Obvious Spatial Heterogeneity Research Articles

Land scale division and multifunctional evaluation for Fuping County, China, based on DEM-based watershed analysis.

Land is the spatial background and basic carrier of human survival and development. The study of land function evaluation at different scales can promote the harmonious coexistence of humans and nature. Taking Fuping County, Hebei Province, China, as an example, this study establishes the theoretical framework of county-level land scale division using a digital elevation model (DEM)-based watershed analysis method and establishes the theory and methodological system of land function evaluation from the perspective of the characteristic scale. The multifunctionality of the land was evaluated using the Carnegie-Ames-Stanford approach (CASA), the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model and comprehensive index evaluation. By using the methods of DEM-based watershed analysis, dominant factor differentiation and layer superposition, a three-level scale system of 'subwatershed scale-land chain scale-land segment scale' and a multifunctional multiscale evaluation index system containing 18 evaluation indices were established. The single-function and multifunction evaluation results of land at different scales were obtained by the comprehensive index method and Getis-Ord Gi* index method. The accuracy of land function evaluation results mainly depends on the selection of the measurement scale. The land measurement scale determined by DEM-based watershed analysis is close to the intrinsic scale of land function evaluation. The scale effect of land function in different temporal and spatial ranges is also evident and shows obvious spatial heterogeneity and difference. At larger scales, individual functions show synergistic effects.

Seasonal changes in ecosystem health and their spatial relationship with landscape structure in china's Loess plateau

Environmental managers have sought to optimize landscape structure to maintain regional ecosystem health (EH). However, we still lack a full understanding of the effects of changing landscape structure on EH, especially in terms of shorter time scales (e.g., monthly or seasonal scales) and spatial heterogeneity. To address this gap, this study used the vigor-organization-resilience-services (VORS) model to assess the annual and seasonal variation of EH in the Loess Plateau (LP) during 2000–2015, and then applied the geographically weighted regression (GWR) model to investigate the spatial effects of different aspects (i.e., landscape composition and configuration) of the landscape structure change on EH over time. Our results showed that the EH level in the LP from 2000 to 2015 displayed temporal non-stationarity at annual and seasonal scales, and a spatial pattern of decreasing from southeast to northwest. The effects of landscape structure on EH had obvious spatial and temporal heterogeneity, depending on the local landscape composition and configuration. In general, landscape configuration exerted a greater impact on EH than landscape composition apart from Shannon’s diversity index and percentage of forestland area, but the intensity and direction of the impact displayed higher temporally instability and therefore should receive more attention. Furthermore, regulation of the dominant patch size, landscape connectivity and forest spatial spacing is the optimal choice for regional ecosystem management. The results suggest that EH responses to changes in landscape structure in the LP vary by time and place, and that the integrating temporal variation and spatial characteristics can help decision-makers make precise spatial arrangements and temporal adjustments to keep the negative ecological impacts within reasonable limits.

Research on the Impact of Digital Technology Application on Households Calculation Based on Household Digital Penetration Index

With the widespread popularization of digital technology and its continuous penetration into family life, the impact of digital technology on the national economy and residents' lives has gradually emerged. Based on the CFPS database, this article uses the A-F model to measure the household digital penetration index, explores the popularity and application of digital technology in households, and uses an empirical model to analyze the impact of the household digital penetration index on household income, consumption and income gaps. Research results show that digital technology has increasingly penetrated households from 2010 to 2020. The household digital penetration index can effectively increase household income and stimulate consumption, but it also widens the household income gap to a certain extent. At the same time, the impact of household digital penetration index on residential households shows obvious spatial heterogeneity.

