Temporal Evolution Characteristics Research Articles

Spatio-Temporal Differentiation of Non-Grain Production of Cropland and Its Influencing Factors: Evidence from the Yangtze River Economic Belt, China

Food security is important to guarantee national security and people’s livelihoods, but the increasingly serious problem of non-grain production (NGP) on croplands has exacerbated the risk of food security and directly affected the sustainable development of the national economy and society. This study adopted 130 cities (states) in the Yangtze River Economic Belt as the research units and used ArcGIS10.8, GeoDA1.22, and Origin2022 software and spatial autocorrelation, standard deviational ellipse, and GeoDetector methods to conduct analyses. This study explored the spatial evolution patterns and factors influencing cropland NGP in the Yangtze River Economic Belt. The results show, firstly, that the NGP rate of cropland in the Yangtze River Economic Belt increased from 35.85% in 2006 to 38.62% in 2022. The number of cities (states) with mild and moderate NGP decreased, while the number of cities (states) with severe NGP increased significantly. Secondly, the spatial distribution of the rate of cropland NGP in the Yangtze River Economic Belt had a strong positive correlation, with “high–high agglomeration” tending to be dispersed, “low–low agglomeration” tending to be concentrated, and the overall trajectory of the center of gravity migrating from the northeast to the southwest. Thirdly, the single-factor detection found that the per capita food possession, slope, elevation, and average annual precipitation had strong explanatory power regarding the spatial difference in cropland NGP in the Yangtze River Economic Belt, and the interaction of any two influencing factors showed nonlinear enhancement. The results of this study can help to precisely identify the spatial and temporal evolution characteristics of cropland NGP in the Yangtze River Economic Belt, which is of great significance for supporting the country in controlling the risk of NGP cultivation, promoting the sustainable development of the Yangtze River Economic Belt, and guaranteeing food security.

Dynamics and causes of cropland Non-Agriculturalization in typical regions of China: An explanation Based on interpretable Machine learning

Cropland resources are crucial for food security and economic development. As a populous nation that considers cropland a valuable strategic resource, China has faced challenges of the phenomenon of the cropland non-agriculturalization (CLNA) in recent years. Studying the spatial and temporal patterns of CLNA in different regions and its driving factors is of great significance for formulating and improving cropland protection policies. Based on remotely sensed land use data, the spatial and temporal evolution characteristics of CLNA and its underlying influencing factors in three typical regions of China (Jilin, Henan, and the Guangdong-Hong Kong-Macao Greater Bay Area) from 2000 to 2020 were revealed by using Moran’s index, Lorenz’s curve, and XGBoost-SHAP model. The results of the study show that: (1). There was a certain amount of CLNA phenomenon in all three regions during the past 20 years, and the phenomenon in the Guangdong-Hong Kong-Macao Greater Bay Area (GHM) was the most serious, with the CLNA area exceeding 6 % of the total cropland in the peak period. The average Gini coefficients of Jilin (JL), Henan (HN) and the GHM were 0.39, 0.45 and 0.77, respectively, and the spatial imbalance of CLNA was the most serious in the GHM, which seriously threatened the food security of the region. (2). In the three study areas, socio-economic factors contributed 68 % (JL), 86 % (HN) and 84 % (GHM) to the CLNA, significantly higher than natural factors, and were the dominant factors influencing the CLNA. (3) Although socio-economic factors played a dominant role in non-agriculturalization, the role of natural factors such as elevation and slope should not be overlooked. These natural factors not only directly affect land usability and suitability but also interact with socio-economic factors, jointly shaping the trends and patterns of CLNA. In specific regions, natural constraints may hinder the conversion of cropland to non-agricultural uses, thus playing a protective role. Conversely, in some areas, favorable natural conditions may combine with strong economic development needs, accelerating the transformation of cropland to non-agricultural uses. This interactive effect of socio-economic factors and natural conditions revealed that the CLNA is a complex process influenced by multiple factors. Overall, this study not only provides an in-depth perspective for understanding the spatiotemporal evolution characteristics and complex driving mechanisms of CLNA but also offers a scientific basis for precisely formulating policies for cropland protection and promoting sustainable land use.

