Accelerated Urban Expansion in Lhasa City and the Implications for Sustainable Development in a Plateau City

Molecular Identification of Babesia and Theileria Infections in Livestock in the Qinghai-Tibetan Plateau Area, China

The northwestern region of China, known as the Qinghai-Tibet Plateau Area (QTPA), is characterized by unique climate conditions that support the breeding of various highly-adapted livestock species. Tick vectors play a significant role in transmitting Babesia and Theileria species, posing serious risks to animal health as well as the economy of animal husbandry in QTPA. A total of 366 blood samples were collected from Tibetan sheep (n = 51), goats (n = 67), yaks (n = 43), cattle (n = 49), Bactrian camels (n = 50), horses (n = 65), and donkeys (n = 40). These samples were examined using conventional and nested PCR techniques to detect Theileria and Babesia species. The overall infection rates were 0.3% (1/366) for Babesia spp. and 38.2% (140/366) for Theileria spp. Notably, neither Babesia nor Theileria species were detected in donkeys and yaks. The infection rates of Babesia and Theileria species among animals in different prefectures were significantly different (p < 0.05). Furthermore, Babesia bovis, B. bigemina, B. caballi, and B. ovis were not detected in the current study. To our knowledge, this is the first documented detection of Theileria luwenshuni infection in Bactrian camels and goats, as well as T. sinesis in cattle and T. equi in horses on the Qinghai plateau. These novel findings shed light on the distribution of Babesia and Theileria species among livestock species in QTPA.

Analysis of Landscape Characteristics and Influencing Factors of Residential Areas on the Qinghai-Tibet Plateau: A Case Study of Tibet, China

The Qinghai-Tibet Plateau is the largest ecological barrier and one of the most vulnerable areas of the ecological environmental system. However, the increasing frequency of human activities in the Qinghai-Tibet Plateau has led to strong interference. Residential areas are the main places in which human activities are carried out and, as such, can effectively reflect the intensity of activities. Based on this, this research takes the Tibet Autonomous Region as the study area and analyzes the distribution characteristics of Tibetan residential areas using Zipf's law and various landscape indices, as well as discussing the influences of altitude, hydrology, ecological environment, and location on residential area distribution. The obtained results indicate the following: (1) The residential areas in Tibet basically conform to the rank-size principle. The residential areas in central and northwest Tibet are concentrated in size distribution, and the relatively large residential areas are prominent, while the residential areas in the eastern Hengduan mountain region are relatively balanced in size distribution. (2) The landscape index results demonstrate that the counties with an unbalanced distribution of residential areas are mainly concentrated in the northwest of Tibet, while the residential areas in the counties and regions where the administrative stations of each prefecture-level city (or region) are located tend to present a polarization phenomenon, with large patches. The area distribution of residential areas showed a "medium-high-low" pattern from southeast to northwest. The residential areas in eastern Tibet have a high degree of fragmentation and a low degree of aggregation, while the residential areas in northwest Tibet have a low degree of fragmentation and a relatively high degree of aggregation. (3) The residential areas in Tibet are most concentrated in the altitude range of 3000-5000 m above sea level and their water affinity and road-affinity are strong, with the distribution of residential areas within 500 m of roads and water networks accounting for more than one-quarter. The vegetation coverage in the residential areas is low, inconsistent with the surface vegetation coverage rate over the whole of Tibet.

Spatial Distribution Characteristics of the Rural Tourism Villages in the Qinghai-Tibetan Plateau and Its Influencing Factors

The development of rural tourism (RT) has great significance in reducing poverty and achieving rural vitalization. Qinghai-Tibetan Plateau (QTP) is a depressed area with rich RT resources due to its unspoiled nature and diverse culture. For future sustainable development of RT in QTP, this paper analyzes the spatial distribution characteristics and its influencing factors of RT villages using various spatial analysis methods, such as nearest neighbor index, kernel density estimation, vector buffer analysis, and geographic detectors. The results show the following. First, the RT villages present an agglomeration distribution tendency dense in the southeast and spare in the northwest. The inter-county imbalance distribution feature is obvious and four relatively high-density zones have been formed. Second, the RT villages have significant positive spatial autocorrelation, and the area of cold spots is larger and of hot spots is smaller. Third, the RT villages are mainly distributed with favorable topographic and climate conditions, near the road and water, around the city, and close to tourism resources. Fourth, the spatial distribution is the result of multifactor interactions. Socio-economic and tourism resource are the dominant factor in the mechanism network. Fifth, based on the above conclusions this study provides scientific suggestions for the sustainable development of the RT industry.