Landsat series images for evaluating ecological restoration effect from multi-time scale based on an ideal reference

Multi-time scale assessment of ecological restoration effects based on objective and scientific approaches can provide crucial information for implementing environmental protection policies and ensuring sustainable regional development. This study evaluated the effect of ecological restoration based on a natural evolution as a reference frame, using yearly Landsat time series. Southern Ningxia in China was selected as the study area. The remote sensing ecological index (RSEI) was calculated. The features of natural evolution were derived from the time series of the RSEI in the natural reserve areas (NRAs). LandTrendr was employed to characterize the disturbance–recovery processes. Furthermore, we adopted the dynamic time-warping method for the entire study period, along with the relative variation ratio (during the disturbance–recovery cycle) to capture the long-term and short-term ecological restoration effects, respectively. The following conclusions were drawn: First, a time-series RSEI based on LandTrendr was used to successfully monitor disturbance–recovery processes. Second, the majority of RSEI disturbances (i.e., >60%) occurred between 2000 and 2005. It is characterized by fewer disturbance times and obvious spatial heterogeneity in disturbance duration. Notably, from 2000 to 2022, the RSEI improved. Additionally, approximately 40% of the study area portrayed a strong similarity to the RSEI of the NRAs. We conclude that quantifying the ecological restoration effect at multi-time scales is a practical operational approach for policymakers and environmental protection. Our study presents novel insights for assessing regional ecological quality, by capturing the processes of natural evolution features in NRAs.

Multiscale assessment of the spatiotemporal coupling relationship between urbanization and ecosystem service value along an urban–rural gradient:A case study of the Yangtze River Delta urban agglomeration, China

Evolutions in land use in urban areas exert a growing influence on ecosystem service value (ESV). As a manifestation of spatial arrangement in mature urban growth, the ecological challenges within urban agglomerations and their surroundings deserve attention. Therefore, clarifying the interrelation within the ESV and urbanization is crucial to constructing sustainable progress-oriented cities. Previous researches on the coordination relationship between ESV and urbanization have been limited to the provincial and county levels, and insufficient consideration has been given to the differences across urban and rural areas at different scales. Utilizing the coupling coordination degree (CCD) model, the present investigation assesses the interplay between urbanization and ESV across various scales within the Yangtze River Delta urban agglomeration (YRDUA) region from 2000 to 2020, and explores the differences in their distributions throughout the urban–rural gradient, aiming to help the regional coordinated development. The findings indicate that from 2000 to 2010, with increasing intensity of land use, the ESV in YRDUA area decreased. But between 2010 and 2020, ESV increased. Moreover, the CCD in the YRDUA has a positive relationship across ESV and urbanization, and is in a status of primary coordination from 2000 to 2020, with a slow upward trajectory. Meanwhile, along the rural–urban gradient, ESV and CCD both are declining, and there is a significant plunge from suburban to urban. And the interactions between ESV and urbanization have obvious spatial heterogeneity, which tends to show the coordination at broader scales, such as provincial and county levels, while manifesting conflicts at finer scales, such as the grid scale. Our findings can help city planners and policy makers to minimize the adverse effects of urbanization sprawl on ecosystem services.

Analysis of sustainable water resource management and driving mechanism in arid region: a case study of Xinjiang, China, from 2005 to 2020.

The long-term dynamic comprehensive evaluation of the water resource carrying capacity (WRCC) and the analysis of its potential driving mechanism in arid areas are contemporary research issues and technical means of mitigating and coordinating the conflict between severe resource shortages and human needs. The purpose of this study was to explore the distribution of the WRCC and the spatiotemporal heterogeneity of drivers in arid areas based on an improved two-dimensional spatiotemporal dynamic evaluation model. The results show that (1) the spatial distribution of the WRCC in Xinjiang, China, is high in the north, low in the south, high in the west, and low in the east. (2) From 2005 to 2020, the centers of gravity of the WRCC in northern and southern Xinjiang moved to the southeast and west, respectively, and the spatial distribution exhibited slight diffusion. (3) The factors influencing the WRCC exhibit more obvious spatial and temporal heterogeneity. The domestic waste disposal rate and ecological water use rate were the main factors influencing the WRCC in the early stage, while the GDP per capita gradually played a dominant role in the later stage. (4) In the next 30 years, the WRCC in Xinjiang will increase. The results provide a theoretical reference for the sustainable development of water resources in arid areas.