Construction of ecological network and its temporal and spatial evolution characteristics: A case study of Ulanqab

Constructing an ecological network is crucial to maintaining ecosystem stability, optimizing ecological space, and ensuring regional ecological security. Using circuit theory, the study integrated habitat condition, ecosystem function, and landscape structure to construct ecological network in Ulanqab. The ecological networks consist of four basic components, including sources, resistance surfaces, corridors and nodes. Ecological sources refer to patches with high habitat quality, while the resistance to species movement between patches is named as ecological resistance surfaces, the important corridors for movement between patches are referred to as ecological corridors, and the vital spots in ecological network are referred to ecological nodes. In addition, the drivers affecting these changes were also analyzed using geographical detector. The results indicated that the area of ecological sources dropped by 19.1 % and the area of high value of ecological resistance surfaces increased from 2000 and 2020. The length of ecological corridors increased by 793.80 km. Mean annual precipitation is the main natural factor influencing the ecological network, and land use intensity and human footprint are the main anthropogenic factors. Our findings suggest that in this region, urban developing should minimize the encroachment on grasslands, forests and waters. Additionally, the availability of water resources should be considered in the planning and implementation of ecological restoration and protection. The findings of the study offer reasonable suggestions for the protection and restoration of priority regions, as well as a scientific foundation optimization and sustainable development of the regional ecological network.

Spatiotemporal evolution and driving factors of vegetation net ecosystem productivity in Henan Province over the past 20 years

Net ecosystem productivity (NEP) is a crucial parameter for assessing the carbon cycle dynamics in terrestrial ecosystems. This study analyzed the spatial and temporal evolution characteristics and future trends of NEP in Henan Province over the past 20 years based on MOD17A3HGF, meteorological, and land-use data, employing the frequency counting method, trend test, Hurst index, and the center of gravity model. Various areas of changes in vegetation carbon sequestration were explored, and the driving factors were quantitatively assessed through correlation analysis, Sankey diagrams, and Geodetector. The results demonstrate that: 1) Continuous temporal changes in NEP in Henan, with annual average values fluctuating between 272.84 and 451.39 gC·m-2·a1, exhibiting an overall upward trend. 2) Spatially, there is a distinct distribution of NEP, concentrating more in the south and less in the north. While the study area generally experiences a dominant gradual enhancement of vegetation carbon sequestration capacity, the middle and north of Zhengzhou City exhibit a significant decline, which is expected to persist in the future. The migration of the centers of gravity of NEP over the past 20 years is characterized by stage-specific differentiation. 3) Among the various land cover types, forests have the strongest carbon sequestration capacity; however, cropland emerges as the province’s main source of NEP due to its extensive size. 4) The driving factors for spatial differentiation in NEP exhibit some temporal variability. Overall, climate factors and atmospheric pollution exert stronger influences, with the interactive explanatory power of the two-factor interaction being higher than that of the single factor. The results of this study can serve as a scientific theoretical basis for ecological policy-making and sustainable development in Henan Province.

Impact of touristification and landscape pattern on habitat quality in the Longji Rice Terrace Ecosystem, southern China, based on geographically weighted regression models

