Spatial heterogeneity of vegetation under different grazing intensities in the Northwest Heilongjiang Steppe of China

In northern China, recent degradation of semi-arid grasslands caused by overgrazing is serious. At Green Grassland Village, west of Daqing City in Heilongjiang Province, three grasslands with different degrees of degradation were surveyed. In the survey, a new method of vegetation analysis based on the beta-binomial distribution, was adopted to describe the frequency of occurrence and spatial heterogeneity for each plant species.Chenopodium centrorubrum, Cleistogenes squarrosa and a Carex species were commonly found in the three grasslands. Non-degraded grassland with light grazing was dominated by Arundinella hirta, Filifolium sibiricium, Lespedeza hedysaroides, Potentilla verticillaris, Stipa baicalensis and Thymus serpyllum. These species belong to the erect-type or do not develop large clones under light grazing. These species can be used as indicators of a well-managed grassland in this area. On the other hand, the degraded grassland with heavy grazing was dominated by Artemisia spp. and Euphorbia humifusa var. pilosa. Artemisia spp., E. humifusa var. pilosa, Eragrostis pilosa and Setaria viridis belong to the creeping-type or develop rather large stocks or stolons under heavy utilization. These species increased the spatial heterogeneity in the degraded grassland with heavy grazing.Under degraded conditions, species diversity decreased and spatial heterogeneity of the communities tended to increase.     

大湘西高级别景区时空分布特征及影响因素的空间异质性

旅游景区既是旅游业发展的先决条件和核心载体,也是最主要和最根本的旅游供给。基于大湘西高级别旅游景区数据,引入高级别景区发展差异指数,运用标准差椭圆分析法、核密度估计、全局空间自相关等多种空间统计方法,对2007年、2012年和2016年大湘西高级别旅游景区时空分布特征进行测度,并运用全局回归（OLS）模型和地理加权回归（GWR）模型,分析大湘西高级别景区影响因素的空间异质性。结果表明：大湘西高级别景区空间分布总体走向为东北—西南方向,且整体呈现小幅度逆时针旋转;高级别景区空间分布格局呈现出由“三核心两区县”向“一极多点”再到双核带动的“遍地开花型”空间格局的演化;高级别景区数量的空间正相关性不断减弱,且其在空间上的分布呈现一定的集聚特征;区域经济发展水平、政府政策扶持力度、交通条件、旅游资源因素对大湘西高级别景区空间分布格局影响显著,且不同影响因素呈现出一定的空间异质性。研究结论可为全域旅游背景下深化旅游景区体制机制改革提供科学依据和参考价值。     

城市生活垃圾处理能力提升的驱动因素研究——基于2004—2020年30个省份的实证分析

提升末端生活垃圾处理能力,走出城市“垃圾围城”之困,一直是地方政府关切的核心议题。为探究城市生活垃圾处理能力的影响因素及其时空差异,从“政府能力系统”视角出发,围绕需求驱动、经济驱动、政策驱动、技术驱动四个维度,提出相关研究假设,并运用2004—2020年30个省份的面板数据进行实证检验。研究发现：生活垃圾清运量、人均GDP、地方环保支出、政策文本出台数量、无害化处理厂数量以及市容环卫专用车辆数均对城市生活垃圾处理能力的提升具有促进作用。在时间变化上,2004—2007年为生活垃圾处理能力初创阶段,受到经济、政策与技术驱动因素的显著影响; 2008—2016年为生活处理能力缓慢提升和局部发展阶段,持续受到技术驱动因素的显著作用;2017—2020年为处理能力全面提升阶段,需求、经济与技术因素均呈现出显著促进作用。在区域变化上,经济驱动的影响效应由东部向西部逐渐减弱,需求驱动、政策驱动因素只在东部地区影响显著,技术驱动因素对不同区域的生活垃圾处理能力均具有显著促进作用。最后,研究从源头减量、资金投入、政策倾斜与技术创新等方面,对促进中国城市生活垃圾处理能力的发展提供了相应的政策建议。     