The Assessment of Industrial Agglomeration in China Based on NPP-VIIRS Nighttime Light Imagery and POI Data

Industrial agglomeration, as a typical aspect of industrial structures, significantly influences policy development, economic growth, and regional employment. Due to the collection limitations of gross domestic product (GDP) data, the traditional assessment of industrial agglomeration usually focused on a specific field or region. To better measure industrial agglomeration, we need a new proxy to estimate GDP data for different industries. Currently, nighttime light (NTL) remote sensing data are widely used to estimate GDP at diverse scales. However, since the light intensity from each industry is mixed, NTL data are being adopted less to estimate different industries’ GDP. To address this, we selected an optimized model from the Gaussian process regression model and random forest model to combine Suomi National Polar-Orbiting Partnership—Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) NTL data and points-of-interest (POI) data, and successfully estimated the GDP of eight major industries in China for 2018 with an accuracy (R2) higher than 0.80. By employing the location quotient to measure industrial agglomeration, we found that a dominated industry had an obvious spatial heterogeneity. The central and eastern regions showed a developmental focus on industry and retail as local strengths. Conversely, many western cities emphasized construction and transportation. First-tier cities prioritized high-value industries like finance and estate, while cities rich in tourism resources aimed to enhance their lodging and catering industries. Generally, our proposed method can effectively measure the detailed industry agglomeration and can enhance future urban economic planning.

Inherent correlation between mechanical and structural heterogeneity in metallic glasses

Comprehending the physical and mechanical behavior of metallic glasses (MGs) from the perspective of local structural heterogeneity has long been one of the most active research topics in the field of metastable materials. In this study, nanoindentation simulations were employed to study the local elastic behavior of the classical CuZr MGs and discuss the inherent correlation between mechanical and structural heterogeneity. The results show that the mechanical response is governed by the heterogeneity of Voronoi clusters in terms of variety, quantity, and connection mode within the range of indentation. A critical dimension to distinguish nanoscale heterogeneity has been found to be around 30 nm, below which the local mechanical responses are directly correlated to the distribution of characteristic clusters and represent obvious spatial heterogeneity. All these results are expected to bridge the gap between the macro-scale isotropy and the nanoscale heterogeneity of MGs.

The Spatial and Temporal Variability of the Blue–Green Spatial Structures of the South Dongting Lake Wetland Areas Amidst Climate Change, including Its Relationship with Meteorological Factors

In recent years, the water level of the Dongting Lake (DTL) has been continuously low, and the wetland area and landscape pattern have changed significantly. Considering the obvious spatial heterogeneity of water regime changes in different waters of the DTL, this paper takes two core areas of the South Dongting Lake Nature Reserve (SDLNR) as study areas and analyzes the spatial distribution characteristics of the wetland blue–green landscape patterns by using remote sensing image data and hydrological and meteorological data. The multi-scale correlation between runoff, precipitation, temperature, and evapotranspiration in the SDLNR was studied via cross-wavelet transform analysis. The results show the following: (1) The change in the blue–green spatial patterns in different regions in different periods is inconsistent, and this inconsistency is related to the topography, climate, and human activities in each region; (2) there are seasonal fluctuations in precipitation, air temperature, and evapotranspiration in the SDLNR. Among them, the annual mean temperature shows a rising trend and passes the significance test with 95% confidence, while the annual mean precipitation and annual mean evapotranspiration show no significant change trend; and (3) our Pearson correlation analysis and cross-wavelet change results show that precipitation and temperature are strongly correlated with runoff, with a resonance period of 8–16 months, while the correlation between evapotranspiration and runoff is not significant. We recommend that policymakers establish an effective early warning system and make plans to store water through micro-terrain transformation in possible climate change treatments and strategies.

Spatiotemporal Pattern of Urban Sprawl Based on the Weighted Urban Proliferation Model: A Case Study of the Bohai Rim Region in China