Although the roles of tourism development and landscape value in the conservation of rice terraces have become increasingly important in recent years, rice terraces still face abandonment and desertification. Habitat quality (HQ) assessments evaluate the biodiversity conservation status of rice terraces; however, the spatial and temporal evolution of rice terrace HQ and influencing factors remains poorly understood. Here, a case study was performed of the Longji Terraces, Longsheng, Guangxi, China. Land use and land cover (LULC) remote sensing data for 1985–2020 (every 5 years) were obtained, and the InVEST-HQ model was used to evaluate and map the spatial and temporal evolution patterns and characteristics of HQ. A landscape pattern index and tourism indicators were combined and used to construct geographically weighted regression (GWR) models to explore the impact of tourism and landscape pattern on HQ. Our findings indicated that: (1) forests and terraces are the dominant landscape patches in Longji because they are better protected. Forest area and HQ changes exhibited temporal consistency, meaning that as forest area increased, HQ improved. (2) Longji Terraces exhibited optimum HQ overall, with a multi-year average of 0.977 and insignificant inter-annual variations. Spatially, the geographical HQ distribution was characterised by ‘low local levels, high global level.’ However, the percentage of HQ degraded areas in the final period reached 68 %, which is significantly greater than that of the improved areas (28 %). Moreover, improved areas had more spatial overlap with administrative villages that present superior tourism development. (3) HQ was significantly negatively correlated with night-time light (NTL), showed periodic changes (first negative, then positive) with Shannon’s diversity index (SHDI), was positively correlated with the contagion index (CONTAG), and showed periodic transitions (initially positive, then negative) with the mean of patch area (AREA_MN), population (POP), and patch density (PD). (4) Over time, the study area HQ showed weaker clustering and increased dispersion. In addition, the influence of tourism and landscape patterns increased from 2000 to 2020, with R2 increasing from 0.42 to 0.95. The results establish a scientific foundation for the conservation of rice terraces and sustainable use of landscape resources.

Intelligent Monitoring Model for Lost Circulation Based on Unsupervised Time Series Autoencoder

Lost circulation, a common risk during the drilling process, significantly impacts drilling safety and efficiency. The presence of data noise and temporal evolution characteristics pose significant challenges to the accurate monitoring of lost circulation. Traditional supervised intelligent monitoring methods rely on large amounts of labeled data, which often do not consider temporal fluctuations in data, leading to insufficient accuracy and transferability. To address these issues, this paper proposes an unsupervised time series autoencoder (BiLSTM-AE) intelligent monitoring model for lost circulation, aiming to overcome the limitations of supervised algorithms. The BiLSTM-AE model employs BiLSTM for both the encoder and decoder, enabling it to comprehensively capture the temporal features and dynamic changes in the data. It learns the patterns of normal data sequences, thereby automatically identifying anomalous risk data points that deviate from the normal patterns during testing. Results show that the proposed model can efficiently identify and monitor lost circulation risks, achieving an accuracy of 92.51%, a missed alarm rate of 6.87%, and a false alarm rate of 7.71% on the test set. Compared to other models, the BiLSTM-AE model has higher accuracy and better timeliness, which is of great significance for improving drilling efficiency and ensuring drilling safety.

Research on Sustainable Land Use in Alpine Meadow Region Based on Coupled Coordination Degree Model—From Production–Living–Ecology Perspective

Changes in land use types in alpine meadow areas have significant impacts on the ecological environment in alpine areas. Exploring land use change is crucial for land use management and optimization in alpine regions. Thus, it is necessary to analyze land use evolution and its drivers in alpine meadow regions from a production–living–ecology space (PLES) perspective by using remote sensing data. We first constructed the PLES evaluation system for Gannan. Then, we analyzed the spatial and temporal evolution characteristics and coupling degree of PLES in the study area. Finally, the driving factors affecting PLES were explored with geodetector. The conclusions of the study reveal that the distribution of productive and ecological spaces is large and concentrated, while the distribution of living spaces is more decentralized. The PLES was mainly concentrated in the area above 2500 m but below 4000 m and with a slope of 40° or less. During the study period, the area of production space showed a decreasing trend, while the areas of living and ecological space both showed increasing trends, primarily occurring at the expense of production space. DEM and GDP were the main factors affecting the distribution of PLES. The coupling level and the degree of coupling coordination were relatively stable in general, showing a pattern of “high in the east and low in the west”. The study provides technical support and a theoretical basis for the future planning of land space and ecological environment optimization in the alpine meadow regions.

Spatiotemporal evolution characteristics and influencing factors of the crop water use efficiency in watersheds based on the water footprint.