Climate suitability assessment on the Qinghai-Tibet Plateau

Climate is an important factor that affects livability, but the climate comfort model used for low altitudes is not applicable to high altitudes, and further study on climate suitability in high-altitude areas is needed. In response to the absence of high-altitude characteristics in the current climate comfort assessment methods, this study adds oxygen content and solar radiation as plateau characteristic indicators. We use the consulting graded method (CGM), least squares method (LSM) and questionnaire survey method (QSM) to obtain comprehensive weights for oxygen content, solar radiation and comfort index to build the Climate Suitability Index of Plateau (CSIP) and assess climate suitability on the Qinghai-Tibet Plateau. The CSIP decreases obviously as elevation increases from southeast to northwest on the Qinghai-Tibet Plateau, which means that the climate becomes increasingly unsuitable from southeast to northwest. The Qinghai-Tibet Plateau is divided into four regions-"very unsuitable" (83.8 × 10⁴ km², 32.4%), "unsuitable" (81.5 × 10⁴ km², 31.6%), "suitable" (67.9 × 10⁴ km², 26.3%), and "very suitable" (24.9 × 10⁴ km², 9.6%)-by the natural break method according to the CSIP. According to the different degrees of response of population density to CSIP, we plot the climate suitability line of the Qinghai-Tibet Plateau to provide basic theoretical support for regional planning in the Qinghai-Tibet region. The CSIP developed in this study provides a new climate suitability assessment method for high-altitude regions and a method for planning human activities on the Qinghai-Tibet Plateau from a climate-focused perspective.

Prediction Power of Logistic Regression (LR) and Multi-Layer Perceptron (MLP) Models in Exploring Driving Forces of Urban Expansion to Be Sustainable in Estonia

Estonia mainly experienced urban expansion after regaining independence in 1991. Employing the CORINE Land Cover dataset to analyze the dynamic changes in land use/land cover (LULC) in Estonia over 28 years revealed that urban land increased by 33.96% in Harju County and by 19.50% in Tartu County. Therefore, after three decades of LULC changes, the large number of shifts from agricultural and forest land to urban ones in an unplanned manner have become of great concern. To this end, understanding how LULC change contributes to urban expansion will provide helpful information for policy-making in LULC and help make better decisions for future transitions in urban expansion orientation and plan for more sustainable cities. Many different factors govern urban expansion; however, physical and proximity factors play a significant role in explaining the spatial complexity of this phenomenon in Estonia. In this research, it was claimed that urban expansion was affected by the 12 proximity driving forces. In this regard, we applied LR and MLP neural network models to investigate the prediction power of these models and find the influential factors driving urban expansion in two Estonian counties. Using LR determined that the independent variables “distance from main roads (X7)”, “distance from the core of main cities of Tallinn and Tartu land (X2)”, and “distance from water land (X11)” had a higher negative correlation with urban expansion in both counties. Indeed, this investigation requires thinking towards constructing a balance between urban expansion and its driving forces in the long term in the way of sustainability. Using the MLP model determined that the “distance from existing residential areas (X10)” in Harju County and the “distance from the core of Tartu (X2)” in Tartu County were the most influential driving forces. The LR model showed the prediction power of these variables to be 37% for Harju County and 45% for Tartu County. In comparison, the MLP model predicted nearly 80% of variability by independent variables for Harju County and approximately 50% for Tartu County, expressing the greater power of independent variables. Therefore, applying these two models helped us better understand the causative nature of urban expansion in Harju County and Tartu County in Estonia, which requires more spatial planning regulation to ensure sustainability.