游客信息行为对文化遗产旅游难忘体验的作用路径及调节效果--以平遥古城为例

以平遥古城为例,探究游客信息行为对文化遗产旅游难忘体验的作用路径和异质性的调节效果。结果发现:游客信息行为对文化遗产旅游难忘体验的影响有直接影响和间接影响两条路径;异质性游客在信息对难忘体验的影响上存在显著调节效果;遗产地吸引力通过对游客再访意图的影响完全转化为难忘体验来发挥作用。     

长江经济带城市扩张与经济增长脱钩关系及其空间异质性

论文基于GIS平台及探索性空间数据分析方法（Exploratory Spatial Data Analysis, ESDA）和脱钩模型,以地级行政单元为对象,分析2000—2013年长江经济带建设用地扩张、经济增长的时空差异及脱钩关系。研究表明：1）近15 a来,长江经济带建设用地扩张与经济增长具有明显的阶段性和区域性。热点分析显示,建设用地增长热点区呈扩散效应,冷点区逐渐缩小。而经济增长的冷、热点区演变格局与建设用地并不同步。2）2000—2013年,长江经济带建设用地扩张与经济增长耦合关系经历了“增长负脱钩、弱脱钩”为主—“弱脱钩”为主—“弱脱钩、增长连结”为主的变化过程。分析表明,近15 a来长江经济带建设用地扩张与经济增长脱钩程度整体趋于优化,其中,负脱钩类型的城市数量降低17.76%,而脱钩类型数量上升11.22%。3）脱钩程度的空间异质性分析显示,长江经济带各时期的城市扩张与经济增长脱钩关系具有弱空间集聚性。总体上,长三角城市群较长江中游、成渝及滇、黔城市群的脱钩程度表现更优。脱钩程度变化机制与城市产业结构、用地效率和用地模式等密切相关。加强土地利用规划管控力度、严格用途管制规则,引导城市精明增长,走内涵式新型城镇化道路是改变经济发展对建设用地扩张依赖的重要途径。     

喀斯特坡地土壤稳渗率空间分布变化特征研究

为查明高异质性背景条件下喀斯特坡地土壤稳渗率空间分布变化特征,在6类典型人为活动方式石灰岩坡地针对4类主要生境类型(土面、土石面、石沟、石缝)开展生境空间分布调查和土壤理化性质分析,并利用Guelph入渗仪进行稳渗率实验。通过对比分析各生境土壤性质和土壤稳渗率关系,结合人为作用方式探讨各生境土壤性质和稳渗率空间变化特征及其演化规律。结果表明:1)喀斯特坡地土壤稳渗率普遍高于非喀斯特地区,喀斯特坡地土壤稳渗率受土壤孔隙和岩石裂隙耦合作用影响。2)各生境条件下土壤稳渗率具有高度的空间异质性,呈现"斑块状"空间分布特征。3)坡地人为作用方式变化将改变原有生境的土壤性质,进而导致各生境土壤稳渗率随人为活动进程发生相应变化。人为踩踏作用影响较小的原生林、次生林和乔灌林坡地土面和土石面生境土壤稳渗率普遍高于石沟和石缝生境,但转变为人为踩踏作用强烈的放牧灌草地或火烧人为干扰地后,土面和土石面生境土壤退化严重,土壤容重和粘粒含量增大,稳渗率显著降低。而石沟和石缝生境土壤性质和稳渗率受影响程度明显小于土面和土石面生境,土壤稳渗率仍可维持较高水平。     