Climate change has exacerbated the contradiction between water scarcity and sustainable agricultural development. Assessing the crop water use efficiency and its influencing factors could provide a decision-making reference to realize Sustainable Development Goal 2. By analyzing the temporal and spatial evolution characteristics of the crop water footprint, the blue water footprint, green water footprint, and grey water footprint were introduced into the super efficiency slack-based measure model to evaluate the crop water use efficiency in basins. The influence of the driving factors was examined by using the geographic detector model. The situation in the provinces along the Yellow River Basin from 2005 to 2020 was used as a verification case. The results indicated that (1) during the study period, crop water use in the basin was mainly based on the blue water footprint, accounting for approximately 55% of the total water footprint, the grey water footprint, accounting for approximately 30% of the total water footprint, and the green water footprint, accounting for the lowest proportion, at approximately 15%. (2) The crop water use efficiency exhibited a spatial distribution pattern of high values in the east and low values in the west, with obvious upstream provinces<midstream provinces<downstream provinces regional characteristics. (3) The driving factors of crop water use efficiency changes could be ranked as follows: effective irrigation rate (0.75) > disposable income of rural residents (0.71) > population urbanization rate (0.65) > degree of agricultural mechanization (0.63) > agricultural disaster rate (0.61). Furthermore, the interaction effects between the driving factors were greater than the effects of the single factors. The study provides an important reference for understanding the changes, driving mechanisms, and impacts of crop water use efficiency in basin areas. It promotes green agricultural transformation and development to address climate change and alleviate the pressure on water resources.

Multi-scale pore model construction and damage behavior analysis of SiCf/SiC composite tubes

SiCf/SiC composite materials are essential for spacecraft thermal protection, determining the safety of spacecraft. However, their complex structures and intricate fabrication processes have led to an unclear understanding of their failure mechanisms, limiting their application. In this study, circumferential compression experiments were conducted, and X-ray computed tomography (X-CT) was used to analyze the distribution characteristics of pore spaces. The experimental results indicate that damage manifests as secondary fracture phenomena based on temporal evolution characteristics. Specifically, after experiencing performance degradation of 24.73–60.96%, the material still maintained basic stability, exhibiting a performance recovery of 31.55–36.1% under the applied load until failure. To predict the dynamic damage behavior of materials at multiple scales, a multi-scale method combining statistical and microscopic approaches was proposed. A micro representative volume element (RVE) random fiber pore distribution model was established based on random processes and random medium theory. Finally, considering the CT data and the principle of minimum potential energy, a macroscopic finite element model of the micro-pores' structural characteristics in a three-dimensional wound tube was reconstructed. The results indicate that cracks initiate around pore defects and gradually propagate to form crack bands. The model closely matches the macroscopic damage and microscopic characteristics of the material. This work provides a new approach for the numerical simulation of pore defects in such materials.

Research on the Value of Water-Related Cultural Heritage Architecture from Historical Environmental Records: Evidence from the Li River Basin in China

Water-related cultural heritage architecture (WRCHA) represents a globally significant and potentially hybrid heritage found across river basins worldwide. Its spatial and temporal evolution characteristics offer insight into the development trends of river basin environments, yet their value within water-related cultural and environmental systems remain incompletely assessed. This study undertakes qualitative and quantitative analyses of the historical spatial and temporal distributions, influencing factors, and environmental changes affecting the water-related culture, climate, population, and urban areas of 295 WRCHA sites in the Li River Basin of China, employing drought–flood indices, GIS analyses, random forest algorithms, and other methodologies. The results reveal that (1) the Lishui Basin contains a significant distribution pattern of agglomeration for WRCHA within the river basin, concentrated along the river, at low altitudes, with minimal terrain variation, and radiating around ancient governance centers, with varying increases observed across different periods and aggregation zones and with significant spatial and temporal heterogeneities; (2) the distribution pattern is influenced by joint natural and human factors, closely tied to variables such as the river network density, DEM, population changes, and distance to ancient government sites; (3) the combination of the architecture’s location and elevation, along with drought–flood curves, reflects the position of the ancient riverbed of the Lishui River and its historical maximum water level. The quantity of new constructions, in conjunction with the distance from ancient government centers and the trends in population change, thus indicates the urban scale and the frequency and severity of disasters. This study provides a research paradigm and historical reference model for investigating environmental changes in watershed systems, aiding in clarifying the historical human–water symbiosis pattern in the middle reaches of the Yangtze River. Such insights will furnish a scientific basis for future regional ecological planning and watershed environmental management.

