Gandaki River Basin (GRB) is an important part of the central Himalayan region, which provides habitat for numerous wild species. However, climatic changes are making the habitat in this basin more vulnerable. This paper aims to assess the potential impacts of climate change on the spatial distributions of habitat changes for two vulnerable species, Himalayan black bear (Ursus thibetanus laniger) and common leopard (Panthera pardus fusca), using the maximum entropy (MaxEnt) species distribution model. Species occurrence locations were used along with several bioclimatic and topographic variables (elevation, slope and aspect) to fit the model and predict the potential distributions (current and future) of the species. The results show that the highly suitable area of Himalayan black bear within the GRB currently encompasses around 1642 km² (5.01% area of the basin), which is predicted to increase by 51 km² in the future (2050). Similarly, the habitat of common leopard is estimated as 3999 km² (12.19% of the GRB area), which is likely to increase to 4806 km² in 2050. Spatially, the habitat of Himalayan black bear is predicted to increase in the eastern part (Baseri, Tatopani and north from Bhainse) and to decrease in the eastern (Somdang, Chhekampar), western (Burtibang and Bobang) and northern (Sangboche, Manang, Chhekampar) parts of the study area. Similarly, the habitat of common leopard is projected to decrease particularly in the eastern, western and southern parts of the basin, although it is estimated to be extended in the southeastern (Bhainse), western (Harichaur and northern Sandhikhark) and north-western (Sangboche) parts of the basin. To determine the habitat impact, the environmental variables such as elevation, Bio 15 (precipitation seasonality) and Bio 16 (precipitation of wettest quarter) highly contribute to habitat change of Himalayan black bear; while Bio 13 (precipitation of wettest month) and Bio 15 are the main contributors for common leopard. Overall, this study predicted that the suitable habitat areas of both species are likely to be impacted by climate change at different altitudes in the future, and these are the areas that need more attention in order to protect these species.

The response of long-term vegetation changes and climate change has been a hot topic in recent research. Previously, a Landsat-based fusion model was developed and used to produce a dataset of normalized vegetation index (NDVI) for the Three-River Headwater region on the Qinghai-Tibet Plateau with a spatial resolution of 30 m and the time spanning the nearly 30 years from 1990 to 2018. In this study, the NDVI was applied to an analysis of the spatial and temporal changes in the alpine grassland and the impacts from climate change using the Theil-Sen Median method and linear regression. The results showed that: (1) The regional mean NDVI was 0.39 and showed a spatial pattern of decreasing from the southeast to the northwest in the recent three decades. Among the three parks, the Lancang River Park had the highest NDVI (0.43), followed by the Yellow River Park (0.38) and Yangtze River Park (0.23). (2) An upward trending was found in the NDVI time series at a rate of 0.0031 yr^–1 (R² =0.62, P < 0.01) over the whole period of 1990–2018. The increasing rate (0.00649 yr^–1, R² =0.71, P < 0.01) in the latter period of 2005–2018 was nearly 2.3 times of that (0.00284 yr^–1, R² =0.31, P < 0.01) in the previous period of 1990–2005. In the latest periods, the three parks experienced rates that were 2.3 to 63 times the corresponding values in the early period. (3) The NDVI is correlated more positively with temperature than precipitation. The impacts of climate change decreased along with the coverage fraction from the higher, median and then lower levels. The climate change can explain 34% of the variability in the NDVI time series of the areas with a higher fraction of grassland coverage, while it was 31% for the median fraction and 20% for the lower fraction. This study is the first to use the 30 m NDVI dataset spanning nearly 30 years to analyze the spatial and temporal variability and climate impacts in the alpine grasslands of the Three-River Headwater region of the Qinghai-Tibet Plateau. The results provide a basis for assessments on the ecological management effects and ecological quality based on long-term baseline data with a higher spatial resolution.

