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The Grain for Green Project has led to remarkable changes in land use and ecological environment on the Loess Plateau. Based on the land use data, vegetation factors and social and economic data of 2000, 2010 and 2020, revising the improved table of equivalent factors of ecosystem service value, using spatial autocorrelation analysis and geographical detector, the ecosystem service value of different grid units was calculated as well as the spatial and temporal variation characteristics of ecosystem service value and the driving mechanism of spatial differentiation were discussed. The results show that comparing with 2000, the area of forest land and construction land is increased, the area of grassland is decreased slightly, and the area of cultivated land is decreased significantly in 2020. The ecosystem service value in 2000, 2010 and 2020 is 756.554, 1147.326 and 1 433.551 billion yuan respectively. The ecosystem service value of grassland and forest land accounts for a relatively large proportion. Among the types of ecosystem service value, the regulation service value is the highest, followed by the sup- port service. The spatial aggregation characteristics of ecosystem service value are mainly high-high aggregation and low-low aggregation. Normalized vegetation index (NDVI), precipitation, net primary productivity (NPP), ecological land area proportion and land use degree have significant effects on the spatial differentiation of ecosystem service value. [ABSTRACT FROM AUTHOR]

Introduction: This research examines the coupling coordinated development dynamics between marine ecological governance and marine economic development in China's coastal provinces. The marine ecological governance and economic development data of China's 11 coastal provinces were comprehensively analyzed from 2011 to 2021. Methods: We established a multi-dimensional evaluation index system for marine ecological governance and economic development, employing the global entropy weight method for quantification. Furthermore, the research examines and analyzes the trends in coordinated development and divergence between these two systems by constructing a coupled coordination degree(CCD) model, utilizing the Theil index decomposition method, and employing the geodetector detector. Results: The Northern marine economic circle outperforms the Eastern and Southern ones regarding marine ecological governance, while the Eastern marine economic circle is the most advanced in marine economic development. The results of the CCD model indicate that Guangdong, Shandong, Hebei, and Jiangsu have the best coupling coordinated development, while Hainan, Tianjin, and Guangxi are at the bottom. The results of the Theil index decomposition method indicate that intra-regional disparities are the primary cause of coupling coordinated regional development variations. At the same time, the results of the geographic detector further substantiate that energy structure, degree of industrial agglomeration, and foreign overseas direct investment are the principal influencing factors. Discussion: The study presents policy recommendations derived from the findings intended to foster the integrated advancement of marine ecology and economy in coastal provinces, reduce regional development disparities, and establish a scientific foundation for achieving a sustainable marine economy. [ABSTRACT FROM AUTHOR]

The landscape of the Poyang Lake wetland is significantly influenced by changes in water levels, impacting the distribution of habitats for migratory birds. While long-term effects of water level variations have been extensively studied, short-term impacts on Siberian crane habitats and their ecological vulnerability remain poorly understood. This study utilized 35 years (1987–2022) of Landsat remote sensing data and daily water level records from Poyang Lake to examine the effects of short-term water level fluctuations on the spatial distribution and ecological vulnerability of Siberian crane habitats. The geographic detector method was employed to quantify the explanatory power and interaction effects of factors, including short-term water level fluctuations, on ecological vulnerability. The findings reveal significant differences in the habitats of wintering Siberian cranes across various water level intervals and short-term fluctuation patterns. Short-term water level fluctuations can result in the largest suitable wintering habitat area for Siberian cranes, reaching 1856.41 km2 in this study. These habitats are highly sensitive to short-term water level changes, with rising and falling trends potentially leading to habitat loss. Oscillating water levels in the short term create broader and more concentrated habitats. Notably, fluctuations at low water levels support the sustainability and stability of crane habitats. Furthermore, short-term water level trends and nature reserves play a critical role in maintaining habitat ecological vulnerability; well-managed and protected nature reserves exhibit significant explanatory power, both in single-factor analysis and in their interaction with other environmental factors. Specifically, these protected areas show explanatory power exceeding the 20% threshold for both water level fluctuations and ranges, highlighting the crucial role of anthropogenic management in mitigating ecological vulnerability. This study emphasizes the necessity of scientifically informed regulation of short-term water level fluctuations to protect Siberian crane habitats and provides a strong scientific basis for decision-making support. [ABSTRACT FROM AUTHOR]

As the main component of terrestrial ecosystem, vegetation plays a very important role in regional ecosystem environmental change, global carbon cycle and climate regulation. The Lower Mekong region (LMR) is at the core of Southeast Asia, its vegetation changes will affect the regional ecosystem and climate. Five countries of LMR were selected as the study area, based on MODIS (Moderate-Resolution Imaging Spectroradiometer) NDVI(Normal Difference Vegetation Index) data from 2000 to 2022, using the Sen's slope estimator, Mann–Kendall trend test and geographic detector to study the spatial and temporal variation trends and driving forces of vegetation coverage. The results showed that:(1) From 2000 to 2022,the vegetation coverage in the LMR showed an overall fluctuating upward trend, the annual average Fractional Vegetation Cover(FVC) value was 0.70, mainly with high vegetation coverage and relatively high vegetation coverage. Vegetation distribution had obviously spatial heterogeneity, and the vegetation of Myanmar, Laos and Vietnam was significantly larger than Thailand and Cambodia.(2) The variation trend analysis of Sen_MK showed that the proportion of improved and degraded vegetation coverage areas in the LMR were 56.33% and 37.55% respectively. The vegetation improvement area was much larger than the vegetation degradation area during 2000–2022. According to the variation trend analysis of different countries, the vegetation coverage improvement area in Vietnam, Myanmar and Thailand were larger than the degraded , the overall vegetation coverage variation trend were good. However, in Laos and Cambodia, the degraded areas were larger than the improved, the overall variation trends of coverage were not good.(3) The results of geographic detector showed that the Land Use and Land Cover(LULC) had the greatest influence on vegetation coverage in the study area.The influencing factors of vegetation coverage were different in the LMR. For Vietnam, Thailand and Laos,elevation and slope factors were second only to LULC, for Myanmar and Cambodia, the influence of precipitation factor was second only to LULC. The results provide scientific data support for understanding the ecological environment status and future changes in the research area. [ABSTRACT FROM AUTHOR]

Aligned with the imperatives of national ecological civilization construction, the systematic investigation into the intricate interplay between shifts in land utilization and the assessment of ecosystem services plays a pivotal and indispensable role in advancing ecological civilization. This endeavor holds significant implications. It aids in optimizing the ecological landscape at the regional level and fosters harmonious coexistence between humanity and the natural world. The study utilizes land-use remote sensing interpretation data from three time periods (2000, 2010, and 2020) and employs various methodologies, including equivalent factor coefficient correction, sensitivity analysis, and spatial autocorrelation. The objective is to uncover the spatiotemporal dynamics of land-use changes and Ecosystem Service Value (ESV) in Lanzhou City. Furthermore, geographic detectors are applied to explore the driving factors influencing ESV spatial heterogeneity and their interactions. The research findings indicate the following: (1) From 2000 to 2020, grassland and cropland were the predominant land-use types in Lanzhou City, with cropland and urban land experiencing the most active changes. (2) ESV in Lanzhou City increased from 179.37 billion RMB in 2000 to 193.86 billion RMB in 2020, reflecting an ESV total growth rate of 8.07% and a gradual improvement in the ecological environment. Spatially, ESV exhibits a "west high, east low" distribution pattern, with the center shifting towards the northwest and southeast, gradually reducing spatial imbalance. (3) Analysis of ESV spatial autocorrelation reveals that high-high clusters are predominantly found within the Tulu Gou National Forest Park and the Xinglong Mountain National Natural Reserve, while low-low clusters are primarily concentrated in the central urban area of Lanzhou City. Over the period from 2000 to 2020, the spatial clustering effect of ESV within the study area has progressively intensified. 4)NDVI, precipitation, and GDP emerge as pivotal factors influencing spatial differentiation within Lanzhou City, with natural and societal elements exerting interactive effects on ESV spatial disparities. The research results integrate environmental considerations into the decision-making process, offering valuable insights for formulating targeted ecological protection policies in Lanzhou City. This study embodies concrete measures taken by Lanzhou City in practicing China's concept of "green water and green mountains are golden silver mountains," providing a theoretical basis for the harmonious and sustainable development of the ecological economy. [ABSTRACT FROM AUTHOR]

Investigating the spatiotemporal variations in Aerosol Optical Depth (AOD) in terrestrial ecosystems and their driving factors is significant for deepening our understanding of the relationship between ecosystem types and aerosols. This study utilized 1 km resolution AOD data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Mann–Kendall (M-K) trend test to analyze the spatiotemporal variations in AOD in seven ecosystems in Northern Xinjiang from 2001 to 2023. The geographic detector model was employed to investigate the effects of driving factors, including gross domestic product, population density, specific humidity, precipitation, temperature, wind speed, soil moisture, and elevation, on the distribution of AOD in the ecosystems. The results indicate that over the past 23 years, wetlands had the highest annual average AOD values, followed by settlements, farmlands, deserts, grasslands, others, and forests, respectively. Furthermore, the AOD values decrease with increasing ecosystem elevation. The annual mean of AOD in Northern Xinjiang generally shows a fluctuating upward trend. The M-K test shows that the proportion of area with an increasing trend in AOD in the settlement ecosystems is the highest (92.17%), while the proportion of area with a decreasing trend in the forest ecosystem is the highest (21.78%). On a seasonal scale, grassland, settlement, farmland, forest, and wetland ecosystems exhibit peak values in spring and winter, whereas desert and other ecosystems only show peaks in spring. Different types of ecosystems show different sensitivities to driving factors. Grassland and forest ecosystems are primarily influenced by temperature and altitude, while desert and settlement ecosystems are most affected by wind speed and humidity. Farmlands are mainly influenced by wind speed and altitude, wetlands are significantly impacted by population density and humidity, and other ecosystems are predominantly affected by humidity and altitude. This paper serves as a reference for targeted air pollution prevention and regional ecological environmental protection. [ABSTRACT FROM AUTHOR]

