Autocorrelation Model Research Articles

Spatio-temporal analysis and simulation of urban ecological resilience in Guangzhou City based on the FLUS model

Prediction of urban ecological risk, which is increasing with the rapid development of China’s economy, has become more complex and difficult, resulting in great damage to the safety of people’s lives and property and the quality of the ecological environment. Elucidation of the change mechanism of the urban ecological resilience level from the perspective of the resilience characteristics and exploration of the spatiotemporal differences of the urban ability are necessary to prevent and resolve ecological risks. To this end, here, a model for the evaluation of urban ecological resilience was constructed by considering three aspects: resistance, adaptability, and resilience. The spatiotemporal change pattern of urban ecological resilience in Guangzhou from 2000 to 2020 was evaluated. Furthermore, a spatial autocorrelation model was used to explore the management model of Guangzhou’s ecological resilience in 2020. Finally, based on the FLUS model, the spatial pattern of urban land use under the 2035 benchmark and innovation- and entrepreneurship-oriented scenarios was simulated and the spatial distribution of the ecological resilience level under different urban development scenarios was evaluated. We found that from 2000 to 2020, areas with a low ecological resilience expanded to the northeast and southeast, whereas areas with a high ecological resilience significantly decreased; from 2000 to 2010, original high-level regions in the northeast and east of Guangzhou were transformed into medium level regions. Further, in 2020, the southwestern region of the city will show a low level of resilience and high density of pollutant discharge enterprises, indicating that the ability to prevent and resolve environmental and ecological risks in this region is relatively low. Additionally, the overall ecological resilience of Guangzhou under the innovation- and entrepreneurship-oriented “City of Innovation” urban development scenario is higher than that under the benchmark scenario in 2035. The results of this study provide a theoretical basis for the development of resilient urban ecological environment.

Research on the Coupling Coordination of Green Finance, Digital Economy, and Ecological Environment in China

This study analyzes the coupling coordination of green finance, digital economy, and ecological environment, and constructs an evaluation index system of coupling coordination degree. Based on the panel data of 30 provinces in China from 2011 to 2020, this study applies the coupling coordination model, spatial autocorrelation model, and gray correlation model to analyze the spatio-temporal evolution characteristics of coupling coordination degree and driving factors. The results indicate that the overall level of green finance, digital economy, and ecological environment maintains steady development, among them, the digital economy is developing the fastest. The coupling coordination degree among the three subsystems exhibits an ascending trend and transitions from dissonance to coordination and displays significant global and local spatial autocorrelation characteristics. Regional disparities exist between the driving factors that influence the coupling coordination degree. Therefore, the existing green financial system should be optimized, coordination of green finance and digital economy synergies should be improved, and each region should devise a development strategy tailored to its regional characteristics.

Experimental Evaluation of the Scale of Fluctuations in Rock Using Ultrasonic Tests

The properties of rock vary with spatial location, and spatial variability is a critical source of uncertainty that affects the safety of rock engineering. However, the key parameter characterizing spatial variability—the scale of fluctuation—is rarely studied in rock engineering. One of the reasons for this phenomenon is the lack of a simple and practical test method to determine the scale of fluctuation of rock. This deficiency hinders the development of reliability-based design in rock engineering. An evaluation method of the scale of fluctuation in rocks based on the compressive wave velocity of drilling cores is proposed to address this problem. First, drilling cores at the Yingliangbao hydropower station were collected, and the wave velocities were measured based on ultrasonic tests. Then, three different statistical methods, namely, the method of moments, maximum likelihood estimation, and Bayesian analysis, were used to evaluate the scale of fluctuation in rocks based on measured wave velocities. Results show that the optimal autocorrelation models that describe the autocorrelation structures of Yingliangbao granite are a single exponential function or cosine exponential function, and that the corresponding scales of fluctuation of Yingliangbao granite range from 6.33 to 12.44 m. In addition, the stationarity of the wave velocity is verified by the modified Bartlett test, and the scale of fluctuation based on in situ ultrasonic tests and the treatment of wave velocities at joint locations is discussed. This study presents a practical and reliable method to evaluate the scale of fluctuation in rocks and provide a reference for reliability evaluations in rock engineering projects.

