中国农业现代化发展水平的空间非均衡及动态演进

研究中国农业现代化发展水平的地区差距以及内部动态分布特征对于制定农业现代化发展的相关政策具有重要意义。本文利用1997-2013年中国31个省、市(自治区)的面板数据,构建了农业现代化发展水平的指标体系,进而采用熵权综合指数法测算出中国农业现代化发展水平的综合指数,同时借助Dagum基尼系数和Markov链估计方法对中国农业现代化发展水平的地区差距及其分布动态进行了实证研究,得到如下结论:1Dagum基尼系数及分解结果表明,中国农业现代化发展水平的总体差距在样本考察期内呈现出先上升、后下降的演变趋势。从三大地区来看,东部地区内差距呈现出上升趋势,而中部和西部地区内差距则呈现出下降趋势。地区间差距是造成中国农业现代化发展水平空间非均衡的首要原因,并且其对总体差距的贡献率呈波动上升趋势;地区内差距对总体差距的贡献率变化较小,而超变密度对总体差距的贡献率呈现出先上升、再下降的演变趋势。2Markov链分析表明,中国农业现代化发展水平状态流动性较低。从整体来看,中国农业现代化发展水平存在较为明显的上升趋势,并且农业现代化发展的低水平省份将逐步减少,总体向中等以上水平发展。针对本文实证结果,由此得到如下政策建议:首先,加大国家对西部地区农业基础设施建设的投入,引导农业科技人才回归;其次,加强区域间农业现代化发展全方位的交流与合作,发挥省区之间的协同效应;最后,因地制宜,充分利用资源禀赋,推动农业现代化发展。     

资源产业空间集聚与区域经济增长:“资源诅咒”效应实证

针对"资源诅咒"研究中自然资源度量指标选取存在的科学性问题,利用资源产业空间集聚代替自然资源丰裕度和资源产业依赖度作为自然资源丰裕程度的解释变量。首先,在Krugman空间基尼系数的基础上,构建适用于测度资源产业空间集聚的计算公式,基于我国30个省(区、市)层面的数据,量化1999—2013年间资源产业的空间集聚程度,分析其排名情况和分布格局。研究显示:我国有15个省(区、市)存在资源产业空间集聚现象,这些地区大多位于长江以北,且均为自然资源富集地区。其次,构建经济增长计量模型,选取存在资源产业空间集聚现象的省(区、市)作为样本空间,并采用多种计量分析和检验方法考察资源产业空间集聚度与区域经济增长之间的直接和间接关系,分析"资源诅咒"的传导机制。研究显示:1在模型整体估计中,资源产业空间集聚的系数符号均为负,且在5%的水平上显著,说明资源产业空间集聚与区域经济增长间的关系呈现负相关,符合"资源诅咒"的基本假设。2在模型分步估计中,人力资本投资、技术创新投入和制造业发展与区域经济增长正相关,符合经典经济增长理论的逻辑关系;物质资本投资与区域经济增长负相关,可能是由于当地经济主体的消费跨期替代弹性较小,导致物质资本投资对经济增长的直接增益效应小于其对社会人力资本积累的负向效应,进而阻碍区域经济增长;政府干涉程度越高越不利于经济增长。根据研究结果,建议应明确市场调节为主、政府调控为辅的导向机制,进一步提升资源产业空间集聚程度,强化行业人员素质与技术水平匹配,逐步提高自然资源生产和利用效率,从而实现加快地区经济转型,有效促进经济可持续发展的全面提升。     

湖北省生态足迹和生态承载力时空动态研究

研究湖北省内部可持续发展的趋势,以2005年、2010年、2013年统计数据为基础,应用生态足迹分析法核算湖北省17个市(州、林区)在三个时间节点的生态足迹与生态承载力,对各地区生态足迹和生态盈亏状况从时间和空间上进行动态研究。研究结果表明:湖北省17个市(州、林区)的总生态足迹和人均生态足迹呈迅速增长趋势,其中中部地区增长最快;2005年生态赤字最为严重的地区集中于以武汉为代表的中东部,2013年生态赤字最为严重的地区集中于中西部,生态赤字空间分布的重心逐渐由东部向西部转移;6种生态生产性土地增长速度由快到慢依次是建筑用地、化石能源、草地、水域、林地和耕地,其中潜江、恩施、天门、仙桃、黄冈等地建筑用地生态足迹增速最快,十堰、鄂州、黄石、荆州、荆门等地则是水域生态足迹增速最快,草地、水域、化石能源用地和耕地的生态足迹增长共同决定各地区人均生态足迹的变化趋势。     

