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Oasis System and Its Reasonable Development in Sangong River Watershed in North of the Tianshan Mountains,Xinjiang,china

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chinese Geographical science 2006年第3期16卷 236-242页

作者： lei jun LUO Geping {2. xiaolei LU Qi institute of Geographical sciences and {2. resources research Chinese Academy of Sciences Beijing 100101 China Xinjiang institute of ecology and {2. Chinese Academy of Sciences Urumqi 830011 China Graduate University of chinese academy of sciences Beijing 100049 China

Under the guide of system theory, taking the oasis in the Sangong River watershed as a case study, this paper analyzes the oasis structure and function from 4 aspects including oasis spatial structure, water resources structure, vegetation structure, economic structure and their corresponding functions. The results indicate that as a typical small-scale watershed, Sangong River watershed has the relatively complete mountain-basin structure, and ecological and productive function. Because of human drastic activity the utilization rate of water resources was as high as 98.7%, and the utilization of groundwater was not reasonable, which resulted in an average annual decline of 0.353m in the water table of alluvial-diluvial-fan oasis, and an average annual increase of 0.047m in the alluvial-plain. The layout of crop and shelter forest benefits to the utilization of water and land resources. The development of oasis economy is at low level, and its eco-economic function is weak.

关键词： oasis structure oasis function oasis economy Sangong River watershed

Decomposition of energy-related carbon emissions in Xinjiang and relative mitigation policy recommendations

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Frontiers of Earth science 2015年第1期9卷 65-76页

作者： Changjian WANG xiaolei zhang Fei WANG {2. lei Li zhang State Key Laboratory of Desert and Oasis ecology Xinjiang Institute of Ecology and Geography Chinese Academy of Sciences Urumqi 830011 China University of chinese academy of sciences Beijing 100049 China Fujian Urban & Rural Planning Design institute Fuzhou 350003 China

Regional carbon emissions research is necessary and helpful for china in realizing reduction targets. The LMDI I （Logarithmic Mean Divisia Index I） technique based on an extended Kaya identity was conducted to uncover the main five driving forces for energy-related carbon emissions in Xinjiang, an important energy base in china. Decomposition results show that the affluence effect and the population effect are the two most important contributors to increased carbon emissions. The energy intensity effect had a positive influence on carbon emissions during the pre-reform period, and then became the dominant factor in curbing carbon emissions after 1978. The renewable energy penetration effect and the emission coefficient effect showed important negative but relatively minor effects on carbon emissions. Based on the local realities, a comprehensive suite of mitigation policies are raised by considering all of these influencing factors. Mitigation policies will need to significantly reduce energy intensity and pay more attention to the regional economic development path. Fossil fuel substitution should be considered seriously. Renewable energy should be increased in the energy mix. All of these policy recommendations, if implemented by the central and local government, should make great contributions to energy saving and emission reduction in Xinjiang.

关键词： carbon emissions Xinjiang index decomposition analysis mitigation policy recommendations

Spatio-temporal Pattern Characteristics of Relationship Between Urbanization and Economic Development at County Level in china

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chinese Geographical science 2019年第4期29卷 553-567页

作者： YANG Zhen zhang xiaolei {2. jun DUAN Zuliang LI Jiangang Xinjiang institute of ecology and {2. Chinese Academy of Sciences Urumqi 830011 China University of chinese academy of sciences Beijing 100049 China

The relationship between china’s urbanization and economic development(RCUED) is an important concern nationwide. As important actors in regional strategy and policy, county-level regions have played an increasingly significant role in the development of china’s social economy. However, the existing {2. on the RCUED lacks the fine depiction of the county-level administrative *** 2.00 and 2.10 census data and the statistical analysis method, we uncovered the evolution characteristics of china’s urbanization and economic development and conducted a quantitative identification for the RCUED with improved methods using the quadrant map approach. In addition, we investigated the spatial correlation effect of the RCUED using the spatial autocorrelation analysis method. The results were as follows: 1) In general, a high degree of matching exists between china’s urbanization and economic development at the county level at the significance level of 0.01. The correlation coefficients between china’s urbanization and economic development in2.00 and 2.10 were 0.608 and 0.603, respectively. 2. A significant regional difference exists in the RCUED at the county level. Based on a comparative analysis of 2.76 county units in china in the two years, we found that county units can be categorized as under-urbanized, basic coordination and over-urbanized in various areas. No situation was observed where urbanization seriously lagged behind the economic development level, so the levels of urbanization and economic development appear to be basically coordinated,and the coordination state may be gradually optimized over time. 3) Over time, the spatial dependency of the RCUED has weakened and the spatial heterogeneity has increased. Northeast china has always been an area characterized by over-urbanization. The number of county units classified as under-urbanized has begun to decline in eastern coastal urban agglomeration areas, while counties rich in resources have transforme

