The investigation of carbon storage in ecosystems and its driving factors is crucial for understanding carbon cycling and achieving the goal of carbon neutrality. The grassland in the Northern Tibetan Plateau is an important grassland ecosystem in China, although the accurate estimation of its carbon stock and our knowledge of its spatial patterns and driving factors in the Northern Tibetan Plateau remain unclear due to insufficient field investigations. In this study, a dataset of 150 measured sample points on the Northern Tibetan Plateau, kriging interpolation and statistical methods were used to estimate the densities of aboveground biomass carbon, belowground root carbon and soil organic carbon at a soil depth of 30 cm, as well as to explore the spatial distribution and the main influencing factors of each carbon pool. The average carbon densities were 0.038 kg C m^–2 in aboveground biomass, 0.284 kg C m^–2 in belowground biomass, and 7.445 kg C m^–2 in the soil. The soil organic carbon accounted for 95.85% of the grassland carbon density. The total carbon storage of the grassland ecosystem in the Northern Tibetan Plateau was about 4.08 Pg C, with a decreasing trend from southeast to northwest. Of the total, the organic carbon stocks of vegetation and soil were 0.58 Pg C (including the aboveground and belowground biomass) and 2.58 Pg C, accounting for 28.29% of the total vegetation carbon and 26.60% of the total soil carbon, respectively, on the Tibetan Plateau, with the remainder stored in the bare land. While the precipitation, temperature and soil texture all affected the ecosystem carbon storage, precipitation played the most significant role and the combination of these three factors explained up to 86.47% of the aboveground carbon density. The aboveground carbon pools in grassland ecosystems of the Northern Tibetan Plateau were most sensitive to climatic factors, while the spatial patterns of belowground and soil carbon storage were more complex. This study provides a spatially accurate assessment of the carbon storage in the grasslands on the Northern Tibetan Plateau.

The compensatory effect and deep impact of the fruit tree economic forest on water and soil conservation ecology in a semi-arid region are investigated by exploring the ecological service value and ecological functions of the fruit tree economic forest, and further by analyzing its functional effects on reducing water and soil loss, conserving water and soil, conserving the water source, improving environmental quality and maintaining biodiversity. This analysis provides a theoretical basis and support for coordinating the relationship between economic and social development, ecological protection, agriculture and forestry in the semi-arid area of the Loess Plateau; promoting the systematic management of mountain, water, forest, farmland, lake grass and sand; and promoting the ecological protection and high-quality development of the whole Hulu River Basin. According to the Standards for Evaluation of Forest Ecosystem Service Function (GB/T38582-2020), the forestry industry standard of the People's Republic of China, the current market method, shadow price method, opportunity cost method, Swedish Carbon Tax law and other methods were adopted. The main functions of the fruit-tree economic forest ecosystem and its eco-economic value in the Hulu River Basin in Pingliang City were quantitatively analyzed, and the existing measured data from domestic ecological stations were combined with quantitative analysis and qualitative evaluation. The calculations included the ecological service values of the fruit tree economic forest ecosystem in water conservation, soil conservation, carbon sequestration, oxygen production, nutrient accumulation, environment purification and biodiversity protection, and the dynamic change characteristics of the ecological function quantity corresponding to its value were systematically analyzed. (1) In the four developmental stages of the fruiting economic forest in the Hulu River Basin in Pingliang City, the ecological function service value showed an increasing trend. Among the stages, the total value contribution of the first stage (2005–2009) is 1.299×10¹⁰ yuan; the second stage (2010–2013) is 2.497×10¹⁰ yuan; the third stage (2014–2017) is 2.662×10¹⁰ yuan; and total value contribution of the fourth stage (2018–2020) is 2.774×10¹⁰ yuan. (2) In the composition of the ecological functional service value of the fruit tree economic forest, the value of water conservation is the highest, accounting for the largest proportion at 32.97% of the total value of ecosystem services. Therefore, it plays an important role in regulating the hydrological balance of the basin in the arid and semi-arid region of the Loess Plateau. The function value of the purifying environment is relatively small, accounting for only 0.19% of the total value, followed by the function value of species conservation, accounting for 5.42%. In order of service value, the ecological function values of water conservation, oxygen release, carbon sequestration, nutrient accumulation, soil conservation, fertility maintenance, species conservation and environment purification accounted for 32.97%, 25.94%, 11.63%, 11.34%, 6.37%, 6.14%, 5.42% and 0.19% of the total value, respectively. The conclusions of this study are basically consistent with other domestic studies. Compared with the annual output value of fruit trees in the same period, the total value of ecological services was 2.42 times of the annual output value of the fruit. Therefore, the fruit tree economic forest not only provides a large amount of fresh fruit products and creates tremendous economic and social benefits for the people, but it also provides a major increase in ecological service value, and the contribution of local GEP is greater than that of GDP. (3) After accounting, the water conservation amount of the fruit tree economic forest (2005–2020) in the Hulu River Basin in Pingliang City was 2.586×10⁹ m³, with 2.135×10⁹ t of soil fixation, 2.264×10⁵ t of fertilizer retention, 9.568×10⁶ t of carbon fixation, 2.562×10⁷ t of oxygen production, 9.278×10⁵ t of nutrient accumulation, and 1.137×10⁵ t of environmental purification function (and within that function, the amount of sulfur dioxide absorbed is 94656.02 t, the amount of fluoride absorbed is 1793.82 t, the amount of nitrogen oxide absorbed is 6406.50 t, and the amount of dust fall is 10794.95 t), and the amount of negative ions provided is 1.564×10²⁵, which greatly regulates and improves the ecological environmental quality of the region.

