Spatiotemporal Heterogeneity Research Articles

Exploring the spatio-temporal driving mechanism of multi-dimensional urbanization on urban residential buildings based on GTWR: a case study of China

ABSTRACT Examining how urbanization affects carbon emissions in the construction industry is crucial for China's efforts to achieve environmentally friendly and low-carbon growth. Nevertheless, current research predominantly employs a unidimensional approach to gauge urbanization, overlooking the nuanced characteristics of novel urbanization. This study explored the spatial and temporal characteristics of the impact of urbanization on carbon emissions from urban residential buildings from a multidimensional perspective, starting from five dimensions: population, economy, land, life, and ecology, using a spatial–temporal geographically weighted regression model (GTWR) and panel data from 30 provinces in China for the period 2010–2020. The findings of this study revealed that, on the whole, population urbanization, land urbanization, and lifestyle urbanization exert a significant facilitating influence on carbon emissions from urban residential buildings. Conversely, economic urbanization exhibits a notable inhibitory effect on carbon emissions from urban residential buildings. Furthermore, ecological urbanization transitions from an inhibitory effect to a promoting effect on carbon emissions from urban residential buildings. The impact of urbanization across various dimensions on carbon emissions from urban residential buildings displays spatiotemporal heterogeneity across different regions and periods. In addition, the structure of energy consumption is a contributing factor to the increase in carbon emissions from urban residential buildings, while there is a notable U-shaped relationship between the level of foreign investment, the industrial structure, and carbon emissions originating from urban residential areas. This study offers profound insights into the relationship between urbanization and carbon emissions, providing valuable guidance for policymakers.

Spatiotemporal characteristics and driving mechanisms of land-use transitions and landscape patterns in response to ecological restoration projects: A case study of mountainous areas in Guizhou, Southwest China

With the acceleration of urbanization and industrialization, the land-use mode in mountainous areas has changed significantly, causing serious ecological destruction. Therefore, improving the efficiency of land-resource use in mountainous areas and enhancing ecological protection are important issues. This study focuses on typical mountainous areas in Guizhou Province to explore their significance not only for ecological restoration but also for sustainable socioeconomic development. In this study, we integrated the framework of the interaction between land-use transitions and landscape patterns and employed Spearman's rank correlation coefficient and a spatial bivariate model to reveal the spatiotemporal heterogeneity of landscape patterns and land-use transitions. The results showed that for 1990–2020, the cultivated, forest, and grassland areas decreased by −1353.66, −749.98 and − 541.72 km2 respectively, whereas the water area, urban, and other construction land increased by 799.69, 542.62, and 1230.90 km2, respectively. Moreover, the cultivated land areas converted into urban and other construction land were 358.03 and 661.77 km2 respectively, and the grassland areas converted into forest and other construction land were 3550.08 and 277.32 km2, respectively. Different land-use transitions presented rapid expansion and contraction characteristics, resulting in an increase in overall patch fragmentation, a decrease in uniformity, and an increase in irregular patches, which enhanced the spatial heterogeneity of diversity and complexity. Finally, the land-use transition effects on landscape patterns were primarily elevation, slope, and primary road facility factors. In-depth research on land-use transitional evolution and its impact on landscape patterns has important theoretical and practical value for formulating land-management policies and promoting sustainable development in mountainous areas.

Spatiotemporal heterogeneity of the relationship between urban morphology and land surface temperature at a block scale

Understanding the relationship between urban morphology and land surface temperature (LST) is essential for mitigating urban heat island (UHI). This study investigates the spatiotemporal heterogeneity of the relationship between urban morphology and LST across 5 experiment sites located in different temperature zones of China at a block scale. Normalized difference vegetation index (NDVI), building density (BD), floor area ratio (FAR), average building height (ABH) and open space ratio (OSR) are adopted to indicate the physical urban morphology. The results show positive relationship between BD and LST, and negative relations between LST and NDVI, ABH and OSR from a global perspective. The relations of FAR to LST are mixed. However, variable relationship between urban morphological indicators (UMIs) and LST are significantly observed at a block scale. 12 scenes that generate local relations of UMIs and LST differing from that of the surroundings are identified. Typical strategies for land development, vegetation phenology, large natural elements and human activities may be the most important causative factors to the heterogenous relationship between urban morphology and LST. Findings derived in the study would promote studies on mechanisms of the effects of urban morphology on LST and contribute to practices of UHI mitigation.