Landscape pattern change simulations in Tibet based on the combination of the SSP-RCP scenarios

Monitoring landscape pattern change can provide spatial explicit basis for future landscape management. The future socioeconomic and climate change drivers should be systematically combined in landscape pattern monitoring, while they are often regarded as independent parameters in landscape monitoring models. This study sought to project the detailed landscape pattern change based on landscape composition and configuration in Tibet by 2030, and combined the shared socioeconomic pathways (SSPs) and representative concentration pathways (RCPs). The results showed area of the unused land and forest will reduce by a minimum standard of 11.42 × 10⁴ and 9.04 × 10⁴ km² from 2010 to 2030, respectively. Other land use types will increase, and the highest increase in grassland will be 9.30 × 10⁵ km². Combined SSP1 and RCP2.6 scenario show high landscape aggregation and low edge density on cultivated land, urban land and grassland in Tibet as a whole. However, in typical cultivated and urban landscape, the abovementioned rule is appeared in the combined SSP4 and RCP6.0 scenario. These findings stress the importance of systematically modeling the socioeconomic demand and climate change in landscape pattern monitoring, and using both landscape composition and configuration indexes for scenario evaluation.

Adventurous tourism: acclimatization problems and decisions in trans-boundary travels

As the twenty-first-Century Maritime Silk Road tourism program aims on development of new tourist routes with special interest on the polar regions of the Arctic and the Antarctic, as well as the Tibetan Plateau, management of climate risks in travels and their reduction is an important issue for achievement of its goals at national and local levels. Acclimatization is crucial for adventurous tourists, and especially for those traveling to extremely cold and highly elevated environments, when climate and weather in tourist destination differ significantly from those at home. The Acclimatization Thermal Strain Index for Tourism (ATSIT) is designed and used to measure numerically the physiological expenses a traveler pays during the acclimatization process. The purpose of the present study is to examine acclimatization consequences for travels from Beijing, capital of China, to destinations at the Arctic, the Antarctic, and the Tibetan Plateau, collectively referred to as the 3Polar regions, during the main seasons of winter and summer, and back. The results show that acclimatizing to cold involves greater physiological strain than adjustment to heat. Acclimatization load in winter is low for all travels from Beijing and back home. ATSIT projections detect the most harmful degree of discomfort for summer travels from Beijing. The greatest acclimatization impact comes when changing locales from hot and humid to cold and dry climatic conditions, which might cause high and very high physiological strain. Moreover, as many destinations in the 3Polar regions, mostly in the Tibetan Plateau, are located in mountains, a special acclimatization plan is required to weaken the threat of mountain sickness. The results will be helpful for warning stakeholders and the decision makers in the tourism sector of economies, and are expected to be translated into action for the development of proper intervention procedures in health control, to minimize population loss.

Assessing Suitability of Human Settlements in High-Altitude Area Using a Comprehensive Index Method: A Case Study of Tibet, China

With the steady advancement of the United Nations Sustainable Development Goals (SDGs), how to build a sustainable environment for human settlements has become a hot topic of research for scholars from various countries. Rational space utilization and resource allocation are the keys to enhancing human well-being and achieving sustainable human settlements. A comprehensive human settlement environment evaluation system, which includes 14 indicators from the natural environment, infrastructure, and public services, was established in this study. The results showed that the habitat suitability area only accounted for 1.61% (2.05% after removing the nature reserve) and all centered on cities and radiated to the surrounding areas. A belt-like suitability distribution pattern of “Yi Jiang Liang He” (i.e., Brahmaputra, Lhasa, and Nianchu Rivers) is formed, and a point-like suitability distribution pattern of the Chamdo Karub District, Nagqu Seni District, and Ngari Shiquanhe Town are formed. The results of the driving factor analysis indicate that the level of public health development in infrastructure and various indicators in public services are the main factors influencing human settlement. There is not much difference in the natural environment in the populated regions, so the suitability of the natural environment is not a significant driving factor. In addition, the reliability of the assessment results was verified by a questionnaire survey of residents in the three regions, and the subjective satisfaction of the residents agreed with the ranking results of the objective evaluation. The evaluation results of this study provide theoretical and directional guidance for the improvement of human settlements on the Qinghai–Tibet Plateau. It will be a useful tool for evaluating human settlements in the region and has a reference significance for the formulation of macro-policy in high-altitude regions.