This study aims to analyze the spatiotemporal land-use patterns in the forest-farmland ecotone of ecologically sensitive areas, together with their effects on carbon storage. Effective approaches were proposed to enhance carbon sequestration. The PLUS-InVEST model was also utilized along with the Geodetector. A systematic investigation was implemented to assess the impacts of spatiotemporal land-use patterns from 1990 to 2030 on the carbon storage of terrestrial ecosystems in the forest-farmland ecotone of the Greater Khingan Mountains. Additionally, the driving factors were determined responsible for the changes in carbon storage. The results were summarized as follows:1) The land-use types that experienced the largest area of transition were forests, grasslands, and croplands between 1990 and 2020. Notably, the highest conversion rates were observed in bare land (75.00%), water bodies (61.33%), and impervious surfaces (61.15%). The forest and grassland areas were expected to significantly increase under natural conservation and ecological protection scenarios by 2030. Furthermore, the areas of cropland and grassland were projected to increase under the cropland protection scenario, while the forest areas decreased greatly. The area of cropland declined in the urban development scenario, due to the urban expansion and land-use changes. 2) The total carbon storage in the study area exhibited a general downward trend, decreasing by 6.08×107 t over the past two decades. The largest decrease in carbon storage occurred in forests, followed by grasslands and croplands. In contrast, there was the increasing carbon storage in the impervious surfaces. The carbon storage in 2020 was compared to the projections for 2030. The total carbon storage for 2030 was projected as 1.555×109, 1.562×109, 1.562×109, and 1.561×109 t, respectively, under the four scenarios of cultivated land protection, natural development, ecological protection, urban development, respectively. All scenarios indicated an increase in the total carbon storage, except for the cropland protection. Different scenarios of land-use management varied greatly in the potential of overall carbon sequestration at regional. Natural conservation and ecological protection share the most promise to increase carbon storage. 3) The elevation, population density, and slope were identified as the primary driving factors behind the spatial differentiation of carbon storage in the study area. Among them, there was the most significant interaction between slope and population density, with an interaction strength of 0.74. There was a much stronger impact of multiple driving factors on carbon storage, compared with any single factor. Multifactorial approaches were also required to analyze the spatial dynamics of carbon storage. Therefore, the carbon dynamics of the ecosystem depended mainly on the land-use transitions in the ecotonal regions, like forest-farmland interfaces. The important implications were gained to develop the data-driven strategies of land management. Carbon sinks were also optimized to support biodiversity conservation. Overall, the significant role of targeted interventions was highlighted for the land-use changes in carbon storage and sequestration at regional scales. The findings can greatly contribute to ecosystem management and climate adaptation in the Greater Khingan Mountains. [ABSTRACT FROM AUTHOR]

Exploring the degree of coupling and coordination of agricultural soil and water resources in different regions is of great significance to optimizing the allocation of agricultural soil and water resources and promoting the transformation and development of agricultural production patterns. Based on the data of 117 county-level agricultural land and water resources in Shanxi province, a regional index system was established with reference to previous studies, and methods such as geographic grid, principal component analysis, cluster analysis, and geodetector were used to study the current status of agricultural soil and water resources utilization and dominant factors in Shanxi in-depth. The results showed that Shanxi agricultural soil and water resources could be divided into 4 first-level regions (Region A, Region B, Region C, and Region D) from good to worse, and each first-level region was subdivided into 3 sub-regions, which could be divided into 12 sub-regions in total. The overall difference between the first-level regions was significant: Region A had superior water and heat conditions and better utilization of soil and water resources (arable land index and water resources index of 0.39 and 0.98, respectively, were the best in the four first-level areas), which was mainly distributed in Yuncheng basin in the southwestern part of Shanxi. Region B had good water and heat conditions and higher utilization rate of water resources, but with average utilization of cultivated land, which wa mainly distributed in Fen river basin in the central part of Shanxi, the Yellow river in the western part of Shanxi and Qin river basin in the southeastern part of Shanxi. Region C had better hydrothermal conditions and good utilization of water resources, but relatively poor utilization of arable land, which was mainly located in the Lvliang mountain system and Taihang mountain. Region D had more general hydrothermal conditions and soil and water resource utilization, and was mainly located in northwestern and north of Shanxi. In terms of sub-region division, the three sub-regions in Region A had balanced distribution of soil and water resources, small differences, concentrated distribution, and balanced region share. Region B was dominated by the sub-region with adequate agricultural water utilization, and its distribution was more concentrated. Region C was dominated by the sub-region of insufficient agricultural water utilization and its contiguous distribution, and the other two sub-regions were small in region and dispersed. Region D was dominated by the sub-region of upgraded agricultural water irrigation, but its distribution was more scattered. Changes in the soil and water resources system in Shanxi were mainly driven by natural factors, and the influences were, in descending order, the water resources index (0.4961), the proportion of water used in agriculture (0.4815), the annual average temperature (0.4480), the irrigation rate of cultivated land (0.4387), and the effective cumulative temperature ≥10℃ (0.4190), among which the interactions of the average annual temperature and the irrigation rate of arable land were the most significant. The results of this study can provide a reference for optimizing the agricultural planting structure in Shanxi. [ABSTRACT FROM AUTHOR]

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

Against the backdrop of global warming, the pollutants that were once “temporarily stored” in the permafrost are gradually being released, posing significant impacts on the environment. This has become an internationally focused hot topic. In this study, the contents of 11 elements such as As, Ti, Cd, Cr, Co, Mn, Cu, Pb, Ni, Zn and V in soil samples from 128 sampling points in the freeze–thaw area of the Tuotuo River in the source region of the Yangtze River on the Qinghai-Tibet Plateau were determined to evaluate the possible sources, contamination status and ecological, environmental and health risks of these elements. The mean values of As, Cd, Pb and Zn were higher than the corresponding Tibet soil background values. Among fourteen PTEs, As, Cd and Pb had the highest average values of enrichment factor and pollution index, indicating that freeze–thaw area soils showed moderate enrichment and pollution with As, Cd and Pb. Mean ecological risk factor (ER) of Cd was 109 and other PTEs mean ER values < 40, whereas ecological risk index (RI) values of all PTEs ranged from 59.5 to 880 and mean RI values was 152, indicating moderate ecological risk in study area. Explanatory power q value of total S (TS) content was 0.217 by GeogDetector, indicating TS was the most significant contributing factor to RI. Correlation analysis and PCA analysis showed that Cr, Cu, Ni, Co, Mn, Ti, V were mainly originated from natural sources, Cd, Pb and Zn from traffic activity, As from long-distance migration-freeze–thaw. [ABSTRACT FROM AUTHOR]

Sloping farmland (SpF) is not only an important space for food production and supply in China's hilly areas, but also a major source of soil erosion. Thus, it is important to achieve a healthy balance between regional food security and environmental protection. Yangtze River Economic Belt (YREB), an important grain production base where SpF concentrated in China, is also faced with serious soil erosion. However, research at the macro scale on the spatiotemporal change of SpF and its driving forces in YREB is still lacking. To bridge the gap, we first analyzed the long-term evolution characteristics of SpF in 1069 counties in the YREB and then explored the driving mechanism of SpF changes during 1980–2020. Results showed that the SpF in the YREB continuously decreased during the study period, with a total area decreasing by 26,300 km2. SpF was primarily concentrated in the upper reaches of the YREB while SpF use dynamic degree varied significantly with the most active change in the lower reaches, reaching to a maximum of 0.324%. The spatial gravity of SpF distribution relocated 20.15 km towards the southwest. As for the driving factors, the socioeconomic factors contributed greater to SpF changes in the whole YREB and its subregions. The intensity of human activities is the most crucial, with factor contribution rate constantly above 0.76. The interactive detection revealed that the prevailing interaction format was primarily bi-enhanced, supplemented with nonlinear-enhanced, which amplified the role of different factors after interacting with them. The pair-wise interaction involving socioeconomic factors had a more potential effect on SpF changes compared to those between physical geography and locational factors. The influence of the intensity of human activities on SpF changes is greatly enhanced after interacting with any factor. It dominated SpF changes in the YREB and its interaction with GDP played an important role at all times. These findings can enlighten differential management strategies of SpF use and ecological conservation in the YREB. [ABSTRACT FROM AUTHOR]