Both Short-term and Long-term Ozone Pollution Alters the Chemical Composition of rice Grain.

The increasing ground-level ozone (O3) is threatening food security, especially in Asian areas, where rice is one of the most important staple crops. O3 impacts on rice could be exacerbated by its spatiotemporal heterogeneity. To improve evaluation accuracy and develop effective adaptations, direct data is urgently needed. Studies on the short-term effects of O3 on rice grain, however, are lacking. Which may lead to an underestimation of the O3 impacts. Through a field experiment, we studied the responses of grain nitrogen, grain carbon, and grain protein in rice cultivars to elevated concentrations of O3 (40 ppb plus that in background air, eO3), especially examining the effects of short-term eO3 during different plant growth stages. We found that long-term eO3 increased grain nitrogen by 29.29% in a sensitive rice cultivar, and short-term eO3 at the tillering and jointing stages increased grain nitrogen by 19.31%, and the grain carbon to nitrogen ratio was decreased by 14.70%, and 21.14% by short-term and long-term eO3. Here we demonstrate that short-term eO3 may significantly affect the chemical composition of rice grains. Previous evaluations of the effects of eO3 may be underestimated. Moreover, changes in the grain nitrogen and grain protein were greater when the short-term eO3 was added to rice plants during the tillering and jointing stage, compared to heading and ripening stage. These results suggest that to improve the tolerance of rice to eO3 to achieve food security, studies on cultivar screening, as well as developing growth-stage-specific adaptations are needed in future.

Methane dynamics altered by reservoir operations in a typical tributary of the Three Gorges Reservoir

Substantial nutrient inputs from reservoir impoundment typically increase sedimentation rate and primary production. This can greatly enhance methane (CH4) production, making reservoirs potentially significant sources of atmospheric CH4. Consequently, elucidating CH4 emissions from reservoirs is crucial for assessing their role in the global methane budget. Reservoir operations can also influence hydrodynamic and biogeochemical processes, potentially leading to pronounced spatiotemporal heterogeneity, especially in reservoirs with complex tributaries, such as the Three Gorges Reservoir (TGR). Although several studies have investigated the spatial and temporal variations in CH4 emissions in the TGR and its tributaries, considerable uncertainties remain regarding the impact of reservoir operations on CH4 dynamics. These uncertainties primarily arise from the limited spatial and temporal resolutions of previous measurements and the complex underlying mechanisms of CH4 dynamics in reservoirs. In this study, we employed a fast-response automated gas equilibrator to measure the spatial distribution and seasonal variations of dissolved CH4 concentrations in XXB, a representative area significantly impacted by TGR operations and known for severe algal blooms. Additionally, we measured CH4 production rates in sediments and diffusive CH4 flux in the surface water. Our multiple campaigns suggest substantial spatial and temporal variability in CH4 concentrations across XXB. Specifically, dissolved CH4 concentrations were generally higher upstream than downstream and exhibited a vertical stratification, with greater concentrations in bottom water compared to surface water. The peak dissolved CH4 concentration was observed in May during the drained period. Our results suggest that the interplay between aquatic organic matter, which promotes CH4 production, and the dilution process caused by intrusion flows from the mainstream primarily drives this spatiotemporal variability. Importantly, our study indicates the feasibility of using strategic reservoir operations to regulate these factors and mitigate CH4 emissions. This eco-environmental approach could also be a pivotal management strategy to reduce greenhouse gas emissions from other reservoirs.

Linkages between digital economy and ecosystem services: Revealing the spatiotemporal relationship based on U-shaped effect

This study employs geographically and temporally weighted regression and spatial Durbin models to investigate the impact of digital economy index (DEI) on ecosystem service value (ESV). Estimates of DEI are obtained from night-time light data, and ESV is assessed by the equivalent factor method. The findings indicate significant spatial agglomeration of both DEI and ESV in China. Overall, the impact of DEI on ESV exhibits a U-shaped effect: initially restrained, then promoted. Moreover, the analysis detects spatiotemporal heterogeneity in the DEI-ESV interaction. Spatially, higher DEI positively impacts lower ESV in eastern China, while lower DEI negatively impacts higher ESV in western China. Temporally, most cities in eastern China, unlike those in western China, surpassed the U-shaped curve's inflection point during the study period. Furthermore, the number of cities exceeding the inflection point has increased, amplifying the dual positive and negative impacts of DEI on ESV over time. By revealing the multi-staged and geographically diverse impact of DEI on ESV, this study helps to address the environmental sustainability challenges posed by the rapid advancement of digital technologies.