Based on the land use data of 2000, 2010, and 2018, ArcGIS, Fragstas, and GeoDa software were used to assess the spatial and temporal evolution of ecosystem service value (ESV) and landscape ecological risk (LER) in the Jinsha River Basin from 2000 to 2018. Their relationship was subsequently examined using bivariate spatial autocorrelation and spatial regression models. The results indicate three important aspects of this system. (1) Between 2000 and 2018, the woodland, grassland, water area, and construction land rose, while the cultivated land and unused land declined, among which the decrease in unused land and the increase in construction land were more prominent. (2) From 2000 to 2018, the value of ecosystem services in the study area increased by 73.09 billion yuan, from 2018.89 billion yuan to 2091.98 billion yuan, while the overall landscape ecological risk index decreased from 0.01029 to 0.01021. The areas occupied by both low-risk and high-risk areas increased, indicating that the ecological environment in the region as a whole has been improving. However, there are still localized areas with deteriorating ecological conditions. (3) There is a positive spatial correlation between landscape ecological risk and ecosystem service values in the study area, demonstrating a high-risk-high-value clustering characteristic, and the landscape ecological risk has a positive effect on the value of all ecosystem services, particularly the value of the regulation services. The findings of this study can be used as a guide for reducing regional ecological risks, enhancing ecosystem services, and enhancing the quality of the ecological environment in the basin.

Given the high degree of fragmentation and poor resistance to disturbance in karst landscapes, it is important to clarify the spatial and temporal dynamics of landscape patterns in karst areas when designing karst ecological protection strategies. Using the Li River Basin as the study area, the spatial distribution and dynamic evolution of landscape patterns in the basin were analyzed at the levels of landscape utilization, landscape type dynamics and landscape pattern indices based on the Landsat series images for 2000 to 2020 obtained from the GEE platform as the data source. The results show three important aspects of this typical karst watershed. (1) There are large differences in landscape structure and landscape type trends between the karst and non-karst areas in the Li River Basin. (2) The comprehensive landscape type dynamic attitude of the Li River Basin is 0.22%, and the composite index of landscape type use varies from 239.49 to 244.88. The degree of landscape use is higher in karst areas than in non-karst areas, and the rate of landscape change in karst areas is more intense. The integrated index of landscape use in karst areas ranges from 262.32 to 270.50, and in non-karst areas it spans 225.28 to 227.01. The integrated landscape type motility in the karst areas is 0.31%, which is about twice as high as that in non-karst areas. (3) The overall landscape evolution of the Li River Basin shows trends of increasing fragmentation, decreasing connectivity, decreasing dominance and increasing heterogeneity, and these trends are particularly prominent in the karst areas. The results of this study can provide a scientific basis for realizing the construction goals of the National Sustainable Development Innovation Demonstration Zone in Guilin, and a technical reference for the ecological environmental management of the karst watershed.