关键词： urbanization economic development relationship spatial-temporal pattern county china

Changes in carbon dioxide emissions and LMDI-based impact factor decomposition: the Xinjiang Uygur autonomous region as a case

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Journal of Arid Land 2014年第2期6卷 145-155页

作者： Li zhang jun {2. Xuan ZHOU xiaolei zhang Wen DONG Yu YANG Xinjiang institute of ecology and {2. Chinese Academy of Sciences University of chinese academy of sciences Department of Mathematics Jinan University institute of Geographic sciences and {2. resources research Chinese Academy of Sciences

Studies on carbon dioxide(CO2.emissions at provincial level can provide a scientific basis for the optimal use of energy and the formulation of CO2.eduction *** studied the variation of CO2.missions of primary energy consumption and its influencing factors based on data in Xinjiang Uygur autonomous region from1952.to 2.08,which were calculated according to the 2.06 IPCC Guidelines for National Greenhouse Gas ***’s CO2.mission process from 1952.to 2.08 could be divided into five stages according to the growth rates of total amount of CO2.missions and CO2.mission *** impact factors were quantitatively analyzed using Logarithmic Mean Divisia Index(LMDI)method in each *** factors,including government policies and technological progress related to the role of CO2.missions,were comprehensively analyzed,and the internal relationships among various factors were *** results show that the contribution rates of various impact factors are different in each ***,economic growth and energy consumption intensity were the main driving factors for *** the implementation of the birth control policy,the driving force of population growth on the increase in CO2.missions has slowly *** energy consumption intensity was further affected by the industrial structure and energy consumption intensity of primary,secondary and tertiary industries,with the energy consumption intensity of the secondary industries and the proportion of secondary industries being the most important factors affecting the energy consumption *** policies and technological progress were also important factors that affected CO2.missions.

关键词： CO2.emissions Logarithmic Mean Divisia Index economic growth energy consumption intensity

Temporal and spatial responses of ecological resilience to climate change and human activities in the economic belt on the northern slope of the Tianshan Mountains, china

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干旱区科学:英文版 2023年第10期15卷 1245-1268页

作者： zhang Shubao lei {2. TONG Yan{2. zhang xiaolei LU Danni FAN Liqin DUAN Zuliang State Key Laboratory of Desert and Oasis ecology/Key Laboratory of Ecological Safety and Sustainable Development in Arid Lands Xinjiang Institute of Ecology and GeographyChinese Academy of SciencesUrumqi 830011China University of chinese academy of sciences Beijing 100049China institute of Geology and Geophysics Chinese Academy of SciencesBeijing 100029China

In the Anthropocene era,human activities have become increasingly complex and *** natural ecosystems need higher ecological resilience to ensure regional sustainable development due to rapid urbanization and industrialization as well as other intensified human activities,especially in arid and semi-arid *** the study,we chose the economic belt on the northern slope of the Tianshan Mountains(EBNSTM)in Xinjiang Uygur Autonomous Region of china as a case *** collecting geographic data and statistical data from 2.10 and 2.2.,we constructed an ecological resilience assessment model based on the ecosystem habitat quality(EHQ),ecosystem landscape stability(ELS),and ecosystem service value(ESV).Further,we analyzed the temporal and spatial variation characteristics of ecological resilience in the EBNSTM from 2.10 to 2.2. by spatial autocorrelation analysis,and explored its responses to climate change and human activities using the geographically weighted regression(GWR)*** results showed that the ecological resilience of the EBNSTM was at a low level and increased from 0.2.32.to 0.2.73 during 2.10–*** spatial autocorrelation analysis of ecological resilience exhibited a spatial heterogeneity characteristic of"high in the western region and low in the eastern region",and the spatial clustering trend was enhanced during the study ***,Gobi and rapidly urbanized areas showed low level of ecological resilience,and oasis and mountain areas exhibited high level of ecological *** factors had an important impact on ecological ***,average annual temperature and annual precipitation were the key climate factors that improved ecological resilience,while average annual evapotranspiration was the main factor that blocked ecological *** the human activity factors,the distance from the main road showed a negative correlation with ecological *** night light index and PM2.5 concentration wer

