Revealing ecosystem services relationships and their driving factors for five basins of Beijing

A clear understanding of the relationships among multiple ecosystem services(ESs) is the foundation for sustainable urban ecosystem management. Quantitatively identifying the factors that influence ES trade-offs and synergies can contribute to deepening ES research, from knowledge building to decision making. This study simulated soil conservation, water yield and carbon sequestration in Beijing, China, from 2015–2018. The spatial trade-offs and synergies of these three ESs within the five major river basins in Beijing were explored using geographically weighted regression. Furthermore, geographical detector was applied to quantitatively identify the driving mechanism of the environmental factors for the ES trade-offs and synergies. The results show the following:(1) the spatial relationships between soil conservation and water yield, as well as between water yield and carbon sequestration, were mainly trade-offs. There was a spatial synergy between soil conservation and carbon sequestration.(2) Regarding the spatial trade-off/synergy between soil conservation and water yield in Beijing, the dominant influencing factor was temperature/elevation, and the dominant interactions of the spatial trade-off and synergy between these two ESs in Beijing and the Chaobai River Basin are all manifested in the superposition of precipitation and potential evapotranspiration, temperature, and elevation.(3) Topographic factors were the dominant factors influencing the spatial relationship between soil conservation and carbon sequestration in Beijing and its five major river basins. As a result of the distribution of water systems and hydrological characteristics of the basins, differences were observed in the effects of different combinations of interaction factors on the spatial relationship between these two ESs in different basins.(4) Temperature had the strongest explanatory power in terms of the spatial trade-offs and synergies between water yield and carbon sequestration. The interactions between precipitation and temperature and between precipitation and elevation were the dominant interactions affecting the spatial relationship between water yield and carbon sequestration in Beijing. Overall, the explanatory power of influencing factors on the trade-offs and synergies and the degree of interaction between factors coexist in different basins with consistency and differences. Therefore, understanding the quantitative characteristics of basin-scale spatial trade-offs and synergies between ESs is important for ecosystem management and the promotion of synergy in different basins.     

黑河流域NDVI与环境因子的空间关联性（英文）

The Heihe River Basin is located in the arid and semi-arid regions of Northwest China. Here, the terrestrial ecosystem is vulnerable, making it necessary to identify the factors that could affect the ecosystem. In this study, MODIS-NDVI data with a 250-m resolution were used as a proxy for the terrestrial ecosystem. By combining these with environmental factors, we were able to explore the spatial features of NDVI and identify the factors influencing the NDVI distribution in the Heihe River Basin during the period of 2000–2016. A geographical detector(Geodetector) was employed to examine the spatial heterogeneity of the NDVI and to explore the factors that could potentially influence the NDVI distribution. The results indicate that:(1) the NDVI in the Heihe River Basin appeared high in the southeast while being low in the north, showing spatial heterogeneity with a q-statistic of 0.38. The spatial trend of the vegetation in the three sub-basins generally increased in the growing seasons from 2000 to 2016;(2) The results obtained by the Geodetector(as denoted by the q-statistic as well as the degree of spatial association between the NDVI and environmental factors) showed spatial heterogeneity in the associations between the NDVI and the environmental factors for the overall basin as well as the sub-basins. Precipitation was the dominant factor for the overall basin. In the upper basin, elevation was found to be the dominant factor. The dominant factor in the middle basin was precipitation, closely followed by the soil type. In the lower basin, the dominant factor was soil type with a lower q-statistic of 0.13, and the dominant interaction between the elevation and soil type was nonlinearly enhanced(q-statistic = 0.22).     