Study on the spatio-temporal patterns of urban air pollution and its spatial mismatch with air pollutant emissions in the Yellow River Basin, China

In order to promote the precise governance of air pollution in the Yellow River Basin(YRB), it is of great significance to reveal the spatio-temporal patterns of urban air pollution in the basin and its spatial mismatch characteristics with air pollutant emissions. Based on spatial autocorrelation model and spatial mismatch model, this paper selected air pollution-related monitoring data from 69 cities in YRB from 2015 to 2020 as samples, and used ArcGIS, Stata, GeoDa and other softwares to analyze the spatio-temporal patterns of urban air pollution and its spatial mismatch characteristics with air pollutant emissions in YRB. The results showed that: (1) Temporally, the average annual Air Quality Index (AQI) values of cities in YRB ranged from 78.22 to 97.08 in 2015–2020, among which, the average annual AQI values of cities in the upper, middle and lower reaches of the basin decreased from 79.86, 89.23 and 122.14 in 2015 to 66.87,82.98 and 98.43 in 2020. (2) Spatially, there were obvious spatial differences in urban air pollution in YRB, and the AQI was roughly distributed in a geographical gradient of upper reaches < middle reaches < lower reaches, and there were significant spatial correlations in urban air pollution, mainly showing ‘high-high’ and ‘low-low’ aggregating characteristics. Among them, the lower reaches of YRB had formed a concentrated ‘high pollution zone’. (3) There was an obvious spatial mismatch between urban air pollution and air pollutant emissions in YRB, among which the spatial mismatch was obvious in cities such as Wuhai, Zibo, Shizuishan, Yangquan, Taiyuan, Datong, Jiyuan, Kaifeng, Puyang and Xi’an. (4) To improve the overall situation of air pollution in the cities of YRB, this paper proposed that the geographical gradient difference of air pollution in the upper, middle and lower reaches of YRB needs to be fully considered, following the principle of ‘focused treatment, gradual progress, enhanced prevention’, and according to the spatial mismatch characteristics of urban air pollution and air pollutant emissions, it is necessary to build a ‘differentiated’ governance strategy system for urban air pollution in the basin, which is ‘tailored to local conditions and categorized measures’.

Investigating the Synergistic Evolution Mechanism of Multi-Scale Cities: A Case Study of Three Urban Agglomerations in Eastern China

Urban growth has evolved from cities to metropolitan areas and urban agglomerations, exhibiting a multi-scale pattern. Urban scaling law can reflect the nonlinear relationship between urban indicators and population size, which is very important for urban planning through analyzing the evolution of urban system characteristics. However, existing studies mainly focused on scalar law within countries, neglecting the multi-scale synergistic evolution of complex urban systems. The purpose of this study is to investigate the scalar relationship between urban indicators and population size at multiple scales from the perspective of individual cities, metropolitan areas, and urban agglomerations, using data from 45 cities in three urban agglomerations in eastern China. Based on the urban scaling law, local spatial autocorrelation model is used to analyze and explore the collaborative evolution of multiple scales. Results show that from the perspective of time evolution, the three urban agglomerations exhibit greater scaling effects than metropolitan areas, with a scaling exponent (β) greater than 1 for urban indicators including economy, land, infrastructure, ecological pressure, and innovation. From the perspective of spatial differences, the spatial development gap between the metropolitan area scale and the urban agglomeration scale is relatively small compared with the city scale. In addition, the Beijing–Tianjin–Hebei urban agglomeration (BTH) mainly displays the synergistic development of the dual-core structure of Beijing and Tianjin. The Yangtze River Delta (YRD) exhibits significant disparities between its cities, resulting in a low degree of overall synergy. In contrast, the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) leads in terms of synergistic evolution. This study is crucial to help understand the development of urban systems at different scales and to support regional planning and the achievement of coordinated development.

