Search

This study assessed the past changes in extreme precipitation and temperature events across the Himalayan Mountains of Pakistan. This cold and mountainous environmental region has witnessed a significant increase in climate-related disasters over the past few decades. Spatiotemporal changes in extreme temperature and precipitation events were analyzed using 24 indices developed by the Expert Team on Climate Change Detection and Indices (ETCCDI). For this study, in situ data of 16 national meteorological stations were obtained from the Pakistan Meteorological Department (PMD) for the past three decades (1991–2020). The significance of the trends was assessed using the modified Mann–Kendall (MMK) test, and the Theil–Sen (TS) slope estimator was used to estimate the slope of the trend. The results showed that there has been a consistent decline in the total precipitation amount across the Himalayan Mountains of Pakistan. The trend exhibited a decrease in the annual average precipitation at a rate of −6.56 mm/year. Simultaneously, there was an increasing trend in the annual average minimum and maximum temperatures at rates of 0.02 °C/year and 0.07 °C/year, respectively. The frequencies of consecutive wet days (CWDs) and maximum 5-day precipitation (RX5day) have decreased significantly, with decreasing rates of −0.40 days/year and −1.18 mm/year, respectively. The amount of precipitation during very wet days (R95p) and extremely wet days was decreased by −19.20 and −13.60 mm/decade, respectively. The warm spell duration (WSDI) and the frequency of warm days (TX90p) across the Himalayan Range both increased by 1.5 and 1.4 days/decade. The number of cold days (TX10p) and cold nights (TN10p) decreased by 2.9 and 3.4 days/decade. The average temperature of the hottest nights (TXn) and the diurnal temperature range (DTR) were increased by 0.10 and 0.30 °C/decade. The results indicated an increasing tendency of dry and warm weather in the Himalayan region of Pakistan, which could have adverse consequences for water resources, agriculture, and disaster management in the country. Therefore, it is essential to prioritize the implementation of localized adaptation techniques in order to enhance sustainable climate resilience and effectively address the emerging climate challenges faced by these mountainous regions. [ABSTRACT FROM AUTHOR]

Introduction: The selection of an optimal scale or granularity in landscape analysis is pivotal for uncovering inherent patterns and changes driven by processes. Variations in spatial resolution can significantly alter the proportions and distributions of various landscape types, thereby impacting the assessment of landscape patterns. Despite its importance, the scale factor is frequently neglected in studies focusing on long-term landscape dynamics. Methods: Bridging this gap, we utilized remote sensing imagery data from 1986 to 2020 for Lushui City, integrating remote sensing (RS) and geographic information system (GIS) technologies to generate land cover maps. Our focus centered on investigating the sensitivity of landscape pattern indices within the 30-1000m scale. Combining the first scale domain with an information loss assessment model, we identified the optimal granularity for the analysis, conducting a detailed spatiotemporal examination of landscape pattern from 1986 to 2020 using the index analysis method. Results and discussion: The results show that: (1) The dominance of forests in Lushui City, yet reveal a significant increase in construction land area over the study period, primarily driven by the conversion of forest and grassland. (2) Among the 10 examined indices, four (PD, ED, TE, and LSI) demonstrated predictable responses to changes in granularity, while three (PAFEAC, COHESION, AI) exhibited unpredictable stepwise reactions. Three indices (LPI, SHDI, PLAND) displayed minimal regularity to granularity changes. (3) The optimal long-term landscape analysis granularity for Lushui was identified as 100 m. (4) Before 1996, the city's landscape exhibited characteristics of aggregation, good connectivity, and minimal anthropogenic disturbance. However, post-1996, the landscape experienced disruptions, leading to an overall increase in fragmentation. The expansion of cultivated land and construction land due to urbanization has intensified landscape fragmentation. However, policies such as converting cropland to forest and planned ecological civilization initiatives have restored forest coverage and improved landscape cohesion and connectivity in Lushui City. This research offers vital insights for ecological planning and resource management in alpine valley watershed cities, deepening our grasp of landscape pattern evolution. [ABSTRACT FROM AUTHOR]

Coastal wetland ecosystems are critical due to their diverse ecological and economic benefits, yet they have been significantly affected by human activities over the past century. Understanding the spatiotemporal changes and underlying factors influencing these ecosystems is crucial for developing effective ecological protection and restoration strategies. This study examines the Tianjin–Hebei coastal wetlands using topographic maps from the 1940s and Landsat satellite imagery from 1975, 2000, and 2020, supplemented by historical literature and field surveys. The aim is to analyze the distribution and classification of coastal wetlands across various temporal intervals. The findings indicate an expansion of the Tianjin–Hebei coastal wetlands from 7301.34 km2 in the 1940s to 8041.73 km2 in 2020. However, natural wetlands have declined by approximately 44.36 km2/year, while constructed wetlands have increased by around 53.61 km2/year. The wetlands have also become increasingly fragmented, with higher numbers of patches and densities. The analysis of driving factors points to human activities—such as urban construction, cultivated land reclamation, sea aquaculture, and land reclamation—as the primary contributors to these changes. Furthermore, the study addresses the ecological and environmental issues stemming from wetland changes and proposes strategies for wetland conservation. This research aims to enhance the understanding among researchers and policymakers of the dynamics and drivers of coastal wetland changes, as well as the major challenges in their protection, and to serve as a foundation for developing evidence-based conservation and restoration strategies. [ABSTRACT FROM AUTHOR]

The impervious surface destroys the regional ecological environment. The research on the correlation between impervious surface and comprehensive ecological effects is of great significance to the optimization of the spatial pattern of land. The impervious surface cover in 2000, 2010, and 2020 was obtained from the linear spectral mixture decomposition model. The spatiotemporal changes characteristics of impervious surface in Nanchang City were analyzed. Indicators such as surface temperature, surface runoff, water network density, habitat quality, NDVI, and carbon emissions were selected to construct a comprehensive ecological effect evaluation system. Geographically weighted regression model was used to explore the spatial correlation between impervious surface changes and the comprehensive ecological effect index in the study area. The results showed that: 1) From 2000 to 2020, the proportion of impervious surface in the total land area of Nanchang City increased from 5.80% to 13.59%, and the overall distribution decreased from the central urban area to the outside, forming a multi-level distribution pattern with the central urban area as the main body, Anyi County and Xinjian District as multiple sub cores. 2) From 2000 to 2020, the concentration of spatial distribution in all districts and counties of Nanchang City was increased, and the impervious surface maintained a rapid growth trend. The central urban area was the area with the most intense transformation from natural surface to artificial surface. 3) From 2000 to 2020, the negative regression impact of impervious surface coverage and comprehensive ecological effect index in Nanchang City first increased and then weakened, from -0.1304 to -0.3745, and then to -0.1099. While the impervious surface deteriorated the regional ecological environment, Nanchang City was actively solving problems such as serious environmental pollution and reduced ecological quality. Nanchang City strives to reasonably protect the ecological environment at the pace of economic development. Nanchang City is moving towards regional sustainable and high-quality development. [ABSTRACT FROM AUTHOR]

Abstract Landscape stability is a paramount concern within the field of landscape ecology. Indices of landscape patterns not only facilitate an effective analysis of land use transformations but also delve into the mechanisms of landscape disturbances across various spatial and temporal dimensions. Utilizing land use data spanning from 2014 to 2022 for the Shibing and Libo-Huanjiang South China Karst (SCK) World Heritage Sites (WHSs), this study delves into the landscape dynamics of these areas over the past 8 years. This investigation employs landscape pattern indices and a moving window technique to construct a landscape stability evaluation model, incorporating indices such as the Contagion Index, Patch Density, and Total Edge Contrast. Moreover, the study employs Moran's I, a spatial autocorrelation index, to scrutinize the shifts in geographical heterogeneity of landscape stability within the said period. The findings reveal: (1) Between 2014 and 2022, the landscape patterns of the Shibing and Libo-Huanjiang WHSs have undergone significant transformations, with Woodland emerging as the predominant landscape type and its area exhibiting an upward trend in recent years. (2) The level of fragmentation within the research area has decreased, landscape diversity has diminished, and the aggregation index has risen, according to the landscape pattern indices from 2014 to 2022, indicating that conservation measures have significantly influenced the evolution of landscape patterns. (3) Throughout most of the study period, landscape stability predominantly remained at a relatively stable level, albeit with noticeable fluctuations in years heavily impacted by human activities. (4) The areas of high-high agglomeration and the hotspots of the heritage sites were primarily concentrated within the core zones of these sites, suggesting focused areas of conservation and landscape integrity.

