北京东灵山地区植物群落多样性研究 Ⅵ.几种类型植物群落物种数目的估计

采用经验贝叶斯方法、非参数方法（刀切法和自助法）和种－面积曲线外推方法对北京东灵山地区５种类型植物群落的物种数目进行了估计,考察了这些方法的估计行为,从中得出如下结论：（１）只要抽样强度不是很小,经验贝叶斯方法就能给出群落物种数目很好的估计,但与非参数方法相比,其估计的标准差较大;（２）在适当的抽样强度下,非参数方法也能给出群落物种数目很好的估计。如果抽样强度过低,则估计值也偏低;相反,如果抽样强度过高,则估计值也偏高。但在各种抽样强度下,非参数方法估计的标准差都比经验贝叶斯方法的小;（３）种－面积曲线２、３、４、５、６可以给出群落物种数目较好的估计,曲线１的估计值偏高,而曲线７、８、９、１０的估计值则偏低;（４）经过几种方法的综合比较,可以对群落１、２、３、４、５的各层及整个群落的物种数目分别做出如下估计;乔木层１６、１９、２１、１２、１６,灌木层１３、１５、２１、１４、２１,草本层４９、４６、５４、８２、５５,整个群落７９、８０、９６、１０７、９２。     

生物群落多样性的测度方法VI：与多样性测度有关的统计问题

物种多样性测度是（群落的）总体参数,它们常常是未知的,需要通过抽样将它们估计出来,因此,必须了解估计量的抽样性质。本文对与一些多样性测度的均值、方差的估计和假设检验以及大、小样本分布等有关的问题作了综述。可以看出大多数多样性测度的抽样性质还不清楚,有些甚至根本就没有研究过。Ｐｉｅｌｏｕ的合并样方法和刀切法是两个比较通用的方法,用它们可以解决其中的一些问题。但相比之下,刀切法更实用。     

iDNA-Methyl: Identifying DNA methylation sites via pseudo trinucleotide composition

Predominantly occurring on cytosine, DNA methylation is a process by which cells can modify their DNAs to change the expression of gene products. It plays very important roles in life development but also in forming nearly all types of cancer. Therefore, knowledge of DNA methylation sites is significant for both basic research and drug development. Given an uncharacterized DNA sequence containing many cytosine residues, which one can be methylated and which one cannot? With the avalanche of DNA sequences generated during the postgenomic age, it is highly desired to develop computational methods for accurately identifying the methylation sites in DNA. Using the trinucleotide composition, pseudo amino acid components, and a dataset-optimizing technique, we have developed a new predictor called “iDNA-Methyl” that has achieved remarkably higher success rates in identifying the DNA methylation sites than the existing predictors. A user-friendly web-server for the new predictor has been established at http://www.jci-bioinfo.cn/iDNA-Methyl, where users can easily get their desired results. We anticipate that the web-server predictor will become a very useful high-throughput tool for basic research and drug development and that the novel approach and technique can also be used to investigate many other DNA-related problems and genome analysis.     

The influence of temperature and precipitation on spring dispersal of Frankliniella fusca changes as the season progresses

Effects of temperature and precipitation on spring dispersal patterns of Frankliniella fusca (Hinds) (Thysanoptera: Thripidae) caught on yellow sticky traps were estimated in central and eastern North Carolina and eastern Virginia, USA, from 1997 to 2001, and in 2004 and 2007. Data were collected from 44 sites within 14 locations over 7 years, resulting in 30 location‐year data combinations. The following independent variables were examined to determine their relationship to the number of F. fusca caught on sticky traps during specified time intervals: cumulative degree days (base 10.5 °C) from 1 November to the start of each trapping interval (DD), number of days with temperatures favorable for flight during each trapping interval (DTFF), and an index of rainfall during specific intervals prior to and during the trapping interval (RI). Regression models that contained various combinations of these variables explained 62, 79, 74, and 68% of the variation in the number of dispersing F. fusca captured during 1–15 April, 16–30 April, 1–15 May, and 16–31 May, respectively. The results provide strong evidence that the suppressive effects of precipitation on growth of local populations developing during late winter and early spring are subsequently manifest at the landscape scale as reductions in the populations of dispersing adults that may persist for as long as 5–6 weeks after the precipitation occurs.     