Impacts of the land use transition on ecosystem services in the Dongting Lake area

Urbanization-induced land use transitions (LUTs) result in a decline in ecosystem services, which has implications for regional ecological security. In order to explore the relationship between ecosystem services and land use transition, this paper utilizes the InVEST model, a geographically weighted regression (GWR) model, to examine the impact of land use transition on ecosystem services in the Dongting Lake area (DLA). The results showed that 1) with the change in urbanization development, the average values of land use transition intensity (LUI) in 2000, 2010, and 2020 are 237.99, 235.82, and 238.92, respectively. Land use dynamics (LUD) show a tendency to increase and then decrease, with average values of 5.58 and 5.62 for the periods 2000–2010 and 2010–2020, respectively, and the transformation of land use shows obvious spatio-temporal heterogeneity. 2) Habitat quality and carbon sequestration showed a downward trend. In contrast, food supply followed an upward trend; soil conservation (SC) and water yield (WY) services initially increased and decreased later. The overall spatial changes in habitat quality and carbon sequestration appear to be insignificant. Food supply shows significant differences in the plains compared to other areas, while soil conservation and water yield service show significant changes in places other than the DLA. 3) From 2000 to 2020, land use transition dynamics, population density, GDP density, night lighting, and transition intensity had mainly negative effects on ecosystem services. Only the Normalized Vegetation Index (NDVI) showed a positive effect on ecosystem services. The results of the research will provide valuable references for the development and implementation of spatial ecological restoration planning and land use policies in the national territory.

Spatiotemporal heterogeneity of lake carbon dioxide flux leads to substantial uncertainties in regional upscaling estimates

Limited field samplings result in significant uncertainties in regional and global estimates of lake carbon dioxide (CO2) emissions. However, quantitative analysis of uncertainty in regional lake CO2 emission estimates remains unclear. In this study, we utilized satellite data to estimate carbon dioxide flux from 113 eastern China lakes, revealing substantial spatial and temporal variations in flux, averaging 18.07 ± 81.83 mg m−2 d−1. Additionally, satellite-estimated total CO2 effluxes indicated previous upscaling studies had overestimated total CO2 effluxes from these studied lakes by approximately 3–11 times, primarily due to substantial variations in lake CO2 fluxes. Insufficient sampling resolution resulted in considerable uncertainty in upscaling estimations. Temporal variations in carbon dioxide contributed greater upscaling uncertainties than spatial variations in carbon dioxide. To capture the dynamics of lake CO2, increasing the number of sampling points and events is necessary as lake size decreases and trophic state increases. Finally, we propose a prediction for the optimal sampling resolution based on lake area and trophic state, recommending an average of 5 points per lake and bi-monthly sampling as the ideal resolution for similar shallow eutrophic lakes. This approach has been validated as effective in lakes across North America and Europe. We believe that future global-scale lake carbon budget estimates would benefit from field observations conducted at more reasonable sampling points and frequency.

Coupling Coordination Relationship and Spatiotemporal Heterogeneity between Functional Diversification and Settlement Evolution in Traditional Mountain Areas (2000–2020): A Case Study of Fengjie County, China

Coupling Coordination Relationship and Spatiotemporal Heterogeneity between Functional Diversification and Settlement Evolution in Traditional Mountain Areas (2000–2020): A Case Study of Fengjie County, China

Full-Dimensional Proportional-Derivative Control Technique for Turing Pattern and Bifurcation of Delayed Reaction-Diffusion Bidirectional Ring Neural Networks