长江中游城市群空间联系研究

基于城市流强度模型和城市间相互作用模型,以长江中游城市群27个地级市为研究对象,分析了城市群内的城市辐射能力及其内在的经济联系。结果表明:(1)长江中游城市群整体集聚和辐射能力较弱,区域内中低级城市流强度的城市占多数;(2)城市群内第二、三产业辐射能力存在较大差异,第二产业呈现出较强的辐射能力,而第三产业辐射能力较弱,并且其空间分布相对较为分散;(3)区域中心城市的核心带动作用总体较弱,辐射范围和辐射强度都有待加强;(4)长江中游城市群内城市间空间联系不够紧密,且联系程度空间差异较大。省际城市之间联系贫乏,城市间尚未形成联系紧密的辐射网络。     

区域大气环境中PM2．5／PM10空间分布研究

提出了一种利用移动监测技术研究区域大气环境中PM2.5／PM10空间分布的方法,并在2004年12月进行了宁波市全市域PM2.5／PM10空间分布的研究。数据显示：相同路径所代表的地区PM2.5和PM10具有很好的相关性,多数路径上PM2.5与PM10数据的相关系数平方在0．95以上,而不同路径上PM2.5与PM10的比值不同。文中给出了宁波市PM2.5／PM10污染的空间分布图,直观地显示出PM2.5／PM10污染的空间分布情况,突出了污染的重点点位和地区。     

四川古镇空间结构特征及区域旅游合作分析

运用空间网络分析方法,对四川省14个国家历史文化名镇的空间分布形态以及空间网络结构的连接性、通达性等进行了分析.结果显示,四川古镇呈集聚分布状态,但空间联系较弱,完善旅游交通网络、塑造古镇整体形象、增强区域合作是提升四川古镇旅游竞争力的有效途径.     

Modeling the Hydrology of Climate Change in California’s Sierra Nevada for Subwatershed Scale Adaptation1

Young, Charles A., Marisa I. Escobar‐Arias, Martha Fernandes, Brian Joyce, Michael Kiparsky, Jeffrey F. Mount, Vishal K. Mehta, David Purkey, Joshua H. Viers, and David Yates, 2009. Modeling the Hydrology of Climate Change in California’s Sierra Nevada for Subwatershed Scale Adaptation. Journal of the American Water Resources Association (JAWRA) 45(6):1409‐1423. Abstract: The rainfall‐runoff model presented in this study represents the hydrology of 15 major watersheds of the Sierra Nevada in California as the backbone of a planning tool for water resources analysis including climate change studies. Our model implementation documents potential changes in hydrologic metrics such as snowpack and the initiation of snowmelt at a finer resolution than previous studies, in accordance with the needs of watershed‐level planning decisions. Calibration was performed with a sequence of steps focusing sequentially on parameters of land cover, snow accumulation and melt, and water capacity and hydraulic conductivity of soil horizons. An assessment of the calibrated streamflows using goodness of fit statistics indicate that the model robustly represents major features of weekly average flows of the historical 1980‐2001 time series. Runs of the model for climate warming scenarios with fixed increases of 2°C, 4°C, and 6°C for the spatial domain were used to analyze changes in snow accumulation and runoff timing. The results indicated a reduction in snowmelt volume that was largest in the 1,750‐2,750 m elevation range. In addition, the runoff center of mass shifted to earlier dates and this shift was non‐uniformly distributed throughout the Sierra Nevada. Because the hydrologic model presented here is nested within a water resources planning system, future research can focus on the management and adaptation of the water resources system in the context of climate change.     