Limits to the estimation of species richness: The use of relative abundance distributions

The present study demonstrates the possibility of estimating species numbers of animal or plant communities from samples using relative abundance distributions. We use log‐abundance–species‐rank order plots and derive two new estimators that are based on log‐series and lognormal distributions. At small to moderate sample sizes these estimators appear to be more precise than previous parametric and nonparametric estimators. We test our estimators using samples from 171 published medium‐sized to large animal and plant communities taken from the literature. By this we show that our new estimators define also limits of precision.     

Evaluation of methods for estimating macroinvertebrate species richness using individual stones in tropical streams

1. The most straightforward way to assess diversity in a site is the species count. However, a relatively large sample is needed for a reliable result because of the presence of many rare species in rich assemblages. The use of richness estimation methods is suggested by many authors as a solution for this problem in many cases.
2. We examined the performance of 13 methods for estimating richness of stream macroinvertebrates inhabiting riffles both at local (stream) and regional (catchment) scales. The evaluation was based on (1) the smallest sub-sample size needed to estimate total richness in the sample, (2) constancy of this size, (3) lack of erratic behaviour in curve shape and (4) similarity in curve shape through different data sets. Samples were from three single stream sites (local) and three from several streams within the same catchment basin (regional). All collections were made from protected forest areas in south-east Brazil.
3. All estimation methods were dependent on sub-sample size, producing higher estimates when using larger sub-sample sizes. The Stout and Vandermeer method estimated total richness in the samples with the smallest sub-sample size, but showed some erratic behaviour at small sub-sample sizes, and the estimated curves were not similar among the six samples. The Bootstrap method was the best estimator in relation to constancy of sub-sample sizes, but needed an unacceptably large sub-sample to estimate total richness in the samples. The second order Jackknife method was the second best estimator both for minimum sub-sample size and constancy of this size and we suggest its use in future studies of diversity in tropical streams. Despite the inferior performance of several other methods, some produced acceptable results. Comments are made on the utility of using these estimators for predicting species richness in an area and for comparative purposes in diversity studies.     

speed‐ne: Software to simulate and estimate genetic effective population size (Ne) from linkage disequilibrium observed in single samples

The genetic effective population size, N_e, can be estimated from the average gametic disequilibrium () between pairs of loci, but such estimates require evaluation of assumptions and currently have few methods to estimate confidence intervals. speed‐ne is a suite of matlab computer code functions to estimate from with a graphical user interface and a rich set of outputs that aid in understanding data patterns and comparing multiple estimators. speed‐ne includes functions to either generate or input simulated genotype data to facilitate comparative studies of estimators under various population genetic scenarios. speed‐ne was validated with data simulated under both time‐forward and time‐backward coalescent models of genetic drift. Three classes of estimators were compared with simulated data to examine several general questions: what are the impacts of microsatellite null alleles on , how should missing data be treated, and does disequilibrium contributed by reduced recombination among some loci in a sample impact . Estimators differed greatly in precision in the scenarios examined, and a widely employed estimator exhibited the largest variances among replicate data sets. speed‐ne implements several jackknife approaches to estimate confidence intervals, and simulated data showed that jackknifing over loci and jackknifing over individuals provided ~95% confidence interval coverage for some estimators and should be useful for empirical studies. speed‐ne provides an open‐source extensible tool for estimation of from empirical genotype data and to conduct simulations of both microsatellite and single nucleotide polymorphism (SNP) data types to develop expectations and to compare estimators.     

利用穗粒结构对水稻产量的拟合及预测

文章首先讨论了模型的拟合效果和预测效果的区别,给出了相应的估算方法,同时也讨论了抽样观测值大小对预测精度的影响,并结合实例说明如何从一组模型中选择一预测效果最好的模型．对1992年中国水稻研究所富阳实验基地和绍兴县测产样本点的数据,得到预测效果较好的模型为：产量预测值=理论产量 线性纠正估计,其中线性纠正的形式对两组数据略有不同．