Spatial–Temporal Evolution of the Coupling Coordination Degree between Water and Land Resources Matching and Cultivated Land Use Eco-Efficiency: A Case Study of the Major Grain-Producing Areas in the Middle and Lower Reaches of the Yangtze River

Improving the coupling coordination degree between water and land resources matching (WLRM) and cultivated land use eco-efficiency (CLUE) is crucial to ensuring national food security and constructing an ecological civilization. This study is based on the data of 71 prefecture-level cities in the major grain-producing areas in the middle and lower reaches of the Yangtze River from 2008 to 2020. The unit area water resource method, the slacks-based measurement (SBM)-undesirable, the Theil–Sen median analysis, the Mann–Kendall trend test, the coupling coordination degree model, and the spatial autocorrelation model are adopted to measure and analyze the WLRM, the CLUE, and the coupling and coordination level, and their spatial–temporal evolution characteristics quantitatively. Results show the following: (1) From 2008 to 2020, the average value of WLRM in the study areas is 18,200 m3/hm2, which is at a medium level, and the provinces show the characteristics of “high in the south and low in the north, with decreasing gradients”. (2) The annual average of CLUE is 0.777, which is in the medium level, and each province has the remarkable characteristics of “one high and four low”. (3) The coupling coordination degree of WLRM and CLUE is in the primary coordination level, which shows a significant positive correlation in space. In the local perspective, it shows the agglomeration characteristics of “high in the south and low in the north, nodule distribution”. In the future, the neighboring prefecture-level cities should actively build a synergistic mechanism for agricultural development, strengthen the reasonable use of water and land resources and pollution control techniques, drive the transformation of low–low aggregation areas to high–high aggregation areas, and improve the overall coordination of the study areas. This approach aims to promote the construction of ecological civilization and guarantee grain security and sustainable development of agriculture in China.

Palenque and Afro-Latino in Los Angeles: Social and Environmental Justice through Mixed Methods

Afro-Latinos, African descendants with Latino ethnicity, have been documented since the 1700s. No geographic studies, however, address the spatial relationships between socioeconomic conditions and environmental risk of Afro-Latinos in Los Angeles, where assumptions of underserved conditions drawn from other minority groups are applied. Palenques, settlements of runaway enslaved Africans in Colombia, became outcast and marginalized through history. In this research we introduce the historical concept of Palenques and propose it as a new sense of place for Afro-Latinos. The methods include descriptive analysis, regression models, spatial autocorrelation models, and factor analysis. They produced a cumulative impact model to estimate life quality. The results show that Los Angeles Palenques have a lower financial status, a higher isolation rate, and higher levels of environmental pollution than the average neighborhoods. The regression models suggest that Latinos of any race have the strongest positive correlation to disadvantaged life quality, whereas the Black population has an extremely weak correlation to vulnerability. Furthermore, the spatial autocorrelation models reveal a strong spatial clustering of highly disadvantaged communities near downtown Los Angeles, where most Latinos of any race live. The main finding of this project challenges previous assumptions about social inequality and environmental injustice toward the multiracial Afro-Latino population.

Spatial modeling of infiltration and its relationship with surface coverage of rock fragments and porosity in soils of an andean micro-watershed in Tolima (Colombia)

Infiltration depends on the surface conditions of the soils, such as surface rock fragments cover and some of the properties of the matrix such as total porosity. Research reports inconclusive results regarding the influence of rock fragment cover on soil water infiltration that usually does not involve the spatial component in the analyses. The objective of this research was to spatially model the steady state infiltration rate and its relationship to rock fragment cover and the total porosity in soils of an Andean micro-basin. Hydrological response units were used to carry out stratified sampling in the basin. Infiltration was measured in the field using double ring infiltrometers. Surface rock fragment cover was estimated visually, and total porosity was determined using a tension table. Results showed that higher values in the rate of soil infiltration predominated on the slopes of the upper parts of the basin, while in the lower parts the values were lower. Infiltration had a logarithmic-exponential type distribution. The spatial autocorrelation model showed the best performance (r = 0.863) to model the relationship between the variables. This was the first research involving spatial modeling of the relationship between rock fragments cover and soil infiltration, showing that infiltration was a spatially correlated variable, related to changes in total porosity and rock fragments cover on the ground surface. This provided new information on the behavior of soils with rock fragments in tropical areas that have been little studied.

