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Copyright of Journal of Resources & Ecology is the property of Journal of Resources & Ecology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background: Describing the transmission dynamics of infectious diseases across different regions is crucial for effective disease surveillance. The multivariate time series (MTS) model has been widely adopted for constructing cross-regional infectious disease transmission networks due to its strengths in interpretability and predictive performance. Nevertheless, the assumption of constant parameters frequently disregards the dynamic shifts in disease transmission rates, thereby compromising the accuracy of early warnings. This study investigated the applicability of time-varying MTS models in multi-regional infectious disease monitoring and explored strategies for model selection. Methods: This study focused on two prominent time-varying MTS models: the time-varying parameter-stochastic volatility-vector autoregression (TVP-SV-VAR) model and the time-varying VAR model using the generalized additive framework (tvvarGAM), and intended to explore and verify their applicable conditions for the surveillance of infectious diseases. For the first time, this study proposed the time delay coefficient and spatial sparsity indicators for model selection. These indicators quantify the temporal lags and spatial distribution of infectious disease data, respectively. Simulation study adopted from real-world infectious disease surveillance was carried out to compare model performances under various scenarios of spatio-temporal variation as well as random volatility. Meanwhile, we illustrated how the modelling process could help the surveillance of infectious diseases with an application to the influenza-like case in Sichuan Province, China. Results: When the spatio-temporal variation was small (time delay coefficient: 0.1–0.2, spatial sparsity:0.1–0.3), the TVP-SV-VAR model was superior with smaller fitting residuals and standard errors of parameter estimation than those of the tvvarGAM model. In contrast, the tvvarGAM model was preferable when the spatio-temporal variation increased (time delay coefficient: 0.2–0.3, spatial sparsity: 0.6–0.9). Conclusion: This study emphasized the importance of considering spatio-temporal variations when selecting appropriate models for infectious disease surveillance. By incorporating our novel indicators—the time delay coefficient and spatial sparsity—into the model selection process, the study could enhance the accuracy and effectiveness of infectious disease monitoring efforts. This approach was not only valuable in the context of this study, but also has broader implications for improving time-varying MTS analyses in various applications. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Soil & Water Conservation (1009-2242) is the property of Institute of Soil & Water Conservation and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

[Objective] This paper explores the spatial-temporal pattern and influencing factors of green land use efficiency in Beijing-Tianjin-Hebei, and provides theoretical reference for promoting the green development and transformation of land use and optimizing the spatial development and protection pattern of land. [Methods] Taking Beijing-Tianjin-Hebei as the research area, we constructed a land green utilization efficiency evaluation index system, used the SBM-DEA model and exploratory spatial data analysis (ESDA) to reveal the characteristics of spatial and temporal patterns of land green utilization efficiency in Beijing-Tianjin-Hebei, and explored the influencing factors by using the Tobit multiple regression model. [Results] (1) Since 2008, the overall green land use efficiency in Beijing-Tianjin-Hebei has been on the rise, especially since 2012, which has reached an effective state. (2) The spatial non-equilibrium characteristics of “high in the middle and low in the surroundings” are shown in the space, with Beijing and Tianjin in the high-efficiency centers, and the positive spatial correlation in the whole area is significant and increasing, the local spatial agglomeration characteristics are obvious, and the efficiency value correlation characteristics among the neighboring cities are significant. (3) Economic development and ecological governance have a significant positive impact on the improvement of land green use efficiency, with the level of economic development having the most prominent impact, while land urbanization and population agglomeration reflect a significant negative impact. [Conclusion] It should accelerate the promotion of the green development transition in Beijing-Tianjin-Hebei, further deepen the Beijing-Tianjin-Hebei synergistic development, and focus on improving the level of economic development in inefficient regions. It is recommended that the optimization of the spatial development and protection pattern of land be strengthened, a strict land-use system be implemented, the restoration and maintenance of land ecosystems be strengthened, and initiatives to improve the efficiency of the green use of land be formulated in a differentiated manner, so as to comprehensively promote the improvement of the efficiency of green land use.

Abstract Background Describing the transmission dynamics of infectious diseases across different regions is crucial for effective disease surveillance. The multivariate time series (MTS) model has been widely adopted for constructing cross-regional infectious disease transmission networks due to its strengths in interpretability and predictive performance. Nevertheless, the assumption of constant parameters frequently disregards the dynamic shifts in disease transmission rates, thereby compromising the accuracy of early warnings. This study investigated the applicability of time-varying MTS models in multi-regional infectious disease monitoring and explored strategies for model selection. Methods This study focused on two prominent time-varying MTS models: the time-varying parameter-stochastic volatility-vector autoregression (TVP-SV-VAR) model and the time-varying VAR model using the generalized additive framework (tvvarGAM), and intended to explore and verify their applicable conditions for the surveillance of infectious diseases. For the first time, this study proposed the time delay coefficient and spatial sparsity indicators for model selection. These indicators quantify the temporal lags and spatial distribution of infectious disease data, respectively. Simulation study adopted from real-world infectious disease surveillance was carried out to compare model performances under various scenarios of spatio-temporal variation as well as random volatility. Meanwhile, we illustrated how the modelling process could help the surveillance of infectious diseases with an application to the influenza-like case in Sichuan Province, China. Results When the spatio-temporal variation was small (time delay coefficient: 0.1–0.2, spatial sparsity:0.1–0.3), the TVP-SV-VAR model was superior with smaller fitting residuals and standard errors of parameter estimation than those of the tvvarGAM model. In contrast, the tvvarGAM model was preferable when the spatio-temporal variation increased (time delay coefficient: 0.2–0.3, spatial sparsity: 0.6–0.9). Conclusion This study emphasized the importance of considering spatio-temporal variations when selecting appropriate models for infectious disease surveillance. By incorporating our novel indicators—the time delay coefficient and spatial sparsity—into the model selection process, the study could enhance the accuracy and effectiveness of infectious disease monitoring efforts. This approach was not only valuable in the context of this study, but also has broader implications for improving time-varying MTS analyses in various applications.

This study aims to assess the spatio-temporal defoliation dynamics of box tree, one of the few evergreen species of the Hyrcanian Forests. For this, we integrated multi-temporal leaf-off optical Sentinel-2 and radar Sentinel-1 data from 2017 to 2021 with elevation data. A state-of-the-art sample migration approach was used to generate annual reference samples of two categories (defoliated and healthy box tree) for a set of target years 2017–2020. This approach is based on field samples of the reference year 2021 and two similarity measures, the Euclidean distance and the spectral angle distance. The analysis of spectral and radar profiles showed that the migrated samples were well representative of both defoliated and healthy box trees categories. The migrated samples were then used for spatially mapping the two classes using support vector machine classification. The results of support vector machine classification indicated a large extent of box tree mortality. The most significant changes from healthy box trees to defoliated ones, or vice versa, occurred during the years 2017 and 2018. In the consecutive years of 2019, 2020, and 2021, no significant changes in the distribution of healthy or defoliated box trees were observed. The statistical assessment also revealed that mortality of evergreen understory tree species can be mapped with practically sufficient overall accuracies reaching from 84% (in 2017) to 91%–92% (in 2020 and 2021) using spaceborne remote sensing data. This information using freely accessible satellite data can benefit forest managers responsible for monitoring landscapes affected by the box moth and facilitates the identification of optimal control programs. [ABSTRACT FROM AUTHOR]