中国国家自然保护地的空间分布特征（英文）

This paper investigated spatial structures of 3418 national protected areas(NPAs) grouped into 13 types using GIS and quantitative analysis, including point patterns, Ripley's K function, hotspot clustering, quadrat analysis, and Gini coefficient. Spatial accessibility was calculated for all NPAs from matrix raster data using cost weighted distance on the Arc GIS platform. The results are as follows:(1) The NNI of NPAs is 0.515, Gini is 0.073, all of which indicates distribution was shown to be a spatially dependent agglomeration, and more balanced in the provinces. The national key parks and the national water conservancy scenic spots had present the strongest aggregation, with NNI of 0.563 and 0.561 respectively, and K index indicates reducing aggregation when distance exceeds 600 km.(2) The national forest parks account for the largest proportion of 22.87% of all NPAs, and the world biosphere reserves the least of 0.77%. The number of NPAs in Shandong with 240 had been the largest one in all the provinces, while Tianjin had the least number including 9 NPAs.(3) There is only one hot spot in the first-class zone, 5 in the second-class zones, and 51 in the third-class zones, which indicates NPAs are also aggregated at microscopic scales.(4) The hotspot NPA regions were mainly concentrated in the middle and lower reaches of the Yellow and Yangtze rivers, east of 100°E. High density of NPAs were generally in flat, water-rich, broad-leaved forest dominated plains and low mountain areas, with fertile soil, pleasant weather, long cultural history, and high transportation accessibility.(5) Average NPA accessible time is 60.05 min, with 70.76% regions being within 60 min, and the furthest was 777 min. The distribution of accessibility was positively related to the traffic lines. Interdepartmental protectionism has meant the various departments developed different management systems, standards, and technical specifications.     

Spatial variation and driving mechanism of soil organic carbon components in the alluvial/sedimentary zone of the Yellow River

Alluviation and sedimentation of the Yellow River are important factors influencing the surface soil structure and organic carbon content in its lower reaches. Selecting Kaifeng and Zhoukou as typical cases of the Yellow River flooding area, the field survey, soil sample collection, laboratory experiment and Geographic Information System(GIS) spatial analysis methods were applied to study the spatial distribution characteristics and change mechanism of organic carbon components at different soil depths. The results revealed that the soil total organic carbon(TOC), active organic carbon(AOC) and nonactive organic carbon(NOC) contents ranged from 0.05–30.03 g/kg, 0.01–8.86 g/kg and 0.02–23.36 g/kg, respectively. The TOC, AOC and NOC contents in the surface soil layer were obviously higher than those in the lower soil layer, and the sequence of the content and change range within a single layer was TOCNOCAOC. Geostatistical analysis indicated that the TOC, AOC and NOC contents were commonly influenced by structural and random factors, and the influence magnitudes of these two factors were similar. The overall spatial trends of TOC, AOC and NOC remained relatively consistent from the 0–20 cm layer to the 20–100 cm layer, and the transition between high-and low-value areas was obvious, while the spatial variance was high. The AOC and NOC contents and spatial distribution better reflected TOC spatial variation and carbon accumulation areas. The distribution and depth of the sediment, agricultural land-use type, cropping system, fertilization method, tillage process and cultivation history were the main factors impacting the spatial variation in the soil organic carbon(SOC) components. Therefore, increasing the organic matter content, straw return, applying organic manure, adding exogenous particulate matter and conservation tillage are effective measures to improve the soil quality and attain sustainable agricultural development in the alluvial/sedimentary zone of the Yellow River.     

1990–2015年横断山区国土空间时空变化研究（英文）

Hengduan Mountains offer land space for a variety of ecological services. However, the sustainable development and management of land space has been challenged by increased human activities in recent years. This paper performs the spatial pattern analysis of the quantitative and structural changes of various landscapes at different altitudes, and uses the land use data in 1990, 2000, 2010 and 2015 to reveal how various land patterns have changed. The results show that, within the production-living-ecological space schema, the ecological space dominates Hengduan Mountains, while the production and living space was mainly distributed in south region. During 1990–2015, the production-living-ecological spatial changes had been gradually accelerated and the regional differences had become more prominent. The agricultural production space had continuously decreased by 1132.31 km~2, and the industrial and mining production space had rapidly increased by 281.4 km~2 during 1990–2015. The living space had steadily increased, and the ecological space had increased with fluctuations. The land space pattern in Hengduan Mountains was greatly restricted by the terrain, such as altitude and slope. The implementations of China Western Development Strategy and the Returning Farmland to Forest Program had favorably promoted the changes of land spatial pattern in Hengduan Mountains.     

