2019 Vol. 29, No. 6

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Articles
Monitoring Intra-annual Spatiotemporal Changes in Urban Heat Islands in 1449 Cities in China Based on Remote Sensing
LI Yuanzheng, WANG Lan, ZHANG Liping, LIU Min, ZHAO Guosong
2019, 29(6): 905-916. doi: 10.1007/s11769-019-1080-9
Abstract:
This study aimed to accurately study the intra-annual spatiotemporal variation in the surface urban heat island intensities (SUHIIs) in 1449 cities in China. First, China was divided into five environmental regions. Then, the SUHIIs were accurately calculated based on the modified definitions of the city extents and their corresponding nearby rural areas. Finally, we explored the spatiotemporal variation of the mean, maximum, and minimum values, and ranges of SUHIIs from several aspects. The results showed that larger annual mean daytime SUHIIs occurred in hot-humid South China and cold-humid northeastern China, and the smallest occurred in arid and semiarid west China. The seasonal order of the SUHIIs was summer > spring > autumn > winter in all the temperate regions except west China. The SUHIIs were obviously larger during the rainy season than the dry season in the tropical region. Nevertheless, significant differences were not observed between the two seasons within the rainy or dry periods. During the daytime, the maximum SUHIIs mostly occurred in summer in each region, while the minimum occurred in winter. A few cold island phenomena existed during the nighttime. The maximum SUHIIs were generally significantly positively correlated with the minimum SUHIIs during the daytime, nighttime and all-day in all environmental regions throughout the year and the four seasons. Moreover, significant correlation scarcely existed between the daytime and nighttime ranges of the SUHIIs. In addition, the daytime SUHIIs were also insignificantly correlated with the nighttime SUHIIs in half of the cases.
Spatiotemporal Variations and Regional Transport of Air Pollutants in Two Urban Agglomerations in Northeast China Plain
LI Xiaolan, HU Xiaoming, SHI Shuaiyi, SHEN Lidu, LUAN Lan, MA Yanjun
2019, 29(6): 917-933. doi: 10.1007/s11769-019-1081-8
Abstract:
Characteristics of air pollution in Northeast China (NEC) received less research attention in the past comparing to other heavily polluted regions in China. Spatiotemporal variations of six criteria air pollutants (PM10, PM2.5, SO2, NO2, O3 and CO) in Central Liaoning Urban Agglomeration (CLUA) and Harbin-Changchun Urban Agglomeration (HCUA) in NEC Plain were analyzed in this study based on three-year hourly observations of air pollutants and meteorological variables from 2015 to 2017. The results indicated that the annual mean concentrations of air pollutants are generally higher in the middle and southern regions in NEC Plain and lower in the northern region. Megacities such as Shenyang, Harbin and Changchun experience severe air pollution, with a three-year averaged air quality index (AQI) larger than 80, far exceeding the daily AQI standard at the first-level of 50 in China. The annual mean PM and SO2 concentrations decrease most significantly in NEC urban agglomerations from 2015 to 2017, followed by CO and NO2, while O3 shows a slight increasing trend. All the six pollutants exhibit obvious seasonal and diurnal variations, and these variations are dictated by local emission and meteorological conditions. PM2.5 and O3 concentrations in NEC urban agglomerations strongly depend on wind conditions. High O3 concentrations at different cities usually occur in presence of strong winds but are independent on wind direction (WD), while high PM2.5 is usually accompanied by weak winds and poor dispersion condition, and sometimes also occur when the northerly or southerly winds are strong. Regional transport of air pollutants between NEC urban agglomerations is common. A severe haze event on November 1-4, 2017 is examined to demonstrate the role of regional transport on pollution.