Temporal Evolution, Oscillation and Coherence Characteristics Analysis of Global Solar Radiation Distribution in Major Cities in China’s Solar-Energy-Available Region Based on Continuous Wavelet Transform

The majority of the energy required for human survival is derived either directly or indirectly from solar radiation, thus it is important to investigate the periodic fluctuations in global solar radiation over time. In this study, six cities—Harbin, Shenyang, Beijing, Shanghai, Wuhan, and Guangzhou—located in the utilizable areas of solar energy in China, were selected, and the periodicity of the daily global solar radiation of these six cities with time were investigated by means of wavelet power spectrum analysis. Furthermore, Harbin, which has the lowest monthly average of global solar radiation in the cold of winter, was selected to explore the temporal evolution relationship between global solar radiation and other meteorological factors, and air quality factors by wavelet coherence analysis. Among the meteorological factors, the correlation between global solar radiation and sunshine duration exhibits the highest level of consistency. Global solar radiation demonstrates a positive association with atmospheric temperature/wind speed/precipitation over the annual cycle. Conversely, it displays a negative correlation with atmospheric pressure during this time frame. Additionally, on shorter timescales, global solar radiation is negatively correlated with air humidity and precipitation. Among air quality factors, the relationship between global solar radiation and CO/NO2/O3/PM2.5/PM10/SO2 primarily manifests in the broader annual cycle time scale. Within this context, global solar radiation shows a positive correlation with O3, while displaying negative associations with the other five air quality indicators. These findings contribute to urban environmental planning and the effective management and utilization of solar radiation, thereby providing valuable insights to guide the future development of cross-regional comprehensive energy utilization projects under diverse climatic and geographical conditions. Additionally, they serve as a reference for subsequent research aimed at enhancing the accuracy of global solar radiation prediction models.

Research on the temporal and spatial pattern evolution characteristics and decoupling effect of electricity power consumption in China

Exploring the evolution of spatial and temporal patterns of electricity power consumption in China is of great significance and value for the promotion of Carbon Peaking and Carbon Neutrality Strategy and the scientific allocation of electricity resources. Therefore, this paper takes China as an example and innovatively applies nighttime light data from a combination of two remote sensing satellites. And using spatial analysis methods to analyze the evolution of spatial and temporal patterns of electricity power consumption over a longer study time series. Meanwhile, this paper also uses the Tapio decoupling model to study the decoupling effect of electricity power consumption and economic growth in China. The results of the study show that, during the period 2000–2019, China's electricity power consumption was in an unbalanced state, with the eastern coastal region dominating. It also formed a gradient distribution from the coastal area to the inland area. In terms of spatial connection, it shows an unbalanced distribution pattern of “low in the west and high in the east”. In addition, the spatial linkage of electricity power consumption among provinces is more than 93 % of weak linkage, and gradually increases to 97 %, indicating that the spatial linkage of electricity power consumption among regions is gradually weakening. The decoupling state of electricity power consumption in China is characterized by two types of decoupling: Weak decoupling and Expansive coupling. The decoupling status has experienced a significant change from 84 % of provinces being Expansive coupling to 100 % of provinces being Weak decoupling.

Link Prediction in Dynamic Social Networks Combining Entropy, Causality, and a Graph Convolutional Network Model.

Link prediction is recognized as a crucial means to analyze dynamic social networks, revealing the principles of social relationship evolution. However, the complex topology and temporal evolution characteristics of dynamic social networks pose significant research challenges. This study introduces an innovative fusion framework that incorporates entropy, causality, and a GCN model, focusing specifically on link prediction in dynamic social networks. Firstly, the framework preprocesses the raw data, extracting and recording timestamp information between interactions. It then introduces the concept of "Temporal Information Entropy (TIE)", integrating it into the Node2Vec algorithm's random walk to generate initial feature vectors for nodes in the graph. A causality analysis model is subsequently applied for secondary processing of the generated feature vectors. Following this, an equal dataset is constructed by adjusting the ratio of positive and negative samples. Lastly, a dedicated GCN model is used for model training. Through extensive experimentation in multiple real social networks, the framework proposed in this study demonstrated a better performance than other methods in key evaluation indicators such as precision, recall, F1 score, and accuracy. This study provides a fresh perspective for understanding and predicting link dynamics in social networks and has significant practical value.