Water conservation is a crucial functional aspect of ecosystem service. Revealing the temporal and spatial changes in water conservation and exploring the factors influencing those changes are of great significance for the utilization of water resources and the construction of ecological civilization. In this study, we estimated the water conservation changes in Jiangxi over the 20 years from 2000 to 2020 by the rainfall storage method. Thereafter, the GeoDetector was applied to analyze the contributions from various factors, including climatic variations and ecosystem transformations, to the changes in the water conservation. The results showed three important trends. (1) From 2000 to 2020, farmland, grassland, water and wetland dominated the northern part of the Poyang Lake Basin except for the forests. The transformations of ecosystem types in the study area mainly occurred between forests, farmland and towns in the 20 years. During this period, the urban area showed a significant increase of 92.63%, while the other ecosystem types showed decreasing trends. (2) The province's water conservation function declined from 2000 to 2020, with a total loss of 97.11×10⁴ m³ km^–2, and in the study area it is characterized as high in the east and west and low in the middle. (3) Factorial analysis showed that the changes in the water conservation were not caused by any one factor alone. The q values of ecosystem type change interactions with the changes in annual precipitation, annual temperature and sunshine hours calculated by the GeoDetector were 0.555, 0.541 and 0.501, respectively. Therefore, the interactions between factors contributed 50% more than the single factors in affecting the changes of water conservation.

Promoting the green development effect characterized by green total factor productivity (GTFP) is the key to achieving high-quality development in the new era. Using the 2001–2021 inter-provincial panel data, the energy and environmental factors were simultaneously included in the analysis framework for assessing the green effect of environmental regulations in China. The Malmquist-Luenberger index based on the SBM directional distance function was used to measure the GTFP and its decomposition terms, the dynamic panel model was further constructed, and the GMM method was used to empirically test the direct and indirect effects of three types of environmental regulation and foreign direct investment (FDI) on GTFP. The results show that China's GTFP is growing at an average annual rate of 2.13%, green technology progress is the source of GTFP growth, and the GTFP regional gap is expanding. There is not a non-linear effect in command-controlled environmental regulation, while the economic incentive type and the voluntary agreement type of environmental regulation respectively show a “U” shaped relationship and an inverted “U” shaped relationship. The control type regulation does not have an indirect effect on GTFP through FDI, but the incentive type and protocol type regulations can drive the promotion of GTFP indirectly through FDI. The GTFP lifting effects of the different types of environmental regulation and FDI show regional heterogeneity. Exploring the green development effect and characteristics of environmental regulation has important theoretical significance and practical value for selecting rational environmental regulation types, adopting differentiated environmental regulation intensities, implementing two-wheel drive to boost GTFP growth, realizing the benign interactions between environmental regulation and FDI, and ultimately promoting high-quality economic development.

Civil nuclear technology has been widely used in agriculture, industry, public safety, public health, environmental protection and other fields. As an emerging strategic industry, it has guided the direction for promoting the transformation and upgrading of traditional industries, leading to a new pole of economic growth and promoting the green development of industries. From the point of view of the carbon footprint, this study calculated the carbon emission of the civil nuclear technology application industry according to the basic accounting content of life cycle analysis (LCA). The minima, maxima and means of the carbon emission status of China (excluding Tibet, Hong Kong, Macao, and Taiwan) from 2000 to 2019 were calculated using SPSS Software, and the carbon dioxide emissions were calculated by the Min-Max normalization method. We then compared the carbon emissions of each type of energy consumed by the civil nuclear industry with the carbon emissions of each of the carbon emission status of China. This comparison showed that the total emission of the civil nuclear technology application industry is small over its whole life cycle, but its output value is relatively large, so it is an environmentally-friendly industry which conforms to the trend of low-carbon development, clean production and green development. These features are in line with the requirements of economic development, so it is conducive to promoting the achievement of carbon peak carbon neutrality. In view of this, in order to further promote the development of the civil nuclear technology application industry, all departments should have a unified understanding, set up a special working coordination mechanism, actively seek the relevant policy support from their superiors, give full play to their own advantages and conduct regular inspections. In addition, we will put in place systems and policies to attract more and better projects, increase the number and improve the quality of projects, promote the “Inner Circle” development of the civil nuclear technology application industry, and expand overseas markets, in order to create an “Outer circulation” highland.