Searching for an Optimized Single-objective Function Matching Multiple Objectives with Automatic Calibration of Hydrological Models
TIAN Fuqiang, HU Hongchang, SUN Yu, LI Hongyi, LU Hui
2019, 29(6): 934-948. doi: 10.1007/s11769-019-1068-5
Abstract:
In the calibration of hydrological models, evaluation criteria are explicitly and quantitatively defined as single-or multi-objective functions when utilizing automatic calibration approaches. In most previous studies, there is a general opinion that no single-objective function can represent all important characteristics of even one specific hydrological variable (e.g., streamflow). Thus hydrologists must turn to multi-objective calibration. In this study, we demonstrated that an optimized single-objective function can compromise multi-response modes (i.e., multi-objective functions) of the hydrograph, which is defined as summation of a power function of the absolute error between observed and simulated streamflow with the exponent of power function optimized for specific watersheds. The new objective function was applied to 196 model parameter estimation experiment (MOPEX) watersheds across the eastern United States using the semi-distributed Xinanjiang hydrological model. The optimized exponent value for each watershed was obtained by targeting four popular objective functions focusing on peak flows, low flows, water balance, and flashiness, respectively. Results showed that the optimized single-objective function can achieve a better hydrograph simulation compared to the traditional single-objective function Nash-Sutcliffe efficiency coefficient for most watersheds, and balance high flow part and low flow part of the hydrograph without substantial differences compared to multi-objective calibration. The proposed optimal single-objective function can be practically adopted in the hydrological modeling if the optimal exponent value could be determined a priori according to hydrological/climatic/landscape characteristics in a specific watershed.
Siting of Dark Sky Reserves in China Based on Multi-source Spatial Data and Multiple Criteria Evaluation Method
WEI Ye, CHEN Zuoqi, XIU Chunliang, YU Bailang, LIU Hongxing
2019, 29(6): 949-961. doi: 10.1007/s11769-019-1079-2
Abstract:
With the rapid development of population and urbanization and the progress of lighting technology, the influence of artificial light sources has increased. In this context, the problem of light pollution has attracted wide attention. Previous studies have revealed that light pollution can affect biological living environments, human physical and mental health, astronomical observations and many other aspects. Therefore, organizations internationally have begun to advocate for measures to prevent light pollution, many of which are recognized by the International Dark-Sky Association (IDA). In addition to improving public awareness, legal protections, technical treatments and other means, the construction of Dark Sky Reserves (DSR) has proven to be an effective preventive measure. So far, as a pioneer practice in this field, the IDA has identified 11 DSRs worldwide. Based on the DA requirements for DSRs, this paper utilizes NPP-VIIRS nighttime light data and other multi-source spatial data to analyze possible DSR sites in China. The land of China was divided into more than ten thousand 30 km×30 km fishnets, and constraint and suitable conditions were designated, respectively, as light and cloud conditions, and scale, traffic and attractiveness conditions. Using a multiple criteria evaluation, 1443 fishnets were finally selected as most suitable sites for the construction of DSRs. Results found that less than 25% of China is not subject to light pollution, and less than 13% is suitable for DSR construction, primarily in western and northern areas, including Tibet, Xinjiang, Qinghai, Gansu and Inner Mongolia.
Using MaxEnt Model to Guide Marsh Conservation in the Nenjiang River Basin, Northeast China
WANG Zhiliang, ZHANG Bai, ZHANG Xuezhen, Tian Hongxu
2019, 29(6): 962-973. doi: 10.1007/s11769-019-1082-7
Abstract:
Incorporating private and working lands into protected area networks could mitigate the isolation state of protected areas (PAs) and improve the efficiency of conservation. But how to select patches of land for conservation is still a troublesome issue. In this study, the MaxEnt model and irreplaceability index were applied to guide marsh conservation in the Nenjiang River Basin, Northeast China. According to the high accuracy of the MaxEnt model predictions (i.e., the average AUC value=0.933), the Wuyuer River and Zhalong marshes in the downstream reaches of Wuyuer River are the optimal habitat for the Red-crowned crane and migratory water-fowls. There are 22 marsh patches selected by the patch irreplaceability index for conservation, of which 12 patches had been included in the current network of protected areas. The other 10 patches of marsh (amounting to 1096 km2) far from human disturbances with high NDVI (up to 0.8) and close distance to water (less than 100 m), which are excluded from the existing network of PAs, should be implemented conservation easement programs to improve the protection efficiency of conservation. Specifically, the marshes at Taha, Tangchi, and Lamadian should be given priority for conservation and restoration to reintroduce migratory waterfowls, as this would lessen the current isolation state of the Zhalong National Nature Reserve.