Currently, the global climate system is complex and ever-changing, with multiple factors influencing climate change. The Qinghai–Tibet Plateau, known as the "Third Pole" of the Earth, is particularly sensitive to global climate change. Without timely and scientific research on the ecological environment of the Qinghai–Tibet Plateau and without summarizing relevant adaptive strategies, global climate change will impact the sustainable development of the plateau. This study utilized Landsat remote sensing images from 2000 to 2020 to extract the snow cover area and snow temperature of the Qinghai–Tibet Plateau using the snow frequency threshold method. The study analyzed the spatiotemporal characteristics of snow cover and temperature over the 20-year period and investigated some of the climate and topographical driving factors influencing their changes. The results showed that from 2000 to 2020, the permanent snow cover area in the Qinghai–Tibet Plateau region showed a fluctuating decreasing trend, reducing from approximately 12.34 thousand km2 to around 9.01 thousand km2; the permanent snow temperature showed an initial increase followed by a decrease during the same period. The highest annual average snow temperature was approximately −3.478 °C, while the lowest annual average temperature was around −8.150 °C. Over the 20-year period, the snow cover area in the plateau was negatively correlated with temperature and precipitation, while snow temperature was positively correlated with temperature and precipitation. The snow cover in the weak wind areas of the plateau showed a significant reduction. Areas with higher average wind speeds, such as shaded slopes and semi-shaded slopes, had larger snow cover areas. These research findings provide important insights into the protection and management of the ecological environment of the Qinghai–Tibet Plateau. [ABSTRACT FROM AUTHOR]

The conflict between economic development and ecological protection continues to intensify, highlighting the necessity for constructing regional ecological security patterns (ESPs) to reconcile the relationship between development and protection effectively. This study used the GMOP and PLUS model to simulate future land use changes by 2030 under the following three scenarios: natural development (ND), ecological protection (EP), and economic development (ED). Employing the MSPA model and circuit theory, it identified ecological source areas and constructed the ESP for the Beijing–Tianjin–Hebei urban agglomeration (BTH) from 2000 to 2030. The results indicate that the proportion of ecological source areas increased from 22.24% in 2000 to 23.09% in 2020, the EP scenario showing the highest proportion of ecological source areas compared with the other two scenarios. These areas are densely distributed in the northern and western mountainous regions, with sparse distributions in the southern plains. The number of ecological corridors grew from 603 in 2000 to 616 in 2020, with the EP scenario having more corridors than the other two scenarios. From 2000 to 2030, corridors in the northern and western mountainous areas were denser, shorter, and more variable, while those in the southern plains were less dense, longer, and relatively stable. Over two decades, habitat areas for species in BTH increased, while landscape connectivity decreased. Compared with 2020 and the other two scenarios, the EP scenario saw an increase in habitat areas and improved landscape connectivity. The impact on ecological corridors and improvement areas primarily arose from a combination of socio-ecological drivers (e.g., elevation, slope, population), while the influence on restoration and key areas mainly stemmed from ecological factors (e.g., elevation, temperature, NDVI, precipitation). The findings demonstrate that distinguishing different geomorphological units to improve and restore the regional environment, while considering socio-ecological drivers, is crucial for restoring the overall ESP and landscape connectivity of BTH. [ABSTRACT FROM AUTHOR]

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

The mainstream basin of the Tarim River serves as a vital ecological security barrier that prevents the merging and expansion of deserts and an important strategic corridor directly linking Qinghai and Xinjiang. With society's development and climate change, ecological issues such as river interruption, vegetation degradation, and land desertification in the basin have notably intensified, and the ecological security is facing a critical test. Exploring the characteristics of landscape changes and their driving factors within the basin is crucial in improving the ecological environment system's management. Based on land use data from 1980 to 2020, this study analyzed the characteristics of the spatiotemporal changes and pattern evolution of the landscape through a landscape transfer matrix and landscape pattern indices. It further revealed the impact factors of the landscape pattern through canonical correspondence analysis. The results showed that (1) in 1980–2020, the areas of desert, forest, farmland, and settlement landscapes increased, while the area of grassland landscape decreased, and the water landscape showed an "increasing–decreasing–recovery" pattern. The landscape transition types mainly included the transition from grassland to desert; mutual transitions among farmland, grassland, and forests; mutual transitions between water and grassland; and the transition from farmland to settlements. (2) The overall landscape pattern demonstrated increased fragmentation, shape complexity, and evenness with decreased aggregation. Furthermore, different landscapes exhibited distinct characteristics of landscape pattern changes; for instance, grassland landscape showed severe fragmentation, while desert landscape displayed the strongest dominance. (3) The landscape pattern was a result of the combined impact of natural and human factors, with the soil thickness (SOT), road density (ROD), annual actual evapotranspiration (AAE), population density (POD), and mean annual temperature (MAT) exhibiting significant influences. Specifically, the settlement and farmland landscapes were mainly influenced by the mean annual relative humidity (MAH), POD, GDP density (GDP), and distance to artificial water (DAW); the forest, grassland, and water landscapes were mainly influenced by the SOT, soil organic matter content (SOM), AAE, ROD, elevation (ELE), MAT, slope (SLP), and distance to natural water (DNW); and the desert landscape was mainly influenced by the DAW, DNW, SLP, AAE, SOT, SOM, and ROD. These findings can provide a scientific reference for landscape management and restoration, as well as sustainable social and economic development, in the mainstream basin of the Tarim River. [ABSTRACT FROM AUTHOR]

Landscape stability is a paramount concern within the field of landscape ecology. Indices of landscape patterns not only facilitate an effective analysis of land use transformations but also delve into the mechanisms of landscape disturbances across various spatial and temporal dimensions. Utilizing land use data spanning from 2014 to 2022 for the Shibing and Libo-Huanjiang South China Karst (SCK) World Heritage Sites (WHSs), this study delves into the landscape dynamics of these areas over the past 8 years. This investigation employs landscape pattern indices and a moving window technique to construct a landscape stability evaluation model, incorporating indices such as the Contagion Index, Patch Density, and Total Edge Contrast. Moreover, the study employs Moran's I, a spatial autocorrelation index, to scrutinize the shifts in geographical heterogeneity of landscape stability within the said period. The findings reveal: (1) Between 2014 and 2022, the landscape patterns of the Shibing and Libo-Huanjiang WHSs have undergone significant transformations, with Woodland emerging as the predominant landscape type and its area exhibiting an upward trend in recent years. (2) The level of fragmentation within the research area has decreased, landscape diversity has diminished, and the aggregation index has risen, according to the landscape pattern indices from 2014 to 2022, indicating that conservation measures have significantly influenced the evolution of landscape patterns. (3) Throughout most of the study period, landscape stability predominantly remained at a relatively stable level, albeit with noticeable fluctuations in years heavily impacted by human activities. (4) The areas of high-high agglomeration and the hotspots of the heritage sites were primarily concentrated within the core zones of these sites, suggesting focused areas of conservation and landscape integrity. [ABSTRACT FROM AUTHOR]

Timely and objective assessment of the optimal season for the construction of remote sensing ecological index (RSEI) is of great significance for accurate and effective assessment of ecological environment quality. We manipulated RSEI in to monitor seasonal variations in ecological environment quality (EEQ) in the Beijing-Tianjin-Hebei (JJJ) region from 2001 to 2020. First, we evaluated image quality across all four seasons and filled in missing observations through liner interpolation. Second, Seasonal RSEI was constructed using MODIS and compared across different years. Third, temporal and spatial variations within the same seasons in EEQ. Additionally, Moran's I was utilized to evaluate spatial autocorrelation of EEQ, and the stability of the correlation between RSEI and four indicators seasonal indicators was compared. The results showed that: 1) the PC1 component concentrates most of the characteristics of the four indicators, especially in summer (over 71%); 2) the Moran' I in the summer of 2001, 2006, 2011, 2016 and 2020 are 0.909, 0.898, 0.917, 0.921 and 0.892, respectively, which indicated that the EEQ has a strong positive spatial correlation. 3) the correlation between the four indicators and summer RSEI showed high correlation in different years, and the standard deviation of the correlation between the four indicators and RSEI fluctuated most slightly in summer, which the std of NDVI, WET, LST and, NDBSI were 0.005, 0.052, 0.026 and 0.017, respectively. This study theoretically demonstrates that summer is the optimal season for constructing RSEI, filling the research gap in previous studies regarding the rationale for selecting images from periods of vigorous vegetation growth for RSEI construction, which can provide a reference for selecting the optimum season for the ecological quality monitoring of urban in the future. [ABSTRACT FROM AUTHOR]