Integrating the ecosystem service in sustainable plateau spatial planning: A case study of the Yarlung Zangbo River Basin

The Yarlung Zangbo River Basin(YZRB) is a key ecological protection area on the Qinghai–Tibet Plateau(QTP). Determination of the ecosystem service values(ESVs) can help recognize the benefits of sustainable management. It is gradually becoming the main path that constructs plateau spatial planning of integrating ecological protection, and achieves global sustainable development goals(SDGs) in China. In this paper, the spatio-temporal dynamic evolutions of the ESVs were estimated on the multiple scales of "basin, subbasin and watershed" from 1980 to 2015. The main factors influencing ESVs were explored in terms of physical geography, human activities, and climate change. It had been proposed that sustainable spatial planning including ecological protection, basin management, and regional development was urgent to set up. Our results show that the increase in wetland and forest and results in an increase of 9.4% in the ESVs. Attention should be paid to the reduction of water and grassland. Water conservation(WC), waste treatment(WT), and soil formation and conservation(SFC) are the most important ecosystem services in the YZRB. At present, the primary problem is to solve the ESVs decreasing caused by glacier melting, grassland degradation, and desertification in the upper reaches region. The middle reaches should raise the level of supply services. Regulation services should be increased in the lower reaches region on the premise of protecting vegetation. The ESVs in adjacent watersheds are interrelated and the phenomenon of "high agglomeration and low agglomeration" is obvious, existing hot-spots and cold-spots of ESVs. Additionally, when the altitude is 4500-5500 m, the temperature is 3-8°C, and the annual precipitation is 350-650 mm, ESVs could reach its maximum. A framework of sustainable plateau spatial planning could provide references to delimit the ecological protection red line, key ecological function zone, and natural resource asset accounting on the QTP.     

Spatial distribution and the scale effect of influencing factors of specialized and sophisticated enterprises that produce new and unique products in the Yangtze River Delta region: Based on the buffer and MGWR analyses北大核心CSCD

High-quality cultivation of specialized and sophisticated enterprises that produce new and unique products is an important starting point for consolidating the security foundation of China's industrial chain and supply chain. Using buffer zone analysis and the multi-scale geographically weighted regression (MGWR) model, this study explored the spatial distribution of specialized and sophisticated enterprises that produce new and unique products in the Yangtze River Delta region and influencing factors in 2021. The study found that: 1) Spatially, Shanghai is the main area where specialized and sophisticated enterprises that produce new and unique products are concentrated, followed by provincial capitals and cities on the coast and along rivers; The overall composition of the industry is unbalanced, and the real economic industries such as machinery and equipment manufacturing and high-tech manufacturing account for a relatively high proportion, but there are differences in different regions. 2) In terms of spatial agglomeration, differences between circles and the scale effect are obvious. Within each province, the spatial distribution of specialized and sophisticated enterprises that produce new and unique products in different cities is uneven. Region-wide, the overall spatial distribution pattern of "one pole and multiple cores" is evident. Shanghai is the main agglomeration area for these enterprises, and the provincial capital cities and cities that are the regional economic centers are the secondary agglomeration areas of these enterprises. 3) The four dimensions of influencing factors—physical geography, government, market, and society—have a scale effect on the spatial distribution of specialized and sophisticated enterprises that produce new and unique products. The degree of land development acts at a small scale, which is a local variable, and shows a large difference in the impact on the spatial distribution of these enterprises across the region. Factors such as elevation, government-business relationship, degree of marketization, number and scale of enterprises, degree of openness, logistics development level, and innovation environment are global variables, and except that the degree of marketization and the number of enterprises have a significant negative impact on the spatial distribution of these enterprises, the impact of all other factors is significantly positive. The research results can provide support for the optimization of the layout of new special expertise enterprise space in the Yangtze River Delta region, in order to provide reference for the formulation of new special expertise policies and industrial planning. © 2023, Editorial office of PROGRESS IN GEOGRAPHY. All rights reserved.     

Effect of human settlements on urban thermal environment and factor analysis based on multi-source data: A case study of Changsha city