The construction industry has become one of the industries that accounts for a relatively large share of China's total carbon emissions. Aiming at the problems of monitoring difficulties, diversity of segmentation types, and uncertainty of carbon emission factors, this study calculates the carbon emissions and intensity of the construction industry in each province of China from 2010 to 2019, analyzes its spatial and temporal variability using the Moran index and the slope index, analyzes the driving factors by combining the Kaya equation and the LMDI method, and verifies the zero-error characteristics by using the IPAT model. The results show that from 2010 to 2019, carbon emissions from the construction industry in China's provincial areas increased in general, with a distribution of "high in the east and low in the west", and the carbon emission intensity declined in general, but some provinces in the north and the center are still higher. Economic development and the increase in housing construction area are the main reasons for the growth of carbon emissions, while the optimization of energy structure and the adjustment of population density reduce carbon emissions. Moreover, the IPAT model verifies the credibility of the results of the LMDI model. This study provides a reference for monitoring and assessing carbon emissions in China's construction industry from the perspective of spatio-temporal characterization, helps regional energy conservation and emission reduction and dual-carbon strategy, and it analyzes the provincial carbon emission intensity to reveal the low-carbon development issues. [ABSTRACT FROM AUTHOR]

Alpine grassland is one of the most fragile and sensitive ecosystems, and it serves as a crucial ecological security barrier on the Tibetan Plateau. Due to the combined influence of climate change and human activities, the degradation of the alpine grassland in Gannan Prefecture has been increasing recent years, causing increases in ecological risk (ER) and leading to the grassland ecosystem facing unprecedented challenges. In this context, it is particularly crucial to construct a potential grassland damage index (PGDI) and assessment framework that can be used to effectively characterize the damage and risk to the alpine grassland ecosystem. This study comprehensively uses multi-source data to construct a PGDI based on the grassland resilience index, landscape ER index, and grass–livestock balance index. Thereafter, we proposed a feasible framework for assessing the comprehensive ER of alpine grassland and analyzed the responsive relationship between the comprehensive ER and comprehensive ecosystem services (ESs) of the grassland. There are four findings. The first is that the comprehensive ER of the alpine grassland in Gannan Prefecture from 2000–2020 had a low distribution in the southeast and a high distribution trend in the northwest, with medium risk (29.27%) and lower risk (27.62%) dominating. The high-risk area accounted for 4.58% and was mainly in Lintan County, the border between Diebu and Zhuoni Counties, the eastern part of Xiahe County, and the southwest part of Hezuo. Second, the comprehensive ESs showed a pattern of low distribution in the northwest and high distribution in the southeast. The low and lower services accounted for only 9.30% of the studied area and were mainly distributed in the west of Maqu County and central Lintan County. Third, the Moran's index values for comprehensive ESs and ER for 2000, 2005, 2010, 2015, and 2020 were −0.246, −0.429, −0.348, −0.320, and −0.285, respectively, thereby indicating significant negative spatial autocorrelation for all aspects. Fourth, ER was caused by the combined action of multiple factors. There are significant differences in the driving factors that affect ER. Landscape index is the first dominant factor affecting ER, with q values greater than 0.25, followed by DEM and NDVI. In addition, the interaction between diversity index and NDVI had the greatest impact on ER. Overall, this study offers a new methodological framework for the quantification of comprehensive ER in alpine grasslands. [ABSTRACT FROM AUTHOR]

Global climate change, driven by increasing carbon emissions, has posed a significant challenge to both human survival and development, becoming a major issue for the sustainable progress of human society. This paper examines the characteristics and differences in the spatio-temporal distribution of carbon emissions and sinks across Wuhan Region that is stratified into three spatial levels: Hubei Province, the Wuhan Metropolitan Area, and Wuhan City. On a finer spatial scale within Wuhan, it uncovers the spatial correlations and disparities between carbon emissions and sinks. Accordingly, the paper proposes strategies and suggestions for reducing carbon emissions and enhancing carbon sinks at the provincial, metropolitan, and municipal levels. These findings are valuable for sustainable regional development and construction of low-carbon eco-cities. [ABSTRACT FROM AUTHOR]

The steady growth of international trade in the post-pandemic era has brought about significant challenges for the publishing industry, particularly with the trend towards regionalization. The decentralization, regionalization and localization of global supply chains have resulted in new changes in the global trade landscape. This paper aims to deepen our understanding of the regional publishing trade between China and ASEAN countries by analyzing its spatio-temporal patterns and internal dynamical mechanisms. We use ArcGIS software to visualize the spatial distribution of the publishing trade between the two regions and employ a Geodetector model to explore the influence of various factors on this trade. Our findings indicate that a set of factors significantly impact the evolution of spatio-temporal patterns in the publishing trade between China and ASEAN, and there is a pronounced disparity in the spatial distribution of the trade across different ASEAN countries. To optimize the industrial and supply chain, China's publishing industry must strive to achieve a better spatial arrangement of its trading activities, promote resource allocation efficiency, and meanwhile expand cultural initiatives at the policy level to promote mutual understanding and exchange with those inactive trading partners. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Zhengzhou University: Engineering Science is the property of Editorial Office of Journal of Zhengzhou University: Engineering Science and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Geography & Geographic Information Science is the property of Geography & Geo-Information Science Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Cultivated land, for which compensation is a practical approach to safeguarding, is a strategic and scarce resource. Evaluating the cultivated land compensation efficiency and identifying its influencing factors are of great significance for monitoring the effect of such compensation and improving the associated policy. A new multi-dimensional framework for estimating the cultivated land compensation efficiency was proposed. This framework not only emphasized the externality of cultivated land but also incorporated its ecological value. Cultivated land compensation efficiency in mainland China from 2000 to 2021 was estimated using this framework and the global Super-SBM model. The panel Tobit model was also adopted to analyze the factors influencing cultivated land compensation efficiency. The results show that (1) Over the past 22 years, the cultivated land compensation efficiency in mainland China initially declined but subsequently exhibited an upward trend, maintaining an average value of 0.724. (2) On a spatial scale, the cultivated land compensation efficiency exhibited pronounced regional pattern, with higher levels observed in the northeastern and southwestern regions of mainland China and lower levels in the eastern region. The cultivated land compensation efficiency in different provinces has distinctive patterns as well. Generally, the cultivated land compensation efficiency is relatively stable in most provinces, though few illustrate an uptrend. (3) Both the ratio of the population with tertiary education and above to the total population and the ratio of primary sector production to GDP affect cultivated land compensation efficiency positively, with the former being more significant. Conversely, GDP per capita, agricultural water consumption, the area affected by disasters, and the ratio of local expenditure on science, technology and education to total fiscal expenditure affect cultivated land compensation efficiency negatively. Therefore, a set of recommendations has been put forward, encompassing the optimization of provincial inputs and outputs, the reinforcement of inter-provincial coordination and collaboration, and the expansion of the talent pool of funds.