Land use and land cover change (LUCC) significantly influences the dynamics of carbon storage in thin terrestrial ecosystems. Investigating the interplay between land use alterations and carbon sequestration is crucial for refining regional land use configurations, sustaining the regional carbon balance, and augmenting regional carbon storage. Using land use data from the Pearl River Delta Urban Agglomeration (PRDUA) from 2010 to 2020, this study employed PLUS-InVEST models to analyze the spatiotemporal dynamics of land use and carbon storage. Projections for the years 2030, 2040, and 2050 were performed under three distinct developmental scenarios, namely, natural development (ND), city priority development (CPD), and ecological protection development (EPD), to forecast changes in land use and carbon storage. The geographic detector model was leveraged to dissect the determinants of the spatial and temporal variability of carbon storage, offering pertinent recommendations. The results showed that (1) during 2010–2020, the carbon storage in the PRDUA showed a decreasing trend, with a total decrease of 9.52 × 106 Mg, and the spatial distribution of carbon density in the urban agglomeration was imbalanced and showed an overall trend in increasing from the center to the periphery. (2) Clear differences in carbon storage were observed among the three development scenarios of the PRDUA between 2030 and 2050. Only the EPD scenario achieved an increase in carbon storage of 1.10 × 106 Mg, and it was the scenario with the greatest potential for carbon sequestration. (3) Among the drivers of the evolution of spatial land use patterns, population, the normalized difference vegetation index (NDVI), and distance to the railway had the greatest influence on LUCC. (4) The annual average temperature, annual average rainfall, and GDP exerted a significant influence on the spatiotemporal dynamics of carbon storage in the PRDUA, and the interactions between the 15 drivers and changes in carbon storage predominantly manifested as nonlinear and double-factor enhancements. The results provide a theoretical basis for future spatial planning and achieving carbon neutrality in the PRDUA. [ABSTRACT FROM AUTHOR]

The exploitation of Maoming oil shale has significantly contributed to the local economic development. However, the mining activities have resulted in a series of ecological and environmental issues. In 2013, the comprehensive ecological restoration project for the Maoming open-pit mine was officially initiated. To monitor the ecological rehabilitation process of abandoned open pit mines, this study focuses on the Maoming oil shale mining area. The temporal and spatial evolution characteristics of the ecological environment in the Maoming oil shale mining area after closure were analyzed using Landsat remote sensing images from 1993 to 2021, taking into consideration factors such as the water area of the pit, fractional vegetation cover （FVC）, and remote sensing ecological index （RSEI）. Geographical detector analysis was employed to investigate the influencing factors of ecological environment quality in the study area. The results revealed that: （1）after the mine was abandoned, the water area within the mine gradually expanded and stabilizing at 4.6 km2 after 2017.（2）Within the 1 km buffer zone of the mine, the value of FVC exhibited minor fluctuations from 1993 to 2013, and showed a significant increase trend from 2014 to 2017, then the growth rate slowed down after 2017. The average of FVC of the north dump reached a value of 0.809 in 2008, and subsequently remained relatively stable.（3）Within the 1 km buffer zone of the mine, there was a noticeable increase in RSEI average values during the mine restoration period, although some areas still experienced slight declines, indicating that implementation of the project may have had certain impacts on the ecological environment during this phase. The average of RSEI of the north dump demonstrated an increasing trend and tended towards stability after 2007.（4）Land use and night light significantly influence spatial distribution patterns of ecological environment quality in this region. This study serves as a valuable reference for evaluating ecological environment quality in mining areas. [ABSTRACT FROM AUTHOR]

[Objective] This study aims to comprehend the spatial distribution patterns of arable soil nutrients in various geomorphic conditions of the Loess Plateau, to unveil the driving factors behind these changes, and to provide the critical insights for precision management in the regional agriculture and the construction of agricultural projects. [Methods] Based on the 2020 soil nutrient data from the Loess Plateau in Shaanxi, the Kriging interpolation method was employed to analyze the spatial patterns of soil nutrients across four different geomorphic types. The driving factors behind these nutrient spatial variations was explored by using the geodetector model. [Results] (1) In the Loess Plateau, spanning from the Great Wall's sandy lands, through the hilly and gully regions of northern Shaanxi, the loess table lands in northern of Weihe River, to the Guanzhong Plain, the average contents of soil organic matter (SOM), total nitrogen (TN), available phosphorus (AP), and available potassium (AK) exhibited a gradual increasing trend. Specifically, the SOM content averaged 10.20, 10.08, 15.28, and 18.78 g/kg, respectively, across these regions. TN averaged 0.63, 0.66, 0.98, and 1.19 g/kg. AP level averaged 12.99, 13.10, 16.97, and 27.24 mg/kg, and AK averaged 117.72, 149.94, 217.27, and 252.83 mg/kg, respectively. This trend indicated a consistent increase from the sandy lands to the plains. (2) In the loess area of Shaanxi, the duration of sunshine had most significant factor influencing overall nutrient contents, followed by annual temperature and fertilizer use. The distribution of nutrients in the windy area was predominantly affected by soil bulk density, whereas in the hilly and gully areas, plateau areas, and plains, fertilizer use was the primary influencing factor. The interaction of various factors provided a more comprehensive explanatory of nutrient dynamics than individual factor alone. [Conclusion] To optimize soil health, it is advisable to increase nutrient input and enhance soil fertility retention in sandy areas and hilly and gully areas. In contrast, the focus should be on improving nutrient utilization efficiency for plateau and plain areas. Additionally, in the process of farmland, it is crucial to tailor human activities to suit the environmental characteristics and specific conditions of different geomorphic regions. [ABSTRACT FROM AUTHOR]

[Objective] The aims of this study are to reveal the temporal and spatial variation characteristics of soil moisture in the Weihe River Basin, to clarify the main factors affecting soil moisture changes, so as to provide scientific basis for effective monitoring of agricultural drought in the Weihe River Basin. [Methods] Based on the MODIS NDVI, LST data and climatic data of Weihe River Basin from 2000 to 2020, integrated trend analysis and geographic detector, the NDVI-Ts characteristic space was constructed, and the spatiotemporal variation of soil moisture and its driving factors were analyzed. [Results] In the past 20 years, the soil moisture in Weihe River Basin showed a significant downward trend at the rate of 0.004 9/a, and there was an obvious drying phenomenon. In different land use types, the soil moisture contents in the past 20 years followed the order: woodland > grassland > cultivated land > urban and construction land. The overall dry and wet grade was mainly normal (0.4≤TVDI < 0.6). The low value areas of soil moisture mainly distributed in the west and north of Weihe River Basin, and the high value area primarily concentrated in the southeast and northwest edge areas. In the sub-basins, the proportion of drought area in the main basin of Weihe River showed an upward trend, in which the decreasing trend of soil moisture in Guanzhong Plain located in the south of the main basin of Weihe River was the most significant. According to the influence analysis of detection factors, it was found that elevation, the average temperature and the potential evapotranspiration were the main factors affecting soil moisture distribution in Weihe River Basin, and their explanatory power was significantly higher than that of other factors. Factor interaction analysis showed that the combination of the average temperature and the cumulative precipitation had a significant effect on the spatial distribution of soil moisture in Weihe River Basin. [Conclusion] Soil moisture in Weihe River Basin had decreased significantly in the past 20 years, and there was an obvious drying trend. The change of soil moisture in Weihe River Basin was mainly affected by topography, geomorphology and meteorological factors. [ABSTRACT FROM AUTHOR]

[Objective] The primary objective of this study is to investigate the spatiotemporal variations in net primary productivity (NPP) of vegetation within Qinghai Lake Basin from 2000 to 2020. Additionally, it aims to reveal the key factors and their contributive drivers of changes in vegetation NPP. The research is designed to provide a baseline scientific investigation on the dynamics of NPP within Qinghai Lake Basin. [Methods] We used data on vegetation NPP, temperature, precipitation, fractional vegetation cover, and human activity intensity in Qinghai Lake Basin from 2000 to 2020 to analyze the spatiotemporal changes of vegetation NPP across sub-basins, elevations, and micro-terrain in Qinghai Lake Basin. We applied spatial analysis using ArcGIS and the geographic detector model to conduct these analyses. Furthermore, we also investigated the correlations of vegetation NPP with temperature, precipitation, and fractional vegetation cover, as well as the driving factors of vegetation NPP. [Results] (1) In the past 21 years, the annual vegetation NPP in the Qinghai Lake Basin exhibited a fluctuating increase across temporal scales, with a growth rate of 2.22 g C·m²/a, and a spatially increasing trend from northwest to southeast. (2) The study also revealed spatially significant correlations between annual vegetation NPP and mean annual temperature, annual precipitation, and annual fractional vegetation cover, with ratios of 40%, 9%, and 59%, respectively. The primary partial correlation coefficients between mean annual temperature and annual precipitation with annual vegetation NPP encompassed 59.26% and 33.39% of the basin area. (3) The results of our study also revealed that temperature (q=0.58), elevation (q=0.54), and human activity intensity (q=0.38) were principal drivers of basin-scale NPP. Additionally, the interactive impact of these factors was found to better explain these drives than any single factor. [Conclusion] The NPP of vegetation in Qinghai Lake Basin increased over temporal scales from 2000 to 2020. Our study showed spatially significant differences in NPP across elevation, sub-watersheds, and microtopographic patterns. The interactions of temperature, altitude, and human activities were the main driving factors of NPP in the Qinghai Lake Basin. [ABSTRACT FROM AUTHOR]

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

In the Bamen Bay area of the Qinglan Harbor Mangrove Provincial Nature Reserve in Wenchang, Hainan Province, China, mangrove aboveground biomass (AGB) was estimated using high-resolution UAV ortho-imagery and UAV LiDAR data. The spatial distribution characteristics of AGB were studied using global Moran's I index and hotspot analysis. Optimal geographic detectors and regression models were employed to analyze the relationship between AGB and key environmental factors. The results indicate that (1) the average AGB in the study area was 141.22 Mg/ha, with significant spatial variation. High AGB values were concentrated in the southwestern and northeastern regions, while low values were mainly found in the central and southeastern regions. (2) Plant species, water pH, soil total potassium, salinity, dissolved oxygen, elevation, soil organic matter, soil total phosphorus, and soil total nitrogen were identified as major factors influencing the spatial distribution of AGB. The interaction results indicate either bifactor enhancement or nonlinear enhancement, showing a significantly higher impact compared with single factors. (3) Comprehensive regression model results reveal that soil total nitrogen was the primary factor affecting AGB, followed by soil total potassium, with water pH having the least impact. Factors positively correlated with AGB promoted biomass growth, while elevation negatively affected AGB, inhibiting biomass accumulation. The findings provide critical insights that can guide targeted conservation efforts and management strategies aimed at enhancing mangrove ecosystem health and resilience, particularly by focusing on key areas identified for potential improvement and by addressing the complex interactions among environmental factors. [ABSTRACT FROM AUTHOR]