A Macroinvertebrate Multimetric Index for the Bioassessment of Wet-lands Adjacent to Agriculture Fields in the Sanjiang Plain, China
WU Haitao, LU Kangle, LYU Xianguo, XUE Zhenshan
2019, 29(6): 974-984. doi: 10.1007/s11769-019-1083-6
Abstract:
Adjacent intensive agriculture disturbs the natural condition of wetlands. However, to assess the effect of this agriculture on wetlands, few studies have used indices based on aquatic invertebrates. Multi-metric indices (MMIs) have been successfully used to assess freshwater ecosystems worldwide and are an important management tool, but little is known about their applicability in the Sanjiang Plain, Northeast China. In this study, we developed a MMIs for aquatic invertebrates to assess freshwater wetlands in this region. The aquatic invertebrate assemblages were sampled in 27 wetlands in the Sanjiang Plain that included those in natural reserves and those affected by adjacent, intensive agriculture. Twenty-four candidate metrics were initially reviewed and screened before four core metrics were selected:total number of taxa, number of Hemiptera taxa, proportion of Gastropoda, and proportion of predators. Mann-Whitney U tests, Box and Whisker plots, correlation analyses, and redundant metric tests were used to assess the ability of metrics to distinguish among reference and impaired wetlands. Four ordinal rating categories for wetland were defined:poor, fair, good, and excellent. Of the impaired freshwater wetlands, 76.2% were in poor or fair categories. The MMIs was robust in discriminating reference wetlands from impaired wetlands and therefore have potential as a biomonitoring tool to assess the condition and to guide the restoration efforts of freshwater wetlands in Northeast China.
Soil Microbial Community and Enzyme Activity Responses to Herbaceous Plant Expansion in the Changbai Mountains Tundra, China
JIN Yinghua, ZHANG Yingjie, XU Zhiwei, GU Xiaonan, XU Jiawei, TAO Yan, HE Hongshi, WANG Ailin, LIU Yuxia, NIU Liping
2019, 29(6): 985-1000. doi: 10.1007/s11769-019-1067-6
Abstract:
As one of the most sensitive regions to global climate change, alpine tundra in many places around the world has been undergoing dramatic changes in vegetation communities over the past few decades. Herbaceous plant species in the Changbai Mountains area have significantly expanded into tundra shrub communities over the past 30 yr. Soil microbial communities, enzyme activities, and soil nutrients are intertwined with this expansion process. In order to understand the responses of the soil microbial communities to such an expansion, we analyzed soil microbial community structures and enzyme activities in shrub tundra as well as areas with three different levels of herbaceous plant expansion. Our investigation was based on phospholipid fatty acid (PLFA) analysis and 96-well microtiter plates. The results showed that herbs have expanded greatly in the tundra, and they have become the dominant species in herbaceous plant expansion areas. There were differences for community composition and appearance among the shrub tundra and the mild expansion, moderate expansion, and severe expansion areas. Except for soil organic matter, soil nutrients were increased in herbaceous plant expansion areas, and the total nitrogen (TN), total phosphorus (TP), available nitrogen (AN), and available phosphorus (AP) were greatest in moderate expansion areas (MOE), while soil organic matter levels were highest in the non-expanded areas (CK). The total soil PLFAs in the three levels of herbaceous plant expansion areas were significantly higher than those in the non-expanded areas, and total soil PLFAs were highest in the moderately expanded area and lowest in the severely expanded area (SEE). Bacteria increased significantly more than fungi and actinomycetes with herbaceous plant expansion. Soil hydrolase activities (β-1,4-glucosidase (βG) activity, β-1, 4-N-acetylglucosaminidase (NAG) activity, and acid phosphatase (aP) activity) were highest in MOE and lowest in the CK treatment. Soil oxidase activities (polyphenol oxidase (PPO) activities and peroxidase (PER) activities) were also highest in MOE, but they were lowest in the SEE treatment. The variations in total soil PLFAs with herbaceous plant expansion were mostly correlated with soil organic matter and available phosphorus concentrations, while soil enzyme activities were mostly correlated with the total soil nitrogen concentration. Our results suggest that herbaceous plant expansion increase the total soil PLFAs and soil enzyme activities and improved soil nutrients. However, soil microorganisms, enzyme activity, and nutrients responded differently to levels of herbaceous plant expansion. The soil conditions in mild and moderate expansion areas are more favorable than those in severe expansion areas.
