It is an important issue for marine economy research filed to analyze and show the research hotspot, the core of author groups, major research institutions and important scholarly journals. Taking 3 441 articles related to marine economy which are retrieved form “China Knowledge Resource Integrated Database” and“Chinese Social Sciences Citation Index” as subjects, we have drawn maps of the research hotspot, the core of author groups, major research institutions and important scholarly journals to by CiteSpace, a visual software for literature analysis. As a result, firstly, since Chinese marine economy research association was established in 1982, marine economy caused concern of scholars gradually. Secondly, the study of China’s marine economy focused on marine economy, marine industry, sustainable development, exploitation of marine resources, coastal tourism, coastal regions, etc. Thirdly, Han Zenglin, Zhang Yaoguang, Zheng Guibin, Yin Kedong, Li Jingyu and Xu Zhibin are the top six prolific authors in marine economy research, and most research teams are study alone, common research teams are made up by authors who come from the same institution; and State Oceanic Administration People’s Republic Of China, Ocean University of China, Liaoning Normal University and Guangdong Ocean University are the top four prolific intuitions. At last, the journal which published the most of articles about marine economy is “Ocean Development and Management”, while “Economic Geography”, “China Population Resources and Environment” and “Resources Science” are the main core journals of marine economy research. The article showed a structure in the marine economy research from various angles, by which we hope to help for the learning of the status of marine economy research.
In the 1920s, Schumpeter proposed the theory of Innovation, but this theory did not arouse the attention by mainstream economists until 1950s-1960s. Though the space research of innovation had also aroused the concern of the geographers during that period, it failed to be the main areas of geography study. Since the 1980s, with "spatial turn" of human geography and emerging of knowledge economy, innovation geography has emerged as an important research area of geography, however, the research on the basic theory of innovation geography is still very limited, and that whether innovation geography as an independent subject is still under debating, therefore, those important issues concerned the discipline of innovation geography, such as the research object, discipline nature and tasks need to be examined further. This article argues that: Innovation Geography is an independent subject studying relationship between human’s innovation activities and geographical environment. The innovation activities of human beings as the most important aspect of human activities have great significances to establishing the intelligent human-earth relationship system. As a branch subject of human geography, innovation geography has cross-discipline nature, because it has close relationship with the branch subject of human geography and other subjects such as political science, management science, economics, policy science, urban planning and so on. We conclude the main tasks of innovation geography as follows: 1) The basic theory of innovation geography; 2) the regional distribution and combination of innovation elements such as talents, capital, technology, etc.; 3) the examination and evaluation of Innovation Milieu and innovation ecology and evaluation; 4) the survey of innovation geography and the study of the space pattern and regional effect of innovation; 5) the study of innovation links, innovation networks and innovation cluster; 6) the study of multi-scale innovation system; 7) the relationship of innovation, urban development and planning.
Under the background of globalization and regionalization, the world’s trade pattern has altered distinctly. Defining trade globalization as the size and complexity of trade network, and regionalization as specific types of linkages betweencountries in the same region, this article analyzes complete auto’s and auto parts’ trade patterns in 2003-2013, and examines whether they become globalized or regionalized using the social network approach. The centrality, E-I index and core-periphery model of the trade network are calculated, and the results are as follows: firstly, exports of auto parts concentrate in emerging markets of east Asia and eastern Europe with the globalization of automobile production, while the exports of complete auto don’t follow that trend. The trade networks of complete auto and auto parts both become denser, which means they turn more global; and the interregional ties of their trade network become stronger, implying more regionalized trade; however, the E-I index shows that globalization seems to be dominating the trade of complete auto and auto parts, while the regionalization process is relatively unconspicuous. Secondly, the trade networks of complete auto and auto parts are characterized by the core-periphery structure. During the research period, Germany, Japan and United States are always the core of complete auto trade network. Germany and Japan mainly play the role of exporters; in contrast, United States participates as importer. China, India, Thailand, South Africa and other emerging markets are in the periphery position. At the same time, the nucleus of auto parts trade network changed from United States and Japan into China and Germany. Auto parts’ trade grows rapidly among Asian countries, and China becomes the core exporter. In Europe, the gravity of auto parts trade network moves from west to east. Thirdly, high technology-intensive parts of cars are less global than resource-intensive parts. East Asia becomes the center of electrical and electric components trade as global electronic industry transfers to east Asia. China replaces United States as the organizer of electrical and electric components trade network. As for the pivotal components of auto mobile, engine-parts are traded among fewer countries than other parts. The core of engine-parts’ trade network used to include United States, Japan and Germany in 2003; Unites States fades out while Germany enhances its control. During the same period, the position of central and east European countries raise in European regional engine-parts’ trade network. In addition, the trade network of tires and tubes which have the lowest added valueis organized in a more globalized way, dispersing to China, India, Brazil and other emerging countries. China displaces the core position of Japan in the regional trade network of Asia.