The Huang-Huai-Hai Plain is one of the typical agri-ecosystems in China, which suffers from cold damage frequently resulting in substantial economic losses. In order to monitor the changes in the occurrence of cold damage in an effective and large-scale manner, and to determine their meteorological causes, this paper collected low temperature data from the agricultural meteorological stations and remote sensing data of MODIS from 2005 to 2015, and constructed a monitoring model of cold damage to winter wheat in Huang-Huai-Hai Plain based on the Logistic regression model. This model was used to analyze the spatio-temporal changes of cold damage of winter wheat in Huang-Huai-Hai Plain from 2011 to 2020, and correlation analysis was performed with the spatio-temporal changes of meteorological factors to ascertain how they affect cold damage. The results show that the harm from cold damage in winter wheat has been gradually decreasing from 2011 to 2020, and the cold damage areas with high probability and high frequency are moving from north to south. The meteorological elements with the greatest impacts on the degree of cold damage from stronger to weaker are heat, precipitation and sunshine duration, whose influence has spatial variability.

This paper aims at the spatiotemporal distribution of rainfall in Ethiopia and developing stochastic daily rainfall model. Particularly, in this study, we used a Markov Chain Analogue Year (MCAY) model that is, Markov Chain with Analogue year (AY) component is used to model the occurrence process of daily rainfall and the intensity or amount of rainfall on wet days is described using Weibull, Log normal, mixed exponential and Gamma distributions. The MCAY model best describes the occurrence process of daily rainfall, this is due to the AY component included in the MC to model the frequency of daily rainfall. Then, by combining the occurrence process model and amount process model, we developed Markov Chain Analogue Year Weibull model (MCAYWBM), Markov Chain Analogue Year Log normal model (MCAYLNM), Markov Chain Analogue Year mixed exponential model (MCAYMEM) and Markov Chain Analogue Year gamma model (MCAYGM). The performance of the models is assessed by taking daily rainfall data from 21 weather stations (ranging from 1 January 1984–31 December 2018). The data is obtained from Ethiopia National Meteorology Agency (ENMA). The result shows that MCAYWBM, MCAYMEM and MCAYGM performs very well in the simulation of daily rainfall process in Ethiopia and their performances are nearly the same with a slight difference between them compared to MCAYLNM. The mean absolute percentage error (MAPE) in the four models: MCAYGM, MCAYWBM, MAYMEM and MCAYLNM are 2.16%, 2.27%, 2.25% and 11.41% respectively. Hence, MCAYGM, MCAYWBM, MAYMEM models have shown an excellent performance compared to MCAYLNM. In general, the light tailed distributions: Weibull, gamma and mixed exponential distributions are appropriate probability distributions to model the intensity of daily rainfall in Ethiopia especially, when these distributions are combined with MCAYM.

In this paper, the quadratic polynomial and cubic polynomial functions were applied to analyze the environmental Kuznets curve (EKC) of carbon emissions in Hebei Province. The improved STIRPAT model was also applied to assess the driving factors and reduction paths for carbon emissions in Hebei Province. The results lead to three main conclusions. Firstly, carbon emissions and economic growth in Hebei Province are in a positive correlation stage which has not formed the EKC curve, and the “decoupling” stage between carbon emissions and economic growth has not arrived yet. Secondly, the industrial structure, per capita GDP, fixed assets investment, population size and urbanization rate account for the highest proportion of carbon emissions. Carbon emissions can be reduced greatly by changing the energy structure, in which the proportion of coal is decreased year by year. Environmental regulation also has an obvious effect on the reduction of carbon emissions. Thirdly, it is suggested that the reduction of carbon emissions in Hebei Province should focus on four tasks: controlling the development of heavy industry, avoiding overcapacity, optimizing the industrial structure and accelerating the development of clean energy.