Soil Microbial Metabolic Quotient in Inner Mongolian Grasslands: Patterns and Influence Factors
CAO Yingqiu, XU Li, ZHANG Zhen, CHEN Zhi, HE Nianpeng
2019, 29(6): 1001-1010. doi: 10.1007/s11769-019-1084-5
Abstract:
Microbial metabolic quotient (MMQ) is the rate of soil microbial respiration per unit of microbial biomass, and represents the capacity of soil microbes to utilize soil organic matter. Understanding the regional variation and determinants of MMQ can help predict the responses of soil respiration rate to global climate change. Accordingly, we measured and analyzed MMQ-related data (e.g., soil basic respiration rate at 20℃ and soil microbial biomass) from 17 grassland sites, which located in meadow steppe, typical steppe, and desert steppe along a 1000-km transect across the Inner Mongolian grasslands, China. Results showed that MMQ varied significantly among the different grassland types (P < 0.05; desert > typical > meadow) and decreased from southwest to northeast (r=-0.81) with increasing latitude (r=-0.50), and with increasing mean annual precipitation (r=-0.69). Precipitation accounted for 56% of the total variation in MMQ, whereas temperature accounted for 26%. MMQ was negatively correlated with precipitation across the Inner Mongolian grasslands. Therefore, climate change, especially in regard to precipitation, may influence soil microbial respiration and soil carbon dynamics through altering MMQ. These results highlighted the importance of spatial patterns in MMQ for accurately evaluating the responses of soil respiration to climate change at regional and global scales.
Prediction of Suitable Habitat for Lycophytes and Ferns in Northeast China: A Case Study on Athyrium brevifrons
LI Yan, CAO Wei, HE Xingyuan, CHEN Wei, XU Sheng
2019, 29(6): 1011-1023. doi: 10.1007/s11769-019-1085-4
Abstract:
Suitable habitat is vital for the survival and restoration of a species. Understanding the suitable habitat range for lycophytes and ferns is prerequisite for effective species resource conservation and recovery efforts. In this study, we took Athyrium brevifrons as an example, predicted its suitable habitat using a Maxent model with 67 occurrence data and nine environmental variables in Northeast China. The area under the curve (AUC) value of independent test data, as well as the comparison with specimen county areal distribution of A. brevifrons exhibited excellent predictive performance. The type of environmental variables showed that precipitation contributed the most to the distribution prediction, followed by temperature and topography. Percentage contribution and permutation importance both indicated that precipitation of driest quarter (Bio17) was the key factor in determining the natural distribution of A. brevifrons, the reason could be proved by the fern gametophyte biology. The analysis of high habitat suitability areas also showed the habitat preference of A. brevifrons:comparatively more precipitation and less fluctuation in the driest quarter. Changbai Mountains, covering almost all the high and medium habitat suitability areas, provide the best ecological conditions for the survival of A. brevifrons, and should be considered as priority areas for protection and restoration of the wild resource. The potential habitat suitability distribution map could provide a reference for the sustainable development and utilisation of A. brevifrons resource, and Maxent modelling could be valuable for conservation management planning for lycophytes and ferns in Northeast China.