Abstract In neural networks, the states of neural networks often exhibit significant spatio-temporal heterogeneity due to the diffusion effect of electrons and differences in the concentration of neurotransmitters. One of the macroscopic reflections of this time-spatial inhomogeneity is Turing pattern. However, most current research in reaction-diffusion neural networks has focused only on one-dimensional location information, and the remaining results considering two-dimensional location information are still limited to the case of two neurons. In this paper, we conduct the dynamic analysis and optimal control of a delayed reaction-diffusion neural network model with bidirectional loop structure. First, several mathematical descriptions are given for the proposed neural network model and the full-dimensional partial differential proportional-derivative (PD) controller is introduced. Second, by analyzing the characteristic equation, the conditions for Hopf bifurcation and Turing instability of the controlled network model are obtained. Furthermore, the amplitude equation of the controlled neural network is obtained based on the multiscale analysis method. Subsequently, we determine the key parameters affecting the formation of Turing pattern depending on the amplitude equation. Finally, multiple sets of computer simulations are carried out to support our theoretical results. It is found that the diffusion coefficients and time delays have significant effects on spatio-temporal dynamics of neural networks. Moreover, after reasonable parameter proportioning, the full-dimensional PD control method can alleviate the spatial heterogeneity caused by diffusion projects and time delays.

Spatiotemporal dynamics and similarity in soil moisture in shallow soils on karst slopes

Understanding the spatiotemporal dynamics and similarity of soil moisture on shallow slopes is important for inferring soil hydrological processes and for vegetation restoration. In karst areas, the spatial distribution patterns and dynamic changes in shallow soil moisture are particularly complex; however, whether there is spatiotemporal similarity in shallow soil moisture on karst slopes has not been fully determined. This work investigated the spatiotemporal dynamic variations in shallow soil moisture in three types of karst slope plots (abandoned land, peanut and Zanthoxylum bungeanum). Wavelet coherence analysis was used to evaluate the spatiotemporal similarity and factors influencing shallow soil moisture under different vegetation types and slope positions. The results indicate that the alternation between dry and wet conditions and spatiotemporal heterogeneity were significant in the shallow soils of slopes. Comparatively, the dry-wet cycle in the shallow soil of abandoned land occurred faster than that in the shallow soil, and the shallow soil for planting vegetation had a better water holding capacity. The terrain and slope position controlled the distribution and dynamic variations in soil moisture on shallow slopes. Compared with those in the middle and upper slopes, the soil moisture in the bottom slopes was greater, and the coefficient of variation was lower. The average coherence between the soil moisture in the different plots was greater than 0.90, and the significant area was greater than 93.0%. The coherence and significant area in the rainy season were significantly greater than those in the dry season. Due to the influence of vegetation types and meteorological conditions, the drought interval after rainfall events led to a decrease in the spatiotemporal similarity of soil moisture. This study indicates that shallow soil moisture in karst slopes exhibits temporal stability and dynamic similarity. The alternation of dry-wet conditions controls the similarity of shallow soil moisture on the slope.

Glacial lake outburst floods threaten China-Nepal connectivity: Synergistic study of remote sensing, GIS and hydrodynamic modeling with regional implications

Holistic study of glacial lakes and glacial lake outburst floods (GLOFs) in the strategically important China-Nepal transportation corridors is imperative for regional connectivity and disaster risk reduction. This study focuses on four China-Nepal transportation corridors, namely Chentang-Kimathanka, Zhangmu-Kodari, Keyrung-Kathmandu and Taklakot-Hilsa from east to west in the Himalayan region. Within a remote integrated framework, we present the latest high-resolution inventory of glacial lakes, assess their decadal spatio-temporal changes (1992–2022), identify potentially dangerous glacial lakes, and apply hydrodynamic model to assess downstream impacts of possible GLOFs along the study area. The results show 2688 glacial lakes (≥0.001 km2) with a total area of 116.10 ± 8.53 km2 over the study area in 2022. Glacial lakes exhibited spatiotemporal heterogeneity in expansion, with overall expansion of 32 % during 30 years. Keyrung-Kathmandu corridor, among others, was assessed with high GLOF susceptibility. Furthermore, hydrodynamic modeling of four highly dangerous lakes in each transportation area reveals that GLOFs have cross-border effects, impacting ∼103 km of China-Nepal highway, 103 bridges, two major dry ports and 3301 buildings in both countries. Based on these findings, we emphasize the joint efforts of both countries for integrated disaster management for smooth connectivity between two countries and saving downstream population through joint cooperation from central to local government levels by initiating artificial lake lowering, developing cross-border early warning systems and cooperation. This study is valuable for presenting a synergistic study of glacial lakes and GLOF for informing decision- and policy-makers of both China and Nepal for a joint approach to disaster mitigation.