Since the reform and opening up, China’s urbanization level has increased rapidly, with the urbanization rate rising from 17.92% in 1978 to 63.89% in 2020. At the same time, the extreme expansion of urban space has gradually become a common phenomenon, and the problem of urban sprawl has become a stumbling block to the high-quality development of Chinese cities. The traditional single-indicator method and multi-indicator method have obvious shortcomings in the richness of index dimension and the subjectivity of indicator selection, respectively, when measuring urban sprawl quantitatively. In this study, based on the weighted urban proliferation (WUP) model, we integrated the three independent dimensions of urban permeation (UP), dispersion of built-up areas (DIS), and utilization density (UD) to verify the applicability and feasibility of the model for quantifying the spatiotemporal pattern of urban sprawl, taking the Bohai Rim region in China as an example. There were four main results. Most cities in the Bohai Rim region had a moderate-to-high level of urban sprawl, with obvious spatial heterogeneity by province. The average WUP of cities in the Bohai Rim region increased by 61.83% from 2000 to 2020, and cities with moderate urban sprawl became cities with high sprawl. The urban sprawl process in the Bohai Rim region accelerated during 2010−2015 and stabilized thereafter. The increase in WUP caused by the growth of built-up areas is the main driver of urban sprawl in the Bohai Rim region. This study found that the WUP model can be effectively applied to the Bohai Rim region of China, where it reflects the multidimensional features of urban sprawl and provides new insight into its spatiotemporal pattern.

Sustainable development assessment of ecological vulnerability in arid areas under the influence of multiple indicators

The fragile ecosystems of arid areas are highly vulnerable, especially under the impact of human activities. Therefore, there is an urgent need to develop appropriate ecological vulnerability assessment models for these areas. In this study, Zhongwei City was taken as the study area. And a multi-indicator comprehensive assessment system was constructed using the optimized featured indicators-vulnerability scoping diagram (FVSD) model. The weights for each indicator were determined using the analytic hierarchy process-entropy weight (AHP-EW) method, leading to the creation of the ecological vulnerability map of Zhongwei City. The results showed that the overall ecological vulnerability of Zhongwei City is high and there is a significant spatial aggregation. There was obvious spatial heterogeneity in the distribution of vulnerability, with high vulnerability mainly concentrated in Haiyuan County, showing a decreasing trend from south to north. Watershed area index, annual average temperature, PM10 and annual afforestation index were the most important indicators affecting the ecological vulnerability, the fragile environmental conditions and human activities combine to shape the spatial heterogeneity of ecological vulnerability. The results of the study have important theoretical and practical implications in guiding ecological management of Zhongwei City. Moreover, the research framework can be replicated in different areas and is instructive for ecological vulnerability studies.

Monitoring and evaluation of vegetation restoration in the Ebinur Lake Wetland National Nature Reserve under lockdown protection.

For a long time, human activities have been prohibited in ecologically protected areas in the Ebinur Lake Wetland National Nature Reserve (ELWNNR). The implementation of total closure is one of the main methods for ecological protection. For arid zones, there is a lack of in-depth research on whether this measure contributes to ecological restoration in the reserve. The Normalized Difference Vegetation Index (NDVI) is considered to be the best indicator for ecological monitoring and has a key role to play in assessing the ecological impacts of total closure. In this study, we used Sentinel-2, Landsat-8, and Moderate Resolution Imaging Spectroradiometer (MODIS) remote sensing data to select optimal data and utilized Sen slope estimation, Mann-Kendall statistical tests, and the geographical detector model to quantitatively analyze the normalized difference vegetation index (NDVI) dynamics and its driving factors. Results were as follows: (1) The vegetation distribution of the Ebinur Lake Wetland National Nature Reserve (ELWNNR) had obvious spatial heterogeneity, showing low distribution in the middle and high distribution in the surroundings. The correlation coefficients of Landsat-8 and MODIS, Sentinel-2 and MODIS, and Sentinel-2 and Landsat-8 were 0.952, 0.842, and 0.861, respectively. The NDVI calculated from MODIS remote sensing data was higher than the value calculated by Landsat-8 and Sentinel-2 remote sensing images, and Landsat-8 remote sensing data were the most suitable data. (2) NDVI indicated more degraded areas on the whole, but the ecological recovery was obvious in the localized areas where anthropogenic closure was implemented. The ecological environment change was the result of the joint action of man and nature. Man-made intervention will change the local ecological environment, but the overall ecological environment change was still dominated by natural environmental factors. (3) Factors affecting the distribution of NDVI in descending order were as follows: precipitation > evapotranspiration > land use type > elevation > vegetation type > soil type > soil erosion > slope > temperature > slope direction. Precipitation was the main driver of vegetation change in ELWNNR. The synergistic effect of the factors showed two-factor enhancement and nonlinear enhancement, and the combined effect of the driving factors would increase the influence on NDVI.