Vegetation greenness has been one of the most widely utilized indicators to assess the vegetation growth status for the better ecological environment. However, in typical tourist regions, the impact of the geographical environment, socioeconomic development, and tourism development on vegetation greenness changes is still a challenge. To address this challenge, we used the Google Earth Engine (GEE) cloud platform combined with a series of Landsat remote sensing images to calculate the fractional vegetation cover (FVC) which can be used as an indicator to characterize the spatiotemporal evolution of vegetation greenness in Hainan Island from 2000 to 2020. Furthermore, we employed geographic detector and structural equation models to quantify the relative importance and explanatory power of the geographical environment, socioeconomic development, and tourism development on vegetation greenness changes and to clarify the interaction of mechanisms of various factors in Haikou and Sanya. The results show that the annual growth rate of the FVC in Hainan Island was 0.0025/a. In terms of spatial distribution, the trend of the FVC changes was mainly characterized by non-significant and extremely significant improvement, accounting for 35.34% and 29.38% of the study area. Future vegetation greenness was dominated by weak counter-persistent increase and weak persistent increase. The geographical environmental factors were the main factors affecting vegetation greenness in Haikou, followed by the socioeconomic and the tourism development factors, while the geographical environmental factors also dominate in Sanya, followed by the tourism development factors and finally the socioeconomic factors. Specifically, the spatial distribution of vegetation greenness was primarily influenced by land use types, elevation, slope, and travel services. Geographical environmental factors could indirectly affect changes in socioeconomic and tourism development, thereby indirectly affecting the spatial distribution of vegetation greenness. These findings can provide some significant implications to guide the ecological environmental protection for sustainable development in Hainan Island in China. [ABSTRACT FROM AUTHOR]

Abstract This paper studied the spatial distribution and influencing factors of heavy metals (HMs) such as Cu, Pb, Zn, Cr, Ni, Cd and As in the soil of Linzhou County in the Lhasa River basin. By collecting 504 surface soil samples, using descriptive statistics, Kriging interpolation and geoaccumulation index methods, combined with the geographic detector model, the spatial distribution characteristics of soil HMs content and its interaction with 19 environmental factors were systematically analyzed.The results showed that the content of heavy metals in the soil in this area was generally higher than the background value of soil in Lhasa, especially Cd and As, which showed strong spatial heterogeneity, suggesting the existence of specific pollution sources.Although the average HMs content was lower than the soil pollution risk screening value, the As, Cd, Pb and Zn contents at some sampling points exceeded the standard, indicating a high pollution risk in some local areas.The spatial distribution of HMs was uneven, with high-value areas of Pb, Zn and Cd mainly concentrated in the west, Cu concentrated in the northwest, while high-value areas of Cr and Ni were similar, mainly concentrated in the west and central regions. Correlation analysis and geodetector models revealed that traffic pollution and soil texture characteristics were the main environmental factors affecting the spatial variation of soil HMs content, and the distance from national highways and urban roads had a particularly significant relationship with Sc and TK.The study provided a scientific basis for the prevention and control of HMs pollution in soil in high-altitude and cold areas, and recommends targeted environmental management and restoration measures.

Abstract Aligned with the imperatives of national ecological civilization construction, the systematic investigation into the intricate interplay between shifts in land utilization and the assessment of ecosystem services plays a pivotal and indispensable role in advancing ecological civilization. This endeavor holds significant implications. It aids in optimizing the ecological landscape at the regional level and fosters harmonious coexistence between humanity and the natural world. The study utilizes land-use remote sensing interpretation data from three time periods (2000, 2010, and 2020) and employs various methodologies, including equivalent factor coefficient correction, sensitivity analysis, and spatial autocorrelation. The objective is to uncover the spatiotemporal dynamics of land-use changes and Ecosystem Service Value (ESV) in Lanzhou City. Furthermore, geographic detectors are applied to explore the driving factors influencing ESV spatial heterogeneity and their interactions. The research findings indicate the following: (1) From 2000 to 2020, grassland and cropland were the predominant land-use types in Lanzhou City, with cropland and urban land experiencing the most active changes. (2) ESV in Lanzhou City increased from 179.37 billion RMB in 2000 to 193.86 billion RMB in 2020, reflecting an ESV total growth rate of 8.07% and a gradual improvement in the ecological environment. Spatially, ESV exhibits a “west high, east low” distribution pattern, with the center shifting towards the northwest and southeast, gradually reducing spatial imbalance. (3) Analysis of ESV spatial autocorrelation reveals that high-high clusters are predominantly found within the Tulu Gou National Forest Park and the Xinglong Mountain National Natural Reserve, while low-low clusters are primarily concentrated in the central urban area of Lanzhou City. Over the period from 2000 to 2020, the spatial clustering effect of ESV within the study area has progressively intensified. 4)NDVI, precipitation, and GDP emerge as pivotal factors influencing spatial differentiation within Lanzhou City, with natural and societal elements exerting interactive effects on ESV spatial disparities. The research results integrate environmental considerations into the decision-making process, offering valuable insights for formulating targeted ecological protection policies in Lanzhou City. This study embodies concrete measures taken by Lanzhou City in practicing China’s concept of “green water and green mountains are golden silver mountains,” providing a theoretical basis for the harmonious and sustainable development of the ecological economy.

Abstract As the main component of terrestrial ecosystem, vegetation plays a very important role in regional ecosystem environmental change, global carbon cycle and climate regulation. The Lower Mekong region (LMR) is at the core of Southeast Asia, its vegetation changes will affect the regional ecosystem and climate. Five countries of LMR were selected as the study area, based on MODIS (Moderate-Resolution Imaging Spectroradiometer) NDVI(Normal Difference Vegetation Index) data from 2000 to 2022, using the Sen’s slope estimator, Mann–Kendall trend test and geographic detector to study the spatial and temporal variation trends and driving forces of vegetation coverage. The results showed that:(1) From 2000 to 2022,the vegetation coverage in the LMR showed an overall fluctuating upward trend, the annual average Fractional Vegetation Cover(FVC) value was 0.70, mainly with high vegetation coverage and relatively high vegetation coverage. Vegetation distribution had obviously spatial heterogeneity, and the vegetation of Myanmar, Laos and Vietnam was significantly larger than Thailand and Cambodia.(2) The variation trend analysis of Sen_MK showed that the proportion of improved and degraded vegetation coverage areas in the LMR were 56.33% and 37.55% respectively. The vegetation improvement area was much larger than the vegetation degradation area during 2000–2022. According to the variation trend analysis of different countries, the vegetation coverage improvement area in Vietnam, Myanmar and Thailand were larger than the degraded , the overall vegetation coverage variation trend were good. However, in Laos and Cambodia, the degraded areas were larger than the improved, the overall variation trends of coverage were not good.(3) The results of geographic detector showed that the Land Use and Land Cover(LULC) had the greatest influence on vegetation coverage in the study area.The influencing factors of vegetation coverage were different in the LMR. For Vietnam, Thailand and Laos,elevation and slope factors were second only to LULC, for Myanmar and Cambodia, the influence of precipitation factor was second only to LULC. The results provide scientific data support for understanding the ecological environment status and future changes in the research area.

[Objective] To implement the new development concept and achieve the “dual carbon”, this study reveals the spatiotemporal evolution characteristics of the carbon rebound effect in the transportation industry and its impact mechanism, expands theoretical boundaries of energy rebound research, provides scientific evidence and strategic references for energy-saving and carbon-reduction practices in the transportation sector based on energy structure transformation. [Methods] This study employed spatial kernel density estimation to analyze the spatiotemporal evolution characteristics of the carbon rebound effect in China’s transportation sector from 2009 to 2021. Panel quantile regression was used to investigate the influence of different factors on the carbon rebound effect at various levels, thereby identifying corresponding driving or restraining mechanisms. A geographic detector model was introduced to further refine the influencing mechanisms. [Results] (1) Before the pandemic, the carbon rebound effect in China’s transportation industry primarily followed a pattern of sharp decline followed by gradual rebound, with spatial correlation observed. (2) The carbon rebound effect in the transportation sector were significantly influenced by spatiotemporal factors. Over time, a spatial distribution pattern gradually developed, with weak rebounds predominating and strong rebounds being secondary. (3) The influencing mechanism of the carbon rebound effect in the transportation sector can be divided into four driving or restraining modes (industry-regulation-facility-market driving mode; industry-regulation-energy driving mode; population-finance-government-R&D restraining mode, and population-finance-government restraining mode). Most provinces were affected by low quantile driving and restraining mechanisms, with only a few provinces continuing to be influenced by high quantile restraining and driving mechanisms, primarily located in the Northeast, Northwest, or Southwest regions. (4) Based on the mechanisms influencing carbon rebound effect in the transportation sector, the geographic detector model was introduced to investigate the impact of multi-factor coordination on carbon rebound effect, with the aim of enhancing the cohesion of regional collaborative governance. [Conclusion] The carbon rebound effect is largely homologous to the energy rebound phenomenon. To incorporate the carbon rebound in the transportation industry into policy considerations, and adopt different policy tools based on its temporal and spatial evolution characteristics are essential for accelerating the transformation of transportation energy and adapting to local conditions for emission reduction.