The China-Pakistan Economic Corridor (CPEC) plays an important role in China's ‘Belt & Road Initiative’. It is also one of the most disaster-prone regions in the world. Considering that decentralized disaster governance has been gaining much attention in the world, this paper systematically analyzes the disaster management system in the CPEC region. Specifically, it compares the national, provincial, municipal and community-level institutional mechanisms for disaster management in China and Pakistan, and then closely examines the current trends of decentralized disaster governance based on a recent round of semi-structured and open-ended interviews in Xinjiang, China and Pakistan. Issues and gaps of decentralized disaster governance were drawn out from the experiences of participation among related stakeholders. We found that although the decentralization of the disaster management system has been the main trend in both China and Pakistan, national and provincial disaster management agencies still play a key role in the disaster relief work. Therefore, the centralization and decentralization of disaster management are not contradictory, but the more disaster governance shifts towards decentralization, the more urgent the consolidation of multi-level (vertical) and broader (horizontal) collaboration becomes. Based on this analysis, we aim to provide insights, lessons and recommendations for the way forward for strengthening disaster management in CPEC. In particular, we summarize different but integrated approaches towards effective disaster risk coping strategies and regional cooperation on disaster management in CPEC.

This study performs the time series analysis of agriculture land in the Nainital District of Uttarakhand, India. The study utilizes Landsat satellite images for the classification of agriculture and non-agriculture land over a time duration of 21 years (2000–2021). Landsat 5, 7 and 8 satellites data have been used to classify the study area with Random Forest classifier. The Landsat satellite images are processed using the Google Earth Engine (GEE) platform. The selection of Random Forest classier has been based on a comparative analysis among Random Forest (RF), Support Vector Machines (SVM) and Classification and Regression Trees (CART). Overall accuracy, user accuracy and producer accuracy and Kappa coefficient has been evaluated to determine the best classifier for the study area. The overall accuracy for RF, SVM and CART for the year 2021 is 96.38%, 94.44% and 91.94% respectively. Similarly, the Kappa coefficient for RF, SVM and CART was 0.96, 0.89, 0.81 respectively. The classified images of Landsat in agriculture and non-agriculture area over a period of 21 years (2000–2021) shows a decrement of 4.71% in agriculture land which is quite significant. This study has also shown that the maximum decrease in agriculture area in last four years, i.e., from 2018 to 2021. This kind of study is very important for a developing country to access the change and take proper measure so that flora and fauna of the region can be maintained.