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

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

The surface solar radiation in most parts of the world has undergone a phenomenon known as global dimming and brightening, characterized by an initial decrease followed by an increase. As a result, the sunshine duration (SD) has decreased in the past 60 years. Against the backdrop of global dimming and brightening, SD has decreased to varying degrees in many regions of China. Using the observed data of SD, cloud amount (total cloud amount and low cloud amount, abbreviated as TCA and LCA), precipitation, and relative humidity (RH) from 34 meteorological stations in Chongqing during the period of 1961–2020, along with a digital elevation model (DEM) with a resolution of 90 m, this study analyzed the spatiotemporal variations and influencing factors of SD. The analysis employed methods such as linear regression, Mann-Kendall test, wavelet transformation, and DEM-based possible SD distributed model. The results showed that the annual SD in Chongqing has significantly decreased over the last 60 years, with a decreasing interannual trend rate (ITR) of 40.4 h/10a. Except for no obvious trend in spring, SD decreased significantly in summer, autumn and winter at the ITR of 21.1 h/10a, 8.5 h/10a and 7.5 h/10a, respectively. An abrupt decrease in the annual SD was found in 1979. The difference before and after the abrupt decrease was 177.7 h. The difference before and after the abrupt decrease was 177.7 h. The annual SD possessed the oscillation period of 11a. The spatial heterogeneity of the mean annual SD during the last 60 years was obvious. The distribution of SD in Chongqing is high in the northeast and low in the southeast. In addition, about 73% of the total area in Chongqing showed a significant and very significant decreasing trend. The regions with significant changes are mainly concentrated in the regions with altitudes of 200∼1000 m. The increasing LCA was the main cause of the decrease of the annual SD in the regions with 200–400 m altitude decreased the most and changed the most. Increasing LCA is the primary cause of the reduction in annual SD, showing a strong negative correlation coefficient of −0.7292. In Chongqing, PM2.5 concentration showed a significant decrease trend in annual, spring, autumn and winter during 2000–2020, but the significant correlation between PM2.5 concentration and SD was only in autumn and reached an extremely significant level. [ABSTRACT FROM AUTHOR]

Grasslands in the Tibetan Plateau (TP) provide substantial ecosystem services (ESs) but face considerable challenges. Previous assessments of grassland ecosystem service value (GESV) have revealed substantial uncertainties due to inconsistencies in GES classifications, land use data, and assessment methods. Here, we propose a new classification system, present merged land use data, and develop integrated comprehensive assessment methods to reassess the GESV in the TP from 1995 to 2015, and then analyzed spatiotemporal changes and driving factors. Our findings indicate that: 1) grasslands dominate the TP, covering approximately 70 % of the land surface, but have been continuously declining, especially during 1995–2000. 2) The value equivalent factor method tends to overestimate GESV, and our reassessment further emphasized the critical role of grasslands. 3) Temporally, GESV exhibited a measured recovery post-2000, though it remained below initial levels. 4) Spatially, GESV declined from southeast to northwest, mainly influenced by precipitation, although this spatial gradient has gradually diminished. 5) Both climatic and anthropogenic factors significantly influenced changes in GESV, but even dual factors had limited explanatory power. Our reassessment sheds light on the spatiotemporal changes and drivers of GESV in the TP over two decades, which is important for grassland management in the region. However, methodological limitations remain, particularly with regard to data accuracy; and further exploration of spatial heterogeneity and multi-factor interactions are also required.

IntroductionThe selection of an optimal scale or granularity in landscape analysis is pivotal for uncovering inherent patterns and changes driven by processes. Variations in spatial resolution can significantly alter the proportions and distributions of various landscape types, thereby impacting the assessment of landscape patterns. Despite its importance, the scale factor is frequently neglected in studies focusing on long-term landscape dynamics.MethodsBridging this gap, we utilized remote sensing imagery data from 1986 to 2020 for Lushui City, integrating remote sensing (RS) and geographic information system (GIS) technologies to generate land cover maps. Our focus centered on investigating the sensitivity of landscape pattern indices within the 30–1000m scale. Combining the first scale domain with an information loss assessment model, we identified the optimal granularity for the analysis, conducting a detailed spatiotemporal examination of landscape pattern from 1986 to 2020 using the index analysis method.Results and discussionThe results show that: (1) The dominance of forests in Lushui City, yet reveal a significant increase in construction land area over the study period, primarily driven by the conversion of forest and grassland. (2) Among the 10 examined indices, four (PD, ED, TE, and LSI) demonstrated predictable responses to changes in granularity, while three (PAFEAC, COHESION, AI) exhibited unpredictable stepwise reactions. Three indices (LPI, SHDI, PLAND) displayed minimal regularity to granularity changes. (3) The optimal long-term landscape analysis granularity for Lushui was identified as 100 m. (4) Before 1996, the city’s landscape exhibited characteristics of aggregation, good connectivity, and minimal anthropogenic disturbance. However, post-1996, the landscape experienced disruptions, leading to an overall increase in fragmentation. The expansion of cultivated land and construction land due to urbanization has intensified landscape fragmentation. However, policies such as converting cropland to forest and planned ecological civilization initiatives have restored forest coverage and improved landscape cohesion and connectivity in Lushui City. This research offers vital insights for ecological planning and resource management in alpine valley watershed cities, deepening our grasp of landscape pattern evolution.

ABSTRACTChina used to have the world’s most stringent prevention policies during the COVID-19 pandemic. The strict lockdown in Xinjiang region in 2022 was considered to be the longest in the process of COVID-19 pandemic prevention. Therefore, we examined the dynamic effects of the COVID-19 lockdown in Xinjiang region using night-time light data. The findings showed that before the outbreak of COVID-19, the night-time light in Xinjiang region still maintained a significant growth. However, after the lockdown of COVID-19 in August 2022, the night-time light showed a significant decrease, especially in August. Urumqi's night-time light decreased by at least 25% compared to the non-lockdown, while that in other major cities was between 5% and 15%. After the lockdown was lifted in November 2022, the night-time light in Urumqi increased by at least 50% compared to the lockdown, while that in other major cities was generally less than 30%. The regions where night-time light decreased in Urumqi were mainly within a radius of 40 km, whereas that in other cities were mainly concentrated within a radius of 6 km. The changes in statistical data and night-time light indicated that the economic activities in Xinjiang region were significantly affected by the COVID-19 lockdown.

With the escalating global climate change and frequent human activities, Inner Mongolia, as a crucial ecological barrier in the Beijing-Tianjin-Hebei region, Bohai Economic Rim, and even the whole country, confronts many ecosystem issues. To reveal the intricate interplay between natural processes, human activities, and policy interventions shaping the region's ecological landscape, we provide a comprehensive analysis of ecological quality in Inner Mongolia from 2002 to 2021. Key findings include: (1) The research uncovers an overall improvement in ecological quality across Inner Mongolia, albeit with certain regions exhibiting a pattern of deterioration followed by improvement, particularly notable in the central part of the province. (2) Cropland, shrub, grassland, barren, wetland, and water are decreasing, while impervious, and forestland are increasing. (3) Precipitation, temperature, and elevation are significant drivers affecting the quality of the ecological environment. Interestingly, while human production and activities have altered ecological conditions, factors like GDP, population density, and night lighting index do not directly impact environmental quality significantly. This underscores the intricate interplay among various factors within the socioeconomic system, highlighting its complexity. (4) Based on these findings, our policy recommendations include strengthening ecological monitoring and management, promoting sustainable urban development, conducting public education and awareness campaigns, and fostering stakeholder collaboration for data sharing and collective understanding. Adopting sustainable management strategies is essential for promoting ecological resilience and mitigating environmental degradation in Inner Mongolia, not only benefiting the local ecosystem but also contributing to national and global environmental well-being. [ABSTRACT FROM AUTHOR]

As a strategic pillar of the Chinese economy, high-quality development of the tourism industry has become a pressing demand in the contemporary era. Following the new developmental concept advocated by the Chinese government, this study has constructed a comprehensive set of indicators for high-quality tourism development. A thorough spatial analysis of the developmental quality of China's provincial tourism industry from 2000 to 2021, as well as the developmental conditions of various subsystems, was conducted by employing the entropy–value–TOPSIS method, Dagum Gini coefficient, and ESTDA approach. The research has found that (1) the overall quality of China's tourism industry has significantly improved, (2) the determinants of differences in tourism-development quality in China transitioned from endowment advantages to innovation capabilities. (3) positive spatial-agglomeration effects are evident in the developmental landscape of China's tourism industry, (4) the quality of regional tourism development is closely related to the economic development of urban agglomerations, (5) China's tourism industry demonstrates resilience and capacity for restructuring in the post-pandemic era. [ABSTRACT FROM AUTHOR]