Background The "Fourteenth Five-Year Plan for Healthy Aging" proposes to promote the realization of healthy aging, which not only requires the elderly to be healthy, but also pays attention to the security. With the deepening of the aging society, there is a significant gap in the level of participation of the current pension insurance system for urban and rural residents in various provinces. Under this background, it is of great significance to study the endowment insurance system. Objective To describ the spatial distribution of the basic old-age insurance participation level of urban and rural residents in 31 provinces in China from 2013 to 2020, to observe the spatial correlation and difference of the participation level among provinces, to analyze the relevant influencing factors, and to provide suggestions for the government and medical and health administrative departments to formulate the old-age insurance policy. Methods The data for this study is sourced from the China Statistical Yearbook from 2014 to 2021. The level of participation in urban and rural residential insurance is calculated based on the ratio of the number of urban and rural residents participating in basic pension insurance by region in the public management, social security, and social organization modules to the end of year population in the population clump. The various indicators of influencing factors are all from the 2014-2021 China Statistical Yearbook. Using ArcGIS 10.8 statistical analysis software, the basic pension insurance participation levels of urban and rural residents in 31 provinces were matched with provincial administrative divisions in China. Descriptive research and analysis were conducted on the differences in pension insurance participation levels among 31 provinces. Using methods such as global spatial autocorrelation and Getis Ord Gi * local hotspots, the spatial correlation and hot and cold spots of participation levels were studied, Study the relevant influencing factors by combining geographic detectors. Results Overall, from 2013 to 2020, the number and level of urban and rural resident insurance participants in China had been continuously increasing year by year; from a vertical structure perspective, there were significant differences in the level of insurance participation among provinces; from a horizontal perspective, from 2013 to 2020, the growth rate of most provinces was positive. The participation level of basic pension insurance for urban and rural residents in 31 provinces of China from 2013 to 2020 had spatial correlation. The central provinces were hot areas, while Shanghai is a cold area. The influencing factors on the participation rate were economic development factors, social development factors, policy factors, and cultural and educational factors in descending order. Conclusion The overall level of participation in basic pension insurance for residents has been increasing year by year, but there are differences in the level of participation and growth rate among provinces. The level of economic development is an important factor affecting the level of participation in basic pension insurance for residents.

In the northwest desert region, soil moisture plays a significant role in the water cycle of the soil vegetation atmosphere system by acting as a carrier of heat and moisture between the land and the atmosphere. The local industrial structure and underlying surface types have been significantly impacted by the Kekeya Greening Project's execution. The study of the Kekeya project's effects on soil moisture can offer pertinent theoretical underpinnings for the project's implementation in the areas of mountains, rivers, forests, farmlands, lakes, grasslands, and deserts. Using the soil moisture data from 2000 to 2020 as the data source, the author studied the temporal change and mutation year of soil moisture in Kekeya using trend analysis and mutation analysis first. The geographical dependency of soil moisture was then studied using the Moran index. Ultimately, factor detection, interaction detection, and risk area detection of geographical detectors provided information about the factors influencing soil moisture in Kekeya. According to the findings, there was a clear rising trend in the soil moisture in Kekeya, along with a seasonal variation in the usual distribution. When moderate rain occurs, the soil moisture reacts more strongly than when light rain occurs. The pace of urbanization has the least effect on soil moisture, while GDP (gross domestic product) has the largest. When two factors combine, the impact on soil moisture is greater than when one item acts alone. [ABSTRACT FROM AUTHOR]

Non-surface coal mining is an important means to obtain coal resources. It is crucial to study the influencing factors and ecological risks of soil heavy metal contents of non-surface coal mines for the protection and management of mine area ecosystems. The current study on soil heavy metals in the Fengfeng coal mine, a non-surface mine located in southern Hebei Province, primarily focuses on assessing local soil pollution levels and analyzing the linear effects of influencing factors, which makes it difficult to provide a scientific basis for the effective treatment of soil heavy metals in the entire region. To comprehensively evaluate the pollution level of soil heavy metal of the Fengfeng coal mine and deeply analyze the main influencing factors and their nonlinear mechanisms, 49 surface soil samples were collected and the contents of seven heavy metals (As, Cd, Cr, Cu, Ni, Pb, and Zn) were determined. The single pollution index method and potential ecological risk assessment method were employed to evaluate the soil heavy metal pollution level and potential ecological risks of the mine area, and the geographic detector was utilized to analyze the main influencing factors of the spatial distribution of soil heavy metal content. The results indicated that the soil heavy metal contents of seven types in the mine area exhibited certain spatial heterogeneity, with an overall distribution pattern of high in the north and low in the south. Only the average content of Cd in the samples exceeded the national natural background value. The comprehensive index of soil potential ecological risk was between 45.70 and 132.77, ranging from mild to moderate risk levels. The single heavy metal pollution indices were ranked as Cd (1.818)>Pb (0.744)>Cu (0.715)>Ni (0.714)>Cr (0.701)> Zn (0.684)>As (0.656). The spatial pattern of soil heavy metal content in the Fengfeng coal mine was influenced by human factors such as mining activities and gangue hills, as well as natural factors such as precipitation and soil moisture. Among them, enterprise distribution and transportation activities were the main influencing factors of the spatial differentiation of heavy metal Ni; mining activities were the main influencing factor of heavy metals Cu, Cd, Cr, Pb, and Zn; soil erosion and soil moisture were the main influencing factors of heavy metal As. [ABSTRACT FROM AUTHOR]

Accurate estimation of the distribution of POC in the sea surface is an important issue in understanding the carbon cycle at the basin scale in the ocean. This study explores the best machine learning approach to determine the distribution of POC in the ocean surface layer based on data obtained using satellite remote sensing. In order to estimate and verify the accuracy of this method, it is necessary to obtain a large amount of POC data from field observations, so this study was conducted in the Mediterranean Sea, where such data have been obtained and published. The research initially utilizes the Geographic Detector (GD) method to identify spatial correlations between POC and 47 environmental factors in the region. Four machine learning models of a Bayesian optimized random forest (BRF), a backpropagation neural network, adaptive boosting, and extreme gradient boosting were utilized to construct POC assessment models. Model validation yielded that the BRF exhibited superior performance in estimating sea-surface POC. To build a more accurate tuneRanger random forest (TRRF) model, we introduced the tuneRanger R package for further optimization, resulting in an R2 of 0.868, a mean squared error of 1.119 (mg/m3)2, and a mean absolute error of 1.041 mg/m3. It was employed to estimate the surface POC concentrations in the Mediterranean for May and June 2017. Spatial analysis revealed higher concentrations in the west and north and lower concentrations in the east and south, with higher levels near the coast and lower levels far from the coast. Additionally, we deliberated on the impact of human activities on the surface POC in the Mediterranean. This research contributes a high-precision method for satellite retrieval of surface POC concentrations in the Mediterranean, thereby enriching the understanding of POC dynamics in this area. [ABSTRACT FROM AUTHOR]

Studying spatial and temporal characteristics of land use changes and the driving factors in the Yellow River Basin as well as simulating and predicting future land use is crucial for resource management, ecological protection, and regional sustainable development in the Yellow River Basin. Based on the China Land Cover Dataset (CLCD) of the Yellow River Basin from 1990 to 2021, this study employs various methods such as the Mann–Kendall test and sliding t-test, land use dynamics, the land use transfer matrix, the standard deviation ellipse, the center of gravity migration model, and a geographic detector to explore the spatial and temporal characteristics of land use changes and driving forces in the Yellow River Basin over the past 30 years. Additionally, the study predicts land use types in the study area for the year of 2030 by using the Future Land Use Simulation (FLUS) model. The results show the following: (1) From 1990 to 2021, the area of forest, grassland, water, and impervious surfaces increased significantly, while the area of cropland, shrub, barren land, and wetlands decreased significantly. The most actively changing land use types are cropland, grassland, barren land, and impervious surfaces. (2) The center of gravity for shrub and impervious surfaces shifted westward, while wetlands showed a trend of obvious concentrated distribution, and the remaining land use types exhibited stable directional distributions. (3) Economic factors had a stronger driving effect on land use changes than topographic and climatic factors. The land use changes in the Yellow River Basin are influenced by the coordinated driving forces of multiple factors. (4) In 2030, the main land use types in the Yellow River Basin are still expected to be cropland, grassland, and forest. However, there will be a significant expansion of impervious surfaces and forest land, with substantial encroachment on cropland and grassland. [ABSTRACT FROM AUTHOR]