FLApy: A Python package for evaluating the 3D light availability heterogeneity within forest communities

Abstract Light availability (LAv) dictates a variety of biological and ecological processes across a range of spatiotemporal scales. Quantifying the spatial pattern of LAv in three‐dimensional (3D) space can promote the understanding of microclimates that are critical to fine‐scale species distribution. However, there is still a lack of tools that are robust to evaluate spatiotemporal heterogeneity of LAv in forests. Here, we propose the Forest Light Analyzer python package (FLApy), an open‐source computational tool designed for the analysis of intra‐forest LAv variation across multiple spatial scales. FLApy is freely invoked by Python, facilitating the processing of LiDAR point cloud data into a 3D data container constructed by voxels, as well as traversal calculations related to the LAv regime by high performance synthetic hemispherical algorithm. Furthermore, FLApy incorporates 37 indicators, enabling users to expediently export and visualize LAv patterns and the evaluation of heterogeneity of LAv at two scales (voxel scale and 3D‐cluster scale) for a range of fine‐scale ecological study purposes. To validate the efficacy of the FLApy, we employed a simulated point cloud dataset that simulates forests (varying in canopy closure). Furthermore, to evaluate real world forest, we executed the standard workflow of FLApy utilizing drone‐derived data from three subtropical evergreen broad‐leaved forest dynamics plots within the Ailao Mountain Reserve. Our findings underscore that a series of indices derived from FLApy provide a robust characterization of light availability heterogeneity within diverse forest settings. Additionally, when juxtaposed with conventional monitoring techniques, the metrics offered by FLApy demonstrated better generality in our field assessments. FLApy offers ecologists a solution for rapid quantification of understory light 3D‐regimes across multiple scales, addressing the disparity between traditional manual approaches and the precision required for contemporary ecological studies. Moreover, FLApy provides robust support for the establishment and expansion of heterogeneity indices based on 3D micro‐environments, enhancing our understanding of the largely uncharted 3D structural patterns. Anticipated outcomes suggest that FLApy will enhance our knowledge concerning the intra‐forest climatic conditions into a 3D context, proving pivotal in the delineation of microhabitats and the development of detailed 3D‐scale species distribution models.

Viral hepatitis in China during 2002–2021: epidemiology and influence factors through a country-level modeling study

BackgroundViral hepatitis imposes a heavy disease burden worldwide and is also one of the most serious public health problems in China. We aimed to describe the epidemiological characteristics of hepatitis in China and to investigate the influencing factors.MethodsWe first used the JoinPoint model to analyze the percentage change (APC) and average annual percentage change (AAPC) of hepatitis in Chinese provinces from 2002 to 2021. We then explored the influencing factors by using the time-series global principal component analysis (GPCA) and the panel fixed-effects model.ResultsThe disease burden varied across different provinces from 2002 to 2021. The AAPC of the total HAV incidence decreased by 10.39% (95% CI: [-12.70%, -8.02%]) from 2002 to 2021. Yet the AAPC of HBV, HCV, and HEV increased by 1.50% (95% CI: [0.23%, 2.79%]), 13.99% (95% CI: [11.28%, 16.77%]), and 7.10% (95% CI: [0.90%, 13.69%]), respectively. The hotspots of HAV, HBV, HCV, and HEV moved from the west to the center, from the northwest to the southeast, from the northeast to the whole country, and from the northeast to the southeast, respectively. Different types of viral hepatitis infections were associated with hygiene, pollutant, and meteorological factors. Their roles in spatial-temporal incidence were expressed by panel regression functions.ConclusionsViral hepatitis infection in China showed spatiotemporal heterogeneity. Interventions should be tailored to its epidemiological characteristics and determinants of viral hepatitis.