[Objective] The aims of this study are to reveal the spatial and temporal variations pattern of grassland greening in Ningxia and proveits driving factors, and provide decision-making reference for effectively managing the grassland carbon reservoir in the ecologically fragile areas of agriculture and animal husbandry in northern China and promoting the long-term ecological increase of grassland in Ningxia. [Methods] Based on NDVI, meteorological and land use data, geographical information map, Sen+Mann-Kendall trend analysis, coefficient of variation, Hurst index, partial correlation analysis, residual analysis methods were adopted. The spatial and temporal distribution and variation characteristics of grassland greenness in Ningxia from 2000 to 2020 were analyzed. The driving mechanism of climate change and human activities on grassland greenness was explored. [Results] The greenness of grassland in Ningxia fluctuated at the rate of 0.007/a, the greenness of meadow grassland was the highest and the fastest growth rate was 0.011/a, and the greenness of desert grassland was the lowest and the slowest growth rate was 0.004/a. The average monthly variation of grassland greenness in Ningxia showed an inverted U-shape, and the maximum greenness of different types of grassland varied greatly, and the minimum value was similar. The spatial difference of grassland greenness in Ningxia was obvious, showing a pattern of high level in the south and the low level in the north. The greenness increased from south to north from March to August, and gradually decreased from north to south from September to February. 97.76% of the greenness of grassland showed an increasing trend, with the largest proportion of extremely significant increase being 48.78%, the greenness of desert grassland and typical grassland changed to high fluctuation and the greening trend was not continuous, and the greenness of meadow grassland changed to medium and low fluctuation and the greening trend was sustainable. Ningxia grassland greenness and temperature were positively correlated with precipitation, and 67.10% of the area was mainly driven by precipitation. The residual analysis showed that human activities mainly had a positive effect on the greenness of grassland in Ningxia, and ecological projects such as returning farmland to grassland promoted the greenness of grassland, and the expansion of construction land led to the reduction of grassland greenness. [Conclusion] Since 2000, the grassland greening of Ningxia has improved significantly, and the increase in southern Ningxia is particularly significant. Desert grassland and typical grassland fluctuate greatly, which needs to reduce the disturbance of human activities in the later management. [ABSTRACT FROM AUTHOR]

[Objective] The aims of this study are to reveal the process of vegetation restoration in loess hilly and gully region before and after the implementation of the Grain for Green Project as well as its topographic differentiation effects, and to provide scientific support for formulating appropriate regional ecological construction and protection countermeasures. [Methods] Based on four Landsat images and digital elevation model data from 1990 to 2019 in the upper reaches of the Beiluo River watershed, the spatiotemporal changes of vegetation coverage and its topographic differentiation characteristics of the study area before and after the implementation of the Grain for Green project were studied using pixel dichotomy model and GIS technology. [Results] (1) The spatial distribution of vegetation coverage in the watershed was high in the southeast and lower in the northwest. From 1990 to 2019, the average annual vegetation coverage of the watershed showed a continuous increasing trend, and the proportion of high-grade vegetation coverage area increased significantly after the implementation of the Grain for Green Project. The proportions of high-grade vegetation coverage area in 1990, 2000, 2010 and 2019 were 0.97%, 6.96%, 42.17% and 64.18%, respectively. (2) In each period of the Grain for Green Project, the vegetation coverage of the watershed improved continuously, but the vegetation degradation occurred in small parts of northwestern of the watershed. During the study period, vegetation coverage structure of the watershed significantly improved. The area with medium-high and high vegetation coverage was mainly transferred in, and the area with medium-low and low vegetation coverage was mainly transferred out. (3) Topographic factors had an obvious impact on the vegetation coverage distribution pattern in the watershed. The vegetation coverage tended to decrease with the increase of elevation. The vegetation coverage was positively correlated with slope, and the steeper the slope, the greater the vegetation coverage. The vegetation coverage showed the characteristics of shady slope＞ half-shady slope＞ flat land＞ half-sunny slope＞ sunny slope. [Conclusion] The implementation of the Grain for Green Project plays a key role in increasing the vegetation coverage in the upper reaches of the Beiluo River watershed, but the vegetation degradation is serious in some areas. In the future, more attention should be paid to the impact of the urban spatial expansion and climate change on vegetation construction in the watershed, so as to cope with the challenges of sustainable development of vegetation ecosystem under the changing environment. [ABSTRACT FROM AUTHOR]

Intensification of urbanization is changing the supply capacities and demand levels of ecosystem services (ESs), and their mismatch has become a major problem for the sustainable development of urban areas. In this study, spatiotemporal changes of three ecosystem services (food provision, C sequestration, recreation) were quantified and imbalances between their supply and demand were identified in Vilnius County (Lithuania) in 2000–2020. The most significant land use transformation was the increase in forest and urbanized land at the expense of agricultural land. The lowest supply and the highest demand for food, carbon sequestration, and outdoor recreation were in the urban center. The urban land ratio had a negative impact on the provision of ecosystems' services during the study period, most notably affecting food supply. Urbanization indicators—population density and urban land area—showed a negative relationship with the provision of ecosystem services. The balance of supply and demand changed during the 2000–2020 period—the growth of suburbs led to the distance of the supply areas from the city, and the area of the intense demand increased. The results of the study highlight the importance of spatial scale in determining the impact of urbanization on ecosystem functions. [ABSTRACT FROM AUTHOR]

Contemporary research on terrestrial carbon exchange processes is paramount for a nuanced comprehension of global and local climatic fluctuations and their interaction with anthropogenic activities. This study delves into the spatiotemporal dynamics of vegetation carbon exchanges within the Three Northern Protection Forest Project Area, leveraging two decades of MODIS NPP data and an innovative NEP estimation model. Our analysis highlights a generally increasing trend in Net Ecosystem Productivity (NEP) from 2000 to 2020, with significant growth in approximately 32.97% of the study area and slight increases in 24.18%. Notably, lower NEP values were found in desert and arid zones, whereas higher values were observed in more vegetated regions like Ningxia, Hebei, Inner Mongolia, and the northeast. The study also assesses the impact of climate variables and land-use changes on NEP, identifying both negative and positive correlations in specific regions. Despite the overall positive trend towards ecological restoration and enhancement, significant uncertainties remain, emphasizing the urgent need for further research to support ecosystem resilience and sustainable management practices. [ABSTRACT FROM AUTHOR]

The determination of compensation standards is the core of horizontal ecological compensation (HEC). However, existing studies focused on the ecological value stocks of ecosystem services (ESs) within an administrative area but ignored their spatial mobility when determining standards, so the HEC policies had difficulty in achieving the desired goals. This study takes the upper-middle reaches of the Yangtze River as the study area, adopts the gravity model to calculate the ecosystem services flow (ESF) in the eight provinces of the area, and formulates a HEC standard accounting model to determine the compensation standards. The results show that there are inhomogeneous distributions of ESs supply and demand from 2005 to 2020. The ESs supply tends to decline, then increase, whereas the demand continuously increases. The total ESF volume from the ESs-providing areas (ESPAs) to the ESs-benefiting areas (ESBAs) first increases and then decreases. In 2020, Tibet, Qinghai, Chongqing, and Hunan are the ESPAs, with Qinghai obtaining the highest compensation standard of 308.56 million CNY and accounting for more than 50% of the total. The ESBAs include Sichuan, Yunnan, Hubei, and Jiangxi, among which Sichuan is the main source of HEC funds with payments of 375.79 million CNY. This study can provide theoretical references for improving HEC rationality, as well as resolving the contradictions between environmental protection costs and benefits externalities for large-scale regions.

Abstract Stringent measures, such as lockdowns, were implemented to curb the virus's spread, leading to reduced pollution levels and environmental improvements at various geographic scales, from cities to regions and nations. Such positive effects have been found and reported for regional scales, but not for a global scale till nowadays. This study aims to fill the gap by uncovering the modifications of global spatiotemporal eco-environmental vulnerability patterns between pre-pandemic (2016) and amid-pandemic (2020) periods. By analyzing various factors influencing the eco-environmental health or geo-health, such as human activities, climate change, and ecological dynamics, we seek to understand the intricate relationships and dynamics within these influential factors. We examined six categories of environmental vulnerability, which encompassed socioeconomics, land resources, natural hazards, hydrometeorology, and topography, using a five-dimensional stressor framework. Our analysis revealed a significant decrease in vulnerability levels across all categories, except for the very low level increased by 78.5% globally. These findings emphasize the detrimental impact of human activities on the global environment. They underscore the urgency of implementing spatial management strategies that prioritize sustainable geo-health development and foster a more resilient Earth.