Vegetation plays an important role in absorbing carbon dioxide and accelerating the achievement of carbon neutrality. As the ecological barrier of North China, the Taihang Mountains are pivotal to the ecological construction project of China. Nevertheless, the dynamic development of the vegetation carbon sink in the region and the impact factors on the sink have not been systematically evaluated. This study employed a comprehensive approach, utilising remote sensing technology and meteorological and topographic data, in conjunction with the net ecosystem productivity (NEP) estimation model to reveal the characteristics of vegetation carbon sinks in the Taihang Mountain, and then revealed the dynamics evolution of the NEP and the inter-annual trend by using Theil–Sen Median slope estimation, the Mann–Kendall test, and the coefficient of dissociation and analysed the driving roles of the influencing factors by using the parameter optimal geographic detector. Our findings suggest that the NEP in the Taihang Mountain area has a clear growth trend in time, the average value of NEP in the Taihang Mountain area is 289 gC-m−2-a−1 from 2000 to 2022, and the spatial distribution shows the characteristics of high in the northeast and low in the middle and west, with a gradual increase from the northeast to the southwest; the areas with high fluctuation of NEP are mainly distributed in the areas around some cities that are susceptible to the interference of natural or anthropogenic factors. The vegetation carbon sinks in the Taihang Mountains are influenced by a variety of natural factors, among which the explanatory power of each natural factor is as follows: DEM (0.174) > temperature (0.148) > precipitation (0.026) > slope (0.017) > slope direction (0.003). The natural factor DEM had the strongest explanatory power for NEP changes, and the two-by-two effects of the natural factors on vegetation carbon sinks were all significantly stronger than the effects of a single factor, in which the interaction between DEM and precipitation had the strongest explanatory power; distinguishing from climate change factors, the contribution of anthropogenic activities to NEP changes in more than 90% of the area of the Taihang Mountainous Region was more than 60%, and the driving force of anthropogenic factors on NEP changes in the Taihang Mountainous Region was significantly stronger than that of natural climate change. The contribution of anthropogenic factors to NEP changes in the Taihang Mountains was significantly stronger than that of natural climate change. The results of this study can not only provide a reference for carbon reduction and sink increase and ecological restoration projects in the Taihang Mountains but also benefit the research paradigm of vegetation carbon sequestration in other regions. [ABSTRACT FROM AUTHOR]

Urban development of clusters situated along rivers significantly affects the health of the river ecosystems, the quality of urban environments, and the overall well-being of local communities. Ecosystem service supply value (ESSV) measures the delivery of ecosystem goods and services within a specific timeframe in a particular area. Using the lower Yellow River urban agglomeration (Shandong section) as a case, we comprehensively applied land use structure and intensity change analysis, quantitative calculation of ESS, and geographical probe methods to unveil ESS and its mechanism of response to the spatio-temporal evolution of the intensity of land use in urban agglomeration along the river. The key results were as follows: (1) Over the past two decades, farmland and construction land areas have continued to decrease and increase, respectively, with the intensity of land use change being highest from 2005 to 2010. (2) ESS has continued to rise over the past 20 years, with the income in 2020 being 11.142 billion yuan, an increase of 31.13%. The "low-value areas" are mainly concentrated in Liaocheng City, Dezhou City, and Tai'an City, which are characterized by predominantly flat terrains where farmland constitutes the principal land use type. Conversely, "high-value areas" are largely in the counties bordering the Yellow River, including the upper estuary in the north and the rugged, southeastern terrains. (3) Areas with concentrated ESSV were primarily localized in the northern estuary area and along the Yellow River in a scattered point-like pattern. The spatial distribution of hotspots has become increasingly concentrated, transitioning from points to planes. Conversely, cold spots initially increased in number before subsequently decreasing. Waterbody was the most sensitive ESSV-determining factor. (4) The spatial heterogeneity of ESSV emerges as a consequence of the interaction of multiple factors, and among these interactions, those involving NDVI and POP contain the greatest explanatory power. Our findings are expected to offer a scientific foundation for optimizing land spatial patterns and enhancing ecological management in the lower Yellow River region. [ABSTRACT FROM AUTHOR]

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Exploring the coupling coordination degree (CCD) between digital village construction (DVC) and agricultural carbon emissions (ACE) is crucial for promoting village revitalization and sustainable agricultural development. Analyzing data from 30 provinces in China in 2011–2020, this paper employs the CCD model, the Dagum Gini coefficient, and the geographic detector for in-depth analysis. The results show that the overall level of CCD gradually increases over time, but the national CCD still remains in a state of "low coordination," and there are apparent spatial differences in the CCD among provinces. In addition, the overall difference in CCD shows a decreasing trend, and the contribution of inter-regional differences has gradually become the most critical source of CCD's regional difference. Finally, the spatial differences of CCD are the result of two-factor interaction, among which the innovation level is the most core driving factor. The above findings provide important implications for China and other developing countries to fully leverage the interaction between village digitalization and agricultural decarbonization to promote sustainable agricultural development. [ABSTRACT FROM AUTHOR]

Arable land green and low-carbon utilization (ALGLU) is an important pathway to safeguard food safety and achieve the green transformation and progress of agriculture, playing a crucial role in promoting agricultural ecological protection and economic sustainability. This study takes the Yangtze River Delta region (YRD), where rapid urbanization is most typical, as the study area. On the basis of fully considering the carbon sink function of arable land, the study measures the green and low-carbon utilization level of arable land in the region using the Super-slack and based measure (Super-SBM) model, and analyzes its spatial and temporal evolution using the spatial autocorrelation model, the center of gravity, and the standard ellipsoid model, and then analyzes its impact with the help of the geographic detector and the geographically weighted regression model. We analyzed the multifactor interaction and spatial heterogeneity of the factors with the help of the geodetector and geographically weighted regression model. Results: (1) The ALGLU in the YRD has shown a fluctuating upward tendency, increasing from 0.7307 in 2012 to 0.8604 in 2022, with a growth rate of 17.75%. The phased changes correspond to national agricultural development policies and the stages of socio-economic development. (2) There are significant spatial differences in the level of ALGLU in the YRD, with high levels distributed in the southwest of Jiangsu, northern Zhejiang, and northwest Anhui, while low levels are distributed in the southwest of the YRD. Positive spatial autocorrelation exists in the level of ALGLU in the YRD. The spatial transfer trends of the gravity and standard deviation ellipses essentially align with changes in the spatial pattern. (3) The level of ALGLU in the YRD is affected by many factors, with the intensity of interaction effects far exceeding that of individual factors. When considering single-factor effects, precipitation, topography, and farmers' income levels are important factors influencing the level of ALGLU. In scenarios involving multiple-factor interactions, agricultural policies become the primary focus of interaction effects. Furthermore, the driving effects of influencing factors exhibit spatial heterogeneity, with significant differences in the direction and extent of driving effects of each factor in different cities. This study can provide valuable insights for future ALGLU in the YRD and regional sustainable development. [ABSTRACT FROM AUTHOR]

In order to explore the characteristics and driving mechanisms of land use and landscape pattern changes in Duyun City, two remote sensing images of Duyun City in 2010 and 2020 were used as data sources. After visual interpretation and accuracy verification, two land use data were formed for analysis. Finally, the driving factors were explored using geographic detectors. The results show that the land type in the study area is mainly forest land, followed by cultivated land, grassland, and construction land;during the research period, the area of cultivated land, grassland, and unused land decreased, while the area of forest land, gardens, construction land, and water increased. The absolute value of land use change dynamics is garden land>unused land>construction land>grassland>water area>cultivated land>forest land. Among them, the growth rate of garden and construction land is relatively large;due to the large base area, the dynamic changes of cultivated land and forest land are not significant. In terms of landscape pattern, the degree of landscape fragmentation has increased. The Shannon Diversity Index (SHDI) and Shannon Uniformity Index (SHEI) showed a slight decrease, indicating a decrease in the degree of diversity among different landscape types. In 2010, land use and landscape patterns were greatly influenced by elevation factors. With the development of the social economy, social and economic factors such as nighttime lighting and population dominated in 2020, and the impact of human activities increased, while the impact of natural factors relatively weakened. [ABSTRACT FROM AUTHOR]

Faced with substantial climatic problems, industrial parks are crucial to attaining sustainable development objectives and China's carbon emission pledges. This study develops an output-oriented undesirable output Super-SBM model under non-incremental settings to evaluate the carbon emission efficiency of 169 national high-tech zones from 2008 to 2021. It utilizes the Dagum Gini coefficient and kernel density estimation approaches to analyze spatial variances and dynamic changes, as well as geographic detectors to assess the variables influencing the spatial development of carbon emission efficiency. This study uncovers a spatial distribution pattern of carbon emission efficiency within the eastern region of the national high-tech zone that is much superior to that in the western region. This tendency is mostly driven by inter-regional disparities. Carbon emission efficiency differences between various high-tech zones are progressively widening, displaying left-tail and polarization phenomena. Economic development gaps emerge as the main intrinsic factor contributing to spatial variations in carbon emission efficiency, with their interaction with land resource utilization being a key driving force. External factors, particularly differences in government interventions, dominate the spatiotemporal evolution of carbon emission efficiency, and their combined effect increases the evolution's explanatory power. These research findings offer a solid foundation for crafting region-specific carbon reduction policies in national high-tech zones and provide valuable insights for enhancing carbon emission efficiency in a coordinated manner. [ABSTRACT FROM AUTHOR]

With economic development and urbanization in China, the rural settlements have experienced great change. To explore the evolution process of rural settlements in terms of land, population and industry can reveal the development law of rural spatial distribution, population structure and industrial economy in different stages and regions. Studying the development status and evolution characteristics of villages in the upper Tuojiang River basin in Southwest China in the past 20 years are of significant value. The upper Tuojiang River basin includes the main types of terrain found in the Southwest region: mountainous, plains, and hills, exhibiting a certain typicality of geographical characteristics. This study took towns and townships at the town-level scale as the basic unit of research, and constructed an evaluation system for village evolution based on' land, population, and industry'. It employed Criteria Importance Through Inter-Criteria Correlation (CRITIC) analysis to examine the characteristics of village evolution in the area from 2000 to 2020, and used geographic detector analysis to identify the leading factors affecting village evolution. The results show that: (1) From 2000 to 2010, villages in the upper Tuojiang River basin experienced significant changes, and the pace of these transformations slowed from 2010 to 2020. (2) From a comprehensive perspective, from 2000 to 2020, villages in hilly areas show a decline, while villages in plain areas near the city center show a positive urbanization development. (3) Road accessibility and distance from the city center are the main factors that explain the spatial differentiation of village evolution degree in the study area. This study elucidates the spatiotemporal evolution characteristics of villages in the upper Tuojiang River basin and identifies the primary factors contributing to their changes, which will provide a reference for investigating the development of rural areas in different terrains of Southwest China. [ABSTRACT FROM AUTHOR]

