The Convention on Biological Diversity (CBD) defines Ecosystem-Based Adaptation (EBA) as "the use of biodiversity and ecosystem services as part of an overall adaptation strategy to help people to adapt to the adverse effects of climate change". Climate change is happening at an unprecedented rate and impacting a large number of people globally. The need for adaptation efforts has never been so urgent. In particular, ecosystem-based adaptation approaches have proved to provide flexible, cost effective and broadly applicable alternatives for reducing the impacts of climate change, and as such are a critical tool at the disposal of adaptation planners for tackling the threats that climate change poses to people's lives and livelihoods across the globe. In this paper, the evolution of the EBA concept is presented; EBA definition, advantages and principles are summarized; EBA tools and methods are introduced; and lessons learned from EBA case studies are explored. Furthermore, challenges of EBA are discussed.
The 100th lecture series/spring 2014 symposium of China Ecological Forum (CEF), which aims to "disseminate new knowledge, exchange new ideas and present new research findings", was held on 25 April 2014 in Beijing. The symposium took "Major international research programs and prospects of ecosystem research in China" as the theme. Academicians Qin Dahe, Yao Tandong, Fu Bojie, and Cui Peng, and Professors Ma Keping, Yu Guirui, Zhang Jiabao, and Qin Boqiang were invited to give keynote speeches. The keynote speakers reported the progresses and trends of major international research programs including the Intergovernmental Panel on Climate Change (IPCC), Future Earth initiative, Third Pole Environment program, International Long-Term Ecological Research (ILTER), Intergovernmental Platform on Biodiversity and Ecosystem Services (IPBES), Biodiversity program (DIVERSITAS), and Fluxes Observation and Research program (FLUXNET), as well as presented the processes and mechanisms of debris flow, carbon flux, farmland fertility improvement, and eutrophication control of lakes. This paper reviews the main contents and highlights of the eight reports and analyzes the major trends of international research programs in the fields of ecology and environment and implications for ecosystem research in China. It also discusses the direction and key issues in scientific research of related fields within China.
Since the Fourth Assessment Report (AR4) was released by the Intergovernmental Panel on Climate Change (IPCC) in 2007, new observations have further proved that the warming of the global climate system is unequivocal. Each of the last three successive decades before 2012 has been successively warmer at global mean surface temperature than any preceding decade since 1850. 1983-2012 was likely the warmest 30-year period of the last 1400 years. From 1998 to 2012, the rate of warming of the global land surface slowed down, but it did not reflect the long-term trends in climate change. The ocean has warmed, and the upper 75 m of the ocean warmed by more than 0.11℃ per decade since 1970. Over the period of 1971 to 2010, 93% of the net energy increase in the Earth's climate system was stored in the oceans. The rate of global mean sea level rise has accelerated, which was up to 3.2 mm yr-1 between 1993 and 2010. Anthropogenic global ocean carbon stocks were likely to have increased and caused acidification of the ocean surface water. Since 1971, the glaciers and the Greenland and Antarctic ice sheets have been losing mass. Since 1979, the Arctic sea ice extent deceased at 3.5% to 4.1% per decade, and the Antarctic sea ice extent in the same period increased by 1.2% to 1.8% per decade. The extent of the Northern Hemisphere snow cover has decreased. Since the early 1980s, the permafrost temperatures have increased in most regions. Human influence has been detected in the warming of the atmosphere and the ocean, changes in the water cycle, reductions in snow and ice, global mean sea level rise, and changes in climate extremes. The largest contribution to the increase in the anthropogenic radiative forcing was by the increase in the atmospheric concentration of CO2 since 1750. It led to more than half of global warming since the 1950s (with 95 % confidence). It is predicted using Coupled Model Intercomparison Project Phase 5 (CMIP5) and Representative Concentration Pathways (RCPs) that the global mean surface temperature will continue to rise for the end of this century, the frequency of extreme events such as heat waves and heavy precipitation will increase, and precipitation will present a trend of "the dry becomes drier, the wet becomes wetter". The temperature of the upper ocean will increase by 0.6 to 2.0℃ compared to the period of 1986 to 2005, heat will penetrate from the surface to the deep ocean which will affect ocean circulation, and sea level will rise by 0.26 to 0.82 m in 2100. Cryosphere will continue to warm. To control global warming, humans need to reduce the greenhouse gas emissions. If the increase in temperature is higher than 2℃ than before industrialization, the mean annual economic losses worldwide will reach 0.2% to 2.0% of income, and cause large-scale irreversible effects, including death, disease, food insecurity, inland flooding and water logging, and rural drinking water and irrigation difficulties that affect human security. If taking prompt actions, however, it is still possible to limit the increase in temperature within 2℃. To curb the gradually out-of-control global warming and achieve the goal of sustainable development of the human society, global efforts to reduce emissions are needed.