Ship emissions are an important factor affecting air quality in coastal areas. The adverse effects of ship emissions on coastal air pollutants are more pronounced in the presence of onshore wind. However, existing studies are based on the summer half of the year and specific stations, so the frequency of onshore winds and their effect on the transport of ship emissions are not fully understood for the whole year or for different seasons. Therefore, in this study, the Yangtze River Delta (YRD) region was selected as the target study area, and the WRF/Chem (The Weather Research and Forecast model coupled with Chemistry) model was used to investigate the impact of ship emissions on PM2.5 in coastal areas under the influence of onshore wind in 2018. There are three main findings. (1) The contribution of ship emissions to PM2.5 under the influence of onshore wind was more significant than either the annual average contribution or the contribution under the influence of non-onshore wind, especially in coastal areas. The contributions of ship emissions to PM2.5 during onshore wind hours reached 9.3 µg m^–3 and 7.4 µg m^–3 in Shanghai and Ningbo, respectively, which were 1.8 and 1.3 times the annual average, respectively. (2) During onshore wind periods, the contribution of ship emissions to PM2.5 increases significantly not only in coastal areas, but also inland. In the central region 200 km from the coast, ship emissions contributed 4.5 µg m^–3 to PM2.5 during onshore wind hours, while the annual average was only 2.5 µg m^–3. (3) Under the influence of onshore wind, the effect of ship emissions on PM2.5 showed obvious seasonal differences. Under the influence of onshore wind, the contribution of ship emissions to PM2.5 was larger in winter than in other seasons. In summer, the contribution of ship emissions to PM2.5 differed the most between onshore and non-onshore wind periods. In spring, the contribution of ship emissions to PM2.5 was greater even though the frequency of onshore wind was the lowest. The contribution of ship emissions to PM2.5 can often be underestimated when only annual or monthly averages are considered. This is detrimental to the accurate prevention and control of ship emissions by relevant authorities during periods of high pollution. The results of this study will help those authorities to understand the transport characteristics of ship emissions in the presence of onshore airflow and provide insights for coastal air pollution control and management.

With the continuous growth of China′s national economy, the people′s spiritual and cultural consumption needs are strong. Cultural and leisure venues are one of the most important spaces for meeting people's increasing needs for a better life. Taking 5625 cultural and leisure venues in Beijing as the research object, we analyzed the spatial and temporal distribution characteristics of the cultural and leisure venues in Beijing from 1994–2019, and the factors influencing them, by using the analysis methods of barycentric coordinates, standard deviation ellipse, kernel density analysis, spatial autocorrelation and Geodetector. The results show four main aspects of this system. (1) The spatial distribution of cultural and leisure venues in Beijing is uneven and shows a “core-edge” pattern. In the long run, there has been a tendency for cultural and leisure venues to spread into the northern and southern suburbs. (2) Beijing's cultural and leisure venues have evolved from a “single-core cluster” in the central city to a “dual-core coexistence” in both the central city and Tongzhou District, in addition to a spatial trend of spreading throughout the whole city. (3) Located in the central city, Xicheng, Dongcheng, Chaoyang and Fengtai form the HH agglomeration of cultural and leisure venues in Beijing, while Huairou and Miyun constitute the LL agglomeration. (4) The spatial distribution of cultural and leisure venues in Beijing is affected by many factors, such as the economy, population, transportation, education and policies, and the main driver is changing from a combination of “economy” and “demand” to the single factor of “economy”.

Integrating the landscape pattern holistically and identifying priority areas for ecological restoration scientifically are the key challenges of national land space planning and ecological protection. Taking Xiushui County, a fragile ecological region in the south, as an example, this study established an evaluation index system based on the pattern-process principle, including the importance of ecosystem services and ecosystem sensitivity, and explored regional priority areas for ecological restoration through GIS spatial analysis technology. The results show that the ecological restoration priority area in the case study area is 2880.64 km² in total, covering 63.93% of the overall area. Of that amount, 367.55 km² is the bottom-line priority areas for ecological restoration, accounting for 8.16%. Regarding land use types within the major ecological restoration priority area, the arable land and construction land areas are 210.83 km² and 122.52 km², covering 55.35% and 51.43% of the overall area, respectively. Determining the priority areas at different levels can help decision-makers to prioritize the restoration needs of degraded areas and provide a basis for adopting targeted ecological restoration measures for areas with different degrees of degradation. Identifying priority areas also provides basic information for the protection and construction of the eco-security pattern of the territorial space, which is vital for improving the regional ecological environmental safety and building a harmonious community between humans and nature.