Evaluation and Analysis of Development Status of Yellow River Beach Area Based on Multi-Source Data and Coordination Degree Model

The Yellow River beach area is the basic component of the Yellow River Basin. Promoting the comprehensive improvement and high-quality development of the Yellow River beach area is an important guarantee of the long-term stability of the Yellow River and an important part of promoting the high-quality development and ecological protection of the Yellow River Basin. In this paper, four new indexes (flood risk intensity index, accessibility index, biological abundance index, and remote sensing ecological index) were extracted from geospatial data and remote sensing images, and a quantitative evaluation model (Ecology-Economy -Society-Flood, EESF) for the development of the Yellow River beach area were constructed based on social statistics, such as flood control and control in the beach area. The coordinated development level of the Yellow River beach area was evaluated by combining the “CRITIC–entropy weight method” and “‘single index quantification–multi-index synthesis–multi-criteria integration’ (SMI-P)—coordination degree model” methods. The spatial autocorrelation model was used to analyze the spatial distribution characteristics of the coordinated development level, and the global sensitivity and uncertainty analysis (GSUA) was carried out for the sensitivity and uncertainty of the parameters. Taking the Yellow River beach area in Shandong Province in 2009 and 2019 as the study object, the research results showed that during this period, the coordinated development level of the Yellow River beach area in Shandong Province showed a gradual upward trend, from 0.344 to 0.580, reaching a basic coordinated state; the overall coordinated development level of the beach area showed significant autocorrelation and small spatial heterogeneity. Grain production was the most sensitive parameter in the coordinated development model of the beach area. The beach area should rationally develop and utilize agricultural resources and promote the integration of ecological industries.

Exploring the relationship and influencing factors of cultivated land multifunction in China from the perspective of trade-off/synergy

In China, the fast growth of the economy and society is causing a change in the multifunction of cultivated land (MCL), but there is still a lack of proper understanding of the structural connections between these internal functions. Based on exploring the theoretical concept of MCL and quantitative measurement, this paper applied the trade-off/synergy model and the bivariate spatial autocorrelation model to investigate the relationships between the various dimensions of MCL, and the influential factors was revealed by Geographical Detectors. Our research demonstrated that the function of China's cultivated land has obviously changed from a single grain production to a complex including social security, ecological and cultural functions during 2010–2020. Through quantitative measurement of MCL, the results show that, on the one hand, the total amount of MCL increases significantly over time; on the other hand, MCL shows a typical spatial differentiation characteristic of “high in the southern and low in the northern”. According to the analysis of trade-off/synergy, overall, the MCL presents a positive synergy situation, and this situation has been enhanced over time. As to the influencing factors, the socio-economic development, especially the rural development, significantly affected the trade-off/synergy. Moreover, multi-factor interaction considerably improves the explanatory power of the trade-off/synergy relationship for MCL. These results provide evidence for establishing a more efficient use of cultivated land and can also provide food security management strategies.

Entropic spatial auto-correlation of voter uncertainty and voter transitions in parliamentary elections

This paper studies a novel spatial auto-correlation model of voter uncertainty across districts. We use the Moran I index to measure the auto-correlation of Shannon, relative Shannon, Tsallis and relative Tsallis entropies of regional electoral outcomes with respect to geographic adjacency, proximity and sectarian adjacency. Using data from the Lebanese parliamentary elections, we find strong geographic and gravitational adjacency correlations. More importantly, there is a notably strong correlation in sectarian adjacency in both 2018 and 2022 elections, with a very high level of confidence. This result asserts the dominance of the sectarian factor in Lebanese politics. We also introduce the method of maximized general entropy estimation that allows us to determine the Markov transition matrix of voters between consecutive elections.

Spatial distribution of common childhood illnesses, healthcare utilisation and associated factors in Ethiopia: Evidence from 2016 Ethiopian Demographic and Health Survey.

