Optimum Sample Size to Detect Perturbation Effects: The Importance of Statistical Power Analysis – A Critique

Abstract. The current article describes statistical power analysis as an efficient strategy for the estimation of the optimum sample size. The principle aim is constructively to criticise and enrich the results presented by Mouillot et al. (1999) , who estimate the optimum sample size for evaluating possible perturbations. The authors did not make any reference to statistical power analysis, even though their objective clearly went beyond a simple stock evaluation to assess management strategies in a particular marine ecosystem. Surprisingly, they proposed (a priori) an ANOVA design to test a hypothesis considering both space and temporal scales. However, the authors did not cover important topics related with power analysis and the precautionary principle, both used into environment impact assessment programmes for marine ecosystems. Based on their results and on statistical power analysis, it is demonstrated that the variability (dispersion statistics), a key factor they used to estimate the sample size, is less relevant than the magnitude of perturbation (effect size). Therefore, a greater effort must be devoted to estimate the effect size of a particular phenomenon rather than a desired variability.     

Heavy metals in marine sediments of Taranto Gulf (Ionian Sea, Southern Italy)

Al, Cr, Cu, Fe, Hg, Mn, Ni, Pb, Ti and Zn concentrations have been determined in surface sediment samples collected in the Taranto Gulf (Ionian Sea, Southern Italy) in order to evaluate their levels and spatial distribution in this important area of the Mediterranean Sea. For various metals, the geoaccumulation index has been calculated as a criterion to assess if their concentrations represent contamination levels or can be considered as background levels. The results show that metals concentrations in sediments can be considered near the background levels found in the Mediterranean Sea.Analytical results have been elaborated by using a Geographical Information System (GIS) software to show metals accumulation areas. Using multivariate statistical analysis, we evaluate the possibility to distinguish the sampling stations, in relation to their geographical position. Results have showed metals distribution in the Taranto Gulf is principally influenced by industrial and urban wastes, located mostly in the northern coastal area of the Ionian Sea. Rivers in the Basilicata region and prevailing anticlockwise marine currents are further factors influencing metal accumulation in sediments.     

基于GIS空间统计分析的广电收视率评估研究——以北京市广电收视覆盖分析系统为例

本文将GIS空间信息统计分析手段应用于广播电视收视率的评估,以层次分析法为基础进行改进,采用抽样调查的方法确定权重,提出较为合理的基于空间信息统计方法的广电人口覆盖分布模型并加以软件实现。以北京市为研究区域,经导入多个版本人口数据实验,发现这种评估方式较好地修正了传统的仅仅按照面积评估覆盖率的评估模型,对于提高广电行业的信息化管理水平具有一定意义。     

基于GIS的区域经济统计分析系统的设计与实现

随着经济的发展,区域间经济相互作用和影响的关系越来越密切,忽略空间相互作用的传统区域经济分析手段和方法开始显现出一些明显的不足。而GIS在处理和分析区域地理数据上具有强大的空间分析能力,为此我们引入GIS工具对区域经济进行分析,相较于传统的分析手法有了很大改善。本文以江西省区域经济数据为例,设计了一个基于GIS的区域经济统计分析系统,并利用Arcob-jects二次开发控件结合VB可视化编程语言,实现了大部分区域经济统计分析功能,最后并将结果进行网络发布。研究结果表明将GIS引入到区域经济统计分析中,更能正确、有效的揭示区域经济发展在空间上的联系,为区域经济研究决策提供服务。     

江西省地质灾害-气象预警预报系统研究

论文采用了降雨特征（用降雨诱发指数表征）与地质环境条件（以地质灾害敏感性指数表征）进行叠加、分析,确定预警预报等级,建立地质灾害-预警预报模型的方法;提出了预警产品制作与发布、多普勒雷达跟踪、应急指导、反馈信息收集、灾情调查的地质灾害气象预警预报工作程序。对近几年江西省地质灾害-预警预报效果分析,总结了地质灾害-预警预报成功与失败的经验教训,提出今后的工作设想与建议。应用基于GIS的地质灾害预警预报系统已在近几年的地质灾害-气象预警预报中不断完善,预警预报精度得到提高,防灾减灾效果明显,对保护人民生命财产安全发挥了重要作用。     