A thorough comprehension of the trade-offs/synergies (TOS) among ecosystem services (ESs) and their underlying drivers are vital for promoting regional sustainable development and making informed decisions. In this study, we explored the spatial and temporal dynamics of six ESs and their driving factors at both the grid and county scales in the Central-southern Liaoning urban agglomeration (CSLUA) utilizing various analytical techniques such as Pearson correlation analysis, geographically weighted regression, self-organized mapping analysis, and Redundancy Analysis. Our results revealed that: (1) Between 2000 and 2020, water yield (WY), soil retention (SR), landscape aesthetics (LA), and food production (FP) exhibited an overall upward trend, while habitat quality (HQ) and carbon storage (CS) demonstrated a decreasing trend; (2) From grid scale to county scale, we found concentration effects of TOS relationships was weaken, mainly between supply services (WY, FP) and other services. The significant relationship between some ES pairs has become neutral. The geospatial heterogeneity of TOS relationships for all ESs was also weakened at county scale. More details of geographical features can be captured at grid scale than at county scale. (3) At both scales of analysis, we identified five ES bundles with different ecological functional characteristics and spatial patterns. We found that the Potential High-value Synergistic Bundle would shift to High-value Synergistic Bundle. Although the areas of the LA bundle increased from the grid scale to the county scale, there is less continuity. (4) The direction of the influence of the driving factor on ES is not constant in time, and the degree of the drivers’ impacts on the six ESs varies on the two scales. But NDVI was the main driver for most of the ESs. This study contributes to expanding our understanding of the relationships between ESs at different scales and could inform sustainable ecosystem management at multiple scales.

Global biodiversity is still being lost at an alarming rate. How to slow the destruction of habitats to protect biodiversity is an urgent issue. As one of the most rapidly developing and active economic regions in China, the habitat quality assessment and impact factor analysis in the Yangtze River Delta region are important for promoting socio-economic development and improving the local ecological environment. The InVEST mode and Geodetector method was used to explore the spatial and temporal variations of the habitat quality and its driving factors in the Yangtze River Delta region. The results show that the averaged habitat quality index showed a decreasing trend during 1980–2020, which accounted about 71.86 % of the Yangtze River Delta region. The habitat quality showed an overall spatial pattern of high in the south and low in the north, and the regional distribution of low habitat quality was dominated. The Moran's I values were larger than 0.8 during 1980–2020, showing a significant positive spatial correlation and a high degree of spatial clustering. The high-high clusters of habitat quality were mainly located in the southwest of the study area, while the low-low clusters were mainly located in the north. During 2025–2060, the habitat quality under the three scenarios exhibited SSP1-RCP19 > SSP2-RCP45 > SSP5-RCP85 and all showed a trend of decreasing in the north of the study area and increasing in the south. Under the two scenarios SSP1-RCP19 and SSP2-RCP45, the habitat quality generally showed an increasing trend, while under the SSP5-RCP85 scenario, it showed a decreasing trend. The slope, DEM, precipitation, construction land index and their interactions played a dominant role in the spatio-temporal variations of the habitat quality. Therefore, the slope, DEM, precipitation and construction land index should be considered when formulating habitat quality protection countermeasures.

[Objective] To scientifically understand the spatio-temporal evolution process and formation mechanism of urban space, agricultural space and ecological space in Qinling-Daba Mountain area is the key to promote the overall coordination of the national spatial development pattern and the rise of the central and western regions, and it is also an urgent need for high-quality transformation and development of the region. [Methods] Based on the methods of spatial transfer matrix, topographic location analysis and random forest regression, the spatial and temporal evolution characteristics and driving mechanism of Qinba Mountain region during 2000—2020 were studied from two dimensions of “pattern scale-topographic location”. [Results] (1) In the past 20 years, the cities and towns in the Qinba Mountain area expanded dramatically, and the agricultural and ecological space continued to shrink. While the population of 58.33% of the counties decreased, the urban land was still expanding, and the “total population and urban size” showed a serious polarization. (2) The phenomenon was characterized by urban and agricultural space “climbing up the hills”, while ecological space “descended into the valleys”. The newly added urban and agricultural space was moved up 1 to 2 topographic positions on average. The dam elevation project of Danjiangkou Reservoir downstream had a significant impact on the overall spatial distribution gradient of the mountainous areas. (3) The dynamic adjustment and replacement of “agricultural space to ecological space” was the leading type of transformation in Qinba Mountain area, and the influence of fiscal expenditure was the most significant. Agricultural space was the main source of new towns, and the scale of urban degradation into agricultural and ecological space was significant in Qinba mountain area. (4) Land development policies, mountain terrain attributes, traffic location conditions and social and economic factors jointly restrict and affect the results of territorial spatial evolution in Qinba Mountain area, and there were obvious differences in the effect intensity and the number of significant factors of various types of factors in different conversion directions. [Conclusion] Promoting the concentration of new towns to the key development zones, scientifically guiding agricultural and ecological space to conform to the topographic gradient layout, carefully carrying out water conservancy project construction, and planning the overall regional layout of the “Three districs and Three lines” will have a positive impact on the optimization of territorial spatial pattern in Qinba Mountain area.

Neurons can exhibit various rhythmic activities such as bursting, spiking, and quiescent states when exposed to external input current stimulus. In this paper, a model of medicinal leech's heart (LH) interneuron is considered to describe the dynamics of neurons with a varied range of electrical activities. The crucial insights into the model's dynamics are explored in three different parameter regimes: phasic spiking, regular spiking, and bursting, based upon the codimension-one bifurcation of the model by considering V K 2 s h i f t as a bifurcation parameter. The spatiotemporal dynamics of the model are explored by allowing 1D and 2D diffusion in the membrane voltage. The 1D diffusive system produces irregular bursting dynamics for the intermediate value of diffusion coefficients, whereas, at higher values, it shows synchronized oscillations. In the presence of 2D diffusion, the emergence of different types of spiral patterns is observed in the system. Furthermore, the system is extended by incorporating electromagnetic induction in the membrane voltage to explore the effect of induction on the various dynamics of neural model. By varying its intensities, the membrane voltage in the extended model produces a variety of discharge modes, such as periodic spiking, fast-spiking, resting, and spike-adding phenomena. In addition, the emergence of anti-spiral patterns in the extended model near subcritical Hopf bifurcation is analytically verified using the complex Ginzburg-Landau equation (CGLE). These findings demonstrate that the firing patterns vary based on the control parameters, and these variations contribute to our understanding of how the brain system transmits and processes the signals. • A slow-fast neuron model of Leech's heart interneuron is considered. • The model is improved by adding EMI to study the impact of magnetic flux. • Bifurcation scenarios and different firing activities of both models are performed. • These systems with diffusion display irregular firing and multi-arm spiral patterns. • CGLE analysis in the system with EMI confirms anti-spiral patterns occurrence. [ABSTRACT FROM AUTHOR]