关键词： ecological resilience ecosystem habitat quality ecosystem landscape stability ecosystem service value spatial autocorrelation analysis geographically weighted regression model economic belt on the northern slope of the Tianshan Mountains

Evolution of economic linkage network of the cities and counties on the northern slope of the Tianshan Mountains,china

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Regional Sustainability 2023年第2期4卷 173-184页

作者： YANG Zeyu zhang Shubao lei {2. zhang xiaolei TONG Yan{2. DUAN Zuliang FAN Liqin State Key Laboratory of Desert and Oasis ecology Key Laboratory of Ecological Safety and Sustainable Development in Arid LandsXinjiang Institute of Ecology and GeographyChinese Academy of SciencesUrumqi830011China College of resources and Environment University of Chinese Academy of SciencesBeijing100049China institute of Geology and Geophysics Chinese Academy of SciencesBeijing100029China

The exchanges between cities and counties in the northern slope economic belt of Tianshan Mountains(NSEBTM)are increasingly frequent and the economic linkages are increasingly close,but the spatial distribution of economic development and linkages among the cities and counties within NSEBTM is ***,it is of great significance to study the evolution of spatial-temporal pattern of the economic linkage network of cities and counties on NSEBTM to promote the coordinated and integrated development of the regional economy on *** this study,we used the modified gravity model and social network analysis method to analyze the spatio-temporal evolution characteristics of the economic linkage network structure of cities and counties on NSEBTM in 2.00,2.10,and *** results showed that the comprehensive development quality level of cities and counties on NSEBTM increased from 2.00 to 2.2.,its growth rate also increased,and its gap between cities and counties continued *** the spatial distribution patterns of the comprehensive development quality level of cities and counties on NSEBTM in 2.00 and 2.10 were presented as“high in the middle and low at both ends”,while the spatial distribution pattern of 2.2. was exhibited as“high value and low value staggered”.The total amount of external economic linkages of cities and counties on NSEBTM showed an obvious upward trend,and its gap between cities and counties continued expanding,presenting a pattern of“a strong middle section and weak ends”.The direction of economic linkages of NSEBTM existed obvious central orientation and geographical *** density of economic linkage network of NSEBTM increased from 2.00 to 2.2.,and the structure of economic linkage network changed from single-core structure centered with urumqi City to multicore structure centered with urumqi City,Karamay City,Shihezi City,and Changji City,shifting from unbalanced development to balanced *** the future,we should

关键词： Entropy method Economic linkages Gravity model Network structure Social network analysis Northern slope economic belt of Tianshan Mountains china

Spatio-temporal variations and influencing factors of energy-related carbon emissions for Xinjiang cities in china based on time-series nighttime light data

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Journal of Geographical sciences 2022年第10期32卷 1886-1910页

作者： zhang Li lei {2. WANG Changjian WANG Fei GENG Zhifei ZHOU Xiaoli Xinjiang institute of ecology and {2. CASUrumqi 830011China University of chinese academy of sciences Beijing 100049China Fujian Urban and Rural Planning&Design institute Fuzhou 350003China Guangdong Provincial Key Laboratory of Remote Sensing and Geographical Information System Guangdong Open Laboratory of Geospatial Information Technology and ApplicationGuangzhou Institute of GeographyGuangdong Academy of SciencesGuangzhou 510070China School of resources and Planning Guangzhou Xinhua UniversityGuangzhou 510520China Suzhou Honglan Data Technology Co. LtdSuzhou 215000JiangsuChina urumqi Meteorological Satellite Ground Station Urumqi 830011China

This essay combines the Defense Meteorological Satellite Program Operational Linescan System(DMSP-OLS)nighttime light data and the Visible Infrared Imaging Radiometer Suite(VIIRS)nighttime light data into a“synthetic DMSP”dataset,from 1992.to 2.2.,to retrieve the spatio-temporal variations in energy-related carbon emissions in Xinjiang,***,this paper analyzes several influencing factors for spatial differentiation of carbon emissions in Xinjiang with the application of geographical detector *** reveal that(1)total carbon emissions continued to grow,while the growth rate slowed down in the past five years.(2.Large regional differences exist in total carbon emissions across various *** carbon emissions of these regions in descending order are the northern slope of the Tianshan(Mountains)>the southern slope of the Tianshan>the three prefectures in southern Xinjiang>the northern part of Xinjiang.(3)Economic growth,population size,and energy consumption intensity are the most important factors of spatial differentiation of carbon *** interaction between economic growth and population size as well as between economic growth and energy consumption intensity also enhances the explanatory power of carbon emissions’spatial *** paper aims to help formulate differentiated carbon reduction targets and strategies for cities in different economic development stages and those with different carbon intensities so as to achieve the carbon peak goals in different steps.

