参数区间估计和样本容量确定在市场调查中的应用

简述了参数区间估计的概念，方法以及样本容量的确定方法，在此基础上，给出市场调查中比率的区间估计，样本容量确定和均值的区间估计实例。     

草原蝗虫密度的抽样技术研究

在蝗虫密度为０．０５～８．５０头／ｍ２的不同类型草地，以投环方式统计不同大小（０．０２、０．０５、０．１０、０．２０、０．３５ｍ２）的铁环击中或套入蝗虫数，计算调查地蝗虫平均数，以笼罩法作为“真值”对照，对不同大小铁环调查数进行统计检验。结果表明，在调查密度范围内，以０．０５、０．１０、０．２０ｍ２铁环的调查数较接近“真值”，其精确性随蝗虫密度的高低略有变动。根据草地蝗虫为Ｐｏｉｓｓｏｎ分布的特点，采用Ｐｏｉｓｓｏｎ置信域和二项式抽样法，建立以０．１０ｍ２环中蝗虫的出现率估测平均密度和反估计的二项式抽样模型，并进行统计检验。最后，以Ｐｏｉｓｓｏｎ置信值为概率保证，提出了理论抽样数计算模型。     

A comparison of catchment based salmonid habitat survey techniques in three river systems in Northern Ireland

Three survey techniques, a fully quantitative, multivariate study; a shorter or truncated fully quantitative method and a Geographical Information System (GIS) based, semi-quantitative, survey technique, were developed to assess in-river salmonid habitats on a catchment wide basis. These methods were tested and compared on three river systems in Northern Ireland: the Blackwater, the Bush and the Main. The research indicated that the fully quantitative method generated an accurate habitat database but required a high investment in time and resources to complete. The truncated survey approach often produced an inaccurate habitat database. The semi-quantitative technique generated a more accurate habitat dataset with greater productivity and efficiency for the resources invested in the survey.     

提高设计质量是实施天然林保护工程的基本保证

在天然林保护工程实施过程中，森林调查设计具有重要作用。本文从合理区划、蓄积量调查、采伐强度、更新方式等方面，论述了提高调查设计质量应采取的措施。     

长北气田C1井组GPS施工测量技术研究

本文详细介绍了长北气田C1井组GPS施工控制网和井位测量的技术方案及施测情况,测量成果均满足测量规范要求,为钻井生产提供了可靠的井位数据,对其他油气施工工程有重要的借鉴作用。     

第8届雨水收集利用国际学术会议概况

第８届国际雨水收集利用大会１９９７年４月２１至２５日在伊朗德黑兰召开，有４０多个国家的１３００余名代表参加，提交论２７４篇，出版论集４卷。会议内容丰富，有大会交流和１０个专题报告，会后代表分６条路线对伊朗考察。我国到会１９人，提交论１２篇，考察西北冷凉半干旱区，下届国际雨水收集利用大会定于１９９９年在巴西召开。     

基于全球导航卫星系统的智能化精细平地系统优化与试验

农田土地精细平整是中国现代地面精细灌溉的重要基础,能提高农田灌溉均匀度,改良土壤水盐分布,控制杂草,达到节水增产的效果。应用GNSS(global navigation satellite system,全球导航卫星系统)技术进行土地精细平整具有不受天气影响、测量速度快、工作效率高等优点,具有广泛应用前景。该文结合中国土地平整的实际情况和前期的研究成果,开发了适合国内应用的GNSS控制平地系统,降低了研发的设备成本,优化完善了平地系统的功能。为减少分立设备数量,提高系统集成度,设计了集成控制终端,集成GNSS接收模块、差分电台模块、核心处理平台和阀控制模块,并设计了集成控制终端的外壳,通过可旋转调整支架固定在拖拉机驾驶室内,具有良好的防尘、降温和牢固等优点;为完善地形测量功能,增加了测量轨迹的实时显示,以及农田面积等地势信息的计算,便于指导后续平整作业;优化了基准设计,建立了坡面平整的数学模型,实现了任意坡度坡面平整。优化后的系统主要由集成控制终端、自主差分GNSS接收设备、液压系统以及平地铲运设备几部分构成;以Visual Studio2008为系统软件开发环境,GNSS精细平整集成软件能够实现农田地势测量、基准设计及平整作业等功能。该智能平地系统在中国农业大学上庄试验站进行了长时间平整实验,平面平整后最大高程差从20.9降到10.5 cm,高程标准差从10.6降到5.5 cm,平地误差小于5 cm的测点累积百分比从77%上升到90%左右,平整效果良好。坡面平整的坡度从0.239%降到0.120%,符合设计要求。结果表明,系统工作稳定可靠,作业精度满足土地精细平整要求,适用于在中国推广应用。     

