丛枝菌根真菌侵染Bt玉米及对其生长的影响

以2个不同转化事件的Bt玉米5422Bt1(Bt11)和5422CBCL(Mon810)及其同源常规玉米5422为对象,研究接种摩西球囊霉(Glomus mosseae)对Bt玉米与常规玉米生长的影响.结果表明:3个品系玉米接菌处理的菌根侵染率明显不同,菌根侵染各参数值总体呈现5422Bt1>5422CBCL>5422趋势;接种处理均促进了玉米的生长,其效应随玉米品系和生育期的不同而呈现差异,喇叭口期5422的地上部干重和总干重显著增加,拔节期5422Bt1的叶片数、茎粗以及喇叭口期的叶片数、茎粗、地上部干重、总干重显著高于对照,5422CBCL拔节期的叶片数和喇叭口期地下部干重增加显著;3个玉米品系菌根真菌依赖性与接菌效应为5422Bt1>5422CBCL>5422,2个Bt玉米品系与Glomus mosseae间的兼容性更好,接种处理对Bt玉米的生长促进作用强于常规玉米.     

Non-parametric smoothing of multivariate genetic distances in the analysis of spatial population structure at fine scale

Species dispersal studies provide valuable information in biological research. Restricted dispersal may give rise to a non-random distribution of genotypes in space. Detection of spatial genetic structure may therefore provide valuable insight into dispersal. Spatial structure has been treated via autocorrelation analysis with several univariate statistics for which results could dependent on sampling designs. New geostatistical approaches (variogram-based analysis) have been proposed to overcome this problem. However, modelling parametric variograms could be difficult in practice. We introduce a non-parametric variogram-based method for autocorrelation analysis between DNA samples that have been genotyped by means of multilocus-multiallele molecular markers. The method addresses two important aspects of fine-scale spatial genetic analyses: the identification of a non-random distribution of genotypes in space, and the estimation of the magnitude of any non-random structure. The method uses a plot of the squared Euclidean genetic distances vs. spatial distances between pairs of DNA-samples as empirical variogram. The underlying spatial trend in the plot is fitted by a non-parametric smoothing (LOESS, Local Regression). Finally, the predicted LOESS values are explained by segmented regressions (SR) to obtain classical spatial values such as the extent of autocorrelation. For illustration we use multivariate and single-locus genetic distances calculated from a microsatellite data set for which autocorrelation was previously reported. The LOESS/SR method produced a good fit providing similar value of published autocorrelation for this data. The fit by LOESS/SR was simpler to obtain than the parametric analysis since initial parameter values are not required during the trend estimation process. The LOESS/SR method offers a new alternative for spatial analysis.     

大尺度下褐飞属种群空间结构初步分析

褐飞虱是我国主要的水稻害虫,有着复杂的空间结构,地统计学可用来分析空间相关变量的结构和插植模拟空间相关变量的分布,运用地统计学中的变差函数和克立格插值法对广东省褐飞虱种群3个主要世代在早稻田间的空间结构进行分析和模拟的结果表明,大尺度的褐飞虱田间种群的空间分布为聚集型,不同世代群在田间的具体分布情况,广东西部地区第一世代褐飞虱的发生密度均高于东部地区。     

Spatial interpolation of N concentrations and δ15N values in the moss Hypnum cupressiforme collected in the forests of Slovenia

Mosses were collected from 103 locations and analyzed for N concentration and δ¹⁵N values. At each location, the samples were collected from two types of site: under the tree canopies and in the adjacent forest openings. A spatial correlation was detected, and ordinary kriging could be applied only to the N in the mosses that were collected in the openings. In contrast, a spatial correlation was not detected for N in the mosses that were collected under the canopies or for the δ¹⁵N of the mosses at either type of site. For those, the spatial interpolation was calculated as the sum of the regression predictions and the inverse distance weighted interpolation of residuals. The maps for the N at both site types (canopy/open) identified similar areas with increased N concentrations. The sole exception was the mosses collected under the canopy, for which some local emitters of NO_x were also identified.     

大尺度下褐飞虱种群空间结构初步分析

褐飞虱是我国主要的水稻害虫,有着复杂的空间结构.地统计学可用来分析空间相关变量的结构和插值模拟空间相关变量的分布.运用地统计学中的变差函数和克立格插值法对广东省褐飞虱种群3个主要世代在早稻田间的空间结构进行分析和模拟的结果表明,大尺度的褐飞虱田间种群的空间分布为聚集型,不同世代褐飞虱种群的局部空间结构有差异,聚集的范围分别为400、200和205km;空间分布模拟地图能反映褐飞虱种群在田间的具体分布情况,广东西部地区每一世代褐飞虱的发生密度均高于东部地区.     

普通克立格法在昆虫生态学中的应用

地统计学是以区域化变量为基础,以变差函数为主要工龄,分析空间相关变量结构的统计方法。在对波动较大的实验变差函数进行拟合时,虽无法获得最优拟合,但运用人机对话的拟合方法来灵活选取参数,可以得到较理想的变差函数模型的参数。本文运用加权多项式回归法以及人机对话的方法,得到了较理想的1级与2级球状模型拟合结果,同时利用直线函数对实验变差函数进行了拟合,最后利用普通Kriging法,对待估计点进行各理论模型的最优、线性、无偏内插估计,得出克立格内插权重。将此方法应用于广东省四会市大沙镇富溪乡试验田稻飞观测数据,由待估点周围若干观测点的数据,有效地估计出待估点的昆虫分布密度,并讨论比较了不同理论模型的拟合效果以及估计误差。结果表明,2级球状模型的拟合最好,一级球状模型次之,直线函数的拟合最差,但直线函数计算最为简便。     

Quantifying the colony shape of the Montastraea annularis species complex

The reef coral Montastraea annularis has been used in a wide range of investigations. Recently, it has been recognized as a complex of three species based on field observations of the variation in colony shape. These observations have also been confirmed by molecular methods as well as morphometrics on individual corallites in the colonies. This paper presents a new quantitative method for measuring overall colony shape based on geostatistics. Seventeen colonies collected from San Blas, Panama in 1995 and 1996 were examined using the Polhemus 3SPACE FASTRAK system to construct three-dimensional coordinates of the center of several hundred corallites in each colony. This method measures the larger bumps or “ridges” as well as the smaller bumps or “lumps” of the colonies. Variograms were then calculated for all the specimens and the lag distances and the values of the variogram were used in a multivariate statistical analysis. Overall, this method indicated that M. annularis and Montastaea faveolata overlap in their relative amount of bumpiness in colony shape while Montastraea franksi is distinct from the other two species. This method has implications for both the modern and fossil record of Montastraea as well as other organisms with similar shapes.