Green electricity (GE) is of great importance for effectively combating climate change and global Sustainable Development Goals (SDGs). The willingness-to-pay (WTP) for GE by end users has great influence on its widespread application, especially at the household level. Researchers have analyzed the mechanisms of residents' WTP and predicted how much they could afford for GE. However, most of these studies have focused on developed (affluent) countries and regions, and residents' WTP as well as the corresponding monetary amount of their WTP were not considered together in previous studies. In this study, we try to fill the gap of the inadequate research of residents' WTP in underdeveloped areas through an analysis of the WTP of urban residents in a small Chinese city (Anyang). A total of 274 household-scale samples were collected by face-to-face interviews in December 2019. We found that approximately 60% of respondents gave a positive response to WTP, with an average value of 8.39 yuan per month. Educational attainment, per capita disposable income in the household, the length of residents' time living in urban areas and the rate of neighbors' approval of WTP are all positively correlated with the tendency of the residents' positive response toward WTP. The three factors of per capita disposable income, the rate of neighbors' approval of WTP and the degree of residents' environmental concerns are positively correlated with the amount of residents' WTP. More importantly, we demonstrated the existence of a weak “Herd Effect” in residents' views of WTP. Finally, some suggestions for policymakers are given, such as raising household income through retraining and raising residents' environmental awareness through education and community advertisements. This study also highlights that the widespread application of GE at the household level will be of great assistance to the GE industry overall. Therefore, the rising economic cost of GE should not be shared by the households in the long term.

Harmonious urban color can reduce urban light pollution, relieve the urban heat island effect, improve the living quality and form a distinctive style. However, due to the manifold architectural styles, urban color in metropolises typically becomes complicated, which may destroy the color harmony of metropolises. Up to now, there has not been enough research on the quantitative expression of the degree of color harmony, and the research on comparing the urban color characteristics of different metropolises is also relatively insufficient. This paper firstly developed a method to quantitatively measure the degrees of color harmony (DCHs) of five metropolises in 2020: London, Tokyo, Chicago, Paris, and Beijing, by writing a Python program and using the Sentinel-2A remote sensing data. GIS buffers were then used to analyze the spatial distribution of the DCHs within each metropolis. In addition, 20 typical samples were selected to analyze the differences of the DCHs between residential and industrial areas. The results showed that: (1) The values of the DCHs of London and Tokyo were the highest, followed by Chicago and Paris, while Beijing was the lowest. (2) The values of the DCHs were increasing from the inside out in Chicago, Paris, and London, while those in Beijing and Tokyo were decreasing. (3) The values of the DCHs in industrial areas were much lower than in residential areas. Based on the above results, policy implications are provided for color management of these metropolises. Lastly, this study may provide a method for the rapid analysis the DCHs for other metropolises.

With the expansion of a city, the urban green space is occupied and the urban heat island effect is serious. Greening the roof surfaces of urban buildings is an effective way to increase the area of urban green space and improve the urban ecological environment. To provide effective data support for urban green space planning, this paper used high-resolution images to (1) obtain accurate building spots on the map of the study area through deep learning assisted manual correction; and (2) establish an evaluation index system of roof greening including the characteristics of the roof itself, the natural environment and the human society environment. The weight values of attributes not related to the roof itself were calculated by Analytic Hierarchy Process (AHP). The suitable green roof locations were evaluated by spatial join, weighted superposition and other spatial analysis methods. Taking the areas within the Chengdu city's third ring road as the study area, the results show that an accurate building pattern obtained by deep learning greatly improves the efficiency of the experiment. The roof surfaces unsuitable for greening can be effectively classified by the method of feature extraction, with an accuracy of 86.58%. The roofs suitable for greening account for 48.08%, among which, the high-suitability roofs, medium-suitability roofs and low-suitability roofs represent 45.32%, 38.95% and 15.73%. The high-suitability green buildings are mainly distributed in the first ring district and the western area outside the first ring district in Chengdu. This paper is useful for solving the current problem of the more saturated high-density urban area and allowing the expansion of the urban ecological environment.