Copyright of Pearl River is the property of Pearl River Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Vegetation, serving as the primary constituent of terrestrial ecosystems, plays a crucial role in regulating energy flow and material cycles and providing vital resources for human socio-economic activities. This study analyzes the spatio-temporal patterns of economic density and vegetation coverage in the Yellow River Basin (YRB) based on forest resource inventory and socio-economic data from 448 counties in 2008, 2013, and 2018. A three-tiered criterion layer is constructed using economic density as the core explanatory variable, encompassing social development factors, land use factors, and natural factors. A two-way fixed effects model is then utilized to analyze the impact of economic density on vegetation coverage. Results reveal that: (1) Spatially, economic density demonstrates a "low in the west and high in the east" pattern, with an overall upward trend in the YRB. Conversely, vegetation cover exhibits a "high in the west and low in the east" pattern, displaying a downward trend. (2) Over the 2008–2018 period, a significant negative correlation between economic density and vegetation cover is observed in each county of the YRB, with vegetation cover decreasing by 1.108% for every 1 unit increase in economic density. Notably, the upstream areas of the YRB experience a significant increase in vegetation coverage, while the middle and lower reaches witness a decrease. (3) Considering control variables, the proportion of the primary industry, urbanization rate, forest protection level, and cultivated land area exert a significant influence on vegetation coverage across the entire basin. Policymakers should formulate relevant policies to achieve sustainable development in the YRB, as discussed in the proposed countermeasures. This study delineates a practical pathway for high-quality economic development and high-level ecological protection in the YRB, offering a valuable reference for analogous research in other regions. [ABSTRACT FROM AUTHOR]

Urban agglomerations are the centers of carbon emissions. However, research on sector-specific carbon emissions in different urban agglomerations is still limited. Drawing on the data of China's six urban agglomerations in 2005, 2010, and 2015, this study investigates the spatio-temporal patterns, regional inequalities, and driving forces of total, industrial, transportation, and residential carbon emissions. The study found that Beijing-Tianjin-Hebei was the total and sectoral emission center among the studied urban agglomerations. Additionally, regional carbon inequalities gradually decreased, implying a growing regional synergistic carbon pattern. The driving forces of carbon emissions, including population, GDP, energy intensity, secondary industry, tertiary industry, foreign investment, urbanization, and green coverage, varied across sectors and regions. Notably, foreign investment could lead to lower carbon emissions in less developed agglomerations like Beijing-Tianjin-Hebei, the Central Plains, and the middle reaches of the Yangtze River, whereas more developed agglomerations like the Yangtze River Delta and the Pearl River Delta benefited less from foreign investment. Besides, ChengYu has good ecological conditions and sustainable development modes, which linked urbanization and green space to reduced carbon emissions in the industrial sector. The findings can help formulate differentiated carbon policy and support sustainable development. [ABSTRACT FROM AUTHOR]

Human settlement development is intricately linked to production and life, and development quality is a partial indicator of the local community's social, economic, cultural, and environmental progress. Furthermore, the human settlements' vulnerability affects their sustainable development potential. Due to the "One Belt, One Road" initiative and land and sea corridor development in southwestern China, the Beibu Gulf coast in Guangxi is the sole waterway bridgehead used by China for opening trade with ASEAN. By examining the region's human settlements and its potential for sustainable development, we established a benchmark for the region's seaward economy and human settlements to achieve synergistic progress, as well as to enhance regional integration. Based on the systematic evaluation of the quality of human settlements along the Beibu Gulf coast in Guangxi, the vulnerability assessment model of human settlement was adopted to analyse the vulnerability and spatial–temporal patterns of nearby human settlements in 2010–2019, while the multiple linear regression model was used to explore their influencing factors. Our findings indicate that the quality of human settlements in the study area has experienced three distinct stages. In the early stage (2010–2012), we noted an overall year-on-year increase in settlement quality. However, in the middle stage (2013–2016), Fangchenggang and Beihai experienced a decline followed by an increase, while Qinzhou demonstrated a steady growth in settlement quality. Qinzhou continued to experience growth, albeit at a slower rate, while Fangchenggang's rate of increase surpassed that of Beihai. The human settlements' high-quality centre shifted between Qinzhou and Fangchenggang in the late stage (2017–2019). Additionally, in recent years, the settlements' high-quality centre has shifted towards the western part of the region. The habitat's sensitivity has grown slowly, as has the responsiveness index, but the vulnerability index continues to decline, and it is characterised by a spatial differentiation ranging from low to high values in a centre–east–west direction. The region's human settlement quality is primarily influenced by economic development. The region's habitat vulnerability is primarily caused by responsibility, and the primary factors affecting responsibility are regional imbalances in social service development, the population's welfare, and employment and infrastructure. [ABSTRACT FROM AUTHOR]

The study of spatial and temporal pattern analysis of urban land use carbon emissions and carbon balance zoning is of great importance for achieving carbon emission reduction and “dual carbon” goals. Taking 46 counties and cities in northern Xinjiang as the study area, using land use and energy data, the carbon emission coefficient method was used to calculate land use carbon emissions from 2000 to 2020, analyze the spatio-temporal evolution of carbon emissions, and make carbon balance zoning for each county and city. The results showed as follows: (1) Carbon emissions showed an overall upward trend, and an exponential upward trend from 2016 to 2020. Carbon uptake decreased slowly, carbon emission intensity decreased first and then increased, and carbon emissions were much higher than carbon uptake. (2) Carbon emission mainly comes from construction land, cities on the north slope of Tianshan Mountain are the main carbon emission cities, carbon absorption mainly comes from grassland and forest land, and the Ili Valley and the southern Altai Mountain are the main carbon absorption cities. (3) The spatial correlation of carbon emissions gradually weakened, the hot spots were concentrated in the vicinity of Karamay City, and the cold spots were concentrated in Ili Prefecture and Altay Prefecture. (4) According to the economic contribution coefficient, ecological carrying capacity coefficient and carbon emissions, it can be divided into five carbon balance zones: carbon sink function zone, carbon sink optimization zone, low-carbon economic zone, carbon source optimization zone and high carbon control zone. [ABSTRACT FROM AUTHOR]

Starting from the coordination level of five sub-systems, namely economic development, ecological environment, science and innovation development, social services and infrastructure, a comprehensive evaluation system for regional coordinated development should be established. Dagum Gini coefficient, standard deviation ellipse, coordination degree model and multi-scale geographical weighted regression model were used to explore the spatio-temporal pattern and dynamic mechanism of Jiangsu’s regional coordinated development level from 2012 to 2021. The results show as follows: (1) The regional coordinated development level of Jiangsu Province has obvious spatial differentiation pattern in the whole and local areas; The level of development is constantly improving, and the speed of improvement is fast in the early stage and slow in the later stage; (2) There are obvious regional differences in Jiangsu’s regional coordinated development, and the differences between regions lead to the imbalance of regional development. The evolution direction of development is from south to north, and the north-south development changes faster than the east-west development, and the north-south difference is large; (3) The effects of various influencing factors on the coordinated development of Jiangsu Province are spatially heterogeneous, and the level of opening up and industry have large spatial heterogeneity and strong driving force on the coordinated development, while the level of consumption, education and traffic have small spatial heterogeneity and weak driving force or have negative effects. [ABSTRACT FROM AUTHOR]

