma, and lower albumin were independent factors for poor prognosis of adult JE. The developed risk prediction model holds great promise in early prognosis assessment of patients, providing a basis for clinical decision-making and early clinical intervention.

Investigating the spatio-temporal interactive relationship between land use structure and ecosystem services in urbanizing China

The negative impacts of urbanization-triggered land use changes on ecosystem services have attracted worldwide attention. However, the interactive relationships between land use structure and ecosystem services remain unclear, which is not conducive to sustainable regional ecological management. This study employed the information entropy and ecosystem services value assessment method to measure the land use structure and ecosystem services at the county level in China between 2000 and 2020, respectively. Then the spatial correlation analysis and decoupling model were used to explore the spatial and temporal interactive relationships between them, respectively. The results indicated that the average information entropy of land use structure (IELUS) and total ecosystem services value (ESV) in China both showed a continuous growth trend during the study period. ESV and IELUS were found to have a significant positive spatial correlation and were dominated by low-value agglomeration. The dominant types of the interactive relationship between IELUS and ESV were strong decoupling and expansion negative decoupling, and the number of counties with expansion negative decoupling decreased rapidly during the study period. These results suggest that differentiated land-use structure management policies ought to be adopted to protect regional ecosystem services.

Spatio-temporal linkage variations between NDVI and tree rings on the leeward side of the northern Patagonian Andes

The Normalized Difference Vegetation Index (NDVI) and tree rings provide different approaches that allow evaluating the productivity of ecosystems. Following this premise, we evaluated the relationship between NDVI and tree-ring widths of Austrocedrus chilensis forests at sectors of the Argentinian northwestern foothills of the Patagonian Andes. To proceed with this study, wood core samples were taken from 153 trees at 6 sites located at different latitudes and along a strong west-east precipitation gradient. The NDVI presented a significant and positive spatial correlation with precipitation, the Standardized Precipitation-Evapotranspiration Index (SPEI-3), soil moisture, and a negative correlation with air temperature at large geographical coverages. Stand location in the latitudinal and meridian coordinates showed a species-specific effect, with greater sensitivity to NDVI in sites located at higher latitudes and under drier conditions. We found stronger associations between stem biomass (tree rings) and canopy biomass (NDVI) in drier sites, assuming a closer link to stressful water conditions. This behavior was accentuated since 1988, which coincides with the increase in air temperature as a result of regional warming processes. These results suggest that site environmental conditions influence how NDVI and ring width are linked, showing the complex dynamics between climate and growth. The results indicate that ring widths of A. chilensis trees have the potential to assess current NDVI variations in the study area, allowing reconstructions of past productivity and potential predictive models of future changes.

Regional Heterogeneity Analysis of Residential Electricity Consumption in Chinese Cities: Based on Spatial Measurement Models

The share of electricity consumption by urban and rural residents in China’s overall electricity consumption is very close to that of the tertiary sector, which has become an important driver of China’s electricity consumption growth. At the same time, due to the mismatch between China’s regional resource endowments and the level of regional development, the regional supply and demand situation for electricity varies. Therefore, it is urgent to clarify the regional differences in residential electricity consumption and the factors affecting it, and accordingly adopt targeted and feasible measures to regulate residential electricity consumption. This article includes data from 285 Chinese prefecture-level cities from 2006 to 2019, and adopts a “three lines” method of region-partitioning (Qinling–Huaihe line, Huhuanyong line, and Shanhaiguan line) to divide four regions. We used spatial econometric models to examine residential electricity consumption and its influencing factors in China from the standpoint of regional heterogeneity. The results show that there is significant regional heterogeneity in residential electricity consumption in China, and the difference between the north of the Shanhaiguan line and other areas is significant. Moreover, there is a positive spatial correlation in the per capita domestic electricity consumption of urban residents, and each influencing factor has obvious regional heterogeneity, among which household appliances are the significant influencing factor. Based on the regional heterogeneity of residential electricity consumption, management measures should be formulated according to local conditions, and the supply of electricity should be ensured by strengthening multidimensional initiatives.