Spatiotemporal Characteristics and Driving Force Analysis of Flash Floods in Fujian Province

Flash floods are one of the most destructive natural disasters. The comprehensive identification of the spatiotemporal characteristics and driving factors of a flash flood is the basis for the scientific understanding of the formation mechanism and the distribution characteristics of flash floods. In this study, we explored the spatiotemporal patterns of flash floods in Fujian Province from 1951 to 2015. Then, we analyzed the driving forces of flash floods in geomorphic regions with three different grades based on three methods, namely, geographical detector, principal component analysis, and multiple linear regression. Finally, the sensitivity of flash floods to the gross domestic product, village point density, annual maximum one-day precipitation (Rx1day), and annual total precipitation from days > 95th percentile (R95p) was analyzed. The analytical results indicated that (1) The counts of flash floods rose sharply from 1988, and the spatial distribution of flash floods mainly extended from the coastal low mountains, hills, and plain regions of Fujian (IIA2) to the low-middle mountains, hills, and valley regions in the Wuyi mountains (IIA4) from 1951 to 2015. (2) From IIA2 to IIA4, the impact of human activities on flash floods was gradually weakened, while the contribution of precipitation indicators gradually strengthened. (3) The sensitivity analysis results revealed that the hazard factors of flash floods in different periods and regions had significant differences in Fujian Province. Based on the above results, it is necessary to accurately forecast extreme precipitation and improve the economic development model of the IIA2 region.

Spatiotemporal Coupling Factors and Mode of Tourism Industry, Urbanization and Ecological Environment: A Case Study of Shaanxi, China

Identifying the factors and patterns of coordinated development in the tourism industry, urbanization, and the ecological environment sheds light on how to ensure the high-quality and sustainable development of the regional economy, but the research on this issue is relatively insufficient. Taking Shaanxi Province as an example, this paper analyzes the spatiotemporal coupling characteristics between the tourism industry, urbanization and ecological environment in cities of Shaanxi Province from 2000 to 2017. After identifying the leading factors of coupling of the three systems, the paper summarizes the coupling development mode in each city under the leading factors. The coupling between the tourism industry, urbanization and ecological environment in various cities has realized the fundamental transformation from incoordination to coordination and finally, formed a spatial development pattern featuring strong central regions, and weak southern and northern regions. Before 2010, ecological environment factors dominated the coupling between the tourism industry, urbanization, and ecological environment in Shaanxi’s cities, while after 2010, urbanization and tourism industry gradually became the leading factors of the coupling development of the three systems. The coupling development mode in each city has generally undergone an evolution process of “ecological environment mode--urbanization mode--tourism industry mode”. A coupling development mode dominated by urbanization has formed in cities in Northern Shaanxi, a coupling development mode dominated by mixed urbanization and the tourism industry has formed in the Guanzhong Region, and a coupling development mode dominated by the tourism industry has formed in cities in Southern Shaanxi. This paper provides theoretical and practical references for promoting the precise macro-control of cities and guaranteeing the high-quality development of the regional economy.

Selected Environmental Assessment Model and Spatial Analysis Method to Explain Correlations in Environmental and Socio-Economic Data with Possible Application for Explaining the State of the Ecosystem

Regional ecosystem health is the basis for regular regional exploration, ecological protection, and sustainable development. This study explored ecosystem health at the southern end of the Hu Line (Sichuan and Yunnan provinces) using the pressure–state–response model and examined the spatial evolution of ecosystem health. The proportion of unhealthy and morbid cities decreased from 45.9% in 2000 to 35.1% in 2016. The imbalance of ecosystem health among cities has gradually increased since 2006, but more high-quality cities have emerged (Z of Moran’s Index < 1.96, p > 0.05). Overall, the regional ecosystem on the southeast side of the Hu Line was healthier than that on the northwest side. Differences in ecosystem health on both sides of the Hu Line showed decreasing trends over time except for the pressure score. The spatial pattern of ecosystem health moved along the Hu Line because the pressure and state scores of ecosystems were mainly determined by the natural environmental conditions. Based on the county-level assessment, the grade of imbalance within cities was divided, and those that were lagging were identified. To correct regional imbalances, a comprehensive and proactive policy framework for a smart development model was put forward in Sichuan and Yunnan.