Spatial-Temporal Evolution Characteristics Analysis of Color Steel Buildings in Lanzhou City

With the continuous acceleration of China’s urbanization process, color steel plate, as a new type of building material, has been widely used in all kinds of temporary buildings and has become the spatial carrier of the specific development stage of urbanization. This study focuses on Lanzhou City as a case study to deeply analyze the spatiotemporal distribution and evolution of color steel plate buildings. Utilizing data extracted from Google imagery and GF-2 satellite images of the built-up areas in Lanzhou, spatial statistical and analytical methods such as centroid analysis, compactness index, and patch density are applied. Systematic analysis is conducted across different time periods and spatial scales to examine the evolution of indicators, including quantity, centroid distribution, spatial clustering, and distribution direction. The results show that from 2013 to 2021, the prevalence of color steel buildings in Lanzhou city initially increased and then decreased, and the number peaked in 2017, but there is a significant difference between distinct areas in the urban area. By quantitatively analyzing the spatial and temporal evolution characteristics of color steel plate buildings, this study reveals the important role it plays in promoting the urbanization process and provides a scientific basis for relevant planning decisions.

The Temporal and Spatial Evolution Characteristics and Driving Factors of Ecosystem Service Bundles in Anhui Province, China

Identifying ecosystem service bundles and their long-term evolutionary characteristics is essential for the overall enhancement of regional ecosystem services, as well as the division and management of functional areas, providing a basis for decision-making in formulating ecological and environmental protection policies, as well as regional development planning. Based on land use, remote sensing, and meteorological data obtained from Anhui Province, this study assessed six important ecosystem service functions, including food production (FP), water yield (WY), carbon sequestration (CS), soil conservation (SC), habitat quality (HQ), and landscape aesthetics (LA), at the township scale in 2000, 2010, and 2020. On this basis, the k-means clustering method was used to identify ecosystem service bundles, analyze the spatio-temporal evolution trajectory of service bundles, and explore the driving factors of the spatio-temporal evolution of ecosystem service bundles using GeoDetector 2015 The results indicate the following: (1) At the spatial level, diverse ecosystem services demonstrate pronounced spatial differentiation. The distribution pattern of HQ, carbon fixation, and SC services is generally lower in the north and higher in the south, with areas of high value predominantly located in the western Dabie Mountains and the mountains of Southern Anhui. Conversely, FP services exhibit the reverse pattern, and WY services display a gradual increase from north to south, while cultural services are more dispersed, with areas of high value primarily located in the western Dabie Mountains, the Yangtze River Basin, and other locations. On the temporal scale, WY, SC, and FP services mainly exhibit an increasing trend, marked by a significant increase, whereas other services tend to present a decreasing trend. (2) Anhui Province can be categorized into four distinct types of service bundles: the grain production bundle (GPB), mountain ecological conservation bundle (MECB), urban living bundle (ULB), and core protection bundle (CPB). Ecosystem service bundles exhibit clear spatial differentiation, and identical service bundles demonstrate substantial clustering in space. Between 2000 and 2020, ecosystem service bundles displayed a marked spatio-temporal evolution, with the prevalence of GPBs diminishing, whereas the share of ULBs progressively increased, and the number of MECBs and CPBs remained largely stable. (3) In the spatio-temporal evolution process, the average annual precipitation, the proportion of forest land, and slope constitute the principal natural factors influencing the spatio-temporal evolution of ecosystem service bundles, while the proportion of construction land represents the primary socio-economic factor, with natural factors exerting a more significant influence than socio-economic factors.