Optimizing cultivated land under non-grain expansion in rural China: unveiling the spatial dynamics of trade-offs and synergies among ecosystem services

ABSTRACT Non-grain expansion in rural China has affected the stability of cultivated land structure and the sustainability of ecosystem services (ESs). Delving into the spatio-temporal heterogeneity of ES interactions is essential for refined and differentiated cultivated land management practices. Taking Tongxiang City as an example, this study mapped the variations of four ESs of cultivated land from 2000–2020, identified their socio-ecological drivers, explored the spatial non-stationarity characteristics of trade-off/synergy among different ESs, and proposed a zoning control framework for cultivated land. The results indicated that (1) food supply (FS) and habitat quality (HQ) decreased by 40.40% and 1.27%, respectively, while carbon sequestration (CS) and soil conservation (SC) increased by 8.5% and 26.21%, respectively. Areas of decreased ES were mainly concentrated in the southwest, while areas of increased ES supply were dispersed. (2) CS-SC and CS-FS ES pairs exhibited obvious trade-offs, with concave trade-offs dominating between 2000 and 2010, and convex trade-offs prevailing from 2010 to 2020. These ES trade-offs were mainly distributed in the southeast and northern regions. HQ-CS and FS-SC presented significant synergies, predominantly characterized by linear synergy and situated in the northern and central areas. (3) The spatial differentiation of ESs was mostly explained by landscape configuration drivers. (4) Different cultivated land zones were delineated based on the spatial non-stationarity of trade-offs/synergies and ES advantage areas. This study contributes to our understanding of the changes in ESs resulting from non-grain expansion and offers valuable guidance for implementing differentiated measures for cultivated land zoning and management.

O-171 Apicobasal RNA asymmetries regulate cell fate in the early mouse embryo

Abstract Assessing the morphological appearance of an embryo as it progresses from zygote to blastocyst is the primary method used by embryologists to evaluate embryo viability and developmental potential. Standard embryo grading techniques, using time-lapse microscopy, analyse morphological characteristics such as size, shape, number, and appearance of blastomeres. The aim of this study was to determine how individual cells of the embryo function on a subcellular level to build a healthy embryo. RNA localisation plays indispensable roles in establishing asymmetries and coordinating cell fate decisions during early embryogenesis across various non-mammalian species. To direct the spatiotemporal distribution of RNA within the cells of an embryo, the microtubule cytoskeleton provides highly sophisticated trafficking pathways. Yet, it remains unknown whether subcellular heterogeneities exist during mammalian preimplantation development and how they contribute to cell fate determination. Using advanced live imaging, we visualised global RNA transcripts at high spatiotemporal resolution from fertilisation to the blastocyst stage in living preimplantation mouse embryos. We discovered apicobasal RNA asymmetries specific to outer cells of the 16-cell stage mouse embryo, coinciding with cell fate decisions and the emergence of the pluripotent inner cell mass. Highly clustered RNAs accumulated proximal to the basal membrane, while more dispersed RNA foci were identified apically as the embryo reaches the late 16-cell stage. The targeted distribution of membrane-less RNA molecules was facilitated by the microtubule cytoskeleton, associated with lysosomes which serve as RNA transport vehicles. We discovered that apically located RNA foci were more dynamic and accompanied an enrichment of translation components. Furthermore, we uncovered that the established RNA asymmetries enhanced translation capacity in apical regions compared to basal regions. These spatiotemporal RNA heterogeneities were unevenly inherited by outer and inner daughter cells during subsequent cell divisions. Notably, embryos that were unable to establish RNA asymmetries failed to allocate cells to the trophectoderm and inner cell mass. Our study provides insights into a subcellular mechanism driving asymmetric RNA localisation and compartmentalised translational regulation in outer cells of the 16-cell stage embryo, which may contribute to cell fate decisions during mammalian preimplantation embryogenesis. We envision that when paired with classical morphological assessment criteria of the embryo, these findings may assist with selecting the embryo with the highest developmental potential.

A Coordinated Emergency Response Scheme for Electricity and Watershed Networks Considering Spatio-Temporal Heterogeneity and Volatility of Rainstorm Disasters

A Coordinated Emergency Response Scheme for Electricity and Watershed Networks Considering Spatio-Temporal Heterogeneity and Volatility of Rainstorm Disasters

A Marginalized Zero-Inflated Negative Binomial Model for Spatial Data: Modeling COVID-19 Deaths in Georgia.