Decoupling Analysis of Urban Growth and Carbon Emissions in Wuhan, 2000-2020

The analysis of the coupling relationship between urban growth and carbon emissions and its synergistic change rule is of great significance to the sustainable development of cities. The BCI index method is used to extract the scope of built-up areas of Wuhan from 2000 to 2020, and the relationship between urban growth and carbon emissions is analyzed based on the Tapio decoupling model. The results show that: (i) The built-up areas of Wuhan City expanded from 2000 to 2020 in all directions with Wuchang, Hankou, and Hanyang as the center, forming a stable monocentric urban spatial structure. The growth of the built-up areas exhibited stage characteristics, including a clear start, acceleration, high-speed growth, and deceleration. (ii) The carbon emissions of Wuhan City from 2000 to 2020 showed an overall growth trend. Three districts, Jiangxia, Huangpi and Hongshan, become high-emission districts, three districts, Caidian, Dongxihu and Xinzhou, become higher-emission districts, and the other seven districts maintain a lower level of carbon emissions; (iii) The carbon emissions and expansion of built-up areas in Wuhan city districts from 2000 to 2020 show obvious spatial and temporal heterogeneity. They present a decoupling of aggregation in the central area and some regression in the periphery, but the overall trend is favorable. The study provides useful references for urban planning and policy making.

Projected Changes in SWA over the Main BRI Regions for Net-Zero and Net-Negative Future

Surface water availability (SWA, calculated by precipitation [P] minus actual evaporation [E]) has great impacts on society. However, it remains unclear how SWA will change in a net-zero and net-negative future. In this study, we examine future changes in P, E, and SWA from the Coupled Model Intercomparison Project Phase 6 (CMIP6) for net-zero (2050–2060) and net-negative (2090–2100) CO 2 emissions periods under pathway SSP1-1.9 relative to historical baseline (1995–2014) in the main Belt and Road Initiative (BRI) regions. We also consider SSP2-4.5 and SSP5-8.5 for comparison. We find that P, E, and SWA changes exhibit obvious spatial heterogeneity, with increase or decrease over different areas for 2050–2060 and 2090–2100 relative to 1995–2014 under 3 scenarios. SWA changes are generally insignificant excluding some isolated areas under SSP1-1.9, yet have statistical significances over Central Africa and many areas in Eurasia for SSP2-4.5 and SSP5-8.5. Average monthly P and E are expected to markedly increase by 2.63 and 2.01 mm, 1.85 and 1.65 mm, for net-zero and net-negative periods under SSP1-1.9. Consequently, the projected monthly SWA will change by 0.78 and 0.36 mm. However, the projected P, E, and SWA have much larger changes in the same periods under the other 2 scenarios, especially 2090–2100. Our research provides previously unknown knowledge that SWA shows quite different changes in the net-zero and net-negative periods under SSP1-1.9 relative to the same periods under SSP2-4.5 and SSP5-8.5, which may facilitate management of water resource risks to ecosystems and human society.

Detecting the Spatial Association between Commercial Sites and Residences in Beijing on the Basis of the Colocation Quotient

Identifying the spatial association between commercial sites and residences is important for urban planning. However, (1) the patterns of spatial association between commercial sites and residences across an urban space and (2) how the spatial association patterns of each commercial format and different levels of residences vary remain unclear. To address these gaps, this study used point-of-interest data of commercial sites and residences in Beijing, China, to calculate colocation quotients, which were used for identifying the spatial association characteristics and patterns of commercial sites and residences in the city. The results show that (1) the global colocation quotient of commercial sites and residences in Beijing is below 1, indicating relatively weak spatial association. The spatial association between each commercial format and residences varies greatly and shows the characteristics of integration of high-frequency consumption and separation of low-frequency consumption. Additionally, the spatial associations between high-grade residences and commercial formats are relatively weak, whereas those between low-grade residences and commercial formats are relatively strong. (2) The local spatial association patterns of various commercial formats and residences exhibit obvious spatial heterogeneity. Overall, the proportions of various commercial formats attracted by residences are considerably higher than those of residences attracted by various commercial formats, revealing spatial asymmetry. Within the Fourth Ring Road, commercial formats are mainly attracted by residences, showing a spatial association pattern of “distribute commercial sites according to the location of residences”. The proportions of residences attracted by commercial formats increase outside the Fourth Ring Road, presenting a spatial association pattern of “commercial formats attracting residences”. The findings offer valuable insights into the development mechanisms of commercial and residential spaces and provide valuable information for urban planning.