We can grasp the marine economic development and existing problems through measuring the marine economy efficiency, which can provide the basis for the marine economy policy. This article is based on consideration of undesirable outputs SBM model, measuring marine economic efficiency value for 11 coastal provinces during 2001 to 2012 and analyzing its spatio-temporal characteristics. Research shows that: 1) The marine economic efficiency value of inconsideration of undesirable output is obviously higher than the one of consideration of undesirable output, which turns out that undesirable output has a significant effect on marine economic efficiency and more accord with the fact. 2) The evolution of marine economic efficiency divided into two stages since 2001, declining with a fluctuant process stage (2001-2008) and rising slowly stage (2009-2012), which presenting the inefficiency is changing to effective state, but still in a low level. The regional disparity shrank at first and then expanded. 3) From the spatial distribution, in 2001, the initial stage in the tenth Five-Year Plan, the spatial pattern of marine economic efficiency shows the characteristics that the efficiency of the northern and southern is high, and the middle area is low, while in 2012, the spatial pattern shows the three pole. The inter-provincial variation of marine economic efficiency varied from province to province. Hainan was high stable level while Guangdong and Fujian were ascending to the high level. Guangxi, Hebei are in the low and descending level, Liaoning, Shandong, Zhejiang belonged to the low but ascending type, while Jiangsu to the low stable type. In order to explain the influence mechanism of marine economic efficiency, this article explains the influence factors from four aspects. From the element level, the marine and land economic base, the national marine policy, the market mechanism and inter-regional economic relations influence the marine economic efficiency by influence the production organization activities of marine enterprise. From the driving fore level, to gain more profit and enhance market competitiveness, the marine enterprises improve their production efficiency, and the introduction of technology, the inter-regional spillover of efficiency and the local government policy can also improve the efficiency. From the path and effect level, the upgrade of marine industry, the expansion of industrial scale, the improvement of technology and management methods can improve the marine economic efficiency. The improvement of marine economic efficiency can form the feedback mechanism affecting the competitiveness of enterprise, industrial upgrading and the marine and land economic development. Finally, this article put forward some recommendations to improve the marine economic efficiency.
Industrial transfer is an effective method to promote economic development of the undertaking regions. Since 1930s research on industrial transfer had formed the flying-geese model, product life cycle theory, marginal industry expansion theory, the eclectic theory of international production ,overlapping industry theory, and the theory of gradient and so on. Early empirical research is mainly about the transfer of industry between developed countries. China's research on industrial transfer started in 1990s. The research content is mainly about the motive, the mode and the mechanism of the industry transfer, study on the ability of undertaking industry is still insufficient. As an important carrier of regional development, six central urban agglomeration plays an important role in transfering the industries of the eastern region, So, what are the differences of the undertaking capacity of the six major urban agglomerations in the central region? What are the strengths and weaknesses of different urban agglomeration to undertake industry? This is very important for different regions to make best use of the advantages and by pass the disadvantages to improve industry utilization efficiency. These are also topics worthy to discuss.Thus,from the perspective of industry’s undertaking place, this article takes six central urban agglomerations as the research object and selects 7 secondary indicators and 27 tertiary indicators to establish evaluation index system, using the principal component analysis (PCA) to evaluate the comprehensive undertaking industry transfer ability of six major urban agglomerations in the central region, and finally draws the following conclusions: Firstly, from the perspective of urban agglomeration, the undertake ability between urban agglomeration varied greatly and the level gap of each subsystem is large. These differences are reflected in the seven subsystems. Secondly, from the perspective of cities, the undertake ability of central city is outstanding, but the overall level is yet to be improved. The number of high and low gradient cities is "polarization". Thirdly, the comprehensive undertaking ability of the urban agglomeration is not only related to the strong undertaking ability of the regional central city, but also closely related to the undertaking ability of non-central cities in the urban agglomeration. Finally, based on relevant research conclusions, this article gives some suggestions to improve the industry capacity of the six major urban agglomeration from seven aspects, including factor of cost, the degree of opening cooperation, the attraction of the market, the ability of technological innovation, the industry matching ability, the level of economic development and the industrial structure level.
