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51.
Here we report on ecology and biodiversity of fungi in a unique mycological sanctuary in Britain, where data on species composition have been collected since 1994. To complement the biodiversity data by the information on the fungal ecological interactions and their role in the overall ecosystem functioning, soil properties and the composition of forest litter and field layer, bacterial population numbers and fungal biomass (in terms of ergosterol) were measured in 8 plots covered with different vegetations (beech, birch, birch-oak-beech, grass) over a May–Aug. period, and the results were analysed by correlation analysis and stepwise regression modelling together with data on protozoa and nematodes available from parallel research. The results highlighted the complexity of factors influencing temporal dynamics and spatial variability of fungal biomass in soil and forest litter. Most of the registered interactions appeared to be transient, and this should be taken into account while interpreting environmental observations. Interpretation of the specific relationships is given and implications for further research and overall ecosystem functioning are discussed.  相似文献   
52.
Genotype-environment interaction has been analyzed in a winter-wheat breeding network using bi-additive factorial regression models. This family of models generalizes both factorial regression and biadditive (or AMMI) models; it fits especially well when abundant external information is available on genotypes and/or environments. Our approach, focused on environmental characterization, was performed with two kinds of covariates: (1) deviations of yield components measured on four probe genotypes and (2) usual indicators of yield-limiting factors. The first step was based on the analysis of a crop diagnosis on four probe genotypes. Difference of kernel number to a threshold number (DKN) and reduction of thousand-kernel weight from a potential value (RTKW) were used to characterize the grain-number formation and the grain-filling periods, respectively. Grain yield was analyzed according to a biadditive factorial regression model using eight environmental covariates (DKN and RTKW measured on each of four probe genotypes). In the second step, the usual indicators of yield-limiting factors were too numerous for the analysis of grain yield. Thus a selection of a subset of environmental covariates was performed on the analysis of DKN and RTKW for the four probe genotypes. Biadditive factorial regression models involved environmental covariates related to each deviation and included environmental main effect, sum of water deficits, an indicator of nitrogen stress, sum of daily radiation, high temperature, pressure of powdery mildew and lodging. The correlations of each environmental covariate to the synthetic variates helped to discard those poorly involved in interaction (with | correlation | <0.3). The grain yield of 12 genotypes was interpreted with the retained covariates using biadditive factorial regression. The models explained about 75% of the interaction sums of squares. In addition, the biadditive factorial regression biplot gave relevant information about the interaction of the genotypes (interaction pattern and sensitivities to environmental covariates) with respect to the environmental covariates and proved to be interesting for such an approach. Received: 8 March 1999 / Accepted: 29 July 1999  相似文献   
53.
Abstract:  Life history parameters tend to differ between aphidophagous and coccidophagous ladybird beetles. It seems that the nature of prey, in particular the abundance, number and size of the colonies and their spatial distribution, may have been selected for the evolution of the life histories in these two groups of coccinellids, leading the aphidophagous ladybird beetles to develop at a fast pace and the coccidophagous beetles at a slower pace. To study the abundance, number and size of the colonies and the spatial distribution of aphid and coccid species, 100 sampling plots regularly spaced along four parallel transects were surveyed in the summer of 2004. At each sampling plot, species abundance, and the number and size of colonies of aphid and coccid species were recorded. Iwao's patchiness regression was used to assess the spatial distribution of aphids and coccids. From this study, it was found that coccids are much rarer than aphids but formed more colonies. Whereas aphids display a stonger tendency to crowding, aphid colonies are randomly distributed in space while coccid groups are aggregated. So, it seems that the abundance and spatial distribution of prey distribution may be factors selecting for the evolution of different life histories among aphidophagous and coccidophagous ladybird beetles.  相似文献   
54.
Carmel  Yohay  Kadmon  Ronen 《Plant Ecology》1999,145(2):243-254
The dynamics of Mediterranean vegetation over 28 years was studied in the Northern Galilee Mountains, Israel, in order to identify and quantify the major factors affecting it at the landscape scale. Image analysis of historical and current aerial photographs was used to produce high resolution digital vegetation maps (pixel size = 30 cm) for an area of 4 km2 in the Galilee Mountains, northern Israel. GIS tools were used to produce corresponding maps of grazing regime, topographic indices and other relevant environmental factors. The effects of those factors were quantified using a multiple regression analyses. Major changes in the vegetation occurred during the period studied (1964–1992); tree cover increased from 2% in 1964 to 41% in 1992, while herbaceous vegetation cover decreased from 56% in 1964 to 24% in 1992. Grazing, topography and initial vegetation cover were found to significantly affect present vegetation patterns. Both cattle grazing and goat grazing reduced the rate of increase in tree cover, yet even intensive grazing did not halt the process. Grazing affected also the woody-herbaceous vegetation dynamics, reducing the expansion of woody vegetation. Slope, aspect, and the interaction term between these two factors, significantly affected vegetation pattern. Altogether, 56% and 72% of the variability in herbaceous and tree cover, respectively, was explained by the regression models. This study indicates that spatially explicit Mediterranean vegetation dynamics can be predicted with fair accuracy using few biologically important environmental variables.  相似文献   
55.