Spatiotemporal variations and spillover effects of regional water resources metabolism efficiency with heterogeneous resource endowments

Abstract Scientific evaluation of water resources metabolism efficiency (WME) has essential theoretical and practical value for regional water resources security and sustainable utilization. Based on the framework of the water resources metabolism process and construction of the indicator system of WME, the spatiotemporal variations of WME were analyzed using the weighted summation method in the Eastern, Central, and Western regions of China during the period from 1990 to 2020 with heterogeneous resource endowments. The exploratory spatial data analysis (ESDA) and spatial Durbin model were applied to analyze the spatial autocorrelation patterns and reveal spillovers of the WME. The results show that (1) The WME increased at different speeds in the Eastern, Central, and Western regions from 1990 to 2020 with heterogeneous resource endowment, and the spatial variation of WME in the Eastern and Central regions was significantly higher than in the Western regions. (2) The WME had significant spatial autocorrelation except in 2015, indicating obvious spatial agglomeration characteristics and spatial heterogeneity simultaneously. (3) The spatial spillover effects analysis indicated that the waste virtual recycling use ratio, the ratio of output virtual water and input virtual water, and industrial water ratio were the primary factors influencing WME.

Potential land-use function conflicts of cultivated land for urban sustainable development: a case study in Yancheng City, China

IntroductionThe evaluation on the trade-off/synergy relationship of urban cultivated land-use function conflicts (CLUFCs) for improving the sustainability of cultivated land ecosystem is one of the solutions to coordinate the contradiction between land health and economic development and alleviate food crises, and achieve “zero hunger” in the United Nations Sustainable Development Goals (SDGs).MethodsIn this study, Yancheng City was taken as the research object, and the cultivated land ecological function (CLEF) was evaluated by the morphological spatial pattern analysis-minimum cumulative resistance (MSPA-MCR) model from the perspective of multi-objective coordinated development of cultivated land, and cultivated land productive function (CLPF) was evaluated by net primary productivity (NPP). In addition, combined with local indications of spatial association (LISA) analysis, the spatial trade-off/synergy relationship between CLPF and CLEF was quantified and analyzed. The spatial principal co-coordinates-redundancy analysis (SPCoA-RDA) was used to explore the influencing factors and mechanisms of CLUFCs.ResultsThe results show that there are obvious spatial heterogeneity and aggregation distribution characteristics of CLUFCs in Yancheng City. Through SPCoA-RDA, it is found that the spatial differentiation of CLUFCs is the result of the combination of internal (population density, road network, and water network) and external (spatial spillover effect) driving factors.DiscussionBased on these results, the study area was divided into eight types of cultivated land suitability zones under four aggregation relationships of CLUFCs. Comprehensively considering production, CLUFCs were evaluated by socio-economic and geo-spatial statistical dates, and strategies for guiding the coordinated development and sustainable management of urban cultivated land had been put forward. This study can provide a theoretical framework and certain feasible suggestions for the sustainable development and the transformation of cultivated land system in agriculture cities.