Analysis and Prediction of Spatial and Temporal Evolution of Ecosystem Service Value on the Northern Slopes of the Kunlun Mountains Based on Land Use

The ecological environment in the mountainous areas of southern Xinjiang is very sensitive and fragile, and identifying the ecological asset retention within the mountainous areas is a top priority at the current stage in the context of comprehensive environmental management in arid zones. This study examines the conversion and ecosystem service values between different land types within the mountainous areas based on a time series of land-use data from 1990 to 2020, and the results show that: (1) The value of ecosystem services on the northern slopes of the Kunlun Mountains shows an overall increasing trend. It increased from CNY 308.645 billion in 1990 to CNY 326.550 billion in 2020. Among them, the value of ecosystem services increased significantly between 2000 and 2010, with an increase of CNY 39.857 billion. Regulatory services accounted for more than 66% of the value of each ecosystem service. (2) Land use on the northern slopes of the Kunlun Mountains has changed significantly since 1990. The areas of cropland, forest land, grassland, watershed, and construction land have all shown an upward trend, with the greatest increase in construction land. The area of unutilized land, on the other hand, has slightly decreased. (3) The value of ecosystem services within the northern slopes of the Kunlun Mountains was spatially high in the south, low in the north, and higher in the west than in the east. The study also found a significant positive spatial correlation between ecosystem service values. In the spatial distribution, the increasing areas were mainly distributed in the southeast, and the decreasing areas were in the north. Changes in land types are expected to include an increase in the area of grassland and woodland, a decrease in unutilized land and cropland, and an overall improvement in the ecological environment of the northern slopes of the Kunlun Mountains in the next decade. This study also provides lessons and references for sustainable development and ecological protection in ecologically fragile regions.

Landscape Fragmentation and Spatial Autocorrelation of a Typical Watershed in the Wenchuan Earthquake-Affected Area—A Case Study in the Longxi River Basin

The 2008 8.0 Ms Wenchuan earthquake caused serious ecological degradation in the northwest of China’s Sichuan Province. Elucidating landscape fragmentation and spatial pattern of post-earthquake landscape is of great interest in order to improve ecological restoration and predict the spatial distribution of damaged ecosystems in earthquake-affected areas. We used four real-time remote sensing images to analyze the landscape pattern characteristics and spatial autocorrelation of the Longxi River Basin before and after the Wenchuan earthquake during the period from 2005 to 2015. In the study period, the degree of landscape fragmentation increased 1 year after the earthquake in 2009 but decreased in 2011 and 2015. The spatial distribution of forest, farmland, and shrub-grassland had significantly positive spatial correlation and the characteristics of spatial aggregation from 2005 to 2015. Construction land had no significant spatial correlation before the earthquake in 2005, but significantly positive spatial correlation after the earthquake, while traffic land had no significant spatial correlation across the study period. Unlike the other landscape types, geological disasters changed from a significantly negative spatial correlation before the earthquake to a significantly positive spatial correlation after the earthquake. However, the positive autocorrelation of all landscape types decreased with the increase of space distance, but in different distance-decay rates. The High-high spatial aggregation areas of geological disasters and construction land clustered gradually upstream of the basin and distributed in Longchi town, respectively; those of farmland distributed in the southeast of the basin increased in 2009 but then decreased, while those of forests had the opposite pattern as the dominant landscape type after the earthquake. Our results elucidated the spatial structure and distribution features of the Longxi River Basin to give a theoretical foundation for assessing the effects of ecological restoration and reconstruction management in earthquake-affected areas.