The Third Pole region, centered on the Tibetan Plateau, is an important geographic unit and one of the most unique coupled geological-geographic-resource-ecological systems in the world, which exerts significant influences on the environmental changes of China, the northern atmosphere and globally. At the same time, the Third Pole region is very sensitive to the impact of global environmental change and human activities in the surrounding areas, therefore has attracted equally high attention of the scientific community as compared to the Arctic and Antarctica. In 2009, The Third Pole Environment (TPE) program was initiated with the support of the Chinese Academy of Sciences. TPE is focused on the interactions between water, ice, atmosphere, ecosystem, soil and human activities, with the aim to study the spatial and temporal characteristics of past environmental changes, interactions between cryosphere, atmosphere, hydrosphere and disaster processes, impact and responses of the ecosystem to environmental changes, impact of human activities on the environmental changes of the region, adaptation to the environmental changes in the region, and finally serve the societies in the region. Since the initiation of the program, with the strong support of the Science Committee and the program office, TPE has efficiently implemented scientific plans and made fruitful progresses in areas including research on the interactions between the Indian monsoon and westerlies, establishing observation platforms, data sharing and education. TPE is planning to further expand the scientific activities into broader fields of research and to the surrounding geographic regions, as well as contribute to the Future Earth international research initiative and future improvements of the environment in the region.
The international ecosystem related research programs are evolving toward global sustainability. They promote the discovery of ecosystem relevant scientific knowledge and corresponding applications. Ecosystem observation and research networks (EORNs) oriented toward multi-scale and multi-platform integration play a fundamental role in scientific knowledge discovery, serving decision making and achieving the sustainability goal. In this paper, the development of ecosystem related international research programs and ecosystem observation and research networks was elaborated, and some insights for the future development of EORNs are further presented. The evolution of international ecosystem related research programs shows that ecosystem research needs platforms founded on interdisciplinary international cooperation. Moreover, it is necessary to couple the understanding of mechanism of ecological processes with global sustainability. International ecosystem observation and research networks are expanding from site to basin and/or regional scales in scope. Their research focuses are broadening from ecosystem to the earth system. Natural ecological factors are gradually coupled with societal and economic aspects. Technologically, EORNs tend to enhance network-based monitoring and research, interrelate ground observation to remote sensing, and emphasize data sharing and integration to stimulate discovery in scientific knowledge. For the future, EORNs should expand the temporal and spatial scale of monitoring, strengthen and standardize network-based observation on individual factors, effectively couple ground observation with remote sensing, pay more attention to monitoring and research on biodiversity, and integrate natural science research with societal and economic studies. More importantly, EORNs must strengthen international cooperation and participate in the global scale observation and research networks.
Eddy Covariance technique (EC) achieves the direct measurement of system functions and processes such as plant productivity, energy balance, and greenhouse gas exchange at ecosystem scale. Coordinated observation through the global flux observation network represents a breakthrough from the observation of ecological phenomena and factors to the measurement of changes in functions of the global ecosystem. This paper first reviews the foundation and development of the Chinese terrestrial ecosystem flux observation and research network (ChinaFLUX). It then systematically introduces the scientific objectives, design concept, measurement system, standardization of observed data, and long-term data accumulation of the network. The paper also assesses the main progresses in research of terrestrial carbon-water-nitrogen budgets, environmental responses of the coupled ecosystem carbon-nitrogen-water cycles, and the spatiotemporal patterns of ecosystem carbon fluxes and mechanisms. Based on an analysis of the trend of development and emerging missions of the global flux network, this paper proposes the directions, key scientific questions and emphases of research of ChinaFLUX to provide references for the development of flux observation and research in China.