The aridity index governs the variation of vegetation characteristics in alpine grassland, Northern Tibet Plateau

The vegetation dynamic (e.g., community productivity) is an important index used to evaluate the ecosystem function of grassland ecosystem. However, the critical factors that affect vegetation biomass are disputed continuously, and most of the debates focus on mean annual precipitation (MAP) or temperature (MAT). This article integrated these two factors, used the aridity index (AI) to describe the dynamics of MAP and MAT, and tested the hypothesis that vegetation traits are influenced primarily by the AI. We sampled 275 plots at 55 sites (five plots at each site, including alpine steppe and meadow) across an alpine grassland of the northern Tibet Plateau, used correlation analysis and redundancy analysis (RDA) to explore which key factors determine the biomass dynamic, and explained the mechanism by which they affect the vegetation biomass in different vegetation types via structural equation modelling (SEM). The results supported our hypothesis, in all of the environmental factors collected, the AI made the greatest contribution to biomass variations in RDA , and the correlation between the AI and biomass was the largest (R = 0.85, p < 0.05). The final SEM also validated our hypothesis that the AI explained 79.3% and 84.4% of the biomass variations in the alpine steppe and the meadow, respectively. Furthermore, we found that the soils with higher carbon to nitrogen ratio and soil total nitrogen had larger biomass, whereas soil organic carbon had a negative effect on biomass in alpine steppe; however, opposite effects of soil factors on biomass were observed in an alpine meadow. The findings demonstrated that the AI was the most critical factor affecting biomass in the alpine grasslands, and different reaction mechanisms of biomass response to the AI existed in the alpine steppe and alpine meadow.

A GIS-Based Support Vector Machine Model for Flash Flood Vulnerability Assessment and Mapping in China

Flash floods are one of the natural disasters that threaten the lives of many people all over the world every year. Flash floods are significantly affected by the intensification of extreme climate events and interactions with exposed and vulnerable socio-economic systems impede regional development processes. Hence, it is important to estimate the loss due to flash floods before the disaster occurs. However, there are no comprehensive vulnerability assessment results for flash floods in China. Fortunately, the National Mountain Flood Disaster Investigation Project provided a foundation to develop this proposed assessment. In this study, an index system was established from the exposure and disaster reduction capability categories, and is based on analytic hierarchy process (AHP) methods. We evaluated flash flood vulnerability by adopting the support vector machine (SVM) model. Our results showed 439 counties with high and extremely high vulnerability (accounting for 10.5% of the land area and corresponding to approximately 100 million hectares (ha)), 571 counties with moderate vulnerability (accounting for 19.18% of the land area and corresponding to approximately 180 million ha), and 1128 counties with low and extremely low vulnerability (accounting for 39.43% of the land area and corresponding to approximately 370 million ha). The highly-vulnerable counties were mainly concentrated in the south and southeast regions of China, moderately-vulnerable counties were primarily concentrated in the central, northern, and southwestern regions of China, and low-vulnerability counties chiefly occurred in the northwest regions of China. Additionally, the results of the spatial autocorrelation suggested that the “High-High” values of spatial agglomeration areas mainly occurred in the Zhejiang, Fujian, Jiangxi, Hunan, Guangxi, Chongqing, and Beijing areas. On the basis of these results, our study can be used as a proposal for population and building distribution readjustments, and the management of flash floods in China.

The Spatiotemporal Distribution of Flash Floods and Analysis of Partition Driving Forces in Yunnan Province

Flash floods are one of the most serious natural disasters, and have a significant impact on economic development. In this study, we employed the spatiotemporal analysis method to measure the spatial–temporal distribution of flash floods and examined the relationship between flash floods and driving factors in different subregions of landcover. Furthermore, we analyzed the response of flash floods on the economic development by sensitivity analysis. The results indicated that the number of flash floods occurring annually increased gradually from 1949 to 2015, and regions with a high quantity of flash floods were concentrated in Zhaotong, Qujing, Kunming, Yuxi, Chuxiong, Dali, and Baoshan. Specifically, precipitation and elevation had a more significant effect on flash floods in the settlement than in other subregions, with a high r (Pearson’s correlation coefficient) value of 0.675, 0.674, 0.593, 0.519, and 0.395 for the 10 min precipitation in 20-year return period, elevation, 60 min precipitation in 20-year return period, 24 h precipitation in 20-year return period, and 6 h precipitation in 20-year return period, respectively. The sensitivity analysis showed that the Kunming had the highest sensitivity (S = 21.86) during 2000–2005. Based on the research results, we should focus on heavy precipitation events for flash flood prevention and forecasting in the short term; but human activities and ecosystem vulnerability should be controlled over the long term.