Covariate-adjusted regression   总被引:1,自引:0,他引:1  
  相似文献   
56.
青藏高原1979-2007年间的积雪变化   总被引:4,自引:0,他引:4  
利用雪深被动微波遥感数据产品,对青藏高原1979—2007年积雪深度、积雪日数的分布变化及其趋势进行了分析。结果表明:青藏高原积雪日数、积雪深度和海拔三者之间在空间上具有显著正相关;青藏高原积雪在1988年发生突变,该年前后积雪分布有显著不同,这与20世纪80年代中后期青藏高原由暖干时期进入暖湿时期有关;将青藏高原按夏季水汽来源不同将其分为南北两部分,发现29年来北部积雪日数变化与全国积雪变化相反呈极显著增加趋势(R2=0.39,P0.01),以1.40 d/a的趋势增加,主要原因是西北部地区冬季积雪日数增加;南部积雪深度与全国积雪变化一致呈极显著减少趋势(R2=0.24,P0.01),以-0.04 cm/a的趋势减少,主要原因是东南部春、夏、秋三季积雪深度减少。  相似文献   
57.
以湘江熬洲断面为例,将该断面水体中总氮浓度及其有关影响因子用三角模糊数来表征.同时,结合己有的模糊线性回归模型成果,构造了带有三角模糊参数的水体中总氮浓度模糊线性回归预测模型.并应用所建模型预测该断面水体中2002-2005年总氮浓度,所得的预测值与已有的实测值之间的相对误差均小于20%,完全满足实际应用对误差的要求,预测合格率为100%,说明这种预测模型在预测河流水体总氮浓度变化中有一定的实用性,为今后开展河流水体中污染物浓度预测提供了新途径.  相似文献   
58.
Genomic selection (GS) has been implemented in animal and plant species, and is regarded as a useful tool for accelerating genetic gains. Varying levels of genomic prediction accuracy have been obtained in plants, depending on the prediction problem assessed and on several other factors, such as trait heritability, the relationship between the individuals to be predicted and those used to train the models for prediction, number of markers, sample size and genotype × environment interaction (GE). The main objective of this article is to describe the results of genomic prediction in International Maize and Wheat Improvement Center''s (CIMMYT''s) maize and wheat breeding programs, from the initial assessment of the predictive ability of different models using pedigree and marker information to the present, when methods for implementing GS in practical global maize and wheat breeding programs are being studied and investigated. Results show that pedigree (population structure) accounts for a sizeable proportion of the prediction accuracy when a global population is the prediction problem to be assessed. However, when the prediction uses unrelated populations to train the prediction equations, prediction accuracy becomes negligible. When genomic prediction includes modeling GE, an increase in prediction accuracy can be achieved by borrowing information from correlated environments. Several questions on how to incorporate GS into CIMMYT''s maize and wheat programs remain unanswered and subject to further investigation, for example, prediction within and between related bi-parental crosses. Further research on the quantification of breeding value components for GS in plant breeding populations is required.  相似文献   
59.
Micro array data provides information of expression levels of thousands of genes in a cell in a single experiment. Numerous efforts have been made to use gene expression profiles to improve precision of tumor classification. In our present study we have used the benchmark colon cancer data set for analysis. Feature selection is done using t‐statistic. Comparative study of class prediction accuracy of 3 different classifiers viz., support vector machine (SVM), neural nets and logistic regression was performed using the top 10 genes ranked by the t‐statistic. SVM turned out to be the best classifier for this dataset based on area under the receiver operating characteristic curve (AUC) and total accuracy. Logistic Regression ranks as the next best classifier followed by Multi Layer Perceptron (MLP). The top 10 genes selected by us for classification are all well documented for their variable expression in colon cancer. We conclude that SVM together with t-statistic based feature selection is an efficient and viable alternative to popular techniques.  相似文献   
60.
Paul Little  Li Hsu  Wei Sun 《Biometrics》2023,79(3):2705-2718
Somatic mutations in cancer patients are inherently sparse and potentially high dimensional. Cancer patients may share the same set of deregulated biological processes perturbed by different sets of somatically mutated genes. Therefore, when assessing the associations between somatic mutations and clinical outcomes, gene-by-gene analysis is often under-powered because it does not capture the complex disease mechanisms shared across cancer patients. Rather than testing genes one by one, an intuitive approach is to aggregate somatic mutation data of multiple genes to assess their joint association with clinical outcomes. The challenge is how to aggregate such information. Building on the optimal transport method, we propose a principled approach to estimate the similarity of somatic mutation profiles of multiple genes between tumor samples, while accounting for gene–gene similarities defined by gene annotations or empirical mutational patterns. Using such similarities, we can assess the associations between somatic mutations and clinical outcomes by kernel regression. We have applied our method to analyze somatic mutation data of 17 cancer types and identified at least five cancer types, where somatic mutations are associated with overall survival, progression-free interval, or cytolytic activity.  相似文献   
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