China has many lakes. Due to the rapid economic development and inappropriate use of lake resources, water pollution and ecosystem degradation are prevalent in most Chinese lakes, especially that the enrichment of nitrogen, phosphorus and other nutrients results in eutrophication, causing frequent cyanobacterial blooms and drinking water supply crises. Owing to the lack of theoretical basis, restoration of eutrophic lakes in China took a wrong strategy in the past-overemphasizing ecological restoration for improving lake environments without proper source control and effluent diversion in watersheds had been the mainstream approach for restoring eutrophic lakes, despite that ecological restoration of lake ecosystems requires a number of conditions. Diagnosis and analysis of these conditions are the prerequisite and basis for the implementation of lake ecological restoration measures. Based on the analysis of the spatial distribution of submersed plants and influencing factors in Lake Taihu, it is found that the key of restoration of submersed plants is underwater light conditions. Underwater light condition is influenced by trophic level, concentration of suspended solids, and depth of lake water. Only when water euphotic depth is close to the water depth (with the ratio of euphotic depth to water depth>0.8), restoration of aquatic plants (especially submersed macrophyte) would be possible. Measures for improving underwater light conditions, including lowering water depth, increasing transparency, and reducing wind all have the effect of increasing the ratio of euphotic depth to water depth. Without these conditions for ecological restoration, source control and reduction of pollutants entering the lakes should be the primary measure for pollution control and restoration of eutrophic lakes. This finding has practical significance for the pollution control and ecological restoration of Chinese lakes.
China Ecological Forum (CEF), a comprehensive academic forum on ecology in China, aims to disseminate new knowledge, exchange new ideas, and present new research findings by holding academic activities including lectures, thematic workshops, high-level seminars, and focal forums. Since its launch in 2005, CEF has held 100 lecture series, 12 large academic seminars, six thematic workshops, and two high-level symposia and forums, having brought together more than 300 well-known experts with half of them from foreign research institutions. As a result, CEF has become an important platform for ecological academic exchange both in China and internationally. Seen from the themes of these lectures, climate change and adaptation, ecosystem assessment and management, and ecosystem service are all hot issues in ecological research. Based on the CEF seminars, five volumes of serial publications on China Ecological Forum have been published since 2009, which cover the main research fields and key scientific issues and reflect the scientific frontiers of contemporary ecological research. By analyzing the themes of lectures and seminars of CEF, this paper explored the change on hot issues in ecological research in recent years, providing references and suggestions for future Chinese ecosystem research.
Various sensors such as GPS units, mobile phones, public transportation passes, and bank cards record the trajectory of human activities. These massive trajectory data contain distribution pattern of human behavior in space and time. The study of trajectory data can reveal individual trajectory patterns, facilitate the understanding of characteristics of human dynamics, and thus support trajectory prediction, urban planning, traffic monitoring and the like. Therefore the study of trajectory data recorded by various sensors has become a focus of research at present. In this paper, we analyze the acquisition and expression of human activity trajectory. The trajectory of human activities can be classified into three broad categories according to the sampling methods and driving factors-through interval sampling, position sampling and event trigger sampling. The trajectory data are composed of origin points, destination points, anchor points and general nodes. The study of trajectory patterns is organized in accordance with anchor points, travel range, shape, origin-destination (OD) flow pattern, and temporal pattern. The results can reflect periodicity and clustering patterns of activities in space and time. On this basis, we summarize the application of human activity trajectory in urban studies from five aspects, including trajectory prediction, dynamic urban landscape delineation, urban traffic simulation and monitoring, urban functional unit identification, and other urban applications. We argue that exploring human activity patterns provides the basis for other studies in urban planning, urban traffic, public security, and so on.