关键词： carbon emissions nighttime light data spatio-temporal variations influencing factors Xinjiang

A joint call for actions to advance taxonomy in china

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Zoological Systematics 2022年第3期47卷 188-197页

作者： Chaodong Zhu Arong Luo Ming Bai Michael COrr Zhonge Hou Siqin Ge jun Chen Yibo Hu Xuming Zhou Gexia Qiao Hongzhi Kong Limin Lu Xiaohua Jin lei Cai Xinli Wei Ruilin Zhao Wei Miao Qingfeng Wang Zhongli Sha Qiang Lin Meng Qu Jianping Jiang Jiatang Li Jing Che Xuelong Jiang Xiaoyong Chen Lianming Gao Zongxin Ren Chunlei Xiang Shixiao Luo Donghui Wu Dong Liu Yanqiong Peng Tao Su Chenyang Cai Tianqi Zhu Wanzhi Cai Xingyue Liu Hu Li Huaijun Xue Zhen Ye Xuexin Chen Pu Tang Shujun Wei Hong Pang Qiang Xie Feng zhang Feng zhang Xianjin Peng Aibing zhang Taiping Gao Changfa Zhou Chen Shao Libin Ma Zhaoming Wei Yunxia Luan Ziwei Yin Wu Dai Cong Wei xiaolei Huang Jingxian Liu Xiangsheng Chen Tianci Yi Zhisheng zhang Zhulidezi Aishan Qin Li Hongying Hu CAS Key Laboratory of Zoological Systematics and Evolution Institute of ZoologyChinese Academy of SciencesBeijing 100101China CAS Key Laboratory of Animal ecology and Conservation Biology Institute of ZoologyChinese Academy of SciencesBeijing 100101China State Key Laboratory of Systematic and Evolutionary Botany Institute of BotanyChinese Academy of SciencesBeijing 100093China State Key Laboratory of Mycology(SKLM) Institute of MicrobiologyChinese Academy of SciencesBeijing 100101China CAS Key Laboratory of Aquatic Biodiversity and Conservation Institute of HydrobiologyChinese Academy of SciencesWuhan 430072China Wuhan Botanical Garden Chinese Academy of SciencesWuhan 430074China Department of Marine Organism Taxonomy&Phylogeny Institute of OceanologyChinese Academy of SciencesQingdao 266071China CAS Key Laboratory of Tropical Marine Bio-resources and ecology South China Sea Institute of OceanologyChinese Academy of SciencesGuangzhou 510301China CAS Key Laboratory of Mountain Ecological Restoration and Bioresource Utilization&Ecological Restoration and Biodiversity Conservation Key Laboratory of Sichuan Province Chengdu Institute of BiologyChinese Academy of SciencesChengdu 610041China State Key Laboratory of Genetic resources and Evolution&Yunnan Key Laboratory of Biodiversity and Ecological Security of Gaoligong Mountain Kunming Institute of ZoologyChinese Academy of SciencesKunming 650221China CAS Key Laboratory for Plant Diversity and Biogeography of East Asia Kunming Institute of BotanyChinese Academy of SciencesKunming 650201China CAS Key Laboratory of Plant Resource Conservation and Sustainable Utilization South China Botanical GardenChinese Academy of SciencesGuangzhou 510650China CAS Key Laboratory of Wetland ecology and Environment Northeast Institute of Geography and AgroecologyChinese Academy of SciencesChangchun 130102China CAS Key Laboratory of Tropical Forest ecology Xishuangbanna Tropical Botanical GardenChinese Academy of SciencesMenglunMenglaYunnan 66630

Taxonomy plays an important role in understanding the origin, evolution, and ecological functionality of biodiversity. There are large number of unknown species yet to be described by taxonomists, which together with their ecosystem services cannot be effectively protected prior to description. Despite this, taxonomy has been increasingly underrated insufficient funds and permanent positions to retain young talents. Further, the impact factordriven evaluation systems in china exacerbate this downward trend, so alternative evaluation metrics are urgently necessary. When the current generation of outstanding taxonomists retires,there will be too few remaining taxonomists left to train the next generation. In light of these challenges, all co-authors worked together on this paper to analyze the current situation of taxonomy and put out a joint call for immediate actions to advance taxonomy in china.