In view of the lack of comprehensive evaluation and analysis from the combination of natural and human multi-dimensional factors, the urban surface temperature patterns of Changsha in 2000, 2009 and 2016 are retrieved based on multi-source spatial data(Landsat 5 and Landsat 8 satellite image data, POI spatial big data, digital elevation model, etc.), and 12 natural and human factors closely related to urban thermal environment are quickly obtained. The standard deviation ellipse and spatial principal component analysis(PCA) methods are used to analyze the effect of urban human residential thermal environment and its influencing factors. The results showed that the heat island area increased by 547 km~2 and the maximum surface temperature difference reached 10.1℃ during the period 2000–2016. The spatial distribution of urban heat island was mainly concentrated in urban built-up areas, such as industrial and commercial agglomerations and densely populated urban centers. The spatial distribution pattern of heat island is gradually decreasing from the urban center to the suburbs. There were multiple high-temperature centers, such as Wuyi square business circle, Xingsha economic and technological development zone in Changsha County, Wangcheng industrial zone, Yuelu industrial agglomeration, and Tianxin industrial zone. From 2000 to 2016, the main axis of spatial development of heat island remained in the northeast-southwest direction. The center of gravity of heat island shifted 2.7 km to the southwest with the deflection angle of 54.9° in 2000–2009. The center of gravity of heat island shifted to the northeast by 4.8 km with the deflection angle of 60.9° in 2009–2016. On the whole, the change of spatial pattern of thermal environment in Changsha was related to the change of urban construction intensity. Through the PCA method, it was concluded that landscape pattern, urban construction intensity and topographic landforms were the main factors affecting the spatial pattern of urban thermal environment of Changsha. The promotion effect of human factors on the formation of heat island effect was obviously greater than that of natural factors.The temperature would rise by 0.293℃ under the synthetic effect of human and natural factors. Due to the complexity of factors influencing the urban thermal environment of human settlements, the utilization of multi-source data could help to reveal the spatial pattern and evolution law of urban thermal environment, deepen the understanding of the causes of urban heat island effect, and clarify the correlation between human and natural factors, so as to provide scientific supports for the improvement of the quality of urban human settlements.     

中国能源生态效率的空间格局与空间效应（英文）

Energy eco-efficiency is a concept integrating ecological and economic benefits arising from energy utilization and serves as a measure of efficiency in the energy–environment–economy system. Using the slacks-based measure(SBM) model considering undesirable output, this study first measures the energy eco-efficiency of provinces in China from 1997 to 2012. It then analyzes the spatial distribution and evolution of energy eco-efficiency from three aspects: scale, intensity, and grain of spatial patterns. Finally, it examines the spatial spillover effects and influencing factors of energy eco-efficiency in different provinces by means of a spatial econometric model. The following conclusions are drawn:(1) The overall energy eco-efficiency is relatively low in China, with energy-inefficient regions accounting for about 40%. Guangdong, Hainan and Fujian provinces enjoy the highest energy eco-efficiency, while Ningxia, Gansu, Qinghai, and Xinjiang are representative regions with low efficiency. Thus, the pattern of evolution of China's overall energy eco-efficiency is U-shaped. Among local regions, four main patterns of evolution are found: increasing, fluctuating, mutating, and leveling.(2) At the provincial level, China's energy eco-efficiency features significant spatial agglomeration both globally and locally. High–high agglomeration occurs mainly in the eastern and southern coastal regions and low–low agglomeration in the northwestern region and the middle reaches of the Yellow River. Changes in spatial patterns have occurred mainly in areas with high–low and low–high agglomeration, with the most remarkable change taking place in the Beijing–Tianjin–Hebei region.(3) There exist significant spatial effects of energy eco-efficiency among provinces in China. For the energy eco-efficiency of a given region, spatial spillovers from adjacent regions outweigh the influence of errors in adjacent regions. Industrial structure has the greatest influence on energy eco-efficiency.     