Spatial count data with an abundance of zeros arise commonly in disease mapping studies. Typically, these data are analyzed using zero-inflated models, which comprise a mixture of a point mass at zero and an ordinary count distribution, such as the Poisson or negative binomial. However, due to their mixture representation, conventional zero-inflated models are challenging to explain in practice because the parameter estimates have conditional latent-class interpretations. As an alternative, several authors have proposed marginalized zero-inflated models that simultaneously model the excess zeros and the marginal mean, leading to a parameterization that more closely aligns with ordinary count models. Motivated by a study examining predictors of COVID-19 death rates, we develop a spatiotemporal marginalized zero-inflated negative binomial model that directly models the marginal mean, thus extending marginalized zero-inflated models to the spatial setting. To capture the spatiotemporal heterogeneity in the data, we introduce region-level covariates, smooth temporal effects, and spatially correlated random effects to model both the excess zeros and the marginal mean. For estimation, we adopt a Bayesian approach that combines full-conditional Gibbs sampling and Metropolis-Hastings steps. We investigate features of the model and use the model to identify key predictors of COVID-19 deaths in the US state of Georgia during the 2021 calendaryear.

Unravelling the spatiotemporal variation in the water levels of Poyang Lake with the variational mode decomposition model

AbstractPoyang Lake is a dynamic floodplain lake system that exhibits complex water level fluctuations and experiences significant regime changes over space and time, which remains to be further explored. This study used the variational mode decomposition (VMD) model to decompose the Poyang Lake's water levels from 1960 to 2022 at four key stations into six intrinsic mode functions (IMFs), namely IMF1–IMF6, representing variations on different time scales. The results present significant spatiotemporal heterogeneity. The multi‐year variation (IMF1) accounts for 5.6%–12.4% of the total variation and displays a northward decreasing trend, reflecting the lake's river‐like characteristics. The spectrum of IFM1 also reveals a significant 3.6‐year fluctuation mainly attributed to the tributary inflow, especially the Ganjiang River. The IMF1 differences between stations show abrupt decreases since the 2000s, indicating the impact of concentrated sand mining activities on the northern and central regions. The annual variation (IMF2) is the most prominent, contributing 76.1%–88.4% of the total variation, and shows a southward attenuation trend, likely due to the weakening influence of the Yangtze River flow. The intra‐annual scale (IMF3–IMF6) represents 6.0%–11.5% of the total variation and exhibits less spatial difference compared to the multi‐year and annual variations. The VMD model effectively separates the water level signals into different frequency bands, providing insights into the complex interactions between the lake, tributaries, and Yangtze River, as well as the impacts of human activities like sand mining, enhancing understanding of floodplain lake dynamics. The results also imply the importance of coping with the water level decline of Poyang Lake.

Coupling Coordination Relationship and Spatiotemporal Heterogeneity between Urbanization and Ecosystem Services in the Songhua River Basin

Rapid urbanization in the Songhua River Basin (SRB), a crucial ecological barrier in China and Northeast Asia, has led to the degradation of ecosystem service functions and a decline in their value, thereby posing a significant threat to regional ecological security. Clarifying the complex coupling coordination relationship between urbanization and ecosystem services (ESs) and identifying the spatiotemporal heterogeneity of their interactions will facilitate the high-quality and coordinated development of urbanization and ESs in the SRB. This study employed a systems approach, treating urbanization and ESs as overarching systems and delineating different aspects of urbanization and ecosystem service functions as subsystems within these systems. The spatiotemporal characteristics of urbanization and the ecosystem service value (ESV) in the SRB from 1985 to 2021 were revealed. The coupling coordination relationship and the spatiotemporal heterogeneity of the interactions between urbanization and ESs in the SRB at both the system and subsystem levels were analyzed using the coupling coordination degree (CCD) model and the spatiotemporal geographically weighted regression (GTWR) model. The findings indicated that during the study period: (1) The urbanization index of SRB rose from 0.09 to 0.34, while the ESV experienced a decrease from 2091.42 × 107 CNY to 2002.44 × 107 CNY. (2) The coupling coordination degree (CCD) between urbanization and ESs in the SRB at both the system and subsystem levels increased significantly, generally transitioning from the moderately unbalanced to the basically balanced stage. Areas with high CCD values were mainly distributed in ecological function areas and low-level urbanized areas, while areas with low CCD values were mainly distributed in grassland ecological degradation areas, ecologically fragile areas, resource-dependent old industrial cities, and highly urbanized areas. (3) The subsystems of urbanization had an overall negative impact on Ess, with varying trends, but the spatial distribution pattern of the interactions remained relatively stable. Conversely, the subsystems of ESs all exhibited a trend of initially strengthening and then weakening their negative impacts on urbanization, and the spatial distribution pattern was highly correlated with the spatial distribution pattern of ESV in the SRB.