[Objective] The ecological water requirement (EWR) of vegetation in different typical zones for the rational allocation of water resources in the Inner Mongolia Autonomous Region was analyzed and calculated to provide scientific suggestions for water resources management and ecological protection in this region. [Methods] Based on the Penman-Monteith formula, this study used measured and multi-source remote sensing data to invert EWR and the ecological water requirement per unit area (ET) for vegetation in four typical regions (western, central, eastern, and northeastern regions) of the Inner Mongolia Autonomous Region from 1990 to 2020. The dominant factors of spatiotemporal variation of ET were determined. [Results] ① EWR showed a trend of decreasing and then increasing over the 30-year study period, with the western region being more stable (maintaining an EWR of around 3.00×1010 m3). The central and eastern regions had EWR of around 6.00×1010 m3, with a large variation and a maximum variation of over 1.00×1010 m3 between years. The northeastern region EWR values were higher and stable at around 1.00×1011 m3. ② EWR was higher in the east and lower in the west, and varied greatly from east to west, with the mean ET value in the northeastern region being nearly 250 mm higher than in the west. [Conclusion] The climatic factors (primarily precipitation and evaporation) and anthropogenic factors (primarily land cover type change) were the key factors for the change of ecological water requirement of vegetation in the Inner Mongolia Autonomous Region, with the latter being more influential than the former.

This study assessed the past changes in extreme precipitation and temperature events across the Himalayan Mountains of Pakistan. This cold and mountainous environmental region has witnessed a significant increase in climate-related disasters over the past few decades. Spatiotemporal changes in extreme temperature and precipitation events were analyzed using 24 indices developed by the Expert Team on Climate Change Detection and Indices (ETCCDI). For this study, in situ data of 16 national meteorological stations were obtained from the Pakistan Meteorological Department (PMD) for the past three decades (1991–2020). The significance of the trends was assessed using the modified Mann–Kendall (MMK) test, and the Theil–Sen (TS) slope estimator was used to estimate the slope of the trend. The results showed that there has been a consistent decline in the total precipitation amount across the Himalayan Mountains of Pakistan. The trend exhibited a decrease in the annual average precipitation at a rate of −6.56 mm/year. Simultaneously, there was an increasing trend in the annual average minimum and maximum temperatures at rates of 0.02 °C/year and 0.07 °C/year, respectively. The frequencies of consecutive wet days (CWDs) and maximum 5-day precipitation (RX5day) have decreased significantly, with decreasing rates of −0.40 days/year and −1.18 mm/year, respectively. The amount of precipitation during very wet days (R95p) and extremely wet days was decreased by −19.20 and −13.60 mm/decade, respectively. The warm spell duration (WSDI) and the frequency of warm days (TX90p) across the Himalayan Range both increased by 1.5 and 1.4 days/decade. The number of cold days (TX10p) and cold nights (TN10p) decreased by 2.9 and 3.4 days/decade. The average temperature of the hottest nights (TXn) and the diurnal temperature range (DTR) were increased by 0.10 and 0.30 °C/decade. The results indicated an increasing tendency of dry and warm weather in the Himalayan region of Pakistan, which could have adverse consequences for water resources, agriculture, and disaster management in the country. Therefore, it is essential to prioritize the implementation of localized adaptation techniques in order to enhance sustainable climate resilience and effectively address the emerging climate challenges faced by these mountainous regions.

Coastal wetland ecosystems are critical due to their diverse ecological and economic benefits, yet they have been significantly affected by human activities over the past century. Understanding the spatiotemporal changes and underlying factors influencing these ecosystems is crucial for developing effective ecological protection and restoration strategies. This study examines the Tianjin–Hebei coastal wetlands using topographic maps from the 1940s and Landsat satellite imagery from 1975, 2000, and 2020, supplemented by historical literature and field surveys. The aim is to analyze the distribution and classification of coastal wetlands across various temporal intervals. The findings indicate an expansion of the Tianjin–Hebei coastal wetlands from 7301.34 km2 in the 1940s to 8041.73 km2 in 2020. However, natural wetlands have declined by approximately 44.36 km2/year, while constructed wetlands have increased by around 53.61 km2/year. The wetlands have also become increasingly fragmented, with higher numbers of patches and densities. The analysis of driving factors points to human activities—such as urban construction, cultivated land reclamation, sea aquaculture, and land reclamation—as the primary contributors to these changes. Furthermore, the study addresses the ecological and environmental issues stemming from wetland changes and proposes strategies for wetland conservation. This research aims to enhance the understanding among researchers and policymakers of the dynamics and drivers of coastal wetland changes, as well as the major challenges in their protection, and to serve as a foundation for developing evidence-based conservation and restoration strategies.

Stringent measures, such as lockdowns, were implemented to curb the virus's spread, leading to reduced pollution levels and environmental improvements at various geographic scales, from cities to regions and nations. Such positive effects have been found and reported for regional scales, but not for a global scale till nowadays. This study aims to fill the gap by uncovering the modifications of global spatiotemporal eco-environmental vulnerability patterns between pre-pandemic (2016) and amid-pandemic (2020) periods. By analyzing various factors influencing the eco-environmental health or geo-health, such as human activities, climate change, and ecological dynamics, we seek to understand the intricate relationships and dynamics within these influential factors. We examined six categories of environmental vulnerability, which encompassed socioeconomics, land resources, natural hazards, hydrometeorology, and topography, using a five-dimensional stressor framework. Our analysis revealed a significant decrease in vulnerability levels across all categories, except for the very low level increased by 78.5% globally. These findings emphasize the detrimental impact of human activities on the global environment. They underscore the urgency of implementing spatial management strategies that prioritize sustainable geo-health development and foster a more resilient Earth. [ABSTRACT FROM AUTHOR]

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

The Taklamakan Desert Region (TDR) and the Gobi Desert Region (GDR) in East Asia significantly impact air quality, human health, and climate through dust aerosols. Utilizing the MERRA-2 dataset's long-term dust aerosol optical depth (DAOD) at 550 nm from 2000 to 2022, we systematically monitored the spatiotemporal dynamics of DAOD. Our analysis covered annual, seasonal, and monthly scales, employing geographical detector analyses to investigate the impact of eight factors on DAOD distribution. Over the 23-year period, the interannual variability in DAOD across East Asia was not pronounced, but a discernible decreasing trend was observed, averaging an annual decrease of −0.0002. The TDR had higher DAOD values (0.337) than the GDR (0.103). The TDR showed an average annual increase of 0.004, while the GDR exhibited an average annual decrease of −0.0003. The spatial distribution displayed significant seasonal variations, with peak values in spring, although the peak months varied between the TDR and GDR. The driving factor analysis revealed that relative humidity and soil moisture significantly impacted the DAOD spatial distribution in East Asia, which were identified as common driving factors for both the region and the major dust sources. Complex mechanisms influenced the variation in DAOD, with interactions between variables having a greater impact than individual effects. The geodetector-derived interaction q-value identified the collective impact of soil temperature and relative humidity (0.896) as having the highest impact on the spatial and temporal DAOD distribution. The overall spatial pattern exhibited a nonlinear enhancement trend, with the TDR and GDR showing bilinear enhancement patterns. These findings contribute to a better understanding of the factors influencing DAOD, offering a theoretical basis for atmospheric pollution control in East Asia. [ABSTRACT FROM AUTHOR]

Monitoring shoreline movements is essential for understanding the impact of anthropogenic activities and climate change on the coastal zone dynamics. The use of remote sensing allows for large-scale spatial and temporal studies to better comprehend current trends. This study used Landsat 5 (TM), Landsat 8 (OLI), and Sentinel-2 (MSI) remote sensing images, together with the Otsu algorithm, marching squares algorithm, and tidal correction algorithm, to extract and correct the coastline positions of the east coast of Laizhou Bay in China from 1984 to 2022. The results indicate that 89.63% of the extracted shoreline segments have an error less than 30 m compared to the manually drawn coastline. The total length of the coastline increased from 166.90 km to 364.20 km, throughout the observation period, with a length change intensity (LCI) of 3.11% due to the development of coastal protection and engineering structures for human activities. The anthropization led to a decrease in the natural coastline from 83.33% to 13.89% and a continuous increase in the diversity and human use of the coastline. In particular, the index of coastline diversity (ICTD) and the index of coastline utilization degree (ICUD) increased from 0.39 to 0.79, and from 153.30 to 390.37, respectively. Over 70% of the sandy beaches experienced erosional processes. The shoreline erosion calculated using the end point rate (EPR) and the linear regression rate (LRR) is 79.54% and 85.58%, respectively. The fractal dimension of the coastline shows an increasing trend and is positively correlated with human activities. Coastline changes are primarily attributed to interventions such as land reclamation, aquaculture development, and port construction resulting in the creation of 10,000.20 hectares of new coastal areas. Finally, the use of Kalman filtering for the first time made it possible to predict that approximately 84.58% of the sandy coastline will be eroded to varying degrees by 2032. The research results can provide valuable reference for the scientific planning and rational utilization of resources on the eastern coast of Laizhou Bay. [ABSTRACT FROM AUTHOR]