Driving factors to agriculture total factor productivity and its contribution to just energy transition

This study explores the intricate relationship between agricultural productivity and the pursuit of a just energy transition in China. As the world's largest emitter of greenhouse gases and a nation grappling with environmental degradation and socio-economic disparities, China faces the imperative to transition toward a more sustainable and equitable energy system. This paper investigates the role of agriculture in this transition, recognizing its pivotal position as a significant emitter of greenhouse gases while also being vulnerable to the impacts of climate change. By examining the potential synergies and conflicts between agricultural productivity enhancement and the goals of reducing emissions and promoting social justice, this study aims to shed light on strategies that can effectively align agricultural development with the objectives of a just energy transition. The result indicates substantial internal disparities and strong agglomeration effects (referring to areas with similar agricultural total factor productivity) within China's agricultural total factor productivity distribution. Over the past 17 years (2005–2021), the average agricultural productivity has shown a commendable upward trend, marking a 2.8% growth rate. This increase signifies ongoing efforts and advancements in the agricultural sector, leading to improved productivity levels. Our results also show a significant positive spatial correlation in agricultural total factor productivity, suggesting a tendency for spatial agglomeration. The years 2005 and 2021 stand out as periods marked by significant adverse effects resulting from the interplay of diverse factors on agricultural productivity. By integrating findings from various sectors, this study provides insights into the complex interplay between agriculture and energy transition, emphasizing the need for integrated, holistic approaches that prioritize sustainability, fairness, and resilience in China's pursuit of a just energy future.

Spatial-temporal characteristics and influencing factors of wildfire occurrence and correlation with WUI presence in Beijing-Tianjin-Hebei region, China

Wildfires not only directly affect ecology but also have a huge impact on social and economic stability. Enhancing the understanding of wildfire influences can guide the design of targeted strategies in mitigation plans and adaptation strategies. Here, we explored the spatial-temporal characteristics of wildfires in the Beijing-Tianjin-Hebei region of China and the mechanisms of the effect of potential influencing factors on wildfire occurrence based on 2014–2020 wildfire data. The results show that wildfires mainly occur in spring and winter and decrease yearly. Among all the considered influencing factors, the occurrence of wildfire is most significantly affected by the temperature vegetation dry index (TVDI) and is also greatly affected by population and economy. Through interaction detection, it was found that the normalized difference vegetation index (NDVI) greatly interfered with wildfires. The high occurrence risk of wildfire was distributed in a blocky pattern in the middle and east of the study area. In addition, we also found a positive spatial correlation between the high wildland-urban interface (WUI) presence and high wildfire occurrence. These findings have improved our understanding of the impact of multiple influencing factors on wildfires and are supposed to facilitate the development of wildfire management strategies.

Spatiotemporal Dynamics of the Suitability for Ecological Livability of Green Spaces in the Central Yunnan Urban Agglomeration

Green spaces are an essential aspect of building an eco-livable city and play an important role in building for eco-livability in the central Yunnan urban agglomeration. However, there are relatively few studies evaluating the eco-livability of green spaces. The establishment of a green-space eco-livability assessment system may help researchers to analyze the eco-livability of urban green spaces more effectively. To address this research gap, we constructed an ecological livability-evaluation index system for green spaces that incorporates three determinants—economic development, social life, and the ecological environment—using the green spaces of the urban agglomeration in central Yunnan as a case study. We used the entropy method to calculate the suitability for ecological livability of the green spaces in each district and county in the central Yunnan urban agglomeration for 2010, 2015 and 2020. We used the spatial autocorrelation analysis function of ArcGIS 10.8 software to explore the spatial clustering characteristics of the suitability for ecological livability of green spaces in the central Yunnan urban agglomeration. The results showed that, from 2010 to 2020, the suitability for ecological livability of green spaces of the 49 districts and counties in the central Yunnan urban agglomeration increased in some districts and decreased in others. The spatial characteristics were high in the central districts and counties and low in the peripheral districts and counties. The spatial characteristics of the suitability of the target layers for economic development and ecological-environment target were consistent with the overall suitability. Through a spatial autocorrelation analysis, we observed that the suitability of green spaces for ecological livability had a positive spatial correlation and demonstrated significant spatial clustering. In this study, we propose recommendations to improve the suitability for ecological livability of green spaces from two dimensions of government policy and urban development, using a combination of the three target layers. The results of the study provide a reference for decision-making in the construction of eco-livable cities in the central Yunnan urban agglomeration.