Generally the living standards of households in China have improved significantly as a result of rapid socio-economic growth. The rapid growth, especially in the urban areas has been one of the sources of carbon emissions. Therefore, the carbon emissions from the urban households should be taken into account. From the consumption point of view, the study analyzed the total, direct and indirect carbon emissions of Chinese urban households. Further, the coefficient variations of the total and per capita carbon emissions were also calculated and subsequently, adopted the structural decomposition analysis to explore the effects of energy structures, industrial structures, and consumption structures between 2003 and 2012. The results indicated that there were significant differences of carbon emissions from urban households between provinces. As compared to that of 2003, the total carbon emission of the urban households has increased while the per capita carbon emission has decreased in 2012. The study revealed population as one of the main source for decreasing regional differences of carbon emission in the urban households. Most provinces with high carbon emissions of urban households could be attributed to large scale of economy. However, some provinces with small scale of economy still have relatively high carbon emissions. Overall, the provinces with high carbon emission from urban household consumption could either be attributed to its rich natural resource base or to the size of its economy. From the geographical perspective, the areas with high carbon emission from the urban households are mainly distributed in the northern provinces and coastal areas. This can be substantiated by the presence of rich coal resources in the northern areas and the presence of either heavy industries or large economy of scale in the coastal areas. Therefore, it is quite evident that the trend of carbon emission from the urban households will keep increasing given the pace of current socio-economic growth. While analyzing carbon emission from the urban households, data were categorized into six different sectors, including agriculture, industry, construction, transport, storage and post, wholesale and retail trades, hotels and catering services, and other industries. The factors including consumption structure, energy structure, and industrial structure have impacts on carbon emission from the urban households in 30 provinces in a descending order (consumption structure>energy structure>industry structure). Among these three structures, although the energy consumption in productive sectors, input-output turnovers and product purchases of the secondary industry were the key effects on local per capita carbon emissions of urban households, different provinces presented their own complex characteristics of driving factors. The government should formulate a policy in dealing with carbon emission from the urban households by engaging all relevant stakeholders, following the above analysis results.
In all mainstream urban planning theories, such as “smart growth”, “new urbanism” and “traffic-oriented development”, it is believed that small-scale mixed communities with sufficient public transport facilities can help promote the utilization of green travelling modes. However, the actual effects of urban form are still in dispute. Besides, there is little empirical evidence in China. As Chinese cities are facing a sharp rise in the volume of automobiles, transport related problems such as increasing carbon dioxide emission, environmental pollution and traffic congestion are becoming more and more serious, leading to a growing concern about transport demand management. Based on abundant literatures on the relationship between urban form and transport behavior, the article tries to put forward a theoretic framework based on the unique urban development background of China. It adopts geo-referenced residential form data and large-scale commuting behavior survey data in Beijing to investigate the spatial differences of residential form, as well as its impact on residents’ commuting mode choice through GIS analysis and Multi-nominal model. There are several findings generated here: 1) The residential form indicators vary widely across space in the city of Beijing. The first indicator, the scale of blocks, declines from urban center neighborhoods to peripheral neighborhoods. Besides, the average block scale is much larger than other mega cities such as New York and Tokyo. The second indicator representing the intensity of land uses is lower in urban center and exurb, and the peak level appears between Ring 2 and Ring 4. As for the third one, the land-use mix indicator, it is quite low in urban center because most parts of the district is traditional residential zone. This indictor rises in the surrounding areas, and goes down in some outskirt towns where segregated manufactory land uses or residential land uses are located. The differentiation of residential form reflects the change of urban development pattern in the city along with time. 2) Residential form indicators impose significant influences on peoples’ commuting mode choice. The over-sized blocks in suburbs of Beijing do not facilitate walking or bicycling commuting, while high-density land uses could reduce the probability of car travelling, and mixed land use encourages people choose walking for commuting. 3) We also find some socio-economic attributes which are often discussed in western literatures also have significant effects on commuting mode choice in Beijing. Low-income people are more likely to choose green travel modes because of their low affordability of private cars; besides, female, middle and old aged residents also show greater likelihood of choosing green travel modes given their relative disadvantage in terms of mobility. The findings shed some light on urban planning in the aim of encouraging green travel, that is, small scale blocks, compact and mixed land uses are also preferred in the Chinese background.