Agricultural Land Suitability of Production Space in the Taihang Mountains, China
GENG Shoubao, SHI Peili, ZONG Ning, ZHU Wanrui
2019, 29(6): 1024-1038. doi: 10.1007/s11769-019-1075-6
Abstract:
The contradiction between the shortage of land for agriculture due to rapid expansion of industrialization and urbanization and increasing population pressure is projected to impose great threats to future food security. Agricultural land suitability evaluation is an effective approach to improve the utilization of land resources for crop production and thus enhance the capacity of food provision. In this study, we evaluated the land suitability for agriculture of the production space in the Taihang Mountains by three steps:establishing indicator system, determining weights for indicators, and constructing a fuzzy matter-element model to assess the grades of suitability. Results showed that the land suitability had a significant linear correlation with potential crop yields, indicating our evaluation was effective to predict crop production. The spatial pattern of land suitability for crop production demonstrated that land with higher suitability was generally located in piedmont plains and basins, while land with lower suitability was mostly situated in mountainous areas. The area of highly, moderately, marginally suitable and unsuitable land for agriculture was 32.13%, 28.58%, 37.49% and 1.80% of the production space, respectively. However, the correlation degree analysis indicated that the requirements of these four suitability grades were currently not satisfied but could be potentially fulfilled. In terms of indicator weights, soil properties were much more important than topography and location conditions to influence the grades of suitability. Among all indicators, slope, soil organic matter, soil texture and soil depth were the most influential factors, so slope farming prevention and organic fertilization were most likely to improve land suitability for agriculture. Compared the outputs of our land suitability evaluation model with the distribution of the existing croplands, we found that about 66.52% of marginally suitable and 54.55% of unsuitable land for agriculture were currently used for croplands. Therefore, de-farming policy should be implemented in areas of these two suitability grades. In contrast, cropland expansion was encouraged in the land that was highly or moderately suitable for agriculture. Our evaluation of agricultural land suitability is beneficial for future land use planning and decision-making in the Taihang Mountains.
Key Factors Affecting Farmers' Choice of Corn Reduction under the China's New Agriculture Policy in the ‘Liandaowan’ Areas, Northeast China
LIU Shiwei, ZHANG Pingyu, LIU Wenxin, HE Xiuli
2019, 29(6): 1039-1051. doi: 10.1007/s11769-019-1078-3
Abstract:
Farmers are the main land managers, and their production decisions crucially affect crop outputs and farmland preservation. Understanding the motivations and factors underlying farmers' decision making is a fundamental to implementation polices of government. This study analyzed factors that influence farmers' choice of corn reduction under the China's new agriculture policy in the ‘Liandaowan’ areas of Northeast China. This study collected data from 106 randomly selected households in 34 villages in ‘Liandaowan’ areas of Northeast China using a semi-structured questionnaire. Results showed that the Chinese corn structural adjustment plan confronted with many constraints, and most of farmers insist on planting corn. Drought and low accumulated temperature, no suitable substitution crop, farmers' preferences, farmers' education and age, relatively high comparative benefit of corn, the availability of machinery and technical assistance, subsidies and low family incomes all influence farmers' choice of corn substitution. Based on our experimental results, we derived important policy implications for promoting corn structural adjustment incorporate increase crop diversity, promote soybean and corn rotation, provide adequate agricultural extension services, and increase the corn substitution subsidies and improve farmers' income.
Spatio-temporal Evolution of Marine Fishery Industry Ecosystem Vulnerability in the Bohai Rim Region
LI Bo, JIN Xiaoming
2019, 29(6): 1052-1064. doi: 10.1007/s11769-019-1076-5
Abstract:
The building of the ocean power strategy and the implementation of the blue agriculture plan urgently need to strengthen the sustainable development of marine fishery. Taking vulnerability as the starting point, this paper constructs the vulnerability index system of marine fishery industry ecosystem from the aspects of sensitivity and response capacity, and combines the entropy method with the Topsis to comprehensively analyze the spatio-temporal evolution characteristics of vulnerability of marine fishery industry ecosystem in the Bohai Rim Region from 2001 to 2015. The results show that:1) In the time dimension, from 2001 to 2015, the vulnerability of the marine fishery industry ecosystem in the Bohai Rim Region shows a fluctuant and degressive trend; 2) In the spatial dimension, the spatial distribution of the marine fishery industry ecosystem vulnerability in the Bohai Rim Region presents the gradient characteristics which shows high vulnerability in the east and low vulnerability in the west. According to the evolution track of the system's vulnerability level, the vulnerability of the marine fishery industry ecosystem is divided into ‘declining’ and ‘stable’ types of evolutionary structures; 3) The development of marine fishery in the Bohai Rim Region needs to be derived from the marine fishery's ecological environment and the industrial development mode and structure, which can improve the marine environment remediation efforts, optimize the marine fishery industry structure, vigorously focus on pelagic fishery, and enhance the introduction of marine fishery's science and technology talents, etc. Then, the marine fishery's development in the Bohai Rim Region will be moving in the green, circular and sustainable direction.