滦河流域鱼类群落结构空间异质性与影响因子分析

掌握鱼类群落结构与环境因子的关系是河流鱼类多样性保护与恢复的基础.基于2016年10月对滦河流域58个采样点的调查数据,通过聚类分析法及NMS（非度量多维标度法,non-matric multidimentionalscaling）分析了滦河鱼类群落空间格局特征,并采用典范对应分析（CCA,canonical correspondence analysis）探讨了影响鱼类群落结构的环境因子.调查期间共采集鱼类15科41属49种,鲤科鱼类最多,为23种.研究表明:①聚类分析发现鱼类空间分布可分为3组,第1组集中在滦河干流中下游及支流汇入干流附近河段,第2组集中在冀东部独流入海的河流,第3组集中在滦河干支流的中上游河段.②NMS结果也证明3组在空间分布上差异明显,第2组与第3组之间没有重叠.③物种数、Shannon-Wiener多样性指数、Margalef丰富度指数和Simpson多样性指数在第1组与第3组之间存在显著差异,而Simpson多样性在第2组与第3组之间也存在显著差异.④单因素方差分析（one-way ANOVA）显示,第1组与第2组、第3组相比,水温与两组之间都有显著性差异,第2组与第1组、第3组之间在电导率、TDS（总溶解固体）、栖境复杂性、速度-深度结合、堤岸稳定性和河水水量状况有显著性差异.⑤典范对应分析发现,影响滦河流域的环境因子包括TDS、浊度、pH与水温等4个水体理化参数以及底质与堤岸稳定性2个栖息地质量参数.研究显示,基于对滦河流域鱼类空间异质性和相关环境影响因子的理解,可为该流域鱼类多样性保护及管理对策制订提供方向.      

In-between regional disparities and spatial heterogeneity: a multivariate analysis of territorial divides in Italy

Processes such as economic polarization, social disparities and the asymmetric distribution of natural capital are becoming progressively more interlinked in developed countries and may reflect the uneven decline of the ‘centre-periphery’ model. The assessment of regional disparities and spatial heterogeneity in socioeconomic phenomena is a key issue in regional studies and takes advantage of the use of multi-domain frameworks and decision support systems. We performed an exploratory analysis of 133 indicators assessing seven thematic domains (demography/settlements, labour market, economic structure, quality of life, agriculture/rural development, landscape/water, environment/soil resources) with the aim of investigating regional disparities in Italy in the light of territorial changes driven by urbanization, industrial decentralization, agricultural intensification and land abandonment. The results of our study indicate that latitude, elevation and urban gradients have determined a complex spatial pattern in both socioeconomic and environmental variables in Italy. The proposed approach provides an overall assessment of the intensity of territorial disparities on a regional scale for each thematic domain, and of intra-region spatial heterogeneity for each indicator, representing a decision-making tool for policies targeting a sustainable and spatially balanced development.     

Analysis on sensitivity and landscape ecological spatial structure of site resources

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Impacts of pollution heterogeneity on population exposure in dense urban areas using ultra-fine resolution air quality data

Traditional air quality data have a spatial resolution of 1 km or above, making it challenging to resolve detailed air pollution exposure in complex urban areas. Combining urban morphology, dynamic traffic emission, regional and local meteorology, physicochemical transformations in air quality models using big data fusion technology, an ultra-fine resolution modeling system was developed to provide air quality data down to street level. Based on one-year ultra-fine resolution data, this study investigated the effects of pollution heterogeneity on the individual and population exposure to particulate matter (PM_2.5 and PM₁₀), nitrogen dioxide (NO₂), and ozone (O₃) in Hong Kong, one of the most densely populated and urbanized cities. Sharp fine-scale variabilities in air pollution were revealed within individual city blocks. Using traditional 1 km average to represent individual exposure resulted in a positively skewed deviation of up to 200% for high-end exposure individuals. Citizens were disproportionally affected by air pollution, with annual pollutant concentrations varied by factors of 2 to 5 among 452 District Council Constituency Areas (DCCAs) in Hong Kong, indicating great environmental inequities among the population. Unfavorable city planning resulted in a positive spatial coincidence between pollution and population, which increased public exposure to air pollutants by as large as 46% among districts in Hong Kong. Our results highlight the importance of ultra-fine pollutant data in quantifying the heterogeneity in pollution exposure in the dense urban area and the critical role of smart urban planning in reducing exposure inequities.