The purpose of study of marine economy vulnerability is to explore means to reduce the vulnerability, which can realize sustainable development of the marine economy. In recent decades, the studies of vulnerability have made remarkable progress in various fields. How to quantify vulnerability has become a hot topic in academic circles. This article presents a new method for quantifying the marine economy vulnerability in Bohai Sea Ring Area. Data envelopment analysis (DEA), which combines multiple inputs and multiple outputs in examining relative efficiency and performance of decision making unit (DMU), has been widely used for the assessments in many domains. Based on understanding of the marine economy vulnerability, we establish assessment indicator system of the marine economy vulnerability from three aspects including pressure, sensitivity and adaptability by combining Pressure-State-Response model (P-S-R) with Exposure-Sensitivity-Adaptability model. This article measures the marine economy vulnerability of 17 coastal cities in Bohai Sea Ring Area from 2000 to 2011 by weighted slacks-based measure (WSBM) model. The kernel density estimation method is employed to analyze the dynamic evolution of the marine economy vulnerability in Bohai Sea Ring Area,and the results can basically reflect the spatio-temporal distribution pattern of the marine economy vulnerability during the study period. The analysis of temporal variation at three time points by kernel density estimation reveals that the marine economy vulnerability in Bohai Sea Ring Area reduced year by year. The spatial pattern for the marine economy vulnerability was divided into four groups: very low, low, moderate, and high. The cities with very low vulnerability are Tianjin, Dalian, Dongying, and Yantai; The cities with low vulnerability are Qinhuangdao, Dandong, Panjin, Huludao, Weihai, and Rizhao; The cities with moderate vulnerability are Qingdao, Weifang, and Binzhou; The cities with high vulnerability are Tangshan, Cangzhou, Jinzhou, and Yingkou. Finally, we study the law of spatial differences for the marine economy vulnerability in Bohai Sea Ring Area, which has certain theoretical value and practical significance for reducing the marine economy vulnerability in this area.
The perspective of entrepreneurial agents for evolutionary investigation on the mechanisms of industrial cluster restructuring is particularly useful for understanding the bottom-up constructing process of restructuring. Based on the discussion on the content of entrepreneurship and concept definition of local entrepreneurship, this article proceeds with the theoretical analysis on the relationship between local entrepreneurship and cluster evolution. In the cluster formation phase, new firms relying upon the similar working experiences and diversifying firms are the critical mass owing to opportunities of interactive learning. In the cluster development phase, localized spin-off dynamics account for the rapid expansion of existing industries. When the cluster matures, the cluster paradox emerges. Agglomeration economies boost the performance of the incumbent firms, but meanwhile increases the degree of competition between new firms and the risk of spillover. In this case, specialized clusters tend to enter the phase of lock-in in particular in face of economic restructuring. Industrial structures with related diversification helps the restructuring of the clusters. However, the structure-determined view tends to overlook the agency of economic actors. Complex theory in evolutionary economic geography views cluster development as a non-linear process in arguing that the decline of clusters is not inevitable and clusters can be upgraded and restructured with new technology or new resources. Relying on the complex thinking in resilience theory, it highlights the new path creation as processes triggered by external shock events, and are jointly formed by existing socio-cultural environment for new business and active initiative taken by the entrepreneurs and their networks. The article tries to integrate the relational and institutional perspective in order to understand the local entrepreneurship as a power practice to legitimize new institutions for new technologies, which is placed in the relational geometries with other cluster agents, such as the local government, global lead firms and related institutes. It is argued that research attention on entrepreneurial attributes and background, as well as their network power is critical for the understandings on cluster evolution mechanism. Last, the direction for future studies on entrepreneurship-driven cluster restructuring within the China transition context is put forward. Firstly, investigation into the role of entrepreneurship should acknowledge the strategic initiatives of different types of entrepreneurs in different industrial milieus and regional circumstances. The interaction and network between local entrepreneurs and other cluster agents should become the research focus in studies of Chinese coastal regions in times of economic restructuring. Secondly, focus on the micro-scale entrepreneurial space should be placed in order to shed light on policy implications on the establishment of start-up parks. The entrepreneurial communities have been rapidly emerging as one of the new urban space in China, which helps to strengthen the trust and sense of identity, and forms the pivotal base for the power practice of the entrepreneurs with other agents.
According to space flow characteristics of the social and economical factors between central towns, we have improved the gravity model and the breaking-point formula. The weighted average of comprehensive strength and location condition of the central town was used to characterize the quality of the town first, and then the geometric average of transportation time and transportation costs between each pair of central towns was used to characterize the transportation distance in the gravity model. After that, we took the quality of the central town to replace the population size in the breaking-point formula. Through the combination utilization of the improved gravity model and breaking point formula, we achieved the quantitative measure of the intensity of spatial interaction between each pair of central towns and the scope of gravity of each central town. The results of the case study of Jinhua City show that: 1) the intensity of spatial interaction between central towns presents a clear clustered space pattern, according to which the central towns can form a spatial integration of ‘two axes and four groups’ in the future; 2) the intensity of spatial interaction between central towns has a remarkable spatial variance feature, differentiation of measures should be taken to promote the coordinated development of the central towns; 3) the scope of gravity of the central towns differs greatly in Jinhua, the attraction of the towns in central group is strongest, the southeast and west groups take the second place and the north group is weakest; 4) according to the relationship of distance between the central towns and the breaking points, we can figure out the primary central town and the key node central town of the group. Therefore, the quantitative measure system of spatial interaction of the central towns formed by this research can provide theoretical and technical methods to support the exploration of the spatial interaction between central towns, which then provides the basis for spatial integration and coordinated development of central towns in a region.