Analysis of Metro Station Ridership Considering Spatial Heterogeneity
GAN Zuoxian, FENG Tao, YANG Min, Harry TIMMERMANS, LUO Jinyu
2019, 29(6): 1065-1077. doi: 10.1007/s11769-019-1065-8
Abstract:
This study aims to explore the role of spatial heterogeneity in ridership analysis and examine the relationship between built environment, station attributes and urban rapid transit ridership at the station level. Although spatial heterogeneity has been widely acknowledged in spatial data analysis, it has been rarely considered in travel behavior studies. Four models (three global models-ordinary least squares (OLS), spatial lag model (SLM), spatial error model (SEM) and one local model-geographically weighted regression (GWR) model) are estimated separately to explore the relationship between various independent variables and station ridership, and identify the influence of spatial heterogeneity. Using the data of built environment and station characteristics, the results of diagnostic identify evidence the existence of spatial heterogeneity in station ridership for the metro network in Nanjing, China. Results of comparing the various goodness-of-fit indicators show that, the GWR model yields the best fit of the data, performance followed by the SEM, SLM and OLS model. The results also demonstrate that population, number of lines, number of feeder buses, number of exits, road density and proportion residential area have a significant impact on station ridership. Moreover, the study pays special attention to the spatial variation in the coefficients of the independent variables and their statistical significance. It underlines the importance of taking spatial heterogeneity into account in the station ridership analysis and the decision-making in urban planning.
Spatial Pattern and Influencing Factor Analysis of Attended Collection and Delivery Points in Changsha City, China
XUE Shuyan, LI Gang, YANG Lan, LIU Ling, NIE Qifan, Muhammad Sajid MEHMOOD
2019, 29(6): 1078-1094. doi: 10.1007/s11769-019-1086-3
Abstract:
Attended collection and delivery points are vital components of ‘last-mile logistics’. Based on point of interest (POI) data for Cainiao Stations and China Post stations in Changsha City, China, this paper provides a detailed exploration of the basic features, spatial distribution, and location influencing factors of attended collection and delivery points. Specifically, analyses of the types, service objects and location distributions of the attended collection and delivery points alongside a discussion of their spatial pattern and influencing factors provides a reference for their general geographic layout and characteristics. The findings of this study indicate that:1) The main mode of operation of attended collection and delivery points is franchises, with other modes of operation rely on supermarkets and other individual shop types. 2) The main service targets of attended collection and delivery points are communities, schools, and businesses, followed by townships, enterprises, scenic spots, and administrative units. 3) Approximately 77.44% of the attended collection and delivery points are located near the exits of service areas; others are situated in the centre of the service areas. For the Cainiao Stations, 80% are located within 125 m of the exit; for the China Post stations, 80% are located within 175 m of the exit. 4) The spatial distribution of the attended collection and delivery points in Changsha is unbalanced, with ‘more centre and fewer surrounding’. The centre is an ‘inverted triangle’, and the edge is an ‘orphan’, showing a northwest-southeast orientation and symmetrical along the axis. The layout of the attended collection and delivery points forms three core areas, and the number of sites decreases with the distance from the core. 5) The number and distribution of the attended collection and delivery points are strongly consistent with the regional economic development level, population, and roadway system traffic convenience. Most attended collection and delivery points are on residential, scientific and educational, and commercial and financial land.