Childhood illnesses, such as acute respiratory illness, fever, and diarrhoea, continue to be public health problems in low-income countries. Detecting spatial variations of common childhood illnesses and service utilisation is essential for identifying inequities and call for targeted actions. This study aimed to assess the geographical distribution and associated factors for common childhood illnesses and service utilisation across Ethiopia based on the 2016 Demographic and Health Survey. The sample was selected using a two-stage stratified sampling process. A total of 10,417 children under five years were included in this analysis. We linked data on their common illnesses during the last two weeks and healthcare utilisation were linked to Global Positioning System (GPS) information of their local area. The spatial data were created in ArcGIS10.1 for each study cluster. We applied a spatial autocorrelation model with Moran's index to determine the spatial clustering of the prevalence of childhood illnesses and healthcare utilisation. Ordinary Least Square (OLS) analysis was done to assess the association between selected explanatory variables and sick child health services utilisation. Hot and cold spot clusters for high or low utilisation were identified using Getis-Ord Gi*. Kriging interpolation was done to predict sick child healthcare utilisation in areas where study samples were not drawn. All statistical analyses were performed using Excel, STATA, and ArcGIS. Overall, 23% (95CI: 21, 25) of children under five years had some illness during the last two weeks before the survey. Of these, 38% (95%CI: 34, 41) sought care from an appropriate provider. Illnesses and service utilisation were not randomly distributed across the country with a Moran's index 0.111, Z-score 6.22, P<0.001, and Moran's index = 0.0804, Z-score 4.498, P< 0.001, respectively. Wealth and reported distance to health facilities were associated with service utilisation. Prevalence of common childhood illnesses was higher in the North, while service utilisation was more likely to be on a low level in the Eastern, South-western, and the Northern parts of the country. Our study provided evidence of geographic clustering of common childhood illnesses and health service utilisation when the child was sick. Areas with low service utilisation for childhood illnesses need priority, including actions to counteract barriers such as poverty and long distances to services.

Is there regional convergence between Morocco and its OECD partner countries in terms of well-being?

Morocco wants its 12 regions to play the role as the main lever of its public policies to initiate harmonized spatial multidimensional development. In the context of this goal and Morocco's openness over the past two decades to bilateral and multilateral cooperation in an effort toward regional integration, this article studies the convergence of 389 regions in 36 countries (Morocco and 35 of its partner member countries of the Organization for Economic Co-operation and Development (OECD)) between 2000 and 2019 in terms of well-being. To this end, we considered the territorial dimension of β-convergence models for well-being and its four domains (economic, social, environmental, and governance). Then, we adapted the absolute β-convergence model taking into account the existence of spatial heterogeneity according to five specifications of spatial models. Thus, apart from environmental domain, we showed that β-convergence of regions is significant for well-being and three of its domains (economic, social, and governance). These convergences are made by a spatially autocorrelated error model (SEM). However, the speed and period of convergence are relatively low for social domain, partly explaining the very exacerbated tensions at the territorial level. The fastest convergence was achieved in governance domain, followed by economic domain. This suggests that emerging countries must pay particular attention to national public action in favor of social cohesion at the territorial level. The lack of convergence in environmental domain calls for common actions for all countries at the supranational level to protect the commons at the territorial level.

Assessment of ecological resilience in Nanchang based on "risk-connectivity-potential".

With the rapid development of urban construction, land for construction continues to expand and the ecological land is shrinking. There are various risks and degradation phenomena. The evaluation of urban ecological resilience thus becomes particularly important. From the perspective of urbanization-induced landscape changes, we evaluated the ecological resilience level of Nanchang from 2005 to 2020 by means of "risk-connectivity-potential" model, spatial autocorrelation model and kernel density assessment, as well as its spatial-temporal variations. The results showed that from 2005 to 2020, the spatial pattern of risk, connectivity, and potential subsystems in the study area was stable, with significant differences. The ecological risk was high in the middle and low in the east and west, while the spatial distribution of connectivity and ecological potential was opposite to the ecological risk, showing a pattern of low in the middle and high in the east and west. The overall level of ecological resilience was not high, with medium and low resilience levels as the main body. The low level continued to grow, and high value areas gradually decreased. The "high-high" cluster type of ecological resilience was decreasing, while the "low-low" cluster type was gradually increasing. Results of Kernel density assessment showed that the overall resilience level of Nanchang had little change, with obvious spatial difference. The number and distribution of different landscape types should be adjusted according to the characteristics of the ecological resilience level of different regions, in combination with the urban planning layout. The connectivity and agglomeration of spatial distribution of different landscape types should be changed to achieve the optimization and improvement of the overall regional ecological resilience level. The results could provide a theoretical basis for urban spatial planning and layout.