Based on the historical loss data, the study builds vulnerability curves and carries out qualitative research on the general vulnerability of Beijing to rainstorms and floods under different rainfall scenarios. The results show that: 1) There is a high correlation between the maximum 2-day rainfall and the loss rates, the established vulnerability curves can express the relation and be used for loss estimation; 2) According to the P-III fitting curves, the once-in-5-year maximum 2-day rainfall in Beijing is 110.5 mm, and the figures for once-in-10-year, once-in-20-year, once-in-50-year and once-in-100-year occasions are 134.8 mm, 159.0 mm, 190.8 mm and 214.8 mm, respectively; 3) With the current ability to resist disasters, under the same rainfall scenario, the crops loss rate is the highest, followed by population affected rate, buildings damaged rate, direct economic loss rate and buildings collapse rate, death or missing rate is the lowest; 4) The loss rate rises dramatically with the increase of maximum 2-day rainfalls. With current social and economic exposure, when the maximum 2-day rainfall recurrence period reached once-in-5-year, population affected may be 6.2×104 and the number of death or missing may be 4 people, the area of crops affected may be 2×103 hm2, the number of buildings damaged or collapse may be 3.5×103, and direct economic loss may be 3×108. When the maximum 2-day rainfall recurrence period reached once-in-100-year, population affected may reach 1.474×106 and the number of death or missing may reach about 50 people, the area of crops affected may reach 7×104 hm2, the number of buildings damaged or collapse may reach 6×105, and direct economic loss may exceed 4×1010 yuan(RMB). So Beijing still needs to give high importance to flood problems and strengthen its flood risk management in this regard.
In this article, based on the average nearest neighbor method, kernel density function, buffer analysis and spatial pattern extraction method, we explore the characteristics of spatial layout and class differences of the banking industry in Guangzhou City and summarize its spatial differentiation model. All of the data are from 1 637 banking outlets distributed in Guangzhou metropolitan areas. The results are shown as follows: 1) The spatial layout of Guangzhou banking shows a significant imbalance and center cluster characteristic. 2) Significant difference is found in distribution characteristics of different types of banks. State-owned commercial bank constitutes the main body of the banking sector in Guangzhou for its convenient service, enormous quantity, high dot density and high grade. 3) The quantity of bank outlets has diminished gradually from the city center to the periphery and shows a ‘circle layer + fan shaped’ space model: the core commercial circle is banking highly concentrated area, the city center is the most significant regional banking density decrease area and the least number of bank is located in the suburb. 4) Different types of banks have different spatial density model. The spatial density of state-owned commercial banks, national joint-stock banks and city commercial banks present non-uniform decline from center to the periphery, and respectively show inverted ‘S’ type, ‘L’ type and ‘ladder’ type curve model. Foreign funded banks and Hong Kong funded banks present a core business agglomeration mode, while the rural commercial bank presents a homogeneous linear model.
The article aims to analyze the impact of geographical proximity and relational proximity of innovative actors on the innovation of agricultural clusters. Taking Shouguang vegetable industrial cluster in Shandong Province, China as a case study, it examines how the geographical proximity and relational proximity among heterogeneous enterprises influence the innovation effects of the cluster, combining the spatial proximity analysis with the social network analysis and the multiple linear regression model, based on the fieldwork and questionnaire data. It is shown that: 1) The spatial agglomeration of enterprises in cluster is conducive to the formation of innovation atmosphere. The leading enterprises have a high degree of geographical proximity with the new agricultural enterprises, while the processing agricultural enterprises distribute relatively decentralized. Farmers collocated primitively evolve into agricultural enterprises through organizational innovation, which results to enterprise agglomeration, division of labor and close connection with each other, then the cluster forms; At the same time, the temporary geographical proximity among enterprises in the cluster, which is the spatial distance between the enterprise and the local vegetable expo park, mirrors the participant performance of enterprises to the meeting network. 2) The enterprises in cluster have close social connection to other innovation actors, and many core nodes in relational network take crucial roles to the allocation of the innovation resources and the diffusion of the tacit knowledge and new technology not only inside cluster but outside cluster as well. The concentration degree of the relational network of enterprises within cluster is lower than that of the whole network, which indicates that the concentration degree of the cluster’s external nodes is higher, and the geographical proximity of enterprises is not consistent with their relational proximity to the cluster enterprises. 3) The regression analysis presents that, with the rapid development of traffic and communication technology, the relational proximity has more significant influence on the innovation process of the vegetable cluster than the permanent geographical proximity, although which still has been playing a positive role. Therefore, the innovation network which is formed by multidimensional proximity not only eliminates the lock-in of the cluster technologies caused by excessive geographical proximity and single proximity, but also provides a new channel for agricultural cluster’s innovation under the background of globalization.