Evaluation and spatial-temporal variations of ecological comprehensive index along the Yellow River of Shanxi Province, China

Ecological comprehensive index can quantitatively and visually analyze the temporal and spatial variations of ecological environment quality in a region. Based on the five indices of fractional vegetation coverage, leaf area index, total primary productivity, land surface temperature and wetness obtained by MODIS satellite data in 2001, 2005, 2010, 2015 and 2020, and coupled the comprehensive quality of the eco-environment (K), we analyzed the temporal and spatial variations of ecological quality along the Yellow River of Shanxi Province from 2001 to 2020 by using the principal component analysis and spatial autocorrelation method. The results showed that the mean value of K in the study area increased from 0.3354 to 0.4389 during 2001-2020. The ecological quality along the Yellow River of Shanxi Province improved overall, but with obvious temporal and spatial variations. On the large scale, it presented a pattern of "better in the south and worse in the north". There was difference between hills and mountains on the small scale. It showed a trend of continuous improvement in time, but the rate of change was different. The trend of improvement in the south was stronger than that in the north. From 2001 to 2020, the global Moran I values of K were all greater than 0.93, indicating that the ecological quality along the Yellow River of Shanxi Province had a strong spatial correlation. The types of spatial agglomeration were mainly high-high and low-low. The high-high agglomeration areas were mainly distributed in blocks in the south, while the low-low agglomeration areas were mainly concentrated in the north. The ecological quality of areas alone the Yellow River of Shanxi Province had been greatly improved during the research period, but there was still obvious spatial heterogeneity, which need to strengthen ecological protection.

Thriving arid oasis urban agglomerations: Optimizing ecosystem services pattern under future climate change scenarios using dynamic Bayesian network

The effects of global climate change and human activities are anticipated to significantly impact ecosystem services (ESs), particularly in urban agglomerations of arid regions. This paper proposes a framework integrating the dynamic Bayesian network (DBN), system dynamics (SD) model, patch generation land use simulation (PLUS) model, and the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model for predicting land use change and optimizing ESs spatial patterns that is built upon the SSP-RCP scenarios from CMIP6. This framework is applied to the oasis urban agglomeration on the northern slope of the Tianshan Mountains in Xinjiang (UANSTM), China. The findings indicate that both the SD model and PLUS model can accurately forecast the distribution of future land use. The SD model shows a relative error of less than 2.32%, while the PLUS model demonstrates a Kappa coefficient of 0.89. The land use pattern displays obvious spatial heterogeneity under different climate scenarios. The expansion of cultivated land and construction land is the main form of land use change in UANSTM in the future. The DBN model proficiently simulates the interactive relationships between ESs and diverse factors. The classification error rates for net primary productivity (NPP), habitat quality (HQ), water yield (WY), and soil retention (SR) are 20.04%, 3.47%, 4.45%, and 13.42%, respectively. The prediction and diagnosis of DBN determine the optimal ESs development scenario and the optimal ESs region in the study area. It is found that the majority of ESs in UANSTM are predominantly influenced by natural factors with the exception of HQ. The socio-economic development plays a minor role in such urban agglomerations. This study offers significant insights that can contribute to the fields of ecological protection and land use planning in arid urban agglomerations worldwide.

Spatio-temporal variation and dynamic risk assessment of drought and flood disaster (DFD) in China

It is important to understand the variations of Drought-Flood-Disaster (DFD) from the past to future for disaster management decision-making under the backdrop of global warming. This study explored the spatio-temporal variations of DFD risks in China from the past (2000–2020) to future (2020–2100) based on the natural and socio-economic datasets. The main findings include: (1) The spatial pattern of disaster vulnerability decreased from 2000 to 2100. The overall vulnerability distribution showed a spatial pattern of high east and low west, and its eastern distribution presented high north and low south. (2) The drought hazard danger degree showed a trend of decreasing first and then increasing with obvious spatial heterogeneity. The flood hazard danger degree had a decreasing spatial distribution from southeast to northwest, with an overall gradually increasing trend. (3) The DFD risks showed a spatial pattern of high east and low west, and were more closely related to disaster vulnerability. Overall, the flood and drought risks had good consistency at the highest level (VI), mainly distributed in the North China Plain, Northeast Plain, eastern Sichuan, and southern Guangdong. This level means that the most severe damage to life and property will occur in these regions. (4) The DFD showed the direction of “north(east)-south(west)”, and the main axis of the ellipse moved north eventually. The DFD hot spots were mainly distributed in North China and the middle and lower reaches of the Yangtze River. The DFD cold spots were mainly distributed in the southwest, Qinghai-Tibet region, and Gansu province.