Spatiotemporal Variations and Determinants of Under-Five Stunting in Ethiopia.

Stunting has been a major concern in sub-Saharan Africa. However, little evidence exists on the spatiotemporal variations in under-five stunting within a national context. This paper examines the spatiotemporal variations in under-five stunting and determinants using data from the Ethiopia Demographic and Health Surveys (2000-2016). Spatial autocorrelation and multilevel logistic regression models were used to conduct the analyses. The stunting prevalence has decreased from 51% to 37%, while the prevalence of severe stunting has decreased by more than half (from 28% to 12%). Wide regional variations in stunting have been consistently observed over the years, which exhibited a higher level of stunting in Tigray (48%), Afar (42%), and Amhara (42%). The results show considerable local and regional variations in under-five stunting levels with diverse patterns of improvements in regional stunting levels over time. Stunting levels were associated with child-level factors such as the sex of a child, birth size, age of a child, birth order, preceding birth interval, and place of birth. Maternal educational attainment, nutritional status, household wealth, toilet facility type, and place of residence were linked to under-five stunting. The regional-level infant mortality rate was associated with under-five stunting. Specially tailored policies and interventions should be devised to address persistent spatial inequalities in stunting by focusing on higher risk populations.

Integration of Marine and Terrestrial Ecological Economies in the Cities of the Bohai Rim, China, Based on the Concept of Viscosity

The integration of sea and land ecological economies is crucial for the development of a high-quality sea–land economy. This study explores and proposes the concept of a sea–land-integrated ecological economy. By constructing the evaluation index system for developing a sea–land-integrated ecological economy, the development level, evolution process, and development trend prediction of a sea–land-integrated ecological economy were evaluated and analysed in cities around the Bohai Sea from 2009 to 2019 using methods such as a model for assessing the development level, a spatio-temporal autocorrelation model, and an exploratory spatio-temporal data analysis model. The results of the study show that (1) the development level of the ecological economy of the cities of Bohai Rim’s sea–land integration generally had an upward trend; however, the magnitude significantly varied between cities; (2) the spatio-temporal autocorrelation pattern formed three major agglomerations with Dalian in the north, Yantai and Qingdao in the south, and Tianjin and Tangshan in the centre as the core cities and contained low agglomerations and scattered L–H spatio-temporal heterogeneous units; and (3) the integration prediction curve for 2020–2029 indicates that the level value for integration of most cities will improve over time.

Evaluation of water ecological security in Huaihe River Basin based on the DPSIR-EES-SMI-P model

Abstract Scientific evaluation of water ecological security has essential theoretical and practical values for protecting and restoring the Huaihe River aquatic ecosystem. Based on the DPSIR-EES model, the water ecological security index (WESI) system of 16 cities in the Anhui section and Shandong section of the Huaihe River Basin was constructed. The ‘single index quantification-multi-index comprehensive-multi-criteria integration’ (SMI-P) evaluation method was used to calculate the WESI of the study area from 2011 to 2020. The spatial autocorrelation model and Markov chain were used to study the spatial distribution characteristics of water ecological security level and the probability of evolution over time. The results show that: (1) The overall WESI of the Huaihe River Basin has increased year by year, but the water ecological security level has been in the early warning (III) stage. Response level and environmental level are the main constraints. (2) During the study period, the spatial distribution of WESI in the Huaihe River Basin was high in the north and south ends and low in the middle. The degree of spatial agglomeration gradually changed from positive correlation to negative correlation. (3) The transfer of water ecological security level has ‘path dependence’ and, ‘self-locking’.