Evolution of Neolithic site distribution(9.0–4.0 ka BP) in Anhui,East China

Based on archaeological surveys of Neolithic cultural development and GIS spatial analysis,this study reproduced the main characteristics of temporal distribution and settlement selection of the sites from the Neolithic Age in Anhui and identified a relationship between environmental evolution and human activity.The results show that altitude,slope direction,and slope gradient were consistent among the settlements at different stages of the Neolithic Age in Anhui,and the sites were mostly distributed in hilly and plain areas on southeast-or south-facing slopes of low gradients close to rivers.We determined that early Neolithic Age(9.0–7.0 ka BP) sites were scattered in small numbers and likely had little cultural exchange with communities of other provinces.The environmental characteristics of various regions in Anhui indicated that the climate was warm and humid with extensive water distribution.The sites of the mid Neolithic Age(7.0–5.0 ka BP) increased rapidly with wide distribution.They were mainly distributed in the plain area north of the Huaihe River and the southwestern areas of Anhui.In the mid Neolithic Age,the warm and humid climate gradually dried,and our ancestors slowly developed cultural exchanges.The largest number of sites existed during the late Neolithic Age(5.0–4.0 ka BP),and were distributed throughout the province.During this period,the overall climate was relatively dry,but humans could still obtain water and other resources through migration.The relatively benign climate facilitated cultural interaction and exchange,which increased during this time,and the Wanjiang culture matured.We also determined that as early civilization evolved,cultures in different regions responded differently to environmental changes.In humid subtropical regions,especially in low-lying plains and areas beside lakes,rivers,and coastal areas,the relatively dry climate in the late period of the middle Holocene,prefaced by a period of high humidity,was conducive to the development of human culture.The evidence from the Neolithic settlements in Anhui therefore reflects this subtropical man-land relationship between cultural development and environmental conditions.     

中国西南地区纵向岭谷地形对区域生态地理格局的作用(英文)

China’s southwestern special terrain pattern as parallel arrangement between longitudinal towering mountains and deep valleys has significant effects on the differentiation of local natural environment and eco-geographical pattern in this region.The 1:50,000 Digital Elevation Model(DEM) data of Longitudinal Range-Gorge Region(LRGR),meteorological observation data from the station establishment to 2010,hydrological observation data,Normalized Difference Vegetation Index(NDVI) and Net Primary Productivity(NPP) products of MOD13 and MOD17 as well as 1:1,000,000 vegetation type data were used.Moisture indices including surface atmospheric vapor content,precipitation,aridity/humidity index,surface runoff,and temperature indices including average temperature,annual accumulated temperature,total solar radiation were selected.Based on ANUSPLIN spline function,GIS spatial analysis,wavelet analysis and landscape pattern analysis,regional differentiation characteristics and main-control factors of hydrothermal pattern,ecosystem structure and function in this region were analyzed to reveal the effects of terrain pattern on regional differentiation of eco-geographical elements.The results show that:influenced by terrain pattern,moisture,temperature and heat in LRGR have shown significant distribution characteristics as intermittent weft differences and continuous warp extension.Longitudinal mountains and valleys not only have a north-south corridor function and diffusion effect on the transfer of major surface materials and energy,but also have east-west barrier function and blocking effect.Special topographic pattern has important influences on vegetation landscape diversity and spatial pattern of ecosystem structure and function,which is the main-control factor on vegetation landscape diversity and spatial distribution of ecosystem.Wavelet variance analysis reflects the spatial anisotropy of environmental factors,NDVI and NPP,while wavelet consistency analysis reveals the control factors on spatial distribution of NDVI and NPP as well as the quantitative relationship with control degree.Special terrain pattern in LRGR is the major influencing factor on eco-geographical regional differentiation in this region.Under the combined effect of zonality and non-zonality laws with "corridor-barrier" function as the main characteristic,special spatial characteristics of eco-geographical regional system in LRGR is formed.     

中国科技资源配置效率测度及其时空格局演变特征(英文)

According to the connotation and structure of science and technology resources and some relevant data of more than 286 cities at prefecture level and above during 2001–2010, using modified method—Data Envelopment Analysis(DEA), science and technology(ST) resource allocation efficiency of different cities in different periods has been figured out, which, uncovers the distributional difference and change law of ST resource allocation efficiency from the time-space dimension. Based on that, this paper has analyzed and discussed the spatial distribution pattern and evolution trend of ST resource allocation efficiency in different cities by virtue of the Exploratory Spatial Data Analysis(ESDA). It turned out that:(1) the average of ST resource allocation efficiency in cities at prefecture level and above has always stayed at low levels, moreover, with repeated fluctuations between high and low, which shows a decreasing trend year by year. Besides, the gap between the East and the West is widening.(2) The asymmetrical distribution of ST resource allocation efficiency presents a spatial pattern of successively decreasing from Eastern China, Central China to Western China. The cities whose ST resource allocation efficiency are at higher level and high level take on a cluster distribution, which fits well with the 23 forming urban agglomerations in China.(3) The coupling degree between ST resource allocation efficiency and economic environment assumes a certain positive correlation, but not completely the same. The differentiation of ST resource allocation efficiency is common in regional development, whose existence and evolution are directly or indirectly influenced by and regarded as the reflection of many elements, such as geographical location, the natural endowment and environment of ST resources and so on.(4) In the perspective of the evolution of spatial structure, ST resource allocation efficiency of the cities at prefecture level and above shows a notable spatial autocorrelation, which in every period presents a positive correlation. The spatial distribution of ST resource allocation efficiency in neighboring cities seems to be similar in group, which tends to escalate stepwise. Meanwhile, the whole differentiation of geographical space has a diminishing tendency.(5) Viewed from LISA agglomeration map ofST resource allocation efficiency in different periods, four agglomeration types have changed differently in spatial location and the range of spatial agglomeration. And the continuity of ST resource allocation efficiency in geographical space is gradually increasing.     

