源于大气的氟在水稻不同器官的分布及对糙米含氟量的影响

用开顶式熏气罩熏气的方法,研究了气源氟在水稻不同器官的分布及对糙米含氟量的影响。结果表明:气源氟主要分布于水稻叶片中,根含氟量不受气源氟的影响;籽粒含氟量取决于籽粒器官形成后空气氟浓度,与籽粒器官形成前的空气氟浓度无关;糙米氟含量与水稻抽穗齐穗后所暴露的氟剂量间呈极显著线性相关关系。     

Obtaining species: sample size considerations

Suppose fish are to be sampled from a stream. A fisheries biologist might ask one of the following three questions: ‘How many fish do I need to catch in order to see all of the species?’, ‘How many fish do I need to catch in order to see all species whose relative frequency is more than 5%?’, or ‘How many fish do I need to catch in order to see a member from each of the species A, B, and C?’. This paper offers a practical solution to such questions by setting a target sample size designed to achieve desired results with known probability. We present three sample size methods, one we call ‘exact’ and the others approximate. Each method is derived under assumed multinomial sampling, and requires (at least approximate) independence of draws and (usually) a large population. The minimum information needed to compute one of the approximate methods is the estimated relative frequency of the rarest species of interest. Total number of species is not needed. Choice of a sample size method depends largely on available computer resources. One approximation (called the ‘Monte Carlo approximation’) gets within ±6 units of exact sample size, but usually requires 20–30 minutes of computer time to compute. The second approximation (called the ‘ratio approximation’) can be computed manually and has relative error under 5% when all species are desired, but can be as much as 50% or more too high when exact sample size is small. Statistically, this problem is an application of the ‘sequential occupancy problem’. Three examples are given which illustrate the calculations so that a reader not interested in technical details can apply our results.     

多效唑在鱼体内的分布,积累与类脂质含量相关性研究

实验水系统中，植物生长调节剂多效唑在鲤科类金鱼体内分布、积累的研究结果表明，＾３Ｈ－ＭＥＴ主要积累在鱼体消化系统；各器官／组织的积累量依次为：肠＞肝＞鳃＞皮＞肉＞骨；多效唑效生物积累因子（ＢＣＦ）和鱼体类脂质含量之间有较高的正相关性。     

沈阳市烟囱分布对大气污染的影响

本文介绍采用航空遥感技术和实地调查研究相结合的方法,分析了沈阳市烟囱数量、高度、密度以及高、中、低架烟囱的分布状况和特点,同时与大气污染监测结果对照分析了沈阳市煤烟型大气污染的规律及特点,研究了沈阳市烟囱分布对大气污染的影响。最后,提出了沈阳市燃煤污染的防治途径。     

厌氧发酵过程pH对微生物多样性和产物分布的影响

采用PCR-DGGE技术,研究了不同pH条件下蔬菜类有机垃圾厌氧发酵过程中的微生物多样性,探讨了微生物群落结构与发酵产物分布的关系.Shannon指数分析表明,pH=7和pH=8时的微生物多样性较高,随时间变化规律相似,而pH=5时的微生物多样性较低.UPGMA聚类分析和PCA分析结果也表明,pH=7和pH=8时的微生物群落结构相似,pH=5与之显著不同.在不同pH条件下的优势菌属都是乳酸细菌和梭菌。微生物多样性的变化与发酵产物分布具有一定相关性,pH通过影响微生物群落结构的变化最终影响发酵产物的分布.图4表2参27     

Model-based combination of spatial information for stream networks

Evolutionary improvements in Geographic Information Systems (GIS) now routinely allow the management and mapping of spatial-temporal information. In response, the development of statistical models to combine information of different types and spatial support is of vital importance to environmental science. In this paper we develop a hierarchical spatial statistical model for environmental indicators of stream and river systems in the United States Mid-Atlantic Region by combining information from separate monitoring surveys, available contextual information on hydrologic units and remote sensing information. These models are used to estimate the indicators throughout the riverine system based on information from multiple sources and aggregate scales. The analysis is based on information underlying the Landscape Atlas of the mid-Atlantic region produced by the US Environmental Monitoring and Assessment Program (EMAP). We also combine information from two overlapping separate monitoring surveys, the EMAP Stream and River Survey and the Maryland Biological Streams Survey. We present a general framework for comparative distributional analysis based on the concept of a relative spatial distribution. As an application, the spatial model is used to predict spatial distributions and relative spatial distributions for a watershed.     

广东省雾霾天气能见度的时空特征分析Ⅰ:季节变化

雾霾已经成为一种新的气象及环境灾害性现象,分析雾霾天气下低能见度的时空分布特征,对掌握雾霾的发生规律和减灾预报具有重要意义。文章利用1980—2003年广东省沿海地区26个地面气象观测站23年的气象观测资料,分析了广东省雾霾天气下能见度的时空分布特征。分析结果发现,1980—2003年广东地区雾霾天气下能见度的季节变化规律与雾天气时能见度的季节变化规律大体一致,即广东地区低能见度天气主要受雾天气的影响;另一方面,雾、霾天气时能见度的季节变化规律有很大不同,雾天气时能见度观测值在冬、春两季相对较高,最低值出现在3月份,最高值出现在9月份,其年变化表现为峰—谷型、稳定型和不规则波动型三种变化;霾天气时能见度的值在秋、冬两季相对较高,最低值出现在6月份,而且在5、6、7三个月中能见度值都很低;受广东沿海地形特征影响,雾天能见度的空间分布从西到东呈低—高—低—高的波列状分布,而霾天气时能见度的空间分布则没有明显的区域差异。     

沈阳市区大气颗粒物元素组分及其分布

本研究采用美国安德逊五段冲击式采样器进行大气颗粒物采样，用中子活化法进行分析，获得４３种元素质量浓度，并求得各种元素的质量中值直径和几何标准差。     

Secondary metabolism — evolution and function: Products or processes?

Summary The distinguishing characteristics of secondary metabolism and its associated metabolites are outlined. Current theories relating to the function of secondary metabolism in plants and micro-organisms are enumerated and the view that consideration of the processes rather than the products may best explain the origins of secondary metabolism is discussed.     

Resampling from stochastic simulations

To model the uncertainty of an estimate of a global property, the estimation process is repeated on multiple simulated fields, with the same sampling strategy and estimation algorithm. As opposed to conventional bootstrap, this resampling scheme allows for spatially correlated data and the common situation of preferential and biased sampling. The practice of this technique is developed on a large data set where the reference sampling distributions are available. Comparison of the resampled distributions to that reference shows the probability intervals obtained by resampling to be reasonably accurate and conservative, provided the original and actual sample has been corrected for the major biases induced by preferential sampling.Andre G. Journel is a Professor of Petroleum Engineering at Stanford University with a joint appointment in the Department of Geological and Environmental Sciences. He is, also, Director of the Stanford Center for Reservoir Forecasting. Professor Journel has pioneered applications of geostatistical techniques in the mining/petroleum industry and extended his expertise to environmental applications and repository site characterization. Most notably, he developed the concept of non-parametric geostatistics and stochastic imaging with application to modeling uncertainty in reservoir/site characterization. Although the research described in this article has been supported by the United States Environmental Protection Agency under Cooperative Agreement CR819407, it has not been subjected to Agency review and therefore does not necessarily reflect the views of the Agency and no official endorsement should be inferred.