Storm struck cities frequently and often suddenly in recent years, leading to urban inundation and threatening life and property in these cities. With the establishment of urban storm-waterlogging monitoring network, real-time and time series rainfall and waterlogging data at the temporal resolution of a few minutes can be easily acquired. Real-time monitoring of inundation thus can be achieved and this provides new ways for research of inundation in cities. At present, however, there is a general lack of in-depth data mining and analysis of the observed data, which leads to the fact that urban inundation monitoring systems are used only for monitoring purposes and waterlogging control is not an integrated part of the system. Based on the monitoring data of urban inundation monitoring system, according to the temporal autocorrelation of waterlogging, spatial correlation of rainfall and the correlation of rainfall and waterlogging, a spatial and temporal auto regressive and moving average model (STARMA) has been built for short-term forecasting of waterlogging in this study. Auto regressive and moving average model (ARMA) is one of the correlation analysis methods of time series data. ARMA combined with spatial analysis methods generates the STARMA model. STARMA model is an effective means for modeling the spatiotemporal processes of geographic phenomena, especially when the mechanism of the spatiotemporal processes is unclear or multiple spatial and temporal variables are involved. STARMA model has been applied in traffic prediction, environment variable prediction and the social and economic fields. In this study, the model is applied in rainfall and waterlogging process simulation and short-term forecasting for the first time. In order to simulate rainfall and waterlogging processes, the traditional STARMA univariate model is modified to create a bivariate model of rainfall and waterlogging. Based on urban inundation monitoring data on 12 July 2012 in Beijing, using Fengbei Bridge, Huaxiang Bridge, Majialou Bridge and Liuli bridge as examples, the STARMA models were built respectively to predict water depth with a 5 minute step at 5, 10, and 15 minutes. The modeling process included creating rainfall stations' spatial weight matrix, model identification, parameter estimation and model verification. The STARMA model form was determined by autocorrelation function and partial autocorrelation, in addition to A-information criterion or Bayesian information criterion. Spatial weight values were calculated by inverse distance weighting (IDW). Parameter estimates were derived by the least square method. The simulation results show that the STARMA model predictions fit well with observed data and accuracy of short-term forecasting is high. The root mean square error (RMSE) is about 0.03, the relative square error (RSE) is about 0.01 and the average error rate is about 5%. When the prediction time increased from 5 to 15 minutes, prediction accuracy slightly decreased. This method improves prediction accuracy and reliability as compared to traditional hydro model simulation and prediction. The research uses urban inundation monitoring network data to predict short-term waterlogging. On the one hand it takes full advantage of the monitoring data, and on the other hand it improves the ability of disaster early warning and emergency command, thus provide decision support for related government departments.
The spatial relationships between fire events and fire-influencing factors have important implications for fire managers and scientifically revealing these relationships is therefore significant for management purposes. The spatial stationary relationships between fire events and fire-influencing factors considered by previous fire risk studies contradict the fact that fire events and their quantifiable influencing factors are always characterized by spatial heterogeneity. If the intrinsically non-stationary relationships between fire events and fire-influencing factors are modeled by some stationary models, misleading and even erroneous conclusions can be drawn, which hamper fire prevention operations. In this study, logistic geographically weighted regression (LGWR) that can account for local variations of spatial relationships between fire events and fire-influencing factors was employed to analyze the influences of different fire-influencing factors on fire events in the high risk season (September and October) from 2002 to 2012 in Henan Province. The independent variables of the model include altitude (Al), slope (Sl), distance to the nearest village (Dv), distance to the nearest path (Dp), land surface temperature (LST), Normalized Difference Vegetation Index (NDVI), and global vegetation moisture index (GVMI); and the binary dependent variable is monthly fire presence, with 1 representing presence and 0 representing absence. A training subset derived from spatial random sampling was created and potential multicollinearity among the independent variables was excluded, and then a LGWR fire probability model was developed using the GWR 4.0 software. The reliability and discrimination capacity of the developed fire probability spatial model was evaluated using a testing subset and an independent validation subset and the results show good model performance. The model was used for fire-influencing factor analysis in the next step. After delineating and overlaying the significant areas of the non-stationary fire-influencing factors, seven fire prevention regions were identified in Henan Province. The relative importance of the non-stationary fire-influencing factors was evaluated by comparing the absolute values of their estimated coefficients spatially. The results indicate that: I) The influences of Sl, Dv, LST, NDVI and GVMI on fire events present significant spatial variability, whereas the influences of Al and Dp exhibit insignificant spatial variability in Henan Province. II) The influences of LST and NDVI on fire events are significant globally in Henan Province, whereas the influences of Sl, Dv and GVMI are only significant locally. The sites most strongly influenced by LST are mainly Nanyang, Zhumadian, Xinyang and their contiguous areas. The sites most strongly influenced by vegetation cover (NDVI) are primarily Zhoukou, Xinyang, Luohe, Xuchang, Zhumadian and Shangqiu. In Xinyang and southeast Zhumadian, fire events are most strongly influenced by Sl, while in Luoyang this factor is Dv, and in Zhoukou and the adjacent area of Luoyang, Nanyang and Pingdingshan, it is GVMI. III) This study demonstrates the usefulness of LGWR for exploring local variations of fire-influencing factors and for examining the validity of a global fire probability model. The practical implication of spatial analysis of fire-influencing factors resulted from LGWR is that different fire prevention policies and emphases should be formulated for each of the seven fire prevention regions. Because of such heterogeneity, fire prevention policies need to take into consideration local conditions.