旧石器时代至商周时期贵州遗址空间分布及其自然环境背景(英文)

This study presents an analysis of the spatial-temporal distribution of 230 archaeological sites in Guizhou Province, Southwest China for three selected time periods from the Paleolithic Age to the Shang-Zhou Dynasties. The relationship between archaeological sites distribution and environmental changes is also discussed based on paleo-environmental proxies of δ18O and δ13C recorded in stalagmites from Southwest China. The results show that: in the Paleolithic Age(260–10 ka BP), archaeological sites were concentrated in the central, northwestern and southwestern parts of Guizhou, where the high-altitudinal karst landforms with many natural caves suitable for human habitation are developed. In the Neolithic Age(10–3.6 ka BP), most of human settlements were concentrated in the central, northwestern and southwestern parts, while, a fewer sites were found on river terraces in the southern and eastern parts, and the intermontane basins in the central and western Guizhou. During the Shang-Zhou Dynasties(3.6–2.2 ka BP), the sites were mainly distributed in the intermontane basins and on river terraces, which were suitable for primitive aerial farming. The analysis of paleo-environmental proxies of δ18O and δ13C since 260 ka BP suggested that climate fluctuations had little impact on human settlements in this study area. The distinct physical environment, especially the spatial patterns of karst landforms and arable land played an important role in the archaeological sites distribution of Guizhou.     

鄱阳湖流域史前人类遗址时空分布及其环境响应（英文）

The temporal-spatial geographic distribution of archaeological sites and its feature between 10.0–2.8 ka BP(ka BP= thousands of years before 0 BP, where "0 BP" is defined as the year AD 1950) were determined, based on GIS spatial analysis in the Poyang Lake Basin. The relationship between geographic distribution of sites of different periods under subsistence existence of ancient civilizations, climate and environmental change was investigated. The results revealed numerous archaeological sites of the Neolithic Age(10.0–3.6 ka BP). The sites were mainly located in the northern part of the Poyang Lake Basin, a hilly and mountainous area with many river terraces suitable for the development of human civilization. The number of archaeological sites rapidly increased during the Shang and Zhou dynasties(3.6–2.8 ka BP) and spread widely on the floodplains of the middle and lower reaches of Ganjiang River and onto the west, south, and southeast beach areas of the Poyang Lake. Holocene records of climate change suggested that it was possible that climate fluctuations had a great impact on human evolution in the study area. Before 3.6 ka BP, westward and northward expansion of Neolithic cultures in the Poyang Lake watershed occurred under the background of climate amelioration(becoming warmer and wetter). The ancient people lived in the hilly areas with high elevation. The simple mode of a fishing and gathering economy was mostly suited to this area in the early Neolithic Age. The scope of human activities was expanded and cultural diversity developed in the late Neolithic Age. However, with population growth and increasing survival pressure in a dry-cold climatic stage after 3.6 ka BP, this simple living mode had to be abandoned, and various forms of economy, the majority being agriculture, were developed on flood plains of the lower reaches of numerous rivers around Poyang Lake. This promoted flourishing of the Bronze culture of South China.     