The distribution of the calculated values of the specific irradiation of the Earth and its surroundings from the Earth's surface to the lower mesosphere is analyzed. The change of incoming transit radiation along three axes of space and time is considered. It was determined that in the annual course of transit irradiation in the polar regions at all altitude levels, two long periods of complete shading (associated with solstices) and two short periods of full illumination (associated with equinoxes) are synchronously observed for the hemispheres. In the latitudinal distribution of annual transit irradiation at all altitude levels in the latitudinal zone of 65°–70° and near it, a maximum is noted in each hemisphere, and a minimum in the equatorial region. For the time interval from 3000 B.C.E. until 2999 A.D. in each hemisphere there are areas of increase, decrease and zero values of transit irradiation. In general, for this time interval there is an increase in transit irradiation of the polar regions of the hemispheres (semi-surfaces of ellipsoids) at all altitude levels and a slight decrease in irradiation to areas located approximately between the polar circles. The result of this is an increase in the transit irradiation of half-surfaces and surfaces of ellipsoids in the space surrounding the Earth. [ABSTRACT FROM AUTHOR]

Seismicity parameters can simplify the understanding of the intrinsic complications that arise in the state of stress across the hypocentral areas of interest. We studied variations of the spatial and temporal changes of these parameters by three different methods: maximum curvature, entire magnitude range, and hierarchical space time point process model across the July 2019 Ridgecrest earthquake region. In order to verify the estimations, the Utsu's test has also been applied. According to the results, seismicity parameters show heterogeneous distribution in this area. The implemented methods provide comparable b-values; however, the b-value displays relatively lower values in northwest and higher values in southeast. Seismicity rate comparison for two periods before and after the M7.1 shock favors change in the b-value. Based on the employed catalog, seismic activity accelerated about half an hour before the M6.4 event. Whereas 2 days before the M7.1 earthquake, seismic activity was low and accelerated approximately 1 day prior to the same event. So there is a clear difference in pre M6.4 and pre M7.1 seismic activity patterns. Moreover, the b-value and magnitude of completeness show decrease before the M7.1 shock, and spatial changes of the b-value expose obvious differences with depth. [ABSTRACT FROM AUTHOR]

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

China's coastal zones, characterized by their ecological vulnerability and significant economic growth, demand effective water conservation management. Such management is pivotal not only for safeguarding water resources but also for ensuring ecological stability and promoting sustainable socio-economic development. In this study, based on the water balance model, the spatiotemporal dynamics of water conservation in the ecosystems of China's coastal areas from 2001 to 2021 were characterized by three dimensions: overall, zonal, and raster. The results show that: ① the distribution pattern of ecosystem water conservation in China's coastal areas from 2001 to 2021 is “high in the south and low in the north”, with a total amount of 117.726 billion m3/a, with the Pearl River Delta and Southwest Coastal Areas as the main high-value areas, and the overall water conservation and its capacity show a “ decreasing-rising-decreasing” pattern. The overall water conservation and its capacity show a fluctuating trend of “falling-rising-falling”. Additionally, water conservation capacity varied significantly among different vegetation types and across marine-terrestrial gradients, with the highest capacity recorded in evergreen coniferous forests and areas situated 140 km from the coastline. ②From 2001 to 2021, the water conservation capacity of China's coastal ecosystems exhibited significant temporal patterns and spatial differentiation along the marine-terrestrial gradient. The research suggests that these patterns of change are intricately linked with the stages of regional development strategies and ecological construction within these coastal zones. ③In China's coastal areas, a mere 11.63 % of the rasters showed significant changes in water conservation, dominated by highly significant and significant increases, mainly in the Southeast Coastal Area, the Pearl River Delta and Southwest Coastal Areas, and the Bohai Bay Coastal Area. This included areas such as the Yangtze River Delta silty coastal plain area, the Bohai Bay silty coastal plain area, the sandy silt coastal hilly terrace area of western Guangdong and Guinan, and other China coastal protection forest system construction projects. ④ Water conservation function within China's coastal ecosystems demonstrates a profound interconnection with both natural and socio-economic determinants. Natural elements such as elevation, slope, and precipitation positively correlate with water conservation metrics. Conversely, evapotranspiration and temperature are inversely related to conservation outcomes. In terms of social factors, water conservation has a significant negative correlation with GDP density and population density, with the highest negative correlation with the GDP2 density.

Abstract Background This study focuses on Dhaka City and its impact on urban surface water. Cities, ecosystems, and agriculture need surface water. It is crucial for water resource planning and environmental preservation. The primary aim is to study how urbanization has affected surface water in Dhaka City over 30 years using satellite imagery. Methods The study analyzed three decades of urban surface water shifts using Landsat 5 TM and Landsat 8 OLI/TIRS satellite imagery and Google Earth Engine (GEE) with JavaScript code for water ratio index detection. To investigate water level changes, field observation surveys and secondary data analysis were conducted. This integrated methodology simplified surface water data extraction and analysis, making remote sensing easier and allowing cloud-based satellite data processing. Results The study demonstrates that the amount of surface water in cities is going down, from 36.23 km2 in 1990 to 5.83 km2 in 2021, which is an enormous decrease. This means that about 20 square kilometers, or 45 percent of the water's surface, have been lost in the last 30 years. The main reasons for the drop are unplanned expansion of cities, accelerated real estate development, and more trade and economic activities in the study area. Conclusions The GEE algorithms provide useful insights into surface water's maximum and minimum extent, enabling appropriate planning and management. These findings aid Dhaka City's water resource management and environmental protection.

The conflict between economic development and ecological protection continues to intensify, highlighting the necessity for constructing regional ecological security patterns (ESPs) to reconcile the relationship between development and protection effectively. This study used the GMOP and PLUS model to simulate future land use changes by 2030 under the following three scenarios: natural development (ND), ecological protection (EP), and economic development (ED). Employing the MSPA model and circuit theory, it identified ecological source areas and constructed the ESP for the Beijing–Tianjin–Hebei urban agglomeration (BTH) from 2000 to 2030. The results indicate that the proportion of ecological source areas increased from 22.24% in 2000 to 23.09% in 2020, the EP scenario showing the highest proportion of ecological source areas compared with the other two scenarios. These areas are densely distributed in the northern and western mountainous regions, with sparse distributions in the southern plains. The number of ecological corridors grew from 603 in 2000 to 616 in 2020, with the EP scenario having more corridors than the other two scenarios. From 2000 to 2030, corridors in the northern and western mountainous areas were denser, shorter, and more variable, while those in the southern plains were less dense, longer, and relatively stable. Over two decades, habitat areas for species in BTH increased, while landscape connectivity decreased. Compared with 2020 and the other two scenarios, the EP scenario saw an increase in habitat areas and improved landscape connectivity. The impact on ecological corridors and improvement areas primarily arose from a combination of socio-ecological drivers (e.g., elevation, slope, population), while the influence on restoration and key areas mainly stemmed from ecological factors (e.g., elevation, temperature, NDVI, precipitation). The findings demonstrate that distinguishing different geomorphological units to improve and restore the regional environment, while considering socio-ecological drivers, is crucial for restoring the overall ESP and landscape connectivity of BTH.

Currently, the global climate system is complex and ever-changing, with multiple factors influencing climate change. The Qinghai–Tibet Plateau, known as the “Third Pole” of the Earth, is particularly sensitive to global climate change. Without timely and scientific research on the ecological environment of the Qinghai–Tibet Plateau and without summarizing relevant adaptive strategies, global climate change will impact the sustainable development of the plateau. This study utilized Landsat remote sensing images from 2000 to 2020 to extract the snow cover area and snow temperature of the Qinghai–Tibet Plateau using the snow frequency threshold method. The study analyzed the spatiotemporal characteristics of snow cover and temperature over the 20-year period and investigated some of the climate and topographical driving factors influencing their changes. The results showed that from 2000 to 2020, the permanent snow cover area in the Qinghai–Tibet Plateau region showed a fluctuating decreasing trend, reducing from approximately 12.34 thousand km2 to around 9.01 thousand km2; the permanent snow temperature showed an initial increase followed by a decrease during the same period. The highest annual average snow temperature was approximately −3.478 °C, while the lowest annual average temperature was around −8.150 °C. Over the 20-year period, the snow cover area in the plateau was negatively correlated with temperature and precipitation, while snow temperature was positively correlated with temperature and precipitation. The snow cover in the weak wind areas of the plateau showed a significant reduction. Areas with higher average wind speeds, such as shaded slopes and semi-shaded slopes, had larger snow cover areas. These research findings provide important insights into the protection and management of the ecological environment of the Qinghai–Tibet Plateau.