The Landsat images of the 2000, 2005, 2010, 2015, 2018 are selected as the data source to retrieve land cover and surface temperature data. The contribution of Sink-Source landscape pattern to the heat island and its ecological effects on urban and rural gradient were analyzed by using Heat Index (HI), Sink and Source Landscape Contribution (CI_sink, CI_source) and Landscape Effect Index (LI) in Haikou. The results show that the heat island is concentrated on the West Coast, and in the central urban and Jiangdong New Area; the HI shows a pattern of decreasing value with the following land types: “Bare land>Artificial surface>Source landscape>Shrub grassland>Farmland>Sink landscape>Woodland>Water body”. In the central city section, the CI_sink and CI_source are relatively large in these five periods. The LI decreases rapidly along the urban-rural gradient, promoting the Urban Heat Island (UHI) to a large degree. In contrast, the suburban area contributes to a lesser degree. Overall, the LI fluctuates, the proportion of mitigating UHI is large, and there is a second peak outside the city center. The existing Source-Sink Landscape contributes the most to UHI in the central urban area, and this contribution decreases along the urban-rural gradient. With the continuous expansion of city-town areas, the proportion of Sink areas has increased along the gradient, and the proportion of Source areas has subsequently declined, resulting in the spatial transfer and diffusion of UHI. Therefore, a UHI mitigation strategy based on the theory of regional landscape systems is proposed here.

Beijing Municipal Administrative Center (Beijing MC) in Tongzhou District has inherited the non-capital core functions of Beijing's central urban area, and its rapid construction and development urgently require a scientific understanding of the pattern of land use evolution in the region. This paper analyzes the pattern of land use evolution in Tongzhou District over the past 40 years, from 1980 to 2020. According to the historical evolutionary characteristics of land use and urban development planning goals, combined with the driving factors of cultural tourism development, the Future Land-use Simulation (FLUS) model is used to simulate the spatial distribution of land use in Beijing MC (Tongzhou District) in 2035 under three scenarios of urbanization acceleration, deceleration and sustainable development. The results show three major trends. (1) Beijing MC (Tongzhou District) is dominated by urban development and construction. During the high-speed urbanization stage from 1980 to 2010, the urban expansion pattern of “along the Sixth Ring Road and along the Grand Canal” was formed. During the low-speed urbanization stage from 2010 to 2020, the land distribution was stable, and Tongzhou District formed a pattern of urban-rural differentiation and land intensification from northwest to southeast. As a typical area of Tongzhou District's urbanization, Beijing MC has the same characteristics of the temporal and spatial evolution as Tongzhou as a whole. (2) By 2035, there are significant differences in land use among the three scenarios with respect to the magnitude of change and spatial distribution. The area and distribution of ecological land under the urban sustainable development scenario are optimal, which is conducive to the realization of sustainable urban development. In analyzing the degree of conformity with the three Beijing MC zoning plans, the prediction simulation under the sustainable development scenario is highly consistent with the land use of the “Beijing Municipal Administrative Center Regulatory Detailed Planning (Block Level) (2016–2035)” (hereinafter referred to as “Planning”) issued by the municipal government. However, there are certain deviations between the simulation predictions in the cultural tourism function area and the livable living scenery area and the corresponding “Planning” expectations. During the urban construction process, the internal ecological land area still needs to be increased. (3) Tongzhou District may lack a close connection between the urban and rural areas in the southeast. Potential risks such as the imbalance in the development of northern and southern townships require further attention in the development process. The prediction and simulation results of the model can provide certain data and methodological support for the construction of a harmonious and livable city in Beijing MC (Tongzhou District).