Analysis of the spatial effect of clean energy development on green economic growth: evidence from China.

Clean energy development has played a pivotal role in economic transformation. Based on the panel data of 30 provinces in China from 2006 to 2021, the spatial Dubin model was used to empirically investigate the impact of clean energy development on green economic growth. Furthermore, this research selected industrial structure optimization as the mediating variable to analyze the mediating effect between clean energy development and green economic growth. The results are as follows. Firstly, there is a positive spatial correlation for green economic development, in which the level of green economic development in a region can be influenced by neighboring regions. Secondly, there is a significant positive relationship between clean energy development and green economic growth, in which the clean energy development has a positive impact on green economic growth. Thirdly, the mediating effect analysis demonstrates that the clean energy development can influence green economic growth through industrial structure optimization. Based on the findings in this paper, several suggestions are proposed. China should formulate a unified national strategy for green economy by coordinating and balancing regional differences, develop the clean energy industry to promote green economic growth, and pay attention to the intermediary effect of industrial structure to promote green economic growth.

The Drug War and Regional Social Capital in Mexico

AbstractThe onset of the war on drugs in Mexico at the beginning of 21st century had far‐reaching effects on its citizens, including most obviously, an unprecedented increase in the homicide rate. We analyse the correlation between violence on social capital in the 32 federal states of Mexico from January 2004 to December 2016. Given the lack of data in the conflict regions of Mexico, we apply the indirect approach proposed by Guriev and Melnikov (2016), which uses internet search engine data to proxy social capital. Our results show a negative relationship between violence and social capital in Mexico. Moreover, we document a positive spatial correlation for social capital. Overall, we present an example of how the analysis of internet‐based data can contribute to the understanding of socioeconomic developments in conflict regions with unreliable standard data.

Research on the Spatial Effect and Threshold Characteristics of New-Type Urbanization on Carbon Emissions in China’s Construction Industry

As the strategic task of China’s modernization, the implementation of new-type urbanization has an important impact on carbon emissions from the construction industry. To fill the gap in considering the spatial correlation and threshold characteristics of new-type urbanization on carbon emissions from the construction industry, this paper constructs a comprehensive evaluation indicator of new-type urbanization, and the spatial economic model and the threshold regression model are adopted to analyze the panel data of 30 provinces in China from 2002 to 2020. The results indicate that (1) carbon emissions from China’s construction industry exhibit a significant positive spatial correlation, with more than half of provinces distributed as H-H and L-L types. (2) New-type urbanization has significant positive direct and indirect effects on carbon emissions in the construction industry; the labor efficiency, energy intensity, and development level of the construction industry and trade openness also have a significant spillover effect on carbon emissions from the construction industry. (3) At this stage, new-type urbanization exhibits a threshold effect on carbon emissions from the construction industry due to the different levels of development and energy intensity of the construction industry. After crossing the threshold value, the promotion effect of new-type urbanization on carbon emissions from the construction industry gradually increases. This paper provides a reference for promoting carbon emission reduction in the construction industry in the process of new-type urbanization.