Efficient urban land use plays a crucial role in promoting regional development and ensuring economic growth. Analyzing the spatio–temporal pattern of urban land high-quality use (ULHU) and identifying its key influencing factors and pathways can contribute to enhancing land use efficiency and achieving high-quality development. This study established a comprehensive measurement indicator system for evaluating ULHU using the entropy method and investigated the spatio–temporal evolution pattern of ULHU in the Greater Pearl River Delta (PRD) urban agglomeration in the years 2005, 2010, 2015 and 2020. Furthermore, a multi-period fuzzy-set qualitative comparative analysis method was adopted to explore the concurrent driving mechanisms that impact ULHU from the configuration perspective. The findings reveal that the level of ULHU has exhibited a significant improvement, increasing from 0.1150 in 2005 to 0.2758 in 2020, with an annual growth rate of 8.739%. The spatial pattern in the PRD region exhibits an incremental distribution, characterized by higher values in the central region and lower values in the peripheral area, as this pattern reveals significant heterogeneity across the region. The configurations for ULHU in the PRD were identified, such as Population-industry-talent driven, Openness-fiscal-talent driven, Population-led, and Population-industry driven. Among these configurations, population density and industrial structure were identified as the core driving factors, while the role of talent resources is gradually diminishing. This study provides practical guidance for promoting the ULHU and optimizing national spatial planning. [ABSTRACT FROM AUTHOR]

Copyright of Remote Sensing for Natural Resources is the property of Remote Sensing for Natural Resources Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Assessing the spatiotemporal patterns of watershed water conservation under the influence of the South Asian monsoon climate and its response to precipitation is essential for revealing the evolving patterns of water conservation under different temporal scales. Following the principles of water balance and using the Soil and Water Assessment Tool (SWAT) model, we investigated the spatiotemporal patterns of water conservation and its response to precipitation in the Fangcheng River Basin of Beibu Gulf. The results showed that water conservation in Fangcheng River Basin calculated by SWAT model were 1637.4 mm • a-1, accounting for 50.7% of the mean annual precipitation. The variation of water conservation in different sub-basins was obviously different. Sub-basins with high forest coverage and steep slopes exhibited higher water conservation, while sub-basins with other land use types (such as cropland and grassland), gentle slopes, and intense human activities showed lower water conservation. At the monthly scale, both water conservation and its variation showed similar response characteristics to precipitation in the basin. The response of water conservation variation to sub-precipitation events could be classified into two types. For the short-term rainfall events (duration ≤ 2 days), water conservation variation showed a linear relationship. For the medium to long-term rainfall events (2 days

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Background: Japanese encephalitis (JE) is a serious health concern in China, with approximately 80 % of global infections occurring in China. To develop effective prevention and control strategies, this study explored the epidemiological characteristics of JE in China based on spatiotemporal data, to understand the patterns and trends of JE incidence in different regions and time periods. Method: The incidence and mortality rates of JE were extracted from the Public Health Data Center, the official website of the National Health Commission of the People's Republic of China, and the National Notifiable Infectious Disease Surveillance System from 2004 to 2019. Joinpoint regression was applied to examine the spatiotemporal patterns and annual percentage change in incidence and mortality of the JE. Results: From 2004 to 2019, a total of 43,569 cases of JE were diagnosed, including 2081 deaths. The annual incidence rate of JE decreased from 0.4171/100,000 in 2004 to 0.0298/100,000 in 2019, with an annual percentage change (APC) of −13.5 % (P

The rapid increase in population and economy, coupled with accelerated urbanization, is placing immense pressure on the water–energy–food (WEF) system. In this context, the water–energy–food nexus framework has emerged, recognizing the interdependencies and interactions among water, energy, and food systems, with the aim of optimizing resource management through cross-sectoral collaboration to promote sustainable development. Understanding the spatio-temporal differentiation patterns of the WEF nexus and elucidating the driving mechanisms behind changes in their coupling relationships is essential. This knowledge is crucial for ensuring the security of each subsystem and enhancing the overall sustainability of interconnected systems through coordinated efforts. To address these challenges, this study first established evaluation indicators for water, energy, and food security to quantify their levels and spatio-temporal dynamics. Subsequently, the degrees of coupling coordination within the WEF nexus were calculated. Finally, the WEF nexus’s spatial correlations were analyzed by using a spatial autocorrelation model. Spatial econometric models then identified key factors affecting its coordination. The results revealed significant spatial heterogeneity in water, energy, and food security across mainland China’s provinces. From 2002 to 2022, water security improved substantially in 87% of the provinces, while energy security began to improve in the eastern regions following a phase of high consumption. Food security saw significant enhancements, particularly in Inner Mongolia and the northeastern provinces. The overall coupling coordination of the WEF nexus improved across 30 provinces, progressing toward primary coordination. However, Henan and Anhui provinces experienced fluctuations in WEF nexus coordination. Spatial correlation analysis showed upward trends and increased clustering in WEF nexus coordination. Factors such as economic development and population positively influenced coordination, while economic agglomeration, education, and effective irrigation area had negative effects. This study elucidates the complex interconnections and key influencing factors within the WEF nexus, providing a reference framework and practical recommendations for equitable resource management.

The integrated development of urban and rural regional functions is a key pathway to alleviate conflicts in territorial space. It is essential to explore the theoretical mechanisms behind the integration of urban and rural regional functions. This study employed entropy weight TOPSIS, kernel density estimation, and an integrated development degree model to analyze the spatio-temporal patterns of urban and rural regional functions in 130 cities along China's Yangtze River Economic Belt. A bivariate spatial autocorrelation model was used to identify response processes. The results showed that: (J) In the Yangtze River Economic Belt, urban and rural regional functions were on the rise, with urban functions forming a ' point-cluster-plane' distribution and rural functions exhibiting a clustered distribution with prominent geographical gradient differentiation from upstream to downstream regions. © The integration of urban and rural functions in these cities evolved from transitional integration to enhancement-oriented integration, with the level of integrated development being higher in downstream regions than midstream and upstream regions. The pattern evolved from centering around major cities to focusing on core urban agglomerations, exacerbating polarization between the east and west and widening intra-provincial disparities. © The mutual development between urban and rural functions was significantly strengthened, undergoing stages of demand integration, guided integration, and spontaneous integration and showing a spiral upward trend from transitional to enhanced and then to optimized integration. Based on these findings, the study suggests that: ( Upstream regions should seize policy-driven development opportunities to attract capital, technology, and labor-intensive industries from downstream regions, concentrating resources to comprehensively promote rural revitalization and dual enhancement of urban and rural functions. © Midstream regions should focus on promoting urban and rural integrated development, strengthening the radiating effects of regional central cities like Wuhan, Changsha, and Nan-chang to drive rural function development. © Downstream regions need to facilitate the gradual shift of production and living activities from urban to rural areas, promote rural land circulation, and scale agricultural production and operations in order to promote high-quality integration of urban and rural regional functions. [ABSTRACT FROM AUTHOR]

Based on subdaily kinematic GNSS solutions, the fault slip properties during the very early postseismic phase after the 2021 M 8.2 Chignik earthquake are investigated in this paper. The very early postseismic deformations captured by near-field GNSS sites can be well depicted by the power model. The comparison of afterslip determined by daily and subdaily GNSS solutions suggests that neglecting very early afterslip can result in the underestimation of postseismic slip. Compared with coseismic slip, the cumulative afterslip of the first 24 h is mainly focused in the southeast of the hypocenter, and the shallow updip afterslip appears after this earthquake. The spatio-temporal evolution of the afterslip reveals that the patch of afterslip is immediately generated after the earthquake, and then the postseismic slip gradually grows along the afterslip patch. The magnitude of the afterslip patch varies remarkably within the 24 h following the earthquake, especially in the first several hours. Meanwhile, the spatio-temporal patterns of aftershocks and afterslip exhibit strong similarity during the first 24 h, suggesting that very early afterslip may be a possible driving factor of aftershocks. Moreover, most of the afterslip patches and aftershocks occurring immediately after this earthquake are situated in the area covered by positive Coulomb Stress Change (CSC), which implies that the immediate afterslip and aftershock activities can be influenced by the coseismic CSC. The following afterslip process further releases coseismic CSC and then influences the spatio-temporal variations of aftershock activities. Thus, the afterslip may be a possible triggering mechanism of very early aftershocks for this earthquake, alongside the effects of the CSC generated by coseismic rupture. [ABSTRACT FROM AUTHOR]

