广西土壤有机质空间变异特征及其影响因素研究

基于广西第二次土壤普查的270个土壤剖面资料,结合1∶50万数字化土壤类型图、土地利用类型图和气象监测数据等资料,利用地统计学和逐步回归分析等方法对广西表层土壤有机质空间变异特征及其影响因素进行了探究。结果表明：广西表层土壤有机质平均含量为3.11±2.19%,变异系数为70.72%,空间分布呈北高南低的趋势。广西表层土壤有机质空间分布受到自然和人为因素的共同影响,土壤类型、成土母质、海拔、土地利用、气候和坡度6个环境因子对全区土壤有机质含量变异的综合解释能力为47.9%。其中,土壤类型是最重要的影响因素,能独立解释其变异的36.0%,海拔和成土母质分别能独立解释28.5%和15.8%。气温对广西土壤有机质空间分布的影响比降水量更加显著,从而造成了广西土壤有机质整体呈南低北高的趋势。同时,土壤有机质对气温的敏感性在一定程度上受到降雨量的制约。此外,研究区农业耕作管理等因素对土壤有机质的影响也不容忽视。     

阿根廷滑柔鱼渔场的初步研究

根据2001年12月至2002年4月"辽渔1号"在西南大西洋(57°W—60°W,41°S—47°S)的柔鱼生产调查资料,对作业渔场的渔获量和水温垂直分布特点进行了初步分析,并运用逐步回归法探讨了周产量(t/week)与各水层温度之间的关系。结果表明:(1)周产量在70t以上的作业区域全部在60°02′W—60°40′W,44°59′S—46°04′S范围内(简称南渔场),周产量在70t以下的作业区域绝大多数集中在57°47′W—58°2′W,41°54′S—42°2′S范围内(简称北渔场);(2)南渔场渔获的表层水温在12.2℃~15.1℃,北渔场渔获的表层水温在10.0℃~12.3℃,两渔场在20~70m水体均出现了强度不等的温跃层;(3)整个作业区域,周产量与水温存在线性相关,相关系数R=0.8515,其中南渔场相关系数R=0.9985,北渔场相关系数R=0.9313。     

Two methods of orthogonally stepwise discrimination and their applications

In this paper, we describe two methods of discrimination based on MSE ratio and regression, respectively, and an algorithm of orthogonally stepwise discrimination. The method is not limited by the assumption that the sample covariance matrix is not ill-conditioned or singular, and by any assumption about the distribution of each population as well. So, it has wide range of application to various problems, particularly, to the problem of discrimination with both quantitative and qualitative variables. After variables are selected in the procedure of stepwise discrimination, they need not be rejected. Several examples have been calculated by using the method, and the results are quite satisfying.     

Hydrous pyrolysis of a Type III source: fractionation effects during primary migration in natural and artificially matured samples

A core from the Cambay Shale Formation of the Cambay Basin, containing immature Type III organic matter, was pyrolysed at 300°C for different durations of time to different maturation levels. Fractionation effects were studied employing a three-step extraction technique after removal of the expelled pyrolysate. The extractable organic matter (EOM) obtained on extraction of the whole core is assumed to be that present in open pores, while that obtained on finely crushing the sample is assumed to be that present in closed pores. The EOM obtained from 1 cm chips is termed EOM from semi-open pores. The gross composition of the pyrolysates expelled during pyrolysis is not similar to the oils reservoired in the area, and there is no significant fractionation observed between expelled pyrolysates and unexpelled EOM. Our study indicates movement of fluids between closed, semi-open and open pores. In both systems, there is a higher concentration of EOM in open pores than in semi-open and closed pores, and the fraction of EOM in open pores is much greater in the artificial system than in the natural system. Fractionation effects on n-alkane and isoprenoid hydrocarbon-based parameters were also studied. n-Alkenes are present in semi-open and closed pores of the immature core and in the core after it was pyrolysed to 300°C for 6 and 48 h, but are absent in the open pores. n-Alkenes are present in closed pores in the naturally matured core. Presence of n-alkenes in the pyrolysates expelled during the 6 and 48 h experiments, but their absence in the open pores of the core, indicates that expulsion also occurs through temporary microfractures during laboratory pyrolysis, whereas in the natural system expulsion from closed pores seems to be only via semi-open and open pores.     

Transformation of Residuals to Avoid Artifacts in Geostatistical Modelling with a Trend

Trend modelling is an important part of natural resource characterization. A common approach to account for a variable with a trend is to decompose it into a relatively smoothly varying trend and a more variable residual component. Then, the residuals are stochastically modelled independent of the trend. This decomposition can result in values outside the plausible range of variability, such as grades below zero or ratios that exceed 1.0. We transform the residuals conditional to the trend component to explicitly remove these complex features prior to geostatistical modelling. Back transformation of the modelled residual values allows the complex relations to be reproduced. A petroleum-related application shows the robustness of the proposed transformation. Furthermore, a mining application shows that when this conditional transformation is applied to the original variable, instead of the residual, simulated values are assured to be nonnegative.     