On the background of the increase of population and the decrease of arable land, how to improve efficiency and quality of farmland use is an important issue in China. We noticed that the administrative villager council as the unique legitimate and formal institution in countryside and the cultivators is restricted in their administrative village. To some extent, the cultivators' activity in the rural area are bound to their contracted land within a certain farming distance. However, the ideas on how to estimate the effect on spatial patters by the farming radius are vague in recent studies because the analysis on the relationship between rural settlements and arable land is qualitative and patial. To compare and evaluate the spatial pattern of cultivated land, we proposed a mothod to estimate the spatial distribution of the farming distance between settlements and farmland using exploratory spatial data analysis (ESDA) and the local indicator of spatial association (LISA). The study area is the Yangshan County located in the northwest Guangdong Province, which is one of the most representative county in the traditional mountain farming district. By this method, we found that the average farming distance changed more quickly than the coverage rate did with the increase of the coverage rate. When the coverage was up to 90%, the average distance increased up to 570 m, and the coverage was up to 100%, the average distance of the eincreased to 1 134 m. In other words, it is equivalent to the distance required to complete 90% of the cultivated land if the cultivators want to completely use 10% of the rest cultivated land with the greater distance. Simultaneously, we found the variation of farming distance in the study area was more accurately according to LISA statistical method. The result showed that: 1) The farming distance was affected by many factors such as quality of arable land and level of terain, and there is a stronger correlation between farming distanc and quality of arable land and level of terain. 2) The spatial distribution of farming distance was nonuniform and the changes from low clustering value to a high value of farming distance indicated that the pattern of arable land in the study area became more decentralized with the increase of the distance scale. 3) the proposed method can expose the spatial differentiation of farming distance in the whole region using exploratory spatial data analysis and it is particularly useful to guide the formulation of public policies for adjustment of rural residential area and the construction of high standard farmland.
Placeness is very important in the process of local population and social. Tourism is an important way of consuming placeness, a variety of elements are used in tourism industry, having different influence on social relations and placeness. This study uses multi-methods research which included listening, photograph, participatory observation, interview and notes, choose recreational areas represent Zhouzhuang of different stages and different types, collects data from fieldwork, tourists, residents, tourism practitioners, tourism manager. Results show that capital power is the material base in space production and placeness. Culture knowledge influences the atmosphere of social space, and formation of placeness naturally through the reproduction of social order and relationships, art plays an important role in building atmosphere, breeding placeness indirect. Folk and life belong to soft power of social cultural, folk activities deeply from the heart promote neighbor friendship and mutual communication different from folk culture governed by discipline, life habit is shaped from poetic resistance of local residents to discipline of power and capital. This article examines the impact of tourism to placeness in ancient town from macro perspective with variety of factors. Although some scholars have started to elements research placeness from a single factor, but there are a lot of work to do about the contribution of various elements on placeness reconstruction. Secondly, the town is a comprehensive tourist destination, there are very different from other types of tourist destinations. Future, it can compare rural tourism, theme parks, cultural and creative park, natural tourist attractions, etc. In addition, different social and cultural backgrounds, different levels of economic development, different natural environment, the contribution of different factors on the development of the tourism industry is not same. The impact on social relations, the formation and construction mechanism requires further discussion. Construction diversification of placeness in Zhouzhuang is along with interaction power among local government, developers, tourists, migrant workers, artists, local residents, For them, there are several or myriad order of Zhouzhuang, each order has its own special style and independent existence. There are all kinds of perceptive world, such as history and culture world, commodity world, religion world, science fiction world, art world, myth world, fantasy world, everyday life world. When the world is stared by different groups of people, they become the authenticity and unique cognitive style. Sometimes they are continuous, sometimes broken. Visitors can jump from one world to another. As a rich history and culture town, along with the development of Chinese tourism industry (from foreign affairs reception period to mass tourism period then mass leisure period), and now it is moving to a new stage of development, tourist consumption patterns change. It brings a new opportunities for town tourism economic development, while facing the challenges of cultural heritage protection and new urbanization construction. Government, developers and local residents make appropriate compromises to meet the needs of tourists gaze. A number of new elements are put into the town for diversify development. On the one hand it brings revenue local residents, on the other hand people began to reflect on tourism modernization and rationalization consequences, re-examine everyday life, cultural practices and significance of local development.