Testing the utility of abiotic surrogates for marine habitat mapping at scales relevant to management

Habitat mapping at the scale at which marine protected areas are designed and managed is essential for assessment of, and design for, representation. Most habitat mapping studies rely solely or in part on abiotic surrogates for patterns of biodiversity. The utility of abiotic variables in predicting biological distributions at the local scale (10 s of km) was tested in a remote video survey of macrobenthos in Moreton Bay, Australia. Habitat classifications of the same set of 41 sites based on 6 abiotic variables and abundances of 89 taxa and bioturbation indicators were compared using correlation, regression and ordination analyses. The concepts of false homogeneity (abiotically similar but biologically distinct) and false heterogeneity (abiotically distinct but biologically similar) were defined to describe types of errors associated with using abiotic surrogates to construct habitat maps, and quantified using two separate methods. Overall, the best prediction by abiotic surrogates explained less than 30% of the pattern of biological similarity. Errors of false homogeneity were between 20% and 62%, depending on the methods of estimation. Predictive capability of abiotic surrogates at the taxon level was poor, with only 6% of taxon/surrogate correlations significant. Abiotic variables did not discriminate sufficiently between different soft bottom communities to be a reliable basis for mapping. These results have implications for the widespread use of abiotic surrogates in marine habitat mapping to plan for, or assess, representation in marine protected areas. Little confidence can be placed in marine habitat classifications based solely or largely on abiotic surrogates without calibration by rigorous biological surveys at the appropriate scale. Therefore, it is questionable whether marine protected areas designed on this basis can have measurable benefits for conservation.     

Sampling saproxylic beetles: lessons from a 10-year monitoring study

We sampled saproxylic beetles using trunk window traps in two birch-dominated forests in Finland during 1990-1999. The sampling scheme, 10 traps attached to living fruiting bodies of Fomes fomentarius growing on dead birches, remained unchanged in both forests throughout the study period. Beetles belonging to 32 selected families were identified every year, whereas all species were identified during the last 4 years. Total number of identified individuals was 40,294 and number of species 583, of which 258 were saproxylic (dependent on dead wood). Species richness of rare and threatened saproxylic beetles in the samples varied a lot between the years and did not fluctuate synchronously between the forests. Variation between years was smaller when all saproxylic species were pooled together and some abundant species fluctuated synchronously in the two forests. Similarity indices and DCA-ordination did not generally suggest decreasing similarity between samples with increasing temporal isolation. Incidence-based similarities of common saproxylic species within and between forests and years were high (means 0.7-0.8), whereas those of rare saproxylics were roughly 50% smaller and much more variable. More than 75% of the common saproxylic species found during the entire 10-year period were detected already after 3 years of sampling but accumulation of rare and threatened species was much slower. Our results suggest that: (1) occurrence of rare and threatened species in samples is much less predictable than that of common species and, e.g. reserve selection based on rarities should be made cautiously; (2) estimation of total number of threatened species in a forest is very difficult, because such species accumulate slowly in the samples; (3) samples from different years can be comparable in certain cases.     

利用人工神经网络以及相关地形属性绘制数字土壤地图

Detailed soil surveys involve costly and time-consuming work and require expert knowledge. Since soil surveys provide information to meet a wide range of needs, new methods are necessary to map soils quickly and accurately. In this study, multilayer perceptron artificial neural networks (ANNs) were developed to map soil units using digital elevation model (DEM) attributes. Several optimal ANNs were produced based on a number of input data and hidden units. The approach used test and validation areas to calculate the accuracy of interpolated and extrapolated data. The results showed that the system and level of soil classification employed had a direct effect on the accuracy of the results. At the lowest level, smaller errors were observed with the World Reference Base (WRB) classification criteria than the Soil Taxonomy (ST) system, but more soil classes could be predicted when using ST (7 soils in the case of ST vs. 5 with WRB). Training errors were below 11% for all the ANN models applied, while the test error (interpolation error) and validation error (extrapolation error) were as high as 50% and 70%, respectively. As expected, soil prediction using a higher level of classification presented a better overall level of accuracy. To obtain better predictions, in addition to DEM attributes, data related to landforms and/or lithology as soil-forming factors, should be used as ANN input data.