空间溢出视角下经济集聚对水污染物排放的影响——基于中国 339 个地级及以上城市数据的实证分析（英文）

Whether economic agglomeration can promote improvement in environmental quality is of great importance not only to China's pollution prevention and control plans but also to its future sustainable development. Based on the COD(Chemical Oxygen Demand) and NH3-N(Ammonia Nitrogen) emissions Database of 339 Cities at the city level in China, this study explores the impact of economic agglomeration on water pollutant emissions, including the differences in magnitude of the impact in relation to city size using an econometric model. The study also examines the spillover effect of economic agglomeration, by conducting univariate and bivariate spatial autocorrelation analysis. The results show that economic agglomeration can effectively reduce water pollutant emissions, and a 1% increase in economic agglomeration could lead to a decrease in COD emissions by 0.117% and NH_3-N emissions by 0.102%. Compared with large and megacities, economic agglomeration has a more prominent effect on the emission reduction of water pollution in small-and medium-sized cities. From the perspective of spatial spillover, the interaction between economic agglomeration and water pollutant emissions shows four basic patterns: high agglomeration–high emissions, high agglomeration–low emissions, low agglomeration–high emissions, and low agglomeration–low emissions. The results suggest that the high agglomeration–high emissions regions are mainly distributed in the Beijing–Tianjin–Hebei region, Shandong Peninsula, and the Harbin-Changchun urban agglomeration; thus, local governments should consider the spatial spillover effect of economic agglomeration in formulating appropriate water pollutant mitigation policies.     

京津冀干旱时空演变规律分析（英文）

Spatio-temporal patterns of drought from 1961 to 2013 over the Beijing-Tianjin-Hebei(BTH) region of China were analyzed using the Palmer Drought Severity index(PDSI) based on 21 meteorological stations. Overall, changes in the mean-state of drought detected in recent decades were due to decreases in precipitation and potential evapotranspiration. The Empirical Orthogonal Functions(EOF) method was used to decompose drought into spatio-temporal patterns, and the first two EOF modes were analyzed. According to the first leading EOF mode(48.5%), the temporal variability(Principal Components, PC1) was highly positively correlated with annual series of PDSI(r=+0.99). The variance decomposition method was further applied to explain the inter-decadal temporal and spatial variations of drought relative to the total variation. We find that 90% of total variance was explained by time variance, and both total and time variance dramatically decreased from 1982 to 2013. The total variance was consistent with extreme climate events at the inter-decadal scale(r=0.71, p0.01). Comparing the influence of climate change on the annual drought in two different long-term periods characterized by dramatic global warming(P1: 1961–1989 and P2: 1990–2013), we find that temperature sensitivity in the P2 was three times more than that in the P1.     

Inter-annual variations in vegetation and their response to climatic factors in the upper catchments of the Yellow River from 2000 to 2010

To understand the variations in vegetation and their correlation with climate factors in the upper catchments of the Yellow River, China, Normalized Difference Vegetation Index（NDVI） time series data from 2000 to 2010 were collected based on the MOD13Q1 product. The coefficient of variation, Theil–Sen median trend analysis and the Mann–Kendall test were combined to investigate the volatility characteristic and trend characteristic of the vegetation. Climate data sets were then used to analyze the correlation between variations in vegetation and climate change. In terms of the temporal variations, the vegetation in this study area improved slightly from 2000 to 2010, although the volatility characteristic was larger in 2000–2005 than in 2006–2010. In terms of the spatial variation, vegetation which is relatively stable and has a significantly increasing trend accounts for the largest part of the study area. Its spatial distribution is highly correlated with altitude, which ranges from about 2000 to 3000 m in this area. Highly fluctuating vegetation and vegetation which showed a significantly decreasing trend were mostly distributed around the reservoirs and in the reaches of the river with hydropower developments. Vegetation with a relatively stable and significantly decreasing trend and vegetation with a highly fluctuating and significantly increasing trend are widely dispersed. With respect to the response of vegetation to climate change, about 20–30% of the vegetation has a significant correlation with climatic factors and the correlations in most areas are positive： regions with precipitation as the key influencing factor account for more than 10% of the area; regions with temperature as the key influencing factor account for less than 10% of the area; and regions with precipitation and temperature as the key influencing factors together account for about 5% of the total area. More than 70% of the vegetation has an insignificant correlation with climatic factors.     