Research on the Temporal and Spatial Evolution Characteristics of the Ecological Level of Urban Production Space: A Case Study of the Upper Reaches of the Yangtze River, China

Research on the Temporal and Spatial Evolution Characteristics of the Ecological Level of Urban Production Space: A Case Study of the Upper Reaches of the Yangtze River, China

Characteristics of Spatial and Temporal Evolution of Land Desertification in Typical Areas of the Horqin Sandy Land in the Past 35 Years and the Driving Mechanism of the Study

Characteristics of Spatial and Temporal Evolution of Land Desertification in Typical Areas of the Horqin Sandy Land in the Past 35 Years and the Driving Mechanism of the Study

Refinement of Different Frequency Bands of Geomagnetic Vertical Intensity Polarization Anomalies before M > 5.5 Earthquakes.

Geomagnetic vertical intensity polarization is a method with a clear mechanism, mature processing methods, and a strong ability to extract anomalous information in the quantitative analysis of seismogenic geomagnetic disturbances. The existing analyses of geomagnetic vertical intensity polarization are all based on the 5~100 s frequency band without refinement of the partitioning process. Although many successful results have been obtained, there are still two problems in the process of extracting anomalies: the geomagnetic anomalies that satisfy the determination criteria are still high in occurrence frequency; and the anomalies are distributed over too large an area in space, which leads to difficulties in determining the location of the epicenter. In this study, based on observations from western China, where fluxgate observation points are positioned in areas with frequent, densely distributed medium-strength earthquakes, we refined the frequency bands of geomagnetic vertical intensity polarization, recalculated the spatial and temporal evolution characteristics of geomagnetic disturbances before earthquakes, and improved the crossover frequency anomaly prediction index while promoting the application of the method in earthquake forecasting.

Does environmental decentralization improve industrial ecology? Evidence from China's Yangtze River Economic Belt

The rational division of environmental management powers between governments is the institutional basis for promoting the transformation of industrial ecology (IE). Based on panel data of 105 prefecture-level cities in the Yangtze River Economic Belt (YREB) of China from 2006 to 2020, this study analyzes the spatial and temporal evolution characteristics of IE and environmental decentralization (ED) in the YREB by constructing evaluation index systems. The spatial econometric model is used to explore the effects of ED on IE under economic growth pressure (EGP) and officials’ tenure (LT). The results indicate that regional differences in IE in the YREB exhibit a fluctuating downward trend and that the imbalance between regions is the leading cause of overall differences. Furthermore, IE presents a significant spatial positive correlation. ED has a restraining effect on IE and is regulated by EGP and LT. Moderate EGP can mitigate the negative effects of ED on IE, while LT intensifies the negative effects of ED on IE. Heterogeneity exists in the relationship between ED and IE in regional locations and pollution control pressure areas. These results are significant for developing a modern industrial system, formulating differentiated environmental protection strategies, and improving the government performance appraisal system.

Characterization and Multi-Scenario Prediction of Habitat Quality Evolution in the Bosten Lake Watershed Based on the InVEST and PLUS Models

Habitat quality is an important basis for human well-being and the achievement of sustainable development. Based on land-use data for the Bosten Lake Basin in 2000, 2005, 2010, 2015, and 2022, the PLUS and InVEST models are applied in this study to predict and analyze land-use changes and explore the spatial and temporal evolution characteristics of the region’s habitat quality. Additionally, we use a geographic detector model to reveal the drivers of spatial variation in habitat quality. The results show that: (1) Land use in Bosten Lake Basin is dominated by grassland and bare land, with an area share of 93.21%. Habitat quality shows a trend of degradation followed by improvement, with a spatial pattern of high in the northwest and low in the southeast. (2) Habitat quality in 2030 increased from 2022 in all cases, with a mean of 0.354 for the natural development scenario, a maximum of 0.355 for the ecological development scenario, and a minimum of 0.353 for the economic development scenario. (3) The main drivers affecting habitat quality in the Bosten Lake watershed are DEM, mean annual precipitation (MAP), and GDP per capita. X1∩X4 (0.50) and X4∩X10 (0.51) are the interaction factors with the largest dominant effect in 2000, 2010 and 2020, respectively.