Soil erosion monitoring in coastal mountainous areas is very important during the construction of Electric-Transmission-Line (ETL) because of the impact this disturbance has on the sensitive environment. In this study, high-resolution remote sensing data and deep learning models including Dense and Long Short-Term Memory (LSTM) were used to fit the popular soil erosion equation, which is called the Revised Universal Soil Loss Equation (RUSLE), for the Min-Yue ETL (in Fujian). The accuracy of soil erosion regression was then evaluated in the transmission line buffer area and sampling spots at two spatial scales in order to obtain the optimized parameters and a suitable model. The results show that the Dense and LSTM models can meet the accuracy requirements by using 10 characteristic values, including soil erodibility, annual rainfall, mountain vegetation index (NDMVI), DEM, slope, four bands gray values of high-spectral image, construction attributes. The optimized parameters for the priority machine-learning model LSTM are as follows: the layer depth is 3, the layer capacity is 512, the dropout ratio is 0.1, and the epoch of the LSTM model is 7060. The regression accuracy of the LSTM model decreases with an increase in soil erosion levels, and the average regression accuracy is greater than 0.98 for the slight level of soil erosion. Therefore, the machine-learning model of LSTM can be applied for quickly monitoring the soil erosion using high resolution remote sensing data.

The implementation of the rural revitalization strategy is a major deployment strategy made by the Party Central Committee on the “agriculture-rural areas-peasants” work. As a special industrial form, rural tourism fully conforms to the general standards of the rural revitalization strategy in terms of economy, society, culture, ecology, and other key aspects. Therefore, it is an important driving force and an effective way to solve the “agriculture-rural areas-peasants” problems and to realize the rural revitalization strategy. This study combines the rural revitalization of ethnic villages and rural tourism in former deep poverty areas, and explores the coupling and coordination between rural tourism and rural revitalization. On the basis of consulting the relevant literature and through qualitative and quantitative research methods, an evaluation index system for the coupling and coordination of rural tourism and rural revitalization in ethnic villages in previously deep poverty areas was constructed. Taking Didigu Village in Ebian Yi Autonomous County as a research case, this study analyzed the comprehensive development level, coupling degree and coupling coordination of its rural tourism and rural revitalization system, then selected the factors and indicators which affect the coordinated development of the coupling of rural tourism and rural revitalization in ethnic villages in order to discuss the leading factors which restrict regional development, and finally put forward targeted optimization countermeasures and suggestions. The results show that rural tourism plays a significant role in guiding rural revitalization, and the interaction between rural tourism and rural revitalization is increasingly enhanced, with large room for future growth. For the former deep poverty minority village, the government's policies, funds, talents and technologies for rural revitalization and rural tourism development play an important role in their coupled development. In order to further improve the coupling degree of rural revitalization and rural tourism, one suggestion is that the government should firmly exercise a top-level design function to improve the quality and efficiency of rural revitalization in order to accelerate the revitalization of rural culture and to drive the improvement of rural tourism quality, thus improving the quality of rural tourism and promoting the revitalization of rural areas.

The coordinated development of urban and rural areas is an important measure for releasing the potential of domestic demand and promoting industrial upgrading. The development of rural industries in metropolitan areas, especially those with rural characteristics, is an important pathway for achieving comprehensive rural revitalization and promoting urban and rural integration in the metropolitan area. Based on the development goal of promoting rural industries in metropolitan areas, this study constructed a performance evaluation index system, including industrial development, industrial integration, rural construction, and farmers' life, and applied the TOPSIS method to evaluate the development of rural characteristic industries in the metropolitan area of Xi'an. The results indicated that the overall development performance of rural characteristic industries in the metropolitan area was at a medium level. The developmental performance at the level of “primary industry-secondary industry-tertiary industry” integration was relatively good, with a certain extension of the industrial chain and expansion of industrial functions, and certain economic benefits were created in this process. However, the development of rural characteristic industries has not effectively driven the development of rural society. In terms of space, the development of rural characteristic industries in the metropolitan area presents a circular distribution feature that decreases from the core circle to the outer circle. In terms of types, there are significant differences in the development levels between the different types, and the weaknesses of different industries vary. Based on these considerations, the key pathway for the collaborative and typified development of regional characteristic industries is proposed.