The demarcation of borders is a process in which spatial orders and relations are configured. It is central to the understanding of the production of social relations and cultural meanings in border areas. This article uses a social constructionist view to capture the variegated meanings that border procures during social changes and social processes. In doing so, this paper understands border as inherently a social product. Its social significance and definition is not fixated a priori, but constituted and negotiated within networks of relations and events. In the meantime, recent advancement in human geography has made a powerful claim that space and spatial relations are important constitutive elements in all social and cultural processes. The border is certainly no exception. The transitional zone defined by geographical borders is not simply a container of social, economic and cultural processes. On the contrary, the production of space and spatial relations is a critical dimension in the constitution of society and culture. With these theoretical points of entry in mind, this paper suggests that border as a social construct can imply closure and simultaneously openness. Social groups in different positions interpret the meanings of borders in radically distinct ways. The power of borders in defining spatial and social orders lies in the production of sociocultural differences and hence the division between "us" and "others". Borders not only delineate respective nation-states, but also create differentiated spaces of identity and belonging. Besides, borders situate different political and social entities in divided social, economic and political contexts, thus holding the potential to create gradients of regional development. In this sense, borders imcubate possibilities of exchange and cooperation in order to reconfigure established orders and relations. Following this view, this article develops a re-conceptualization and re-interpretation of the border. It reviews the current literature of border studies in human geography by engaging with a number of parallel topics. The main body of the article starts by briefly reviewing some conceptual explanations of borders and border areas. It then moves to elaborate on the sociocultural significances of borders, with specific focuses on implications of closure and openness. The following section turns its attention to the issue of openness in particular, and review extant studies of cross-border spatial practices. Three viewpoints can be concluded from discussions in this article. First, the border is an important symbolic marker. It defines the social and cultural differences between "us" and "others". It also allocates social members to different social and political entities, thus creating differentiated spaces of belonging. Second, because of the existence of borders, regions at the two sides of the borders are thus embedded in radically distinct social, economic and political contexts. This results in cross-border regional disparity, which in turn creates opportunities for cross-border exchange and cooperation. Finally, for a significant number of social members, the border is constitutive of their everyday social life. It is a socio-spatial order that they need to constantly negotiate and respond to. Often, they are set to challenge established spatial orders, but in the meantime they are able to take advantage of the spatial relations defined by borders to create new possibilities of life.
Dark tourism is an important part of economic and social recovery and rebuilding in places where major disasters have taken place. Dark tourism has become one of the hot research topics in tourism studies at home and abroad. Published research focuses primarily on visitor motivations in war/event dark tourism destinations. This study seeks to fill the gap by developing conceptual models to illustrate visitor motivations in a natural disaster site dark tourism destination and analyze the characteristics of visitors from different sources. The catastrophic Wenchuan Earthquake of 8.0 on the Richter scale struck western Sichuan, China on 12 May 2008. The urban area of Beichuan County was one of the most severely impacted sites in the earthquake. This study employed an on-site questionnaire survey at the Beichuan Earthquake Museum on 16-21 August 2012to test the conceptual model of visitor motivations, with 294 participants of domestic visitors. Visitors from Sichuan Province were extracted as a sub-sample set to build a structural equation model. Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were used to extract the main factors of visitor motivations. The result shows that visitor motivations to this natural disaster site dark tourism destination can be classified into five categories: Education-memorial motivation, social and family motivation, feelings-witness motivation, identification-experience motivation, and curiosity motivation. Visitor motivations in dark tourism destinations normally include mourning of the victims and facing the death, but our survey result indicates that visitor motivations in this case focuses on experiencing the feelings about natural damage, education, and understanding the disaster.In the next step, structural equation modeling was used to test the influence degree of cognitive desire and event attention on visitor motivations. The findings indicate that for all visitors, their event attention has a significant effect on education-memorial motivation, social and family motivation, feelings-witness motivation, and identification-experience motivation but has no significant effect on curiosity motivation; visitors' cognitive desire has a significant effect on education-memorial motivation, social and family motivation, feelings-witness motivation, and curiosity motivation, but has no significant effect on identification-experience motivation. The result for the visitors from Sichuan shows that visitors' event attention has no significant effect on feelings-witness motivation; visitors' cognitive desire has no significant effect on social and family motivation. Findings from this research indicate: that (1) Cognitive desire and event attention have some effects on visitor motivations in this natural disaster site dark tourism destination; (2) Visitors from Sichuan have a stronger sense of identity about the regions affected by the Wenchuan Earthquake and also have more fears about the destructive force of the natural disaster; (3) Education-memorial motivations can best embody the positive implication of dark tourism.