Impacts of the Qinghai–Tibet Railway on Accessibility and Economic Linkage of the Third Pole

Constructing the Qinghai–Tibet Railway (QTR) was a landmark project and was beneficial to the sustainable development of the Third Pole. To understand the sustainable development of remote regions by the provision of railway, we studied the QTR’s impact on accessibilities and economic linkages for four cities in the Third Pole, Xining, Golmud, Nagqu, and Lhasa, and between these four cities and 29 capital cities in mid-eastern China. First, employing average shortest travel time (ASTT) and weighted average travel time (WATT) as indicators, we calculated the railway-based accessibilities for June 2006 and January 2013. Then, using a gravity model, railway-based economic linkages were determined. The results demonstrate that: (i) ASTT for Xining–Golmud decreased by 4.14 h from June 2006 to January 2013. Both ASTT and WATT indicated that the accessibilities of the four cities and between these four cities and 29 capital cities in mid-eastern China improved significantly, and the spatial disparity in accessibility for the four cities decreased, which increased the balance and sustainability of the transportation system; (ii) the average contribution rate of the QTR to improving economic linkages for six routes among the four cities was 25.29%, with the Xining–Nagqu and Nagqu–Lhasa linkages improving most significantly; (iii) the QTR strengthened economic linkages between the four cities and mid-eastern cities. Because of the QTR, the economic linkages between the four cities and 29 capital cities increased 27.58% on average. The spatial disparity in interurban economic linkages also decreased. Transporting products from Tibet should be promoted to strengthen the sustainability of economic growth.

It’s Not a Fad: Smart Cities and Smart Villages Research in European and Global Contexts

Research on smart cities matures, and new interdisciplinary approaches to the study of smart cities, is increasing. At the same time, problems pertinent to communities inhabiting rural areas are also addressed, as a part of discussions in neighboring fields of research, such as environmental studies, sociology, and agriculture. Arguably, the concept of ‘the village’ has been largely absent in the academic debate, even if rural areas and countryside communities have been a subject of concern for robust policy frameworks, such as the European Union’s Cohesion Policy and Common Agricultural Policy. As a result, when advances in sophisticated information and communication technology (ICT) led to the emergence of a rich body of research on smart cities, the application and usability of ICT in the context of a village remained underdiscussed in the literature. Through this Special Issue, and the Editors’ earlier research on this topic, the Editors hope that the idea of the ‘smart village’ will be introduced into the debate. Against this backdrop, the objective of this opening review is three-fold: (i) to outline the conceptual boundaries of the term smart village, (ii) to highlight the thrust of the challenge inherent in smart villages research, and (iii) to shed light on the smart village research agenda as it unfolds. The relevance and validity of these claims are supported by references to research submitted to the Special Issue titled “Sustainable Smart Cities and Smart Villages Research”.

Phenology Response to Climatic Dynamic across China’s Grasslands from 1985 to 2010

Because the dynamics of phenology in response to climate change may be diverse in different grasslands, quantifying how climate change influences plant growth in different grasslands across northern China should be particularly informative. In this study, we explored the spatiotemporal variation of the phenology (start of the growing season [SOS], peak of the growing season [POS], end of the growing season [EOS], and length of the growing season [LOS]) across China’s grasslands using a dataset of the GIMMS3g normalized difference vegetation index (NDVI, 1985–2010), and determined the effects of the annual mean temperature (AMT) and annual mean precipitation (AMP) on the significantly changed phenology. We found that the SOS, POS, and EOS advanced at the rates of 0.54 days/year, 0.64 days/year, and 0.65 days/year, respectively; the LOS was shortened at a rate of 0.62 days/year across China’s grasslands. Additionally, the AMT combined with the AMP explained the different rates (ER) for the significantly dynamic SOS in the meadow steppe (R2 = 0.26, p = 0.007, ER = 12.65%) and typical steppe (R2 = 0.28, p = 0.005, ER = 32.52%); the EOS in the alpine steppe (R2 = 0.16, p < 0.05, ER = 6.22%); and the LOS in the alpine (R2 = 0.20, p < 0.05, ER = 6.06%), meadow (R2 = 0.18, p < 0.05, ER = 16.69%) and typical (R2 = 0.18, p < 0.05, ER = 19.58%) steppes. Our findings demonstrated that the plant phenology in different grasslands presented discrepant dynamic patterns, highlighting the fact that climate change has played an important role in the variation of the plant phenology across China’s grasslands, and suggested that the variation and relationships between the climatic factors and phenology in different grasslands should be explored further in the future.