关键词： Endangered taxonomists morphology-based taxonomy integrative taxonomy capacity building systematics

Mapping essential urban land use categories in china(EULUC-china):preliminary results for 2.18

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science Bulletin 2020年第3期65卷 182-187页

作者： Peng Gong Bin Chen Xuecao Li Han Liu Jie Wang Yuqi Bai Jingming Chen Xi Chen lei Fang Shuailong Feng Yongjiu Feng Yali Gong Hao Gu Huabing Huang Xiaochun Huang Hongzan Jiao Yingdong Kang Guangbin lei Ainong Li Xiaoting Li Xun Li Yuechen Li Zhilin Li Zhongde Li Chong Liu Chunxia Liu Maochou Liu Shuguang Liu Wanliu Mao Changhong Miao Hao Ni Qisheng Pan Shuhua Qi Zhehao Ren Zhuoran Shan Shaoqing Shen Min{2. Shi Yimeng Song Mo Su Hoi Ping Suen Bo Sun Fangdi Sun Jian Sun Lin Sun Wenyao Sun Tian Tian Xiaohua Tong Yihsing Tseng Ying Tu Hong Wang Lan Wang Xi Wan Zongming Wang Tinghai Wu Yaowen Xie Jian Yang {2. Yang Man Yuan Wenze Yue Hongda Zeng Kuo zhang Neng zhang Tao zhang Yu zhang Feng Zhao Yichen Zheng Qiming Zhou Nicholas Clinton Zhiliang Zhu Bing Xu Ministry of Education Key Laboratory for Earth System Modeling Department of Earth System ScienceTsinghua UniversityBeijing 100084China Tsinghua Urban institute Tsinghua UniversityBeijing 100084China Center for Healthy Cities Institute for China Sustainable UrbanizationTsinghua UniversityBeijing 100084China Department of Land Air and Water ResourcesUniversity of CaliforniaDavisCA 95616-8627USA Department of Geological and Atmospheric sciences Iowa State UniversityAmesIA 50011USA State Key Laboratory of Remote Sensing science Institute of Remote Sensing and Digital EarthChinese Academy of SciencesBeijing 100101China AI for Earth Laboratory Cross-Strait InstituteTsinghua UniversityBeijing 100084China International institute for Earth System sciences Nanjing UniversityNanjing 210093China research Center for ecology and Environment of Central Asia Chinese Academy of SciencesUrumchi 830011China Key Laboratory of Forest ecology and Management Institute of Applied EcologyChinese Academy of SciencesShenyang 110016China National Engineering Laboratory for Applied Technology in Forestry&ecology in South china College of Life Science and TechnologyCentral South University of Forestry and TechnologyChangsha 410004China College of Surveying&Geo-Informatics Tongji UniversityShanghai 200092China Department of Urban Planning College of Architecture and Urban PlanningTongji UniversityShanghai 200092China beijing institute of Urban Planning Beijing 100045China Department of Urban Planning School of Urban DesignWuhan UniversityWuhan 430072China College of Earth sciences Jilin UniversityChangchun 130061China research Center for Digital Mountain and Remote Sensing Application Institute of Mountain Hazards and EnvironmentChinese Academy of SciencesChengdu 610041China institute of Remote Sensing and Geographic Information System School of Earth and Space SciencesPeking UniversityBeijing 100871China Department of Urban and Regional Planning School of Geography and PlanningSun Yat-sen Univ

Land use reflects human activities on *** land use is the highest level human alteration on Earth,and it is rapidly changing due to population increase and *** areas have widespread effects on local hydrology,climate,biodiversity,and food production[1,2..However,maps,that contain knowledge on the distribution,pattern and composition of various land use types in urban areas,are limited to city *** mapping standard on data sources,methods,land use classification schemes varies from city to city,due to differences in financial input and skills of mapping *** address various national and global environmental challenges caused by urbanization,it is important to have urban land uses at the national and global scales that are derived from the same or consistent data sources with the same or compatible classification systems and mapping *** is because,only with urban land use maps produced with similar criteria,consistent environmental policies can be made,and action efforts can be compared and assessed for large scale environmental ***,despite of the fact that a number of urban-extent maps exist at global scales[3,4],more detailed urban land use maps do not exist at the same *** at big country or regional levels such as for the United States,china and European Union,consistent land use mapping efforts are rare[5,6](e.g.,https://***/open_land_use/).

关键词： EULUC-china 土地利用类型