Due to the rising manufacturing costs of China's eastern coastal areas after the global financial crisis, there is a clear trend of industrial relocation and population shift to the central and western regions of the country. Migrant workers who are yet fully integrated into the urban system in eastern China become the main returning population. Since these returning migrant workers tend to be skilled and possess certain capitals, their return has important social and economic implications for the urbanization and industrialization of the destination areas. Therefore, the study of migrant workers' return intention, destination and employment choices, income expectation, as well as the development of appropriate planning initiatives has important theoretical significance and practical values. Zhoukou in Henan Province is a traditional agricultural area and an important population exporting region in recent years. According to incomplete statistics, more than a million migrant workers work outside for multiple years. Due to the accelerated industrial transfer in Zhoukou, return of these migrant workers is becoming increasingly obvious. Therefore, we choose Zhoukou as a case study area to explore the return intention of migrant workers in traditional agricultural area and planning response of the local governments. In this research, we collected data using questionnaire survey combined with in-depth interviews. We conducted field research in June 2012 in 17 villages using stratified sampling and systematic sampling method. Each village provided a list of 20 migrant workers and their telephone numbers. We randomly selected 305 migrant workers among these and conducted semi-structured telephone interviews with the survey participants, which generated155 valid questionnaires. The questions asked cover the demographic characteristics of the participants, such as gender, age, education level, job type, income, marital status, monthly income. Also, workplace, return intention, reasons for return, destination and employment choices, and income expectation upon returning were surveyed. Based on the result of the survey, the paper analyzes the spatial pattern of flow of migrant workers and their return intention, and emphatically investigates reasons and incentives for return and destination and employment choices. Several conclusions are drawn as follows: (1) return intention of migrant workers is strong and many have planned to return in the near future; (2) the incentives for return are diversified, and the county seats are the most important choice of destination for work and living following home village; (3) job opportunities and high quality of education and health care are the most important factors that attract migrant workers. Finally, the paper proposes four planning responses of the government and institutions: decentralization and strengthening the power of the counties, promoting healthy interactions of the "double shifts", balancing the location of public service facilities, and speeding up the reform of land transfer and eliminating restrictions of the population registration system.
Innovation is an important research topic of agricultural cluster at present. However, existing research on agricultural industry cluster has focused on the evolution mechanism, innovation models and competitiveness of such clusters and studies on innovation efficiency of agricultural clusters are relatively few. Exploring the key influencing factors of innovation will play an important role in guiding the development of agricultural clusters. Innovation of agricultural industry cluster is often reflected in product innovation and benefit, mainly through investment in scientific research, developing innovation networks, among others. The two-phase DEA-Tobit model has been used to analyze efficiency and influencing factors of multiple inputs and outputs for national, regional, and agricultural innovation systems and is considered an effective quantitative analysis method. Based on survey data, this paper analyzes the innovation efficiency and influencing factors of the vegetable industrial cluster in Shouguang County, Shandong Province, China, using a two-phase DEA-Tobit model. The DEA model analysis shows that innovation in this vegetable industrial cluster is in a good condition, with the large enterprises being the best. The scale of the vegetable industrial cluster in Shouguang County is at approximately the optimal state, while the comprehensive innovation efficiency is only at the average level, not reaching the optimal state. The main reason for this is the pure technical inefficiency derived from the lack of scientific research and technology strength. Tobit regression analysis indicates that knowledge dissemination and absorption capacity of enterprises, financial support of the government, innovative spirit of entrepreneurs and enterprises' development extroversion strength have significant positive correlation with agriculture innovation, while the scale of enterprises do not have significant influence on the cluster's innovation efficiency. The knowledge dissemination and absorption capacity of enterprises not only enables enterprises to have innovation resources in the cluster innovation network, but also has effects on innovation efficiency. Financial support of the government has the greatest influence on industrial cluster innovation, and the government has an important role in innovation of agricultural industry cluster. The innovative spirit of entrepreneurs represents an attitude towards innovation and development, thereby affecting enterprise investment in research and innovation. The paper also presents suggestions for encouraging agricultural innovation. Through facilitating the development of the cluster's innovation network, strengthening support from government agencies and foreign investment and cultivating the innovative spirit of entrepreneurs, efficiency oriented enterprise resource utilization will prevail.