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Alpine grassland is one of the most fragile and sensitive ecosystems, and it serves as a crucial ecological security barrier on the Tibetan Plateau. Due to the combined influence of climate change and human activities, the degradation of the alpine grassland in Gannan Prefecture has been increasing recent years, causing increases in ecological risk (ER) and leading to the grassland ecosystem facing unprecedented challenges. In this context, it is particularly crucial to construct a potential grassland damage index (PGDI) and assessment framework that can be used to effectively characterize the damage and risk to the alpine grassland ecosystem. This study comprehensively uses multi-source data to construct a PGDI based on the grassland resilience index, landscape ER index, and grass–livestock balance index. Thereafter, we proposed a feasible framework for assessing the comprehensive ER of alpine grassland and analyzed the responsive relationship between the comprehensive ER and comprehensive ecosystem services (ESs) of the grassland. There are four findings. The first is that the comprehensive ER of the alpine grassland in Gannan Prefecture from 2000–2020 had a low distribution in the southeast and a high distribution trend in the northwest, with medium risk (29.27%) and lower risk (27.62%) dominating. The high-risk area accounted for 4.58% and was mainly in Lintan County, the border between Diebu and Zhuoni Counties, the eastern part of Xiahe County, and the southwest part of Hezuo. Second, the comprehensive ESs showed a pattern of low distribution in the northwest and high distribution in the southeast. The low and lower services accounted for only 9.30% of the studied area and were mainly distributed in the west of Maqu County and central Lintan County. Third, the Moran’s index values for comprehensive ESs and ER for 2000, 2005, 2010, 2015, and 2020 were −0.246, −0.429, −0.348, −0.320, and −0.285, respectively, thereby indicating significant negative spatial autocorrelation for all aspects. Fourth, ER was caused by the combined action of multiple factors. There are significant differences in the driving factors that affect ER. Landscape index is the first dominant factor affecting ER, with q values greater than 0.25, followed by DEM and NDVI. In addition, the interaction between diversity index and NDVI had the greatest impact on ER. Overall, this study offers a new methodological framework for the quantification of comprehensive ER in alpine grasslands.

AbstractThe COVID-19 has caused adverse effects in various aspects, and its impact on population mobility cannot be ignored. In this study, we obtain mobility data for the Beijing–Tianjin–Hebei region during the Chunyun period of 2019–2021 and divide it into four stages. By developing directional weighted networks, the mobility patterns for pre- and post-epidemic are examined. Firstly, the migration scale declines significantly post-epidemic. The fourth stage migration scale exceeds 65% of 2019 in 2021 indicating the situation improves. Secondly, the structural characteristics are compared. The average degree values, clustering coefficients, and path lengths in the fourth stage of 2021 are higher than the values in 2020, showing the recovery of migration, but also efficiency degradation. Thirdly, community detection results show that three communities can be highlighted in the network, which followed Regional Development Pattern. Finally, the findings of Modified Alter-based Centrality and Alter-based Power models show that Beijing (27.78, 17.74) and Tianjin (14.92, 4.38) are typical cities, Tangshan (3.74, 0.03) and Langfang (3.40, 2.00) are gateway cities and others are general cities. A reasonable population distribution has not been formed. The study provides fresh perspectives for applying spatio-temporal data in health emergencies, and the results provide theoretical support for policy formulation of socio-economic recovery.

Polymorphism has been described in many avian taxa including Ardeidae. This study investigated the spatio-temporal distribution of color polymorphic forms (with regard to the color of the unfeathered parts (legs/lores)) of the Great White Egret Ardea alba alba in internet images from Europe. In total, 140 images of presumed polymorphs from 16 countries (from 2006 to 2021) have been collected and examined. Eight coloration schemes of visible unfeathered parts were distinguished. Since some polymorphs may represent the subspecies Eastern Great Egret Ardea alba modesta, the ratio of beak length to total head length was compared among individuals representing the nominal and Eastern Great Egret subspecies. The ratio distributions were similar in all compared groups; thus, polymorph egrets may represent both of these subspecies. Most polymorph images originate from the Netherlands and the southwestern Norwegian coast. This may have resulted from specific local diets and contact with hormone-disrupting compounds. Nevertheless, some observation biases, such as the presence of local breeding population or high numbers of nature photographers, could have affected our observation pattern. Some analyzed features also followed temporal patterns. Most polymorphs were observed during the breeding season, suggesting disruptions of sex hormones as a possible cause. Studies of spatio-temporal patterns of polymorph occurrence may allow us to obtain insights into the causes of large variation in coloration schemes in polymorphic species. [ABSTRACT FROM AUTHOR]

Introduction: Dengue fever is a vector-borne viral disease in Malaysia, and the increasing incidence of the disease necessitates an investigation of its temporal course to ensure effective detection and containment. The aim of this study is to investigate the spatial and temporal distribution of dengue fever in the region. Methods: Daily confirmed dengue fever cases from a five-year epidemic in Seremban were used to generate monthly and annual total case counts for temporal analysis. Then, the Getis-Ord Gi and Global Moran's I were used to plot dengue hotspots and cluster areas. The researchers also calculated and plotted mean and standard deviation ellipses to analyse the direction of dengue case distribution, which runs from southeast to northwest. Results: The study found that there was a clustering of dengue cases in Seremban district with a z-score of 36.9 and a p-value of 0.01. The hotspot pattern in Seremban increases over time and expands every year from 2017 to 2021. Finally, the study suggests that the pattern of dengue fever outbreak in the region is likely influenced by environmental conditions related to the ecology of the Aedes mosquito. Conclusion: Spatiotemporal dengue studies provide snapshots of the location of future dengue epidemics to ensure effective detection and containment of dengue fever, which is proving difficult due to the complex interactions between relevant epidemiological factors and a range of environmental, climatic, and societal characteristics that require further investigation. [ABSTRACT FROM AUTHOR]

Copyright of Chinese Journal of Applied Ecology / Yingyong Shengtai Xuebao is the property of Chinese Journal of Applied Ecology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Chinese Journal of Applied Ecology / Yingyong Shengtai Xuebao is the property of Chinese Journal of Applied Ecology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Human-carnivore conflict is frequently defined as a clash that is the result of interaction among community and wildlife or events by humans or wildlife that has an unpleasant outcome on both. Intimidation caused by carnivore towards injuries to individual, financial defense, damages to crops is increasing or the opinion that wildlife causes threats to human safety, health, food, and property. The current study was conducted from June to November, 2018, at Saiful Mulook National Park Khyber Pakhtunkhwa, Pakistan. For this purpose, 22 villages were selected in and around the park where the population of the wildlife was high. For the study purpose, questionnaire based survey and interview were conducted. In the study area, 300 questionnaire were distributed through which the opinion of the respondent was taken by asking 13 different questions like crop damage, livestock depredation, season and months of damage, and people attributes towards the wildlife, etc. The domestic animals killed by the wildlife in the study area were the goats and sheep, (38.98%). The rate of depredation of livestock has been recorded to increase in the early summer season (60%), spring (15%), followed by winter (12%), and autumn is less (13%). Wildlife damage maize crop and majorly attack on the area of crops which are close to the forest in summer. [ABSTRACT FROM AUTHOR]