松花湖富营养化现状及其影响因素分析

通过2002年和2003年对东北地区松花湖水体富营养化状况进行调查和采样分析，对大量数据的多元相关分析和多元逐步回归分析、AGP试验和利用综合营养状态指数法进行评价。结果表明：松花湖处在中营养和轻度富营养状态；总磷是限制水体富营养化的主要因子之一。水体中变温层的形成，限制了上、下层湖水的混合，对下层水体中的溶解氧、无机氮和可溶性磷酸盐产生影响，随着变温层的消失，下层内的营养物质转移到湖上层，为藻类的繁殖提供条件。     

利用可见光/近红外反射光谱估算土壤总氮含量的实验研究

利用土壤的室内反射率光谱，探讨土壤氮元素的高光谱机理。利用土壤光谱各吸收带的特征参数与总氮含量进行逐步回归运算，确定与氮元素关系比较密切的几个吸收带。计算出这几个特征吸收带内土壤反射率的变化形式：一阶导数(FDR)、倒数(1/R)、倒数之对数(log(1/R))、波段深度(Depth)，并与总氮含量进行逐步回归分析，得到比较理想的结果：建模样本的Ra^2(修正的判定系数)分别为0．789、0．753、0．736、0．699，验证样本的Ra^2分别为0．759、0．468、0．794、0．725。可见土壤的反射率光谱与氮元素含量之间存在比较明显的相关性，可见光／近红外反射光谱具有快速估算土壤中氮元素含量的潜力。     

Assessing regression‐based statistical approaches for downscaling precipitation over North America

This paper assesses linear regression‐based methods in downscaling daily precipitation from the general circulation model (GCM) scale to a regional climate model (RCM) scale (45‐ and 15‐km grids) and down to a station scale across North America. Traditional downscaling experiments (linking reanalysis/dynamical model predictors to station precipitation) as well as nontraditional experiments such as predicting dynamic model precipitation from larger‐scale dynamic model predictors or downscaling dynamic model precipitation from predictors at the same scale are conducted. The latter experiments were performed to address predictability limit and scale issues. The results showed that the downscaling of daily precipitation occurrence was rarely successful at all scales, although results did constantly improve with the increased resolution of climate models. The explained variances for downscaled precipitation amounts at the station scales were low, and they became progressively better when using predictors from a higher‐resolution climate model, thus showing a clear advantage in using predictors from RCMs driven by reanalysis at its boundaries, instead of directly using reanalysis data. The low percentage of explained variances resulted in considerable underestimation of daily precipitation mean and standard deviation. Although downscaling GCM precipitation from GCM predictors (or RCM precipitation from RCM predictors) cannot really be considered downscaling, as there is no change in scale, the exercise yields interesting information as to the limit in predictive ability at the station scale. This was especially clear at the GCM scale, where the inability of downscaling GCM precipitation from GCM predictors demonstrates that GCM precipitation‐generating processes are largely at the subgrid scale (especially so for convective events), thus indicating that downscaling precipitation at the station scale from GCM scale is unlikely to be successful. Although results became better at the RCM scale, the results indicate that, overall, regression‐based approaches did not perform well in downscaling precipitation over North America. Copyright © 2013 John Wiley & Sons, Ltd.     

网络大数据下的中国现代食甜习惯空间分布特征及其影响因素研究

饮食地理文化作为地域文化中最具地方特色的重要元素,在现代人口大规模流动背景下呈现出全新的多样化局面,而基于传统认知的“南甜北咸”的地域分异已然不能代表中国现代食甜分布的空间特征。因此,本文采用网络爬虫技术,获取我国大陆31个省会城市共计约2000万条美食消费数据,从传统类菜品、主食类菜品、饮料类和甜品类菜品4个方面计算城市食甜度,在ArcGIS、MySQL软件支持下,借助GIS空间分析和数理统计方法探究我国现代食甜习惯的空间分布特征,分析影响食甜分布的因素。研究发现：① 中国食甜在空间分布上存在显著的地域分异特征,聚类分析评价参数R ²高达0.88,现代食甜习惯总体呈现“东高北中,西微内低”的包围式格局;② 从整体抑或局部角度,在1%显著性水平上莫兰指数均为正,中国食甜分布呈现显著的空间正相关关系,形成特色鲜明的3个地理集聚区,即以苏浙沪闽为主的东南沿海高甜集聚区,以渝黔川为主的西南内陆低甜集聚区和以陕宁为主的西北内陆低甜集聚区;③ 构建了中国现代食甜习惯分布影响因素模型,其拟合精度为0.82,分析结果显示降水、湿度、气温等气象要素及地理位置是影响现代我国食甜空间分布的重要因素。     

A new assessment model for evacuation vulnerability in urban areas

In the high-speed urbanization process of China, the urban population has been increasing significantly, leading to a high-density aggregation of population. However, the sharp increase in population density has not produced commensurate improvements in the road networks. On the contrary, the population increase induced a serious evacuation vulnerability, which cities experience during various hazards and catastrophic events. Therefore, research on evacuation vulnerability is important to urban planning. To assess the evacuation vulnerability, the optimal and worst scenarios should be considered because all possible evacuation plans occur between these extremes. However, most previous evacuation vulnerability studies are based on the worst-case scenario, only providing an upper bound of a potential evacuation assessment. To provide a more comprehensive theoretical basis for decision-makers to understand the consequences caused by all possible evacuations, this paper proposes an optimal evacuation vulnerability assessment model that provides the lower bound on potential evacuation difficulties. The model is solved by a stepwise spreading algorithm based on Graph Theory. Subsequently, to evaluate the effectiveness of the model, the study adopts the model to assess the evacuation capability of different road network topologies. A comparison with previous research was performed. The model was demonstrated in an application to the South Luogu Alley of Beijing, China. The significance of this paper is that the combination of our model with previous research may provide a more complete theoretical basis for an evacuation vulnerability assessment.