Existing research underscores the significance of block form in fostering urban vitality. However, there is a dearth of evidence on its influence on the catering industry's vitality. Additionally, current studies investigating the correlation between block form and urban vitality have frequently neglected disparities among various types of blocks with dominant functions. We employ a multi-scale geographically weighted regression and a geographic detector to elucidate the effects of block form and the heterogeneity of blocks with dominant functions on the catering industry's vitality. Our findings suggest that the suitable block form can mitigate the catering industry's reliance on factors such as the regional population and public transportation infrastructure, to a certain degree. High-rise buildings and irregular block plans positively influence the catering industry's vitality, while the effects of block area, building density, and functional density display considerable spatial heterogeneity. Commercial blocks are most influenced by block form, whereas public service blocks are least affected. The methodology of this study can be replicated globally to guide urban planners in judiciously allocating commercial facilities, based on the varying spatial form requirements of different blocks, thereby fostering a vibrant city. [ABSTRACT FROM AUTHOR]

To clarify the spatial distribution rules and driving factors of China ′ s rural tourism model villages and facilitate high-quality development of rural tourism, this study used the spatial analysis methods of kernel density, standard deviation ellipse, geographic detector, and spatially weighted regression to investigate the spatial distribution pattern and its influencing factors. The study produced several interesting results. At the national scale, the model villages show a northeast – southwest distribution trend, with a central axis generally along the line of Shandong–Henan–Sichuan. There is also an obvious agglomeration distribution trend having the spatial characteristics of a “three-pole, multi-core, and contiguous”distribution. The spatial distribution of different types of model villages varies greatly. At the provincial scale, the model villages in high-latitude and high-altitude areas of provinces have a sparse spatial distribution, most provinces show low-focus distribution characteristics, the development degree of model villages is best in Beijing, Shanghai, and Hainan, and a rural tourism agglomeration area has been initially formed. The spatial distribution of the model villages is affected by the economic development level (impact intensity 0.65), the level of policy support (0.56), scale of the tourism industry (0.48), and road traffic (0.42)factors. The intensity of the impact decreases in turn and presents a certain degree of spatial heterogeneity, and its natural distribution tends toward model villages being distributed on the third level of terraces below the elevation of 500 m, the third level of river within a buffer zone of 6 km, and the subtropical monsoon area. The research shows that the model villages are clustered and distributed in space under the effects of both human and natural factors. [ABSTRACT FROM AUTHOR]

The poverty-stricken counties on the Qinghai-Tibet Plateau are characterized by ecological vulnerability and ecological degradation, which are vulnerable to economic development and human activities, thereby leading to frequent alterations of Land carbon sink changes. Therefore, it is of great significance to study the changes of land carbon sink capacity during the process of eradication of extreme poverty in poverty-stricken counties. Using remote sensing images and socio-economic data, this paper constructed land transfer matrix and land carbon sink model to analyze the changes of land carbon sink capacity in poverty-stricken counties and identified the relevant impact factors through geographic detectors. The results show significant changes in carbon sink-type land and a continuous decrease in the snow area, resulting in an obvious trend of grassland area decrease and barren area increase. Land carbon sink capacity of poverty-stricken counties during the eradication of extreme poverty is higher with an added value of 2.74 times than that before this period. Using the geographic detector to analyze the related factors, strong explanatory power was found in cash crops per capita, share of secondary industry, population density and per capita savings on the changes of carbon sink capacity in poverty-stricken counties. [ABSTRACT FROM AUTHOR]

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IntroductionThis research examines the coupling coordinated development dynamics between marine ecological governance and marine economic development in China’s coastal provinces. The marine ecological governance and economic development data of China’s 11 coastal provinces were comprehensively analyzed from 2011 to 2021.MethodsWe established a multi-dimensional evaluation index system for marine ecological governance and economic development, employing the global entropy weight method for quantification. Furthermore, the research examines and analyzes the trends in coordinated development and divergence between these two systems by constructing a coupled coordination degree(CCD) model, utilizing the Theil index decomposition method, and employing the geodetector detector.ResultsThe Northern marine economic circle outperforms the Eastern and Southern ones regarding marine ecological governance, while the Eastern marine economic circle is the most advanced in marine economic development. The results of the CCD model indicate that Guangdong, Shandong, Hebei, and Jiangsu have the best coupling coordinated development, while Hainan, Tianjin, and Guangxi are at the bottom. The results of the Theil index decomposition method indicate that intra-regional disparities are the primary cause of coupling coordinated regional development variations. At the same time, the results of the geographic detector further substantiate that energy structure, degree of industrial agglomeration, and foreign overseas direct investment are the principal influencing factors.DiscussionThe study presents policy recommendations derived from the findings intended to foster the integrated advancement of marine ecology and economy in coastal provinces, reduce regional development disparities, and establish a scientific foundation for achieving a sustainable marine economy.

Previous optimization approaches with regard to the overall urban form can no longer meet the demand for accurately implementing building energy consumption carbon emission reduction at small spatial scales. This study constructed building energy consumption-oriented urban functional area division method using points of point-of-interest (POI), three-dimensional building and roadway data with urban functional areas as units. The method linked POI to buildings, using building volume as an auxiliary parameter to determine the functional attributes of blocks while taking into account the building operational energy consumption. The residential functional areas, commercial functional areas and industrial functional areas, which account for more than 90% of the total building operation energy consumption and the top three in terms of share, are selected as the analysis objects. Geographic detector was applied to analyze the mechanism of carbon metabolism in the compact spatial patterns of these three functional areas. The case study in Xiamen, China reveals that (1) Three-dimensional building compactness is an important factor influencing building energy consumption(normalized difference vegetation index q-value is 0.227); (2) the difference in energy consumption between different compactness classes in residential and commercial functional areas is significant, while not in industrial functional areas; (3) according to the three-dimensional building compactness optimization path of this study, the building operation energy consumption in central Xiamen City could be optimized to reduce by 7% in 2015. Based on the self-created building energy consumption-oriented functional area division method, it is concluded at the functional areas scale that different types of urban functional zones have different optimization methods for three-dimensional building compactness. Such optimization can save construction resources and achieve double carbon more effectively.

[Objective] This study was aimed to understand the spatiotemporal changes in extreme climate and its influence on vegetation. [Methods] Based on daily meteorological data (1960—2020) from 115 weather stations in the Qinling-Daba mountains (QBMs) and surrounding areas and satellite-derived normalized difference vegetation index (NDVI), the spatiotemporal variation characteristics of the NDVI in the QBMs and its response to 19 extreme climate indices were analyzed. Geographic detector was used to identify the contribution rate of extreme climate indices and their influence on the NDVI. [Results] (1) The NDVI significantly increased in the majority of the QBMs (80.34%) and decreased in only a few regions (1.09%) from 2000 to 2020. The interannual change rate in the study area was approximately 0.03/10 a. (2) Noticeable warming was observed in the QBMs from 1960 to 2020, with the temperature increasing more at night than during the day, and regions with a larger change in extreme temperature events were mostly found in the Western Qinling Mountains (WQMs). During the study period, extreme precipitation events showed weak changes, extreme precipitation intensity increased in the southwestern QBMs, while in the eastern QBMs, extreme precipitation intensity decreased but extreme precipitation frequency increased. (3) Extreme precipitation events were the main factor affecting NDVI in the west Qinling region, while extreme temperature events were the main factor affecting NDVI in the Qinling and Daba mountain regions; the impact of extreme climate events on NDVI was not independent, and the interaction between extreme climate indices enhances the impact of a single factor on NDVI in a double-factor or nonlinear way. [Conclusion] The spatiotemporal changes in extreme climate and its influence on vegetation were clarified, which could establish scientific evidence for the protection and restoration of vegetation in the QBMs in response to global climate change.

Abstract Studying the relationships between vegetation cover and geography in the Mongolian region of the Yellow River Basin will help to optimize local vegetation recovery strategies and achieve harmonious human relations. Based on MOD13Q1 data, the spatial and temporal variations in fractional vegetation cover (FVC) in the Mongolian Yellow River Basin during 2000–2020 were investigated via trend and correlative analysis. The results are as follows: (1) From 2000 to 2020, the vegetation cover in the Mongolian section of the Yellow River Basin recovered well, the mean increase in the FVC was 0.001/a, the distribution of vegetation showed high coverage in the southeast and low coverage in the northwest, and 31.19% of the total area showed an extremely significant and significant increase in vegetation cover. (2) The explanatory power of each geographic factor significantly differed. Precipitation, soil type, air temperature, land use type and slope were the main driving factors influencing the spatial distribution of the vegetation cover, and for each factor, the explanatory power of its interaction with other factors was greater than that of the single factor. (3) The correlation coefficients between FVC and temperature and precipitation are mainly positive. The mean value of the FVC and its variation trend are characterized by differences in terrain and soil characteristics, population density and land use. Land use conversion can reflect the characteristics of human activities, and positive effects, such as returning farmland to forest and grassland and afforestation of unused land, promote the significant improvement of regional vegetation, while negative effects, such as urban expansion, inhibit the growth of vegetation.