Vegetation, serving as the primary constituent of terrestrial ecosystems, plays a crucial role in regulating energy flow and material cycles and providing vital resources for human socio-economic activities. This study analyzes the spatio-temporal patterns of economic density and vegetation coverage in the Yellow River Basin (YRB) based on forest resource inventory and socio-economic data from 448 counties in 2008, 2013, and 2018. A three-tiered criterion layer is constructed using economic density as the core explanatory variable, encompassing social development factors, land use factors, and natural factors. A two-way fixed effects model is then utilized to analyze the impact of economic density on vegetation coverage. Results reveal that: (1) Spatially, economic density demonstrates a “low in the west and high in the east” pattern, with an overall upward trend in the YRB. Conversely, vegetation cover exhibits a “high in the west and low in the east” pattern, displaying a downward trend. (2) Over the 2008–2018 period, a significant negative correlation between economic density and vegetation cover is observed in each county of the YRB, with vegetation cover decreasing by 1.108% for every 1 unit increase in economic density. Notably, the upstream areas of the YRB experience a significant increase in vegetation coverage, while the middle and lower reaches witness a decrease. (3) Considering control variables, the proportion of the primary industry, urbanization rate, forest protection level, and cultivated land area exert a significant influence on vegetation coverage across the entire basin. Policymakers should formulate relevant policies to achieve sustainable development in the YRB, as discussed in the proposed countermeasures. This study delineates a practical pathway for high-quality economic development and high-level ecological protection in the YRB, offering a valuable reference for analogous research in other regions.

Efficient urban land use plays a crucial role in promoting regional development and ensuring economic growth. Analyzing the spatio–temporal pattern of urban land high-quality use (ULHU) and identifying its key influencing factors and pathways can contribute to enhancing land use efficiency and achieving high-quality development. This study established a comprehensive measurement indicator system for evaluating ULHU using the entropy method and investigated the spatio–temporal evolution pattern of ULHU in the Greater Pearl River Delta (PRD) urban agglomeration in the years 2005, 2010, 2015 and 2020. Furthermore, a multi-period fuzzy-set qualitative comparative analysis method was adopted to explore the concurrent driving mechanisms that impact ULHU from the configuration perspective. The findings reveal that the level of ULHU has exhibited a significant improvement, increasing from 0.1150 in 2005 to 0.2758 in 2020, with an annual growth rate of 8.739%. The spatial pattern in the PRD region exhibits an incremental distribution, characterized by higher values in the central region and lower values in the peripheral area, as this pattern reveals significant heterogeneity across the region. The configurations for ULHU in the PRD were identified, such as Population-industry-talent driven, Openness-fiscal-talent driven, Population-led, and Population-industry driven. Among these configurations, population density and industrial structure were identified as the core driving factors, while the role of talent resources is gradually diminishing. This study provides practical guidance for promoting the ULHU and optimizing national spatial planning.

The Association of Southeast Asian Nations (ASEAN) has attracted considerable attention for its rich land ecosystem productivity. However, recent excessive human disturbances may have triggered significant transformations. Consequently, understanding the spatio-temporal dynamics of ecosystem productivity in this region is crucial for strengthening regional ecological sustainability and implementing climate change mitigation strategies. In this study, we harnessed multi-source remote sensing data, an improved CASA model, Theil-Sen Median estimators, Mann-Kendall tests, and Hurst exponent to estimate the net ecosystem productivity (NEP) of the ASEAN region and simulate its spatiotemporal dynamics change. The results showed that the mean annual NEP from 2001 to 2020 in ASEAN was 396.83gC/m2, exhibiting a gradual downward trend. From a spatiotemporal tendency perspective, the areas of NEP decline in the ASEAN region far outweighed the areas of increase, with 60.03% of the total area showing a decrease in NEP, 33.14% showing a boost, and 6.83% showing no significant change. In terms of change persistence, 79.3% of NEP demonstrated anti-persistence, indicating a stronger trend of NEP change reversal. Coupling analysis results indicated that the areas with a future increasing trend of NEP constituted 36.11% of the total area, while areas with no significant future change accounted for 0.08%, areas with a future decreasing trend included 25.21%, and 38.6% of the region exhibited uncertain future trends. Researchers should continually monitor areas with decreasing NEP and uncertain future trends. This study, driven by remote sensing data and combined with the improved CASA model, has successfully estimated the Net Ecosystem Productivity (NEP) at both site and regional scales. The analysis results of NEP in the ASEAN region have enhanced our comprehension of the spatio-temporal patterns of vegetation carbon balance changes in ASEAN, providing data support for formulating “low-carbon economy” strategies and promoting the sustainable development of regional ecosystems.

Food production security (FPS) and agricultural ecological protection (AEP) are both among the paramount issues affecting the country. There are multiple nonlinear interactions between the two systems, while fewer studies have focused on the interaction patterns between them. To realize China's national strategic goals of food security and ecological protection, the interaction between FPS and AEP needs to be analyzed. Based on the evaluation index system of the coupling and coordination between the two systems, this article analyzes the spatio-temporal differentiation and influencing factors in 13 main food-producing regions in China from 2009 to 2021 using the state-space method and spatial econometric model. The following three conclusions were found: First, the overall development levels of both FPS and AEP show an increasing trend, but regional differences are obvious. Second, the coupling coordination degree and stage of the two systems present an upward trend, but the overall development level remains low, with obvious regional differences: Liaoning is still on the imminent disorder stage, while Heilongjiang has taken the lead into the intermediate coordination stage. Third, the total power of grain machinery and the soybean corn planting ratio have a significant positive impact on the coupling and coordination between FPS and AEP. The results make up for the lack of research on coupling and coordination between FPS and AEP, and provide a feasible development path for exploring coordinated development of FPS and AEP in China's main food-producing areas.

The Yellow River Basin (YRB) constitutes an important grain-producing area, as well as an economic core area in China. However, drought and water shortage have always been important factors restricting the agricultural sustainable development of this region. The intensity of agricultural drought in the YRB and the factors affecting it need to be urgently clarified. Based on this, this study attempts to assess the spatio-temporal characteristics of agricultural drought in the YRB using the improved traditional temperature vegetation dryness index (ITVDI) and to identify the type and intensity of constraint effects of human activities (population, GDP, land use type), climate change (temperature, precipitation) and topography (elevation, slope) on drought in the YRB with the constraint line method. Results appeared that from 2001 to 2015, the drought intensity in the YRB exhibited fluctuating changes, while it decreased after 2015. Spatially, the drought characteristics of the YRB existed large heterogeneous, with drought showing a significant increase in the northwestern and downstream areas and a significant decrease in the central part of the basin. There were eight types of constraining effects of human activities, climate change, and topographic factors on drought intensity in the YRB, including U-shaped curve, positive linear, negative linear, logarithmic, negative convex, positive convex, exponential, and hump-shaped. Precipitation and temperature were the most direct factors affecting drought intensity and would exert a binding effect on both the upper and lower boundaries of drought intensity. The constraint effect of precipitation on drought varied in space. In the upstream and midstream, precipitation constrained the upper and lower boundaries of ITVDI, and the constraint effect increased with the increase of precipitation. In the downstream, the constraint effect of precipitation did not change significantly, and the maximum value of ITVDI was always less than 0.8. Temperature had upper and lower boundary constraint effects at three scales. The constraining effects of elevation, slope, GDP, and population were stable across scales. It should be noted that the constraint effect of land use type on drought exhibited U-shaped, and the threshold point of minimum values appeared in the areas covered by grassland and water. The constraint line method can improve the drought monitoring ability of ITVDI, as well as help to clarify the constraint factors and mechanism of drought intensity in the YRB and provide scientific decision-making support to mitigate regional drought and promote regional sustainable development.