The mainstream basin of the Tarim River serves as a vital ecological security barrier that prevents the merging and expansion of deserts and an important strategic corridor directly linking Qinghai and Xinjiang. With society’s development and climate change, ecological issues such as river interruption, vegetation degradation, and land desertification in the basin have notably intensified, and the ecological security is facing a critical test. Exploring the characteristics of landscape changes and their driving factors within the basin is crucial in improving the ecological environment system’s management. Based on land use data from 1980 to 2020, this study analyzed the characteristics of the spatiotemporal changes and pattern evolution of the landscape through a landscape transfer matrix and landscape pattern indices. It further revealed the impact factors of the landscape pattern through canonical correspondence analysis. The results showed that (1) in 1980–2020, the areas of desert, forest, farmland, and settlement landscapes increased, while the area of grassland landscape decreased, and the water landscape showed an “increasing–decreasing–recovery” pattern. The landscape transition types mainly included the transition from grassland to desert; mutual transitions among farmland, grassland, and forests; mutual transitions between water and grassland; and the transition from farmland to settlements. (2) The overall landscape pattern demonstrated increased fragmentation, shape complexity, and evenness with decreased aggregation. Furthermore, different landscapes exhibited distinct characteristics of landscape pattern changes; for instance, grassland landscape showed severe fragmentation, while desert landscape displayed the strongest dominance. (3) The landscape pattern was a result of the combined impact of natural and human factors, with the soil thickness (SOT), road density (ROD), annual actual evapotranspiration (AAE), population density (POD), and mean annual temperature (MAT) exhibiting significant influences. Specifically, the settlement and farmland landscapes were mainly influenced by the mean annual relative humidity (MAH), POD, GDP density (GDP), and distance to artificial water (DAW); the forest, grassland, and water landscapes were mainly influenced by the SOT, soil organic matter content (SOM), AAE, ROD, elevation (ELE), MAT, slope (SLP), and distance to natural water (DNW); and the desert landscape was mainly influenced by the DAW, DNW, SLP, AAE, SOT, SOM, and ROD. These findings can provide a scientific reference for landscape management and restoration, as well as sustainable social and economic development, in the mainstream basin of the Tarim River.

[Objective] The study used the data of 30 provinces (municipalities and autonomous regions) of China from 2004 to 2018 to reveal the spatial and temporal change characteristics and efficiency decomposition of China’s high-quality development of industry based on the super-slacks-based measure (SBM) model and Malmquist-Luenberger (ML) index model, considering non-expected output. The Tobit panel regression model was used to explore the driving mechanism of technological innovation on the development. [Methods] The study used the data of 30 provinces (municipalities and autonomous regions) of China from 2004 to 2018 to reveal the spatial and temporal change characteristics and efficiency decomposition of China’s high-quality development of industry based on the super-slacks-based measure (SBM) model and Malmquist-Luenberger (ML) index model, considering non-expected output. The Tobit panel regression model was used to explore the driving mechanism of technological innovation on the development. [Results] (1) Temporally, China’s high-quality development efficiency of industry showed an overall fluctuating upward trend, and it roughly showed a step-like geographical divergence pattern decreasing from the southeast coast to the northwest inland in space. (2) The ML index and decomposition results show that the improvement of the level of China’s high-quality development of industry mainly came from technological progress, and technical efficiency had less influence. (3) Technological innovation had a significant positive driving effect on the efficiency of high-quality development of industry. However, there were regional heterogeneity in the impact, and the improvement of technological innovation level in the eastern, central, and western regions had a positive driving effect on the improvement of high-quality development level, while the relationship between technological innovation level and high-quality development of industry in the northeastern region was not significant. [Conclusion] Technological innovation was an important means to realize China’s high-quality development of industry, and it was recommended to promote the transformation of industrial development to green, low-carbon, and high-quality development by improving the mechanism of technological innovation, strengthening the cultivation of innovative talents, and narrowing the regional gap of technological innovation.

Often characterized as “sentinels of lake aquatic ecosystems”, different life-form aquatic vegetation covering dynamics reflects both short- and long-term climate fluctuations and human activities. Previous assessments often lack comprehensive spatiotemporal coverage of aquatic vegetation dynamics, prompting a deeper understanding of aquatic vegetation variations and underlying drivers of such change. This article first presents a dataset of semi-decadal-scale trends in aquatic vegetation covering of 616 China’s lakes (>10 km2) from 1986 to 2020, after validating a machine learning method of random forest (RF) by field investigations and literature reviews. The total area of aquatic vegetation in lakes nationwide was varied from 10,345.40 km2 to 17,329.31 km2 (a 67.51 % increase) since 1986, with a growth rate of 169.85 km2/yr. As of 2020, the aquatic vegetation is mainly concentrated in Tibetan Plateau Lake Zone (TPL) (55.99 %) and Eastern Plain Lake Zone (EPL) (25.86 %), followed by other regions. It was identified the changes in aquatic vegetation area experienced three periods: moderate growth (1986–1999), slight losses (2000–2010), and marked recovery (2011–2020). Specifically, the TPL experienced the most remarkable expansion, primarily contrbution from submerged aquatic vegetation (SAV). It is found that smaller lakes in plain area are more conducive to the growth of aquatic vegetation, as shown by the increase in the percentage of aquatic vegetation area (PAV) with the decrease in lake size. But the lakes in TPL showed after 2010 larger lakes are more advantageous in aquatic vegetation recovery, attributing to climate-induced lake expansion. Furthermore, lakes with more intricately shapes also exhibited relative advantages in aquatic vegetation expansion. Geographic and climatic factors also played a pivotal role, with altitude notably influencing temperature and precipitation, thus exerting a considerable impact on aquatic vegetation growth. This study have estimated the semi-decade dynamic characteristics of aquatic vegetation in lakes across China since 1986, concluded that aquatic vegetation ushered in a vigorous recovery period around 2010, offering compelling evidence for the increasing greening trend of aquatic ecosystems.

Urban water bodies constitute a vital element within the urban ecosystem. Knowledge of the spatiotemporal changes in urban water bodies and their relationship with economic development in China is critical for sustainable development. However, previous studies usually investigated the spatiotemporal changes of urban water bodies at discrete time points and ignored the relationship between urban water bodies and economic development. Here, this study first corrected freely available water body products based on spatiotemporal majority filter, thereby obtaining an improved yearly urban water body dataset. Then, the research adopted Moran’s I and Anselin Local Moran’s I to explore the spatial distribution patterns of urban water bodies and employed linear regression and segmented linear regression to investigate the temporal abrupt change and long-term trend of urban water bodies. Finally, we used geodetector to evaluate the relative contributions of GDP to the spatial heterogeneity of trends in urban water bodies. The study revealed a significant spatial autocorrelation in the distribution of urban water bodies, particularly notable in the “High-High” cluster within the Yangtze and Pearl River Deltas. It was observed that approximately 40 % and 60 % of total cities experienced an abrupt change in permanent and seasonal urban water bodies, respectively. Specifically, the majority of these abrupt changes occurred during 2010–2013. When considering both long-term trends and abrupt changes, permanent urban water bodies in Chinese cities exhibited primarily a steadily increasing trend, while seasonal water bodies in Chinese cities displayed two distinct temporal patterns: a steadily increasing trend and a decreasing trend followed by a subsequent increasing trend. Furthermore, it was noted that GDP exhibited a significantly positive correlation with the temporal changes of permanent urban water bodies from 2000 to 2020 at the national scale while it first showed a significantly negative correlation with the temporal changes of seasonal urban water bodies from 2000 to 2012 and then showed a significantly positive correlation from 2012 to 2020 on a national scale. In conclusion, we found that GDP played a more important role in driving the spatial heterogeneity of trends in urban water bodies during 2012–2020 compared to 2000–2012, with the relative contribution of ∼ 32.5 %.

Understanding of the ecosystem services (ESs) supply–demand balance, coupling, and coordination are vital for sustainable development in society. To reveal the changing pattern and underlying mechanisms of the supply–demand matching, coupling, and coordination in ESs, in this study, we used the InVEST model to quantify the supply of the following three ESs in Hunan Province in central China from 2000 to 2018: soil conservation (SC), water yield (WY), and carbon retention (CR). Using socioeconomic data, the capacity and demand for food supply (FS) and the demand for the other three ESs were quantitatively evaluated. The Z-score standardized data were used to divide the quadrants to clarify the supply–demand matching situation. Additionally, the elasticity coefficient model and coupling coordination degree (CCD) model were used to evaluate the supply–demand coupling relationship and coordination level. Our results indicate the following: (1) The supply of CR and FS in Hunan Province increased by 12.67% and 19.48%, respectively, while that of SC and WY decreased by 2.57% and 22.83%, respectively; the demand for SC, WY, CR, and FS increased by 0.329%, 9.43%, 142.05%, and 6.23%, respectively. The supply of CR is less than the demand, showing a clear supply–demand contradiction; the supply of SC, WY, and FS exceeded the demand; both had notable spatial heterogeneity. (2) The area of high supply–high demand (HS–HD) and high supply–low demand (HS–LD) matching types decreased, whereas the low supply–low demand (LS–LD) and low supply–high demand (LS–HD) matching types increased. Additionally, the Changsha–Zhuzhou–Xiangtan urban agglomeration (CZX) and selected districts in northern and central Hunan face a shortage of ESs. (3) The supply–demand coupling relationship of the SC and FS services was primarily positive while that of the WY and CR services was negative. (4) The supply–demand CCD of the four ESs was in an unbalanced state and demonstrated different trends. This study provides novel insights for decision-making regarding the optimisation of the spatial pattern of the land use in Hunan Province.