In urban areas, variations in the functional usage of buildings or their clusters directly influence the 2D/3D morphology of buildings which can lead to changes in the ventilation potential (VP) at different heights, but there is a lack of refined quantitative relationship analysis between 3D building form parameters (BFPs) and VP at different heights within a certain urban area. The objective of our study is to obtain simulated wind field data from different heights, considering distances from roads, and transverse and longitudinal sections. We employ partial correlation analysis, simple correlation analysis, and Geographic detectors to uncover the extent and mechanisms of the influence of BFPs on the ventilation effectiveness of neighborhoods in a major urban center in China, specifically Nanjing. The findings demonstrate that, at all heights, there is an inverse relationship between wind speed and building density (BD), with the location of higher wind speed generally aligning with the intersection points. The correlation coefficients between BD and simulated wind speed are 0.040 (1.5 ​m), −0.475 (10 ​m), and −0.314 (30 ​m), while the correlation coefficients between building height (BH) and simulated wind speed are 0.237. However, no significant correlation is observed between floor area ratio (FAR) and simulated wind speed. Geographic detector analysis reveals differences in the correlation between BFPs and simulated wind speed at different heights within various building functional areas. Our study provides some practical information for urban planners and designers to carry out wind sensitivity and adaptation planning and urban design.

Abstract The contamination and quantification of soil potentially toxic elements (PTEs) contamination sources and the determination of driving factors are the premise of soil contamination control. In our study, 788 soil samples from the National Agricultural Park in Chengdu, Sichuan Province were used to evaluate the contamination degree of soil PTEs by pollution factors and pollution load index. The source identification of soil PTEs was performed using positive matrix decomposition (PMF), edge analysis (UNMIX) and absolute principal component score-multiple line regression (APCS-MLR). The geo-detector method (GDM) was used to analysis drivers of soil PTEs pollution sources to help interpret pollution sources derived from receptor models. Result shows that soil Cu, Pb, Zn, Cr, Ni, Cd, As and Hg average content were 35.2, 32.3, 108.9, 91.9, 37.1, 0.22, 9.76 and 0.15 mg/kg in this study area. Except for As, all are higher than the corresponding soil background values in Sichuan Province. The best performance of APCS-MLR was determined by comparison, and APCS-MLR was considered as the preferred receptor model for soil PTEs source distribution in the study area. ACPS-MLR results showed that 82.70% of Cu, 61.6% of Pb, 75.3% of Zn, 91.9% of Cr and 89.4% of Ni came from traffic-industrial emission sources, 60.9% of Hg came from domestic-transportation emission sources, 57.7% of Cd came from agricultural sources, and 89.5% of As came from natural sources. The GDM results showed that distance from first grade highway, population, land utilization and total potassium (TK) content were the main driving factors affecting these four sources, with q values of 0.064, 0.048, 0.069 and 0.058, respectively. The results can provide reference for reducing PTEs contamination in farmland soil.

Alpine grasslands, a crucial component of the Qinghai–Tibet Plateau, play a vital role in maintaining ecological barriers and facilitating sustainable development, and the exact stability change is also the key to coping with climate change and implementing ecological protection projects. The purpose of this study was to identify the spatial and temporal distribution of multi-stage alpine grassland and explore its inter-annual distribution and growth stability. The Guoluo Tibetan Autonomous Prefecture, China (hereinafter referred to as Guoluo), where alpine grassland is widely distributed, was selected as the research area. Long-term stable grassland samples constructed using the Mann–Kendall–Sneyers mutation test method were analyzed alongside random forest classification to identify multi-stage grassland distribution trends from 1990 to 2020. Based on the Fractional Vegetation Cover (FVC) and coefficient of variation (Cv), spatial and temporal changes in grassland quality and their driving factors were discussed. The results show the following: (1) Remote sensing grassland extraction, based on the establishment of long-term stable grassland samples and random forest classification, demonstrated high accuracy and reliability, with OA and Kappa coefficients consistently above 0.89 and 0.77, and PA and UA maintained consistently at approximately 0.9. (2) The distribution of grassland in Guoluo corresponded to the spatial patterns determined by the natural geographical environment, showing a gradual trend from high-cover grassland in the southeast to low-cover grassland in the northwest. The proportion of medium and high-cover grasslands slightly increased, indicating an improvement in grassland quality. However, the encroachment and degradation caused by human activities and climate change resulted in a slight decrease in the proportion of grassland area compared with 1990. (3) Despite the overall grassland ecosystem still having relative stability, local grassland quality changes dramatically, mainly in the north of Maduo County. And significant fluctuations in the area of grassland quality were noted over the last two decades, suggesting potential degradation in ecosystem stability. Climate change and human activities were identified as primary drivers of these changes. Climate change is dominant in the alpine region. The low-warming region is dominated by human activities. These findings offer essential insights for the planning and implementation of alpine grassland ecosystem protection and restoration initiatives and also have important value for exploring the evolution law of alpine grassland ecosystems. [ABSTRACT FROM AUTHOR]

Identifying the spatial characteristics of ecosystem service (ES) supply and demand is crucial for effective ecosystem management and restoration. Past related studies have primarily focused on balancing ES supply and demand and supply clustering, with less attention focused on the drivers of demand clustering and their spatial evolution. This study explored the spatiotemporal supply–demand dynamics in four crucial ecosystem services (ESs) in the Sichuan-Yunnan ecological buffer area region between 2005 and 2019, namely water yield, net primary production, soil conservation, and habitat quality. Self-organizing maps and geographical detectors were used to classify supply–demand ES bundles as their main drivers, respectively. The main results of the study included: (1) A decline in habitat quality, whereas net primary productivity, water yield, and soil conservation increased. However, there were increasing demands for habitat quality, water yield, and net primary productivity, despite the decrease in demand for soil conservation. (2) Demand for habitat quality was met by supply, whereas there were deficits in soil conservation, water yield, and net primary productivity, which contributed to the demand in the east exceeding that elsewhere. (3) The proportion of ES bundle 2 increased, whereas those of the remaining ES bundles declined. Similarly, the areas of ES demand bundles (ESDBs) 1 and 4 decreased, whereas those of 2 and 3 increased. While the spatial extent of the ESBs remained relatively stable, those of the ESDBs in the northern regions increased. Key factors influencing the spatial distribution of ES supply include human activities, population density, and precipitation, whereas land use, population density, and the human activity index primarily affect demand distribution. The results of this study can act as a reference for comprehensive regional ecosystem management. [ABSTRACT FROM AUTHOR]

The natural ecological background of the Yellow River Basin is fragile. Long-term human development and construction activities have led to habitat fragmentation and biodiversity reduction. The Landsat remote sensing image data of 2000, 2010 and 2020 were selected to calculate four indicators of greenness, humidity, dryness and heat to build remote sensing ecological index (RSEI). The RSEI was used to evaluate spatial-temporal evolution characteristics and trends of ecological environment quality in 8 cities and counties (districts) along the main stream of the Yellow River in Henan Province, and geographic detector was used to analyze its driving factors. The results indicate that a) the average RSEI in the study area from 2000 to 2020 is 0.7311, and the overall ecological environment quality is above the middle level. Lingbao City and Zhengzhou City have poor ecological environment quality, while Xin' an County and Mengjin District have good ecological environment quality. b) Over the past 20 years, the ecological environment quality has first been deteriorated and then improved, and most of the areas show an overall improvement trend. The improvement of ecological environment quality in the lower reaches is better than that in the middle reaches. c) The single factor detection results indicate that the driving factors that characterize human activities, such as land use types and GDP, gradually enhance their impact on the quality of the ecological environment. The results of multi factor interaction detection indicate that there is a strong interaction between GDP, land use type and population density with other factors. [ABSTRACT FROM AUTHOR]

[Objective]The aims of this study are to optimize the fine management of cultivated land in Shaanxi Province, to coordinate the contradiction between food demand growth and environmental constraints, to maintain regional food security, and to promote agricultural modernization.[Methods]The Guanzhong area was taken as the research area. Based on land use data and other natural economic data, Lorentz curve, coefficient of variation method, landscape index, spatial autocorrelation and other methods were used to construct an evaluation model of cultivated land fragmentation to explore the temporal and spatial changes of cultivated land fragmentation(CLF)in Guanzhong area, and geographic detectors were used to analyze the driving force of CLF in the area.[Results](1)The spatial distribution of cultivated land resources in Guanzhong area was relatively balanced, and the degree of cultivated land specialization remained at a high level.(2)The spatial and temporal differences in the degree of CLF in Guanzhong region were significant, and the overall degree of CLF showed a downward trend, but the degree of CLF in some areas showed a trend of increasing and decreasing, and the overall trend was low in the east and high in the west.(3)The spatiotemporal differentiation of CLF in Guanzhong region was affected by many factors, and the comprehensive influence of socio-economic factors was significantly stronger than that of natural factors, among which altitude, population density, per capita arable land area and regional GDP were the main influencing factors. The interaction effect between factors was stronger than that of single factor, and two-factor enhancement and nonlinear enhancement were the mainstay.[Conclusion]The problem of cultivated land fragmentation in Guanzhong area has been improved to a certain extent in the past 20 years, but there are large regional differences, and the comprehensive management of cultivated land fragmentation should be further strengthened in terms of social and economic factors, so as to promote the development of agricultural mechanization and modernization in Guanzhong area. [ABSTRACT FROM AUTHOR]