Promoting the comprehensive resources and environmental efficiency (CREE) in urban agglomerations (UAs) is of great practical significance for China’s sustainable development. However, CREE in UAs of underdeveloped regions has not received enough attention. Under this background, we constructed a systematic and coherent framework to study CREE and took the five UAs of Northwest China as a case. The super epsilon-based measure (EBM) model was performed to quantify CREE during 2000–2017. Subsequently, we analyzed the spatio-temporal patterns in detail. Through the Super-EBM and GTWR (geographically and temporally weighted regression) model, the endogenous components and exogenous determinants of CREE were examined. The results indicated that the CREE in the five UAs of Northwest China underwent a slight decrease as a whole, and showed an intensified spatial divergence. It exhibited an obvious discontinuity and path bifurcation while being negatively correlated with spatial imbalance across the UAs. The CREE of different UAs showed various spatial distribution characteristics. Regarding the endogenous mechanism, the UAs had certain commonalities and characteristics. The exogenous mechanism manifested certain spatial heterogeneity across UAs while it was generally consistent within each single UA. These results could provide insightful recommendations for the resources and environmental governance in the study area and other similar regions.

The new-type urbanization and integrated urban-rural development are important for the construction of a new development pattern of dual circulation at home and abroad. Based on the panel data of 31 provinces in China from 2001 to 2020, the new-type urbanization and integrated urban-rural development evaluation index system were constructed respectively; then, the coupling coordination degree model and panel regression model were used to analyze the spatio-temporal pattern and influencing factors of the coupling coordination development of new-type urbanization and integrated urban-rural development. The results show that ① the overall provincial new-type urbanization index of China shows a significant upward trend, with the highest new-type urbanization index in the eastern region, followed by the central region and the lowest in the western region; provincial rural-urban integration index of China shows a downward trend, and the level of rural-urban integration in the eastern region is higher than that in the central and western regions. ② The level of the new-type urbanization and integrated urban-rural coupling coordination development in 31 provinces, autonomous regions and municipalities has been continuously improved, and the coupling coordination degree shows a trend of “primary coordination→intermediate coordination→good coordination”, with a spatial pattern of high in the eastern region and low in the western region; the relative development stage has changed from lagging new-type urbanization to synchronous development, and then to lagging integrated urban-rural development; the eastern region is in the lagging stage of integrated urban-rural development, and the central and western regions are gradually moving toward synchronous development. ③ Economic development level, government capacity, input in science and technology, and input in education have a positive promoting effect on the coupling coordination development, while industrial structure level has an inhibitory effect; the effects of economic development level, input in science and technology, and input in education have significant regional heterogeneity. [ABSTRACT FROM AUTHOR]

From 2020 to 2021,the "Elephants Wandering North" ("Yi Lu Xiang Bei",the collective migration of Yunnan elephants to the north and back) event attracted the attention of the domestic and international media. It is of great significance to explore the related social media information for the construction of ecological civilization in China Using Sina Micro-blog as the data source, this paper uses Python to crawl the data of the main micro-blog posts and comments of the "Yi Lu Xiang Bei" event from March 1st,2020 to November 30th, 2021, and cleans and segments the data to conduct the spatio-temporal analysis and e-motional analysis, in order to summarize the rule and provide the reference for the public opinion analysis of the medium-scale and long-time scale network event and the ecological civilization construction. It is found as follows. Firstly, this event is a mass media introduction event. The popularity trend of micro-blog posts and comments is roughly synchronous, but the time points of the peaks are slightly different. Secondly, at the national scale, Yunnan, Henan and Sichuan have higher heat intensity, while the spatial patterns of heat intensity in the eastern, central and western regions have their own characteristics. In Yunnan, the heat intensity of micro-blog is concentrated in the place where elephants pass by, and the overall spatial autocorrelation is not significant. Thirdly, the word cloud map analysis and word frequency statistics of users emotions when posting blogs show positive emotions as a whole. However, there is a slight deviation in the emotional focus of micro-blog posts and comments, and the text similarity between them is low. In the analysis of social semantic network, there are differences in the center and sub-center of micro-blog posts and comments. [ABSTRACT FROM AUTHOR]

In conjunction with Earth's ongoing global warming, the Southwest China (SWC) region has become a fascinating case study on the control of local climate change. Moreover, an entire period of climate change may partially mask the patterns in some stages. Therefore, in this research, we investigated the spatial patterns of the significant turning years of climatic factor change, and determined the heterogeneity of the spatial patterns of climate change before and after the significant turning years. We used the long time-series of the CRU datasets (CRU_TS4.02) from 1901 to 2017 with a piecewise linear regression model to explore the significant turning-year distribution characteristics of inter-annual and inter-seasonal climate factor changes, and further describe and quantize the differences in the spatio-temporal patterns of climate factors before and after the significant turning years on the grid scale in SWC. Overall, the trends in temperature and precipitation factors in SWC were segmented over the last 120 years, with significant turning years with different regional and stepwise characteristics. In terms of timing, temperature and precipitation factors changed significantly in 1954 and 1928, respectively, and overall temporal variability (0.04 °C/(10 a) (p < 0.05), −0.48 mm/(10 a)) masked the magnitude or direction of variability (0.13 °C/(10 a) and 0.16 °C/(10 a) both at the level of p < 0.05 before the turning year, 19.56 mm/(10 a) (p < 0.05) and 1.19 mm/(10 a) after the turning year) around the watershed years. Spatially, the significant turning years were concentrated in the periods 1940–1993 (temperature) and 1910–2008 (precipitation), and the distribution pattern of the turning years was patchy and concentrated. The turning years of temperature factors were gradually delayed from east to west, and the variability of climate factors before and after the turning years exhibited significant shifts in location (e.g., temperature decreased from southeast to northwest before the turning year and increased after the turning year). After the turning year, the warming variability of the temperature factor increased, while the increasing variability of the precipitation factor decreased. Further integrated analysis revealed that the increase in variability of the climate factor after the turning year was mainly due to the increase in winter and autumn variability (0.05 °C/(10 a), 7.30 mm/(10 a) in autumn; and 0.12 °C/(10 a), 1.97 mm/(10 a) in winter). To the extent that this study provides a necessary academic foundation for efficiently unveiling the spatio-temporal variability properties of climate factors against the background of modern global climate change, more attention should be paid to the location and phase of the study. [ABSTRACT FROM AUTHOR]