To understand the effect of tourism on local soil ecological system, soil samples from the Yaoquan Mountain of Wudalianchi were collected to explore the impact of tourism on fungi community structure and analyze the response relationship between soil chemical properties and fungi community structure. The results indicated that the fungi number was between 0.34×106 cfu/g and 2.47×106 cfu/g in soil samples of the Yaoquan Mmountain. A total of 95 fungi were isolated and purified, respectively belonging to 2 classes, 4 orders, 6 families, 12 genus. A similarity of 45.3% was observed for the whole mountain fungal community structure. Aspergillus and Penicillium were the ubiquitously distributed fungi species for the Yaoquan Mountain. In terms of fungi diversity index, evenness index and richness index, the differences were not significant among samples from mountaintop, mountainside and mountain foot. In addition, no obvious variation was found in different mountain locations for total nitrogen, total phosphorus, available phosphorus, pH value except organic matter. In comparison with mountaintop background area, significant lower fungi number were discovered in buffer area and activity area, which demonstrated the obvious effects of tourism development. However, there was no significant difference in terms of the fungi quantity among the samples from mountainside, activity area, buffer area and background area. In comparison with mountainfoot background area, the fungi quantity in activity area was significantly different, but that in buffer area was much similar. The diversity index (H′) decreased firstly and then increased. RDA analysis found organic matter displayed the largest effect on the distribution of fungal community structure, followed by total nitrogen, total phosphorus, available phosphorus and pH value. When the soil organic matter was in the range of 60.75-90.70 g/kg, there was a significant positive correlation between Stachybotrys and soil organic matter. But when soil organic matter was between 10.36-63.84 g/kg, a significant negative correlation was built between Gliocladium and organic material. For instance, no Gliocladium was detected in mountaintop samples whose soil organic matter was highest (97.14±14.07 g/kg). The quantity of Rhizoctonia was negatively correlaed with all test factors, and it was detectable only in active area. So organic matter and fungi number can be used as indicators for the Yaoquan Mountain ecological system, and the presence of Rhizoctonia can serve as a co-indicator to assess the disturbance degree to which the Yaoquan Mountain suffered from. In summary, with the development of local tourism industry, soil fungi number of the Yaoquan Mountain suffered by showing a decreasing trend. In addition, fungi community structure changed accordingly with the emergence of the strains that adapt to the changing ecological condition. Given above, it can be known that changes in soil chemical properties affected fungi survival environment to a certain extent, which triggered the appearance of some adapting fungi community. All in all, the tourism development and the regional soil heterogeneity are major causes for fungi community structure variability.
Solar radiation data can be used to simulate surface dynamic and thermal process. Solar radiation data is the important input parameter of the models in ecology, hydrology, crop, solar radiation transmission, global circulation and so on. Quantitative simulation of solar radiation is important for understanding climate change in Northwest China. However, the solar radiation stations are sparse in Northwest China, so using small amount of radiation site data interpolating or extrapolating is difficult to obtain the spatial distribution of solar radiation data. There are more many weather stations in Northwest China, so it is one of the best methods to simulate the solar radiation by using a large number of meteorological observations. In this article, the LM (Levenberg-Marquardt) algorithm is used to optimize the BP neural network (LM-BP neural network is abbreviation of BP neural network for the optimization). This article simulates solar radiation using LM-BP neural network, H-S and A-P climate models at Urumqi, Kashi, Hami, Xining and Guyuan radiation stations and uses MPE, MBE and RMSE indexes of accuracy assessment to test the three models. The results indicate that LM-BP neural network has the highest accuracy in model simulations, showing satisfactory performance compared with the simulation results of traditional two climate models, simulated and observed values of fitting degree model is superior to H-S and A-P climate models. So we selects the LM-BP neural network model to simulate solar radiation in Northwest China. Basing on the meteorological data from 159 weather stations in Northwest, we apply the BP neural network optimized LM (Levenberg - Marquardt) algorithm to simulate the total month solar radiation during 1990-2012 in these meteorological observation stations. Then the solar radiation value of the 159 weather stations and the measured radiation data of the 25 radiation observation station to obtain the spatial-temporal distribution of annual average solar radiation by interpolation, and analyzes. These results indicate that average annual total radiation in 1990-2012 in Northwestern ranges from 262 MJ/m2 to 643 MJ/m2, presenting the distribution pattern of high in the middle, low on both end. LM neural network is a promising method for solar radiation simulation, which can be used in the simulation of solar radiation in the area of no radiation observation.