Study region: Minjiang River Basin of China. Study focus: This paper aimed to study the spatiotemporal changes in water cycle components including evapotranspiration (ET) and terrestrial water storage in a watershed. To achieve this, we proposed a method that is based on the water balance and utilizes measured annual precipitation and runoff data to correct ET products. Subsequently, we derived the annual terrestrial water storage changes and performed trend analysis on the water cycle components by the Mann-Kendall trend test. New hydrological insights for the region: (1) The Global Land Data Assimilation System (GLDAS) product overestimated ET from 2000 to 2019 in the Minjiang River Basin (MJB), which was 105.18 mm higher than ET. Through sub-basin validation, the relative error between the corrected ET and the ET is less than 5.1%. The proposed method can construct a reasonable annual dataset of water cycle components. (2) From 2000–2019, the Minjiang River Basin witnessed non-significant increasing trends in precipitation and runoff. However, significant growth was observed in ET, indicated by a Mann-Kendall trend test Z-value of 2.63. The variation in ET was primarily influenced by the normalized difference vegetation index (NDVI) (correlation coefficients of 0.37) and temperature (correlation coefficients of 0.48). The terrestrial water storage change fluctuated between − 400 and 355 mm. The relationships among the water cycle components, as represented by the runoff coefficient and evapotranspiration coefficient show non-significant changing trends. Both displayed a non-significant decreasing trend. From 2000–2019, the water cycle process remained relatively stable under changing environments in the MJB.

In order to control the desertification, large-scale afforestation programs have been attempted worldwide. Among them, China initiated the world’s largest afforestation program, Three-North Afforestation Program (TNAP, 1978–2050), in which the afforestation in sandy land has been questioned during the first 40 years. In fact, the contribution of the TNAP to vegetation establishment and its effectiveness in desertification control still remain unclear, which limited the further construction of the program. To answer the questions, we detected the dynamics of vegetation distribution (forest, shrubland, and grassland) and desertification status (slight, moderate, severe, and extremely severe) during 1978–2017 in the sandy land (45.5 million ha), by visual interpretation of 5-period remote sensing images with validation based on 3,100 sample plots from field surveys and 15,175 sample plots from the National Forest Resource Inventory. Vegetation degradation was identified by analysis combining the trends of net primary productivity and precipitation use efficiency. By Geographical Detector model, the driving forces of vegetation degradation (climate change, human activities, vegetation type, and sandy land type) were ranked and the contributions of the influential factors (climate change, human activities, and vegetation dynamics) to desertification changes were estimated. The results showed that for the 40 years, vegetation coverage increased by 0.5%, with increasing 113.8% and 338.8% of forest and shrubland, but decreasing 9.0% of grassland. Desertification area had little change while the overall intensity decreased. The TNAP contributed to desertification dynamics by 10.3%, which is lower than expected. Vegetation type was the dominant factor of vegetation degradation in general. Forest is less suitable for afforestation in sandy land than shrubland and grassland because of its lower stand establishment rate, higher degradation rate, and less contribution to desertification control. Thus, adjusting vegetation type to match local conditions (e.g., use shrub-land, grassland, and native species) and improving the vegetation resistance (e.g., transform monoculture forests into mixed forests, and make proper proportion for forest, shrubland, and grassland) was suggested. Our study provided specific and feasible strategies for further planning and implementation of TNAP, and references for vegetation restoration of sandy lands worldwide.

The rapid increase in the intensity of human activities has continuously changed the global underlying surface, resulting in ecological risks to the regional landscape. In this study, an ecological risk system was constructed for the watershedscale landscape using a variety of landscape pattern indices. The global major basins and sub-basins were taken as the research objects. The land use raster data was collected for 34 consecutive years from 1982 to 2015. The spatiotemporal ecological risk of the global landscape was analyzed at the watershed scale. The various driving factors of landscape ecological risks were then quantified using geo-detectors. At the same time, the spatiotemporal variation was determined for the global net primary productivity (NPP) of vegetation at the watershed scale, in order to reveal the impact of global landscape ecological risks. The results showed that: 1) The range of spatial variation was 0-0.29 for the multi-year average ecological risk of the global landscape at the watershed scale. Specifically, the high-value areas were distributed mainly in the temperate and cold temperate zones, arid climate zone, and polar zone near the Arctic. Meanwhile, 17.44% and 23.45% of the watershed landscape ecological risks showed a significant increase and decrease trend from 1982 to 2015, respectively (P<0.05). 2) There was a large spatial variation in the coefficient of variation of landscape ecological risk in the arid climate, subtropical, and tropical zones. Furthermore, 36.82% watershed of significant change-points were found in the landscape ecological risk from 1988 to 2006. The spatial distribution of the watersheds with the significant changes in the landscape ecological risk was basically consistent with that of watersheds with significant change-points (P<0.05). The global underlying surface changed greatly in the 1990s, indicating the great variation in the landscape ecological risk. 3) There was the greatest impact of precipitation on the landscape ecological risk of major- and sub-watersheds at the multi-year scale. The influencing factors on the landscape ecological risk of watersheds were ranked the descending order of the precipitation, temperature, NDVI, population density, altitude, slope, and gross domestic product. There were also complex interactions among the various influencing factors on the landscape ecological risk. 4) The annual NPP of 52.32% and 12.60% of the watersheds increased and decreased significantly from 1982 to 2015, respectively. The landscape ecological risk was conducive to the NPP in the 9.11% watershed with a significant positive correlation between annual landscape ecological risk and annual NPP (P<0.05). By contrast, the annual landscape ecological risk was significantly negatively correlated with the annual NPP in the 11.43% watershed (P<0.05), where the reduction of landscape ecological risk was conducive to the NPP. The finding can also provide a solid scientific basis for global carbon neutrality and carbon sinks in the terrestrial ecosystems under climate change. [ABSTRACT FROM AUTHOR]

Background: This study focuses on Dhaka City and its impact on urban surface water. Cities, ecosystems, and agriculture need surface water. It is crucial for water resource planning and environmental preservation. The primary aim is to study how urbanization has affected surface water in Dhaka City over 30 years using satellite imagery. Methods: The study analyzed three decades of urban surface water shifts using Landsat 5 TM and Landsat 8 OLI/TIRS satellite imagery and Google Earth Engine (GEE) with JavaScript code for water ratio index detection. To investigate water level changes, field observation surveys and secondary data analysis were conducted. This integrated methodology simplified surface water data extraction and analysis, making remote sensing easier and allowing cloud-based satellite data processing. Results: The study demonstrates that the amount of surface water in cities is going down, from 36.23 km2 in 1990 to 5.83 km2 in 2021, which is an enormous decrease. This means that about 20 square kilometers, or 45 percent of the water's surface, have been lost in the last 30 years. The main reasons for the drop are unplanned expansion of cities, accelerated real estate development, and more trade and economic activities in the study area. Conclusions: The GEE algorithms provide useful insights into surface water's maximum and minimum extent, enabling appropriate planning and management. These findings aid Dhaka City's water resource management and environmental protection. [ABSTRACT FROM AUTHOR]

Dongting Lake Plain is a historic foundation for China's commodity grain production. We used Landsat images to interpret the rice planting pattern from 1990 to 2020 based on the vegetation index curve and crop time window differences. The research aims included the spatiotemporal change in the rice planting area and the multiple cropping index, the transformation properties between single-crop and double-crop, and influence factors of rice cultivation. The findings indicated that the rice planting area has increased by 23.64% over the past 30 years. However, the multiple cropping index decreased by 17.39%. The area of single-crop rice increased by 2.6 times, while the area of double-crop rice decreased by 23.19%, which indicated that the planting intensity of rice has decreased. The area where rice has been steadily planted for 30 years is approximately 5600 km2, accounting for 87% of all rice planting land in this study area. The transformation from double-crop rice to single-crop rice was the most obvious characteristic of internal changes. The marginal benefits of current agricultural policies have decreased. This research may provide a theoretical basis for the refined management of rice and improve agricultural policies. More clouds in the remote sensing image limited the time resolution. Future research may further explore the comprehensive influencing factors. [ABSTRACT FROM AUTHOR]