Tourism can cause serious environmental pollution due to high consumption levels. With the development of tourism in Mount Wutai, the environmental pressure has been increasing. This study explored the influences of tourist arrivals in Mount Wutai, ticket revenue from domestic tourists in Mount Wutai, national passenger turnover, energy intensity, GDP per capita in Wutai County and GDP per capita in China on the tourism ecological footprint in Mount Wutai from 2005 to 2019. The extended STIRPAT (Stochastic Impacts by Regression on Population, Affluence and Technology) model was constructed by using principal component regression. The results were as follows: (1) The tourism ecological footprint in Mount Wutai increased during the study period, from 27798.07 gha in 2005 to 67467.36 gha in 2019. (2) From 2005 to 2019, tourist arrivals in Mount Wutai, ticket revenue from domestic tourists in Mount Wutai, national passenger turnover, GDP per capita in Wutai County and GDP per capita in China grew, while energy intensity declined. (3) The extended STIRPAT model showed that the elasticity coefficients of tourist arrivals in Mount Wutai, ticket revenue from domestic tourists in Mount Wutai and national passenger turnover were 0.086%, 0.075% and 0.164%, respectively, which indicated that the tourism ecological footprint in Mount Wutai would increase by 0.086%, 0.075% and 0.164%, respectively, when those parameters increased by 1%; the elasticity coefficients of GDP per capita in Wutai County and GDP per capita in China increased at an escalating pace, but the environmental Kuznets curve did not exist, indicating that economic growth did not alleviate the environmental pressure during the study period; the elasticity coefficient of energy intensity was –0.108%, which indicated that the tourism ecological footprint would decrease by 0.108% when energy intensity increased by 1%. Therefore, the implementation of effective policies and technological innovation would significantly reduce the tourism ecological footprint in Mount Wutai.

Rural governance is the basic requirement for promoting the modernization of the national governance system and governance capacity, so it is closely related to the implementation of the national rural revitalization strategy and the realization of the modernization goal of national governance. Taking 2189 rural governance demonstration villages and towns in China as the research object, the spatial distribution structure and influencing factors of rural governance demonstration villages and towns were explored in this study by using the nearest neighbor index method, the kernel density estimation method, the grid dimension analysis method and the spatial autocorrelation analysis method. The results show that the spatial distribution of rural governance demonstration villages and towns in China tends to be clustered, and the spatial differentiation is obvious. The analysis of kernel density in the rural governance demonstration villages and towns presents a number of kernel centers in space, and the distribution pattern of secondary centers is in the form of a belt distribution, which is formed by decreasing and spreading around the surrounding kernel centers. The rural governance demonstration village and town system features obvious scale-free areas and fractal characteristics. The spatial distribution of the rural governance demonstration villages and towns is mainly influenced by natural and cultural factors, among which, the topography and lake water systems are the main influencing factors. Among the humanistic factors, the social economy, transportation and national culture are the main influencing factors, while the influence of population distribution is not significant.

Studies of species habitat and distribution patterns are an important prerequisite for conservation efforts, and habitat quality and integrity play a crucial role in the population health and recovery of endangered species. This is especially applicable to the snow leopard, a top predator that is key to highland mountain ecosystems. In this study, 112 valid snow leopard distribution loci obtained by infrared camera surveys in the mid-eastern Tianshan, Xinjiang were examined. Combined with 12 characteristic environmental variables, the maximum entropy model (MaxEnt) and GIS techniques were used to analyse the potential distribution areas and suitable habitats of snow leopards in the mid-eastern Tianshan. The results showed that the total area of suitable habitat for snow leopards in the mid-eastern Tianshan was 15919 km², and the most suitable habitat was mainly concentrated in a western patch around Wusu, Hutubi, and the southern mountains of Urumqi. The results of a Jackknife analysis showed that land cover type, the daily difference in average temperature, isothermality, slope, and altitude were important factors affecting the distribution of snow leopards. Deciduous coniferous forests, grasslands, and bare rock areas with sparse vegetation at altitudes from 2500 m to 5000 m are the areas where snow leopards have a higher probability of occurrence in the mid-eastern Tianshan. This study determined the key distribution areas of snow leopards and provides a scientific basis for establishing key areas for snow leopard monitoring and protection in the mid-eastern Tianshan.