Coupling Coordination and Spatiotemporal Evolution of Low-Carbon Logistics, Industrial Agglomeration, and Regional Economy in the Yangtze River Economic Belt

The logistics industry plays a crucial role in the global economy, but also poses significant challenges to the economy, society, and environment due to increasing carbon emissions. Therefore, coordinated development between the logistics industry and regional economy has become a strategic choice for achieving sustainable development. Taking the Yangtze River Economic Belt as an example, this study constructs an evaluation index system of “low-carbon logistics–industrial agglomeration–regional economy” to explore the coupling coordination relationship and spatiotemporal distribution characteristics of the three systems from 2006 to 2020. Furthermore, it analyzes the spatial correlation features and evolutionary trends of the coordinated development among the three systems. The results indicate that during the study period, the coupling coordination degree among the three systems in the Yangtze River Economic Belt showed a fluctuating upward trend but with a relatively low level of coordination. There were significant regional differences, presenting a stepped distribution pattern of “high in the east and low in the west.” The coordinated development among the three systems exhibited a significant positive spatial correlation, with “H–H” and “L–L” agglomerations being dominant. The spatial distribution of coupling coordination degree remained relatively stable, with the overall center of gravity located in the southeast of Hubei Province. The spatial evolution pattern showed a distinct “northeast–southwest” direction. Finally, suggestions for the coordinated and sustainable development of the three systems are put forward.

Aquaculture industry under the blue transformation in Jiangsu, China: Structure evolution and spatial agglomeration

Abstract This article focuses on studying the spatial distribution and evolution of the aquaculture industry in Jiangsu, a significant coastal province in China, within the context of the blue transformation. By collecting spatial data on the aquaculture industry and using ArcGIS software, this article analyses the characteristics of spatial changes and the driving forces behind them in Jiangsu’s aquaculture industry while providing predictions for future pattern evolution. The findings reveal that the overall distribution of the aquaculture industry in Jiangsu Province exhibits strong directionality but weak density, primarily oriented in the northwest–southeast direction. There is an evident trend of the industry shifting from the northern to the western regions and from the central to the northwest areas of the province. This indicates that initially, the aquaculture industry was primarily concentrated in the inland regions, while marine aquaculture gradually influenced the industry structure after 2010. Although the aquaculture industry shows signs of diversification, industry agglomeration is only observed in approximately 30.8% of the cities that exhibit a positive spatial correlation, which is a relatively small proportion compared to the total number of cities. However, despite the overall negative correlation in spatial distribution, the absolute difference between Moran’s I of all cities and zero is less than 0.4. This suggests that the spatial differences are not significant, regardless of the spatial autocorrelation characteristics of the overall distribution of a city. Based on the findings, this article recommends the urgent need for the development of policies that promote industry agglomeration in order to achieve effective regulation and pollution control in aquaculture.

Assessing the spatial spillover effects and influencing factors of carbon emission efficiency: a case of three provinces in the middle reaches of the Yangtze River, China.

Studying urban carbon emission efficiency is vital for promoting city collaboration in combating climate change. Prior research relied on traditional econometric models, lacking spatial spillover effects understanding at the urban scale. To provide a more comprehensive and visually insightful representation of the evolving characteristics of carbon emission efficiency and its spatial clustering effects and to establish a comprehensive set of indicators to explore the spatial spillover pathways of urban carbon emission efficiency, we conducted an analysis focusing on 42 cities in the middle reaches of the Yangtze River. By employing the index decomposition method, the super-efficiency SBM model, spatial autocorrelation analysis, and the spatial Durbin model, the study calculates the urban carbon emission efficiency from 2011 to 2019 and analyzes the spatial spillover effects and influencing factors of urban carbon emission efficiency. The main conclusions are as follows: (1) Jiangxi Province displayed stable urban carbon emission efficiency evolution, while Hubei and Hunan showed significant internal disparities. (2) Positive spatial correlation exists in urban carbon emission efficiency, with an imbalanced distribution. (3) Various factors influence urban carbon emission efficiency. Technological innovation and economic development have positive direct and indirect impacts, whereas industrial structure, urbanization, population, and energy consumption have negative effects. Spatial spillover effects of vegetation coverage are insignificant. These methods and findings offer insights for future research and policy formulation to promote regional sustainable development and carbon emission reduction.