TOWARD ESTABLISHING THE CONCEPT OF PHYSICAL URBAN AREA IN CHINA

I.IntroduchollWiulegeOgraphystudiestheterritoria1systemsabouttherelationsbforeenhumanbeingSandthenature[I4],urbanmpaphyfocusesspecificallyonthespatialoopltizationandprocessofurbanterritory,anditsinteraCtionwiti1Otherterritorialsystems.Usually,wedoresearch…     

Analysis of the effect of geology, soil properties, and land use on groundwater quality using multivariate statistical and GIS methods

The regional survey of groundwater used as a small water supply system was performed to know the effect of geology, soil properties and land use on groundwater quality at Nonsan City, Korea. A total of 126 groundwater samples were collected and analyzed at the study area. The multivariate statistical methods, principal components analysis and discriminant analysis, and GIS technique were used for the quantitative interpretation of groundwater quality. The study area is mainly composed of Precambrian gneiss, Jurassic granite, and Cretaceous volcanics, and metasedimentary rocks of the Ogcheon zone. The land use was grouped as paddy, upland, grassland, resident, point source, industrial area, and water system. The soil properties were classified as 4 major groups, Entisols, Alfisols, Inceptisols, and Ultisols, by the degree of development, and reclassified as 11 subgroups. The modified and simplified geologic map, soil map, and land use map were made by using ARCGIS soft-ware. The area of geology, soil property, and land use affecting the groundwater quality for each well were also calculated by ARCGIS soft-ware to acquire the quantitative parameters for multivariate statistical analysis. The monitoring results of groundwater in the study area showed that 13%-21% of the groundwater samples exceeded the portable water guideline and the main causes were turbidity, bacteria, arsenic and nitrate-N. The spatial distribution of each component showed the close relationship between groundwater quality and geology reflecting the topography, land use.     

Spherical Slepian functions and the polar gap in geodesy

The estimation of potential fields such as the gravitational or magnetic potential at the surface of a spherical planet from noisy observations taken at an altitude over an incomplete portion of the globe is a classic example of an ill-posed inverse problem. We show that this potential-field estimation problem has deep-seated connections to Slepian's spatiospectral localization problem which seeks bandlimited spherical functions whose energy is optimally concentrated in some closed portion of the unit sphere. This allows us to formulate an alternative solution to the traditional damped least-squares spherical harmonic approach in geodesy, whereby the source field is now expanded in a truncated Slepian function basis set. We discuss the relative performance of both methods with regard to standard statistical measures such as bias, variance and mean squared error, and pay special attention to the algorithmic efficiency of computing the Slepian functions on the region complementary to the axisymmetric polar gap characteristic of satellite surveys. The ease, speed, and accuracy of our method make the use of spherical Slepian functions in earth and planetary geodesy practical.     

内蒙乌拉山金矿床钾长石的矿物化学及有序度的分析

采用电子探针显微分析(EMPA)和粉末X射线衍射(XRD)分析了采自乌拉山金矿床含金钾长石石英脉、石英脉以及其他类型岩石中的10 0多个钾长石样品的化学成分和结果状态,并采用R和Q模式聚类分析、Spearman等级相关分析方法对实验数据进行了统计分析。结果表明,含金矿脉、岩浆热液脉和蚀变花岗岩中的钾长石为中等到最大微斜长石,其特征为K2 O含量高,但相对而言,Na2 O、CaO和BaO的含量低。其他岩石类型中的钾长石的化学成分和结果状态变化很大,可以从透长石、正长石到微斜长石,其特征为K2 O的含量相对较低,但Na2 O、CaO和BaO的含量相对较高。含金样品中的钾长石通常更富K2 O ,表明金的成矿作用与富钾的热液流体和碱质交代作用有关。乌拉山金矿床的成矿作用分为两个阶段,主要的含金钾长石石英脉中的钾长石富K2 O ,形成温度为30 7～379℃,平均为35 3℃;第二阶段含金石英脉中的钾长石含K2 O较低,形成温度为2 6 0～318℃,平均为2 81℃。这些结果表明成矿流体与岩浆热液作用有关,流体朝温度降低、K2 O含量降低的方向演化,K2 O含量高的热液流体和2 6 0～380℃的形成温度有利于金的成矿作用。