To cope with the difficulties of integrating migrant workers into urban life and inefficient land use caused by conventional urbanization, China has proposed a new type of urbanization policy. This policy may have a significant impact on the spatial patterns of rural settlements in China. Exploring this potential impact is conducive to the proposal of scientific plans for the spatial patterns of rural settlements. Therefore, this paper chooses Dingzhou, one of the pilot cities of this new-type urbanization, as the research area to carry out a simulation study on the impact of the new-type urbanization policy. Dingzhou has invested heavily in the new-type urbanization construction in recent years, but the influence of the policy on rural settlements remains unclear. Based on the theoretical framework of previous studies, this paper set up three scenarios, namely “conventional urbanization”, “new-type urbanization”, and “counter-urbanization”. This paper used FLUS (Future Land Use Simulation) Model and various spatial data to simulate the spatial patterns of rural settlements in Dingzhou in 2030 under the different scenarios. By comparing the different scenarios, the impacts of the new-type urbanization policy on the spatial patterns of rural settlements in Dingzhou were evaluated. The results indicated that: (1) From 2000 to 2015, the area of rural settlements in Dingzhou increased by 11.12%. Spatially, the density of rural settlements around the cities and towns increased, and rural settlement areas were mainly converted from cultivated land. Rural settlements were mainly transformed into urban land and cultivated land. (2) The overall simulation accuracy of FLUS was 0.89, so it can be well applied to the simulation of rural settlements. (3) In all three scenarios, rural settlements expanded along their edges, and the closer they were to towns, the more obvious the expansion was. In the counter-urbanization scenario, the change of rural settlements was most dramatic. (4) The new-type urbanization policy makes the spatial patterns of rural settlements in Dingzhou more stable and more intensive.

In many highly dense urban environments, the urgent needs of residents for increasing green space, improving the quality of the community environment and reconstructing the relationships among residents have given birth to the new space type of community gardens. However, China still lacks this relevant experience. In contrast, New York City's community gardens had a relatively early start, and they now have rich experience in space construction, operation and maintenance. Given their level of experience, they can be used as references for the development of community gardens in China. This paper adopts a bibliometric research method, identifies 201 periodical literature sources published between 2000 and 2020 from the core library of the Web of Science as the object of study, and finally assesses the research hotspot for transferring from macro-research to space-type construction method, social impact, and so on, through CiteSpace software analysis. By virtue of the research process analysis and the results of field surveys and interviews, this paper probes the development status of space construction and social organization construction of the community gardens in New York City, and summarizes that area's effective experience of development. Based on the current development situation of China's community gardens, it is proposed that the development of community gardens should be directed by ensuring the land for development, giving full play to social benefits, and mobilizing social organizations, so as to effectively realize urban space construction and social governance.

The mining of placer iron ore greatly influences the surrounding desert grassland. In Agdala Town, Qinghe County, Xinjiang, the soil seed bank is severely damaged, and the utilization and productivity of desert grasslands are almost zero, which seriously affects the safety of the ecological environment and the development of local animal husbandry. It is very important to supplement soil seed banks to enhance the species composition of desert grasslands after ecological restoration. In this study, the effects of the seed bank, species composition, and seed burial depth on the seedling emergence rate at placer iron ore site before and after artificial seed bank replenishment were compared using the germination tray method. The original soil seed bank in the study area contained only four species, which were all annual plants. The dominant species were Salsola ruthenica and Corispermum orientale, and the soil seed bank density was very small. The emergence regularity of the soil seed bank was closely related to water content, and the emergence of annual vegetation was explosive. Seed burial depth affected the emergence rate of perennial grass, and we determined that a burial depth of 0–5 cm was the most effective for emergence. This indicates that seedling emergence of artificially supplemented soil seed bank can be completed within 7 days if the sowing depth is appropriate; sowing depths greater than 5 cm affect seed germination. These findings provide a basis for selecting species to populate large areas.