Soil health plays a vital role in sustainable agronomy development. Earthworms are visible organisms in the soil ecosystem, rendering them convenient to monitor soil health. Household detergents are widely used for daily cleaning purposes. To study their effects on two types of earthworms, Pheretima guillelmi and Eisenia andrei, dilutions of six household detergents (1‰, m/v), such as perfumed soap, washing powder, shampoo, dish washing liquid, bath lotion, and lavatory cleanser, were prepared to immerse 20 earthworms for 4 h or more, either directly or mixed with Yellow-brown soil samples from a peanut cultivation field; rain water without detergent dilutions served as the control. Surviving earthworms were counted, and the survival rate was calculated. The results showed that after 4 h of immersion in the six detergent dilutions, 100% of the E. andrei died, whereas 100% of P. guillelmi survived. When the immersion period was extended to 24 h, 100% of the P. guillelmi also died. However, after adding the six detergent dilutions to Yellow-brown soil after the earthworms had drilled into it, 100% P. guillelmi and E. andrei survived after 4 h in control solutions and two detergents dilutions, namely perfumed soap and lavatory cleanser. However, 100% of the P. guillelmi died in the other four detergent dilutions. In contrast, 30%, 24%, 19%, and 12% E. andrei survived in washing powder, shampoo, dish washing liquid, and bath lotion treatments, respectively. It can be concluded that dilutions of the six household detergents (1‰; m/v) can kill P. guillelmi and E. andrei both in soil and on direct exposure. This is the first study to report the mortality of earthworms after exposure to dilutions of household detergents.

Thaipotamon chulabhorn (Mealy Crab) is a freshwater crab, listed as ‘Least Concerned’ in the IUCN Red List of Threatened Species. Nonetheless, this crab is exclusively found in one small area of the Dun Lumpun Forest, Thailand, and currently faces high exposure to environmental changes. This study aims to investigate key dynamic factors that influence vulnerability to environmental changes of the Mealy Crab. The study was conducted between 15 March and 23 October 2016, covering the local summer until the end of the rainy season and being influenced by strong El Niño, thus suggesting drought episodes. This vulnerability assessment was carried out through crab population records from 1997 to 2016, field measurements/surveys, and interviews with experienced park rangers. The results revealed that drought is the major vulnerability factor that is threatening the population of the crabs and their livelihoods (7.96 out of 10), followed by an increased number of their natural enemies (7.41), variations in groundwater level (6.11), changes in groundwater quality (4.63), changes in forest soil (4.63) and human intervention (4.26). Since 1996, human intervention has been found to have a little direct impact on the crab population due to the restricted access to forest resources. The 2016 drought was accompanied by anomalously low rainfall and the early onset of the rainy season, contributing to an earlier and shorter mating period of the crabs. Nonetheless, a consistently increased number of the Mealy Crab population indicated that they are not significantly vulnerable to a larger number of their natural enemies, and even to the changes in groundwater and forest soil. In conclusion, the crab population was increasing along with changes in the habitat and climate and its growth cycle was unusual during the drought.

Medicinal and aromatic plants (MAPs) have been grown and used extensively for health care and healing practices since time immemorial in Nepal. They possess cultural, religious and economic values in Nepalese communities. In recent years, the MAPs sector is a growing commercial sector in Nepal that provides livelihood opportunities for low income generating people especially in the Himalayas. In this regard, this study assesses the contribution of MAPs to the gross domestic product (GDP) of Karnali Province of Nepal. A total of 58 species of MAPs were identified in Karnali Province. It was found that various parts of these annuals, biennials and perennial plants have been used as medicines, perfumes and food. MAPs in Karnali Province generated economic output equivalent to NPR 160738 million (USD 1.39 billion) or 1.03% of GDP of Karnali Province and 0.02% of the National GDP in the fiscal year 2019/2020. However, the findings revealed that the current GDP estimate undervalues the contribution of the MAPs sector to the national GDP due to the non-inclusion of ethnobotanical uses of medicinal plants. Moreover, if all cash and environmental benefits people derive from this sector could be valued and recorded in the System of National Accounts, the GDP from MAPs would be much higher than the amount estimated in this study. We conclude that MAPs have a reasonable contribution to the GDP of Karnali Province and Nepal.