Land Cover Changes as a Result of Environmental Restrictions on Nitrate Leaching in Dairy Farming

Nitrate leaching forms an important environmental problem because it causes pollution of groundwater and surface water, and adds to already problematic eutrophication. This study analyses the impact of reductions in nitrate leaching on land cover decisions of dairy farms, of which the activities make an important contribution to nitrate leaching. As the level of nitrate leaching depends on groundwater depth as well as on the supply of nitrogen, spatial variation in groundwater levels will cause a spatial variation in land cover under restrictions on nitrate leaching. A non-linear partial optimisation model for the economic and ecological aspects of the problem were used to show how land cover and dairy farms' financial balances change when nitrate losses are reduced. The model is spatially explicit, and describes nitrate leakage and yields of maize and grass as a function of groundwater depth, including the effects of various grazing systems. The model analyses the decisions of a risk neutral agent who minimises costs under the following constraints: (i) production, feed requirements and mass balances for fodder; (ii) constraints for nitrate leaching. Economic costs are attributed to increased costs of fodder and processing of manure when nitrate restrictions are tightened. An important result of the study is the variation in compliance costs and land cover for maize and grass production brought about by spatial variation in groundwater depth. While the effects are negligible for some shallow groundwater classes, it is extremely difficult in other classes – if not impossible – to obtain the EU standard of maximum admissible losses of 34 kg N ha^–1 at low costs. The study shows an important reduction in land cover by maize.     

Using Multi-Scale Sampling and Spatial Cross-Correlation to Investigate Patterns of Plant Species Richness

Land managers need better techniques to assess exoticplant invasions. We used the cross-correlationstatistic, I _YZ, to test for the presence ofspatial cross-correlation between pair-wisecombinations of soil characteristics, topographicvariables, plant species richness, and cover ofvascular plants in a 754 ha study site in RockyMountain National Park, Colorado, U.S.A. Using 25 largeplots (1000 m²) in five vegetation types, 8 of 12variables showed significant spatial cross-correlationwith at least one other variable, while 6 of 12variables showed significant spatial auto-correlation. Elevation and slope showed significant spatialcross-correlation with all variables except percentcover of native and exotic species. Percent cover ofnative species had significant spatialcross-correlations with soil variables, but not withexotic species. This was probably because of thepatchy distributions of vegetation types in the studyarea. At a finer resolution, using data from ten1 m² subplots within each of the 1000 m² plots, allvariables showed significant spatial auto- andcross-correlation. Large-plot sampling was moreaffected by topographic factors than speciesdistribution patterns, while with finer resolutionsampling, the opposite was true. However, thestatistically and biologically significant spatialcorrelation of native and exotic species could only bedetected with finer resolution sampling. We foundexotic plant species invading areas with high nativeplant richness and cover, and in fertile soils high innitrogen, silt, and clay. Spatial auto- andcross-correlation statistics, along with theintegration of remotely sensed data and geographicinformation systems, are powerful new tools forevaluating the patterns and distribution of native andexotic plant species in relation to landscape structure.     

Modelling Temperature Trends in New Zealand

If global warming is accelerating, then one might expect temperatures for most stations to be accelerating and perhaps variability to be increasing. In this study, we examine 57 New Zealand temperature time series for evidence of non-linearity and changing variability. These correspond to time series for annual minima, annual means and annual maxima for 19 stations. Estimation is by an extended least-squares method. We find a surprising diversity of behaviour of these series – presumably reflecting their different geographic factors as well as series length. We give evidence of regions where temperatures are decreasing. For series where a linear trend is significant, it is downwards in about one third of the cases. This proportion was higher in the South Island, especially for series of minima. Where a non-linear trend is significant, temperatures are decelerating in about one half of the cases. The ratio of downward to upward trends is highest among annual maxima and South Island minima and smallest in annual means. Where a linear trend in the variability is significant, it is decreasing in 13 cases and increasing in 5 cases, although possibly this is partly due to poorer quality data last century. Where a non-linear trend in the variability is significant, variability is decelerating in about two thirds of the cases. The results are used to project upper and lower return levels of minima, means and maxima for each of the series to the year 2010.