Shallow soil with low water availability is the key limiting factor for plant growth and reproduction in vulnerable karst regions. Annual herbs are pioneers adapted to these areas; however, little is known about the responses of their seeds and infructescence, and the germination of their offspring to these limited water and soil resources. In this study, we investigated how the seed and fruiting phenology plasticity and offspring seed germination rates of two annual Asteraceae herbs (Xanthium sibiricum and Bidens pilosa) respond to the harsh karst soil environment, by assessing the seed number, seed biomass and offspring seed germination rate. X. sibiricum and B. pilosa were grown under three soil thicknesses and three water availability levels in a full two-way randomized block design. The key results were as follows: (1) The number and biomass of progenies (infructescence and seeds) of X. sibiricum decreased with the decline of soil thickness and/or water availability (P <0.05). The infructescence and seed biomass of B. pilosa increased with the decline of water availability. (2) Seed quantity and seed biomass of X. sibiricum showed no correlation after their parents experienced resource reductions. A significant positive relationship between seed number and seed biomass was observed in B. pilosa (P <0.05). (3) The offspring seed germination rate of X. sibiricum did not change with the decrease of soil thickness under three levels of water treatment. However, the offspring seed germination rate of B. pilosa decreased significantly with the decrease of soil thickness under the control water level (P<0.05). The results show that X. sibiricum tends to improve its competitiveness by ensuring the quantity and quality of offspring in order to adapt to the shallow karst soils and dry karst habitats. In contrast, B. pilosa adapts to the unfavorable karst habitats by a risk-sharing strategy. B. pilosa produces more and bigger seeds to in an attempt to expand its survival range and escape from the unfavorable living environment, but this results in a lower seed number and germination rate of its progeny under the karst soil resource reduction.

Key Biodiversity Areas (KBAs) are ecological conservation priorities proposed by IUCN and widely recognized by most countries. Evaluating the changes in the ecological characteristics in KBAs is important for biodiversity conservation and the construction of Protected Areas (PAs). There are various ecosystem types in the Belt and Road Initiative (BRI) region, which has an extremely high value of biodiversity conservation, and the KBAs should be the prime targets of ecological protection efforts. Using the data of land cover, NDVI and Nighttime Light (NTL), we analyzed the ecological conditions of the KBAs in the BRI region, and their temporal and spatial variations, from the perspectives of vegetation coverage and human activities. The conclusions are: (1) There is generally no significant difference in the land cover of the KBAs, among which forest, wilderness and grassland are the main types; (2) The NDVI of the KBAs showed an increase, indicating that the vegetation was gradually improving, while a few KBAs presenting vegetation degradation were mainly distributed in the Indochina Peninsula, Qinghai-Tibet Plateau and Central and Western Asia; and (3) The NTL in the KBAs was very low, indicating that the human pressure on the natural ecosystems was limited, and only a few KBAs distributed in Central and Eastern Europe, India, and the Indochina Peninsula have high human activity intensity which also showed an increase. This study emphasizes that we should make full use of the biome succession law, and limit the interference of human activities on natural ecosystems for ecological protection of the KBAs, so as to continuously make new breakthroughs in the construction of Protected Areas (PA) in the BRI region.

The Belt and Road Initiative (B&R Initiative) is a crucial strategy to promote regional sustainable development in the new era. However, the realization of the B&R Initiative faces huge challenges because of the dual characteristics of a fragile eco-environment and strong dependence on ecological resources for economic development in the Belt and Road (B&R) countries. The ecological carrying capacity (ECC) is a crucial indicator for evaluating regional sustainable development. From the perspective of the relationship between the supply and consumption of ecological resources, this study uses net primary productivity data to measure the supply capacity of ecological resources, and it uses the agricultural production and trade data provided by the United Nations Food and Agriculture Organization to measure the level of ecological resource consumption. These supply and consumption data are then used to assess the ECC and ecological carrying status (ECS) of the B&R countries in 2017. The results show that: (1) The ECC of the B&R is 11.097 billion people; the ecosystem can also support 6.433 billion people, and the ECC is in a state of rich and surplus. (2) The ECS is polarized among the regions and countries along the B&R. Of the 65 countries, the ECC of 40 countries is in a rich and surplus state, mainly in Mid-East Europe and Southeast Asia, while the ECC of 19 countries is in severe overload, mainly in West Asia/Middle East. (3) Although the ecosystems still have ample carrying space in countries along the B&R, ecological protection is still facing enormous challenges during the implementation of the B&R Initiative combined with the internationally recognized ecological protection standards as well as the forecasts of the population and economic development. As the core content of building a new international trade network, the B&R Initiative will help to solve the spatial mismatch between the supply and consumption of ecological resources, which provides a new opportunity to coordinate the contradiction between the ecological protection and social demands of the B&R countries.