The interaction between vegetation and atmosphere is a research focus and hotspot in the field of earth science under the background of global change. Net primary productivity (NPP) has become a key link of biogeochemical cycle process of terrestrial ecosystems in the global and regional scale, which embodies the complex interaction between vegetation, soil and climate, and is strongly influenced by human activities and global environmental change. Therefore, it has important significance to know the spatial and temporal pattern, variation characteristic and the relationship between terrestrial NPP and climate factors, especially temperature and precipitation, in the evaluation of environment quality, estimation of the terrestrial carbon source/sink potentials, and the management and use of natural resources. Based on the average annual NPP data of MOD17A3 data and temperature and rainfall data from meteorological stations during 2001-2010, the temporal and spatial pattern and dynamic change of vegetation NPP in southeastern China and their relationship with climate elements were analyzed using GIS spatial analysis technology and mathematical statistics method. The results indicate that average annual vegetation NPP in southeastern China gradually decreased from the southern to the northern parts and from the eastern to the western parts as a whole. Different vegetation types had different average annual NPP, with evergreen broad-leaved forest had the highest average annual NPP and deciduous coniferous forest had the lowest NPP. In addition to deciduous coniferous forest, the NPP of high forest was significantly higher than that of low vegetation such as field crops and herbaceous plants. The average annual vegetation NPP reduced slightly as a whole in southeastern China during 2001-2010, and it increased rapidly during 2001-2004, after then it reduced gradually. Spatially, vegetation NPP decreased significantly in the southern regions, but increased significantly in the northern regions. In Jiangsu, southern Anhui, Zhejiang, Jiangxi, western Fujian, central and southern Hunan and northern Guangdong, vegetation NPP decreased at a rate of over 150 g/m2 per year in carbon value, but in southwestern Shanxi, western and central Henan, northwestern Hubei and northwestern Anhui, vegetation NPP annual carbon value increased at a rate of over 150 g/m2 per year in carbon value. The correlation between vegetation NPP and rainfall and temperature showed significant regional differences, with closer relationship between vegetation NPP and rainfall in northern regions, where precipitation increased in most areas in the past 10 years, and in the southern regions, where plum rains were removed northerly, and temperature increased in most of areas.
To study the regional differences of hydrochemistry of natural water in Xinjiang, 51 natural water samples from Hotan Prefecture, Xinjiang were collected and analyzed. 103 sets of data on natural hydrochemistry in other parts of Xinjiang were collected from published papers. The results showed that: total dissolved solid (TDS) in natural water from Southern Xinjiang(1 589.4 mg/L) was 3.1 times as high as that of Northern Xinjiang(513.5 mg/L). TDS and TH in 83.33% and 89.59%, respectively, of natural water samples from Northern Xinjiang were to the standards for drinking water quality, while the figures for natural water samples from South Xinjiang were 62.26% and 70.75% respectively. The water type in North Xinjiang were Ca-HCO3 and Ca·Mg-HCO3·SO4 mainly,while the water type in South Xinjiang were Na·Ca-Cl·SO4 and Na·Mg-Cl·SO4. The mean/average concentration of nitrate ion(NO3-) in natural water from North Xinjiang(5.2 mg/L) was higher than that of South Xinjiang(2.7 mg/L). Main conclusions: The significant regional differences of hydrochemistry between North Xinjiang and South Xinjiang coincided with tectonic division in Xinjiang. Regional differences of hydrochemistry of natural water in Xinjiang resulted from the interaction of geological factor, hydrometeorologic factor and human activities. Chemical constituents of natural water from Xinjiang were mainly determined by rock weathering and evaporation concentration. Chemical constituents of natural water from North Xinjiang were mainly from carbonatite and evaporite weathering. And chemical constituents of natural water from South Xinjiang were mainly from carbonatite, silicate minerals and evaporite weathering. The evolution of chemical constituents of natural water in North Xinjiang was less affected by evaporation concentration than that in South Xinjiang. In addition, NO3- concentration in natural water from Xinjiang was high, indicating that human activities also had an impact on the regional differences of hydrochemistry to some extent.