近20年来伊洛河流域典型地区森林景观格局动态

Based on the information from forest resources distribution maps of Luoning County of 1983 and 1999,six indices were used to analyze spatial patterns and dynamics of forest landscapes of the typical region in the middle of the Yihe-Luohe river basin.These indices include patch number,mean patch area,fragment index,patdch extension index,etc,The results showed that;(1) There was a rapid increase in the number of patch and total area from 1983 to 1999 in the study area,The fragment degree became very high.(2) The area of all the forest patch types had witnessed great changes,The fractal degree of each forest patch type became big from 1983 to 1999 ,The mean extension index of Robinia pseudoacacia forest ,non- forest shrub forest ,sparse forest ,and Quercus species forest in creased rapidly,but that of economic forest became zero ,The fractal dimension each showed that forest coverage has been promoted.(3)The changes of landscape patterns were different in different geomprhic regions.From 1983 to 1999 the vegetation cover area,the gross number and the density of patch,diversity and evenness of landscape were all reduced greatly in gullies and ravines,but the maximum area and the mean area of patch types were increased ,In hilly region,both the forest cover area and the number of patch increased from 1983 to 1999,but the mean area of patch was reduced greatly,In mountain region,even though the area under forest canopy reduced from 1983 to 1999 ,the patch number was increased greatly,the mean area of all patch types was reduced ,the extension index,diversity index and evenness index of landscape were all increased.Furthermore,because of different types of land use,human activtiy and terratin ,the vegetation changes on northern and southern mountain slopes were different.According to these analyses,the main driving forces,such as the policies of management,market economy,influence of human activities etc.are brought out.     

2000-2010年黄河上游流域植被年际变化及其对气候要素的响应(英文)

To understand the variations in vegetation and their correlation with climate factors in the upper catchments of the Yellow River, China, Normalized Difference Vegetation Index(NDVI) time series data from 2000 to 2010 were collected based on the MOD13Q1 product. The coefficient of variation, Theil–Sen median trend analysis and the Mann–Kendall test were combined to investigate the volatility characteristic and trend characteristic of the vegetation. Climate data sets were then used to analyze the correlation between variations in vegetation and climate change. In terms of the temporal variations, the vegetation in this study area improved slightly from 2000 to 2010, although the volatility characteristic was larger in 2000–2005 than in 2006–2010. In terms of the spatial variation, vegetation which is relatively stable and has a significantly increasing trend accounts for the largest part of the study area. Its spatial distribution is highly correlated with altitude, which ranges from about 2000 to 3000 m in this area. Highly fluctuating vegetation and vegetation which showed a significantly decreasing trend were mostly distributed around the reservoirs and in the reaches of the river with hydropower developments. Vegetation with a relatively stable and significantly decreasing trend and vegetation with a highly fluctuating and significantly increasing trend are widely dispersed. With respect to the response of vegetation to climate change, about 20–30% of the vegetation has a significant correlation with climatic factors and the correlations in most areas are positive: regions with precipitation as the key influencing factor account for more than 10% of the area; regions with temperature as the key influencing factor account for less than 10% of the area; and regions with precipitation and temperature as the key influencing factors together account for about 5% of the total area. More than 70% of the vegetation has an insignificant correlation with climatic factors.     

基于GIS的中国人口重心的密度分级与曲线特征

In this paper, with the spatial analysis functions in ArcGIS and the county-level census data of 2000 in China, the population density map was divided and shown by classes, meanwhile, the map system of population distribution and a curve of population centers were formed; in accordance with the geographical proximity principle, the classes of population densities were reclassified and a population density map was obtained which had the spatial clustering characteristic. The multi-layer superposition based on the population density classification shows that the population densities become denser from the Northwest to the Southeast; the multi-layer clustering phenomenon of the Chinese population distribution is obvious, the populations have a water-based characteristic gathering towards the rivers and coastlines. The curve of population centers shows the population densities transit from the high density region to the low one on the whole, while in low-density areas there are relatively dense areas, and in high-density areas there are relatively sparse areas. The reclassification research on the population density map based on the curve of population centers shows that the Chinese population densities can be divided into 9 classes, hereby, the geographical distribution of Chinese population can be divided into 9 type regions: the concentration core zone, high concentration zone, moderate concentration zone, low concentration zone, general transitional zone, relatively sparse area, absolute sparse area, extreme sparse area, and basic no-man's land. More than 3/4 of the population of China is concentrated in less than 1/5 of the land area, and more than half of the land area is inhabited by less than 2% of the population, the result reveals a better space law of China’s population distribution.