Spatial-Temporal Characteristics and Driving Factors of Coupling Coordination between the Digital Economy and Low-Carbon Development in the Yellow River Basin

Enhancing the level of coupling coordination between the digital economy and low-carbon development is not only an inevitable choice for implementing the strategy of ecological protection and high-quality development in the Yellow River Basin, but also a key path to achieve China’s “Double Carbon” goal. The level of coupling coordination between the digital economy and low-carbon development in 78 cities in the Yellow River Basin from 2011 to 2020 is measured by a coupling coordination model, and the spatial-temporal characteristics and driving factors are analysed using the Dagum Gini coefficient, spatial autocorrelation model and geographic detector. This study found the following: (1) Rapid growth of the digital economy, with the slow growth of low-carbon development. The degree of coupling coordination of the two systems steadily improved and moved from a stage of near-disorder to primary coordination. (2) The degree of coupling coordination is spatially characterised by lower reaches &gt; middle reaches &gt; upper reaches, and provincial capitals and some coastal cities have a higher level of coupling coordination. Spatial differences in coupling coordination tend to widen, with inter-regional differences being the main source of overall differences. (3) There was a significant positive spatial correlation in the degree of coupling coordination. Local spatial clustering characteristics were dominated by High-High (H-H) clustering areas in Shandong and Low-Low (L-L) clustering areas in south-eastern Gansu. (4) The degree of coupling coordination was driven by both internal and external factors of the two systems, with internet penetration and the size of the telecommunications industry within the digital economy system as the most important factors driving the coupling coordination, and the interactions between the different drivers were all enhanced.

Farmers’ social networks and regional spillover effects in agricultural climate change mitigation

Climate change poses a severe threat to global agricultural production and rural livelihoods, and since agriculture itself is a significant source of greenhouse gas (GHG) emissions, it can also play an important role in climate change mitigation. This article investigates how farmers’ social networks influence the adoption of on-farm mitigation strategies. More precisely, we use a network autocorrelation model to explore the relationship between a farmer’s own mitigation behavior and the mitigation behavior and knowledge of his fellow farmers. The analysis is based on a regional case study in Switzerland and uses data obtained from personal network interviews combined with survey and census data of 50 farmers. Half of them are members of a local collective action initiative for agricultural climate change mitigation, while the others do not participate in the initiative. We find that, on average, farmers with a larger network adopt more mitigation measures, and furthermore, mitigation adoption is linked with the level of knowledge within farmers’ networks. Indeed, the likelihood that non-members will adopt mitigation measures increases if they are closely associated with members of the collective action, suggesting a local spillover effect. It follows that strengthening knowledge exchange among farmers and supporting local farmers’ initiatives can potentially contribute to the diffusion of agricultural climate change mitigation practices.

Spatial relationship of the saturated hydraulic conductivity and rock fragments on the soil surface in an Andean microwatershed

ABSTRACT Saturated hydraulic conductivity (Ks) is an important soil variable. Multiple investigations have analysed the influence of rock fragments on saturated hydraulic conductivity, but they hardly involve the spatial component. This research spatially modelled the Ks and its relationship with the contents of rock fragments, organic carbon, and total porosity in the surface horizon of the soils of a tropical Andean micro-basin. Hydrologic response units were used to run a stratified-type sampling. Ks was determined using the constant head method and the total porosity using the tension table. Disturbed samples were used to determine rock fragments and organic carbon content. Results showed that the Ks had an exponential distribution, with high values located in areas of the middle and upper parts of the basin. The distribution was spatially related to the content of rock fragments, the total porosity and the organic carbon content using the spatial autocorrelation model with which it was obtained the best fit results between the observed values of Ks and their predicted values on the soil surface (r = 0.883). The inclusion of these three variables in pedotransfer functions and hydrological models would reduce the uncertainty in estimating the saturated flow of soil water in stony soils.