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Principal Coordinates (principal + coordinate)
Terms modified by Principal Coordinates Selected AbstractsSeasonal and substrate preferences of fungi colonizing leaves in streams: traditional versus molecular evidenceENVIRONMENTAL MICROBIOLOGY, Issue 2 2005Liliya G. Nikolcheva Summary Aquatic hyphomycetes are the main fungal decomposers of plant litter in streams. We compared the importance of substrate (three leaf species, wood) and season on fungal colonization. Substrates were exposed for 12 4-week periods. After recovery, mass loss, fungal biomass and release of conidia by aquatic hyphomycetes were measured. Fungal communities were characterized by counting and identifying released conidia and by extracting and amplifying fungal DNA (ITS2), which was subdivided into phylotypes by denaturing gradient gel electrophoresis (DGGE) and terminal-restriction fragment length polymorphism (T-RFLP). Mass loss, fungal biomass and reproduction were positively correlated with stream temperature. Conidial diversity was highest between May and September. Numbers of different phylotypes were more stable. Principal coordinate analyses (PCO) and canonical analyses of principal coordinates (CAP) of presence/absence data (DGGE bands, T-RFLP peaks and conidial species) showed a clear seasonal trend (P, 0.002) but no substrate effect (P, 0.88). Season was also a significant factor when proportional similarities of conidial communities or relative intensities of DGGE bands were evaluated (P, 0.003). Substrate was a significant factor determining DGGE band intensities (P = 0.002), but did not significantly affect conidial communities (P = 0.50). Both traditional and molecular techniques suggest that strict exclusion of fungi by substrate type is rare, and that presence of different species or phylotypes is governed by season. Biomasses of the various taxa (based on DGGE band intensities) were related to substrate type. [source] Towards an integrated computational tool for spatial analysis in macroecology and biogeographyGLOBAL ECOLOGY, Issue 4 2006Thiago Fernando L. V. B. Rangel ABSTRACT Because most macroecological and biodiversity data are spatially autocorrelated, special tools for describing spatial structures and dealing with hypothesis testing are usually required. Unfortunately, most of these methods have not been available in a single statistical package. Consequently, using these tools is still a challenge for most ecologists and biogeographers. In this paper, we present sam (Spatial Analysis in Macroecology), a new, easy-to-use, freeware package for spatial analysis in macroecology and biogeography. Through an intuitive, fully graphical interface, this package allows the user to describe spatial patterns in variables and provides an explicit spatial framework for standard techniques of regression and correlation. Moran's I autocorrelation coefficient can be calculated based on a range of matrices describing spatial relationships, for original variables as well as for residuals of regression models, which can also include filtering components (obtained by standard trend surface analysis or by principal coordinates of neighbour matrices). sam also offers tools for correcting the number of degrees of freedom when calculating the significance of correlation coefficients. Explicit spatial modelling using several forms of autoregression and generalized least-squares models are also available. We believe this new tool will provide researchers with the basic statistical tools to resolve autocorrelation problems and, simultaneously, to explore spatial components in macroecological and biogeographical data. Although the program was designed primarily for the applications in macroecology and biogeography, most of sam's statistical tools will be useful for all kinds of surface pattern spatial analysis. The program is freely available at http://www.ecoevol.ufg.br/sam (permanent URL at http://purl.oclc.org/sam/). [source] Do community-level models describe community variation effectively?JOURNAL OF BIOGEOGRAPHY, Issue 10 2010Andrés Baselga Abstract Aim, The aim of community-level modelling is to improve the performance of species distributional models by taking patterns of co-occurrence among species into account. Here, we test this expectation by examining how well three community-level modelling strategies (,assemble first, predict later', ,predict first, assemble later', and ,assemble and predict together') spatially project the observed composition of species assemblages. Location, Europe. Methods, Variation in the composition of European tree assemblages and its spatial and environmental correlates were examined with cluster analysis and constrained analysis of principal coordinates. Results were used to benchmark spatial projections from three community-based strategies: (1) assemble first, predict later (cluster analysis first, then generalized linear models, GLMs); (2) predict first, assemble later (GLMs first, then cluster analysis); and (3) assemble and predict together (constrained quadratic ordination). Results, None of the community-level modelling strategies was able to accurately model the observed distribution of tree assemblages in Europe. Uncertainty was particularly high in southern Europe, where modelled assemblages were markedly different from observed ones. Assembling first and predicting later led to distribution models with the simultaneous occurrence of several types of assemblages in southern Europe that do not co-occur, and the remaining strategies yielded models with the presence of non-analogue assemblages that presently do not exist and that are much more strongly correlated with environmental gradients than with the real assemblages. Main conclusions, Community-level models were unable to characterize the distribution of European tree assemblages effectively. Models accounting for co-occurrence patterns along environmental gradients did not outperform methods that assume individual responses of species to climate. Unrealistic assemblages were generated because of the models' inability to capture fundamental processes causing patterns of covariation among species. The usefulness of these forms of community-based models thus remains uncertain and further research is required to demonstrate their utility. [source] Genetic and Pathogenic Variation Among Tobacco Black Shank Strains of Phytophthora parasitica var. nicotianae from the Main Tobacco Growing in ChinaJOURNAL OF PHYTOPATHOLOGY, Issue 5 2003X. G. Zhang Abstract Pathogenic and genetic variability among seven populations of Phytophthora parasitica var. nicotianae from individual tobacco fields (Yunnan, Shandong, Henan, Heilongjiang, Shanxi, Fujian and Sichuan provinces) were investigated using pathogenicity and randomly amplified polymorphic DNA (RAPD) analyses; 63 strains were isolated from different fields of seven tobacco growing regions, using tobacco cv. Hongda as a baiting host. Pathogenic variability was evaluated in greenhouse studies using five tobacco cultivars that have different levels of resistance to tobacco black shank; 75 and 73% of the strains were pathogenic on M3 and M4, 29 and 33% on M1 and M2, and 94% were pathogenic on M5, respectively. Disease severity incited by different strains varied significantly on individual tobacco cultivars. The percentage of strains pathogenic on different cultivars varied among locations. Genotypic variation among 63 strains was evaluated by RAPD analysis. Ten primers detected 89 polymorphic bands. Cluster and principal coordinates analysed cluster groups. the minor group contained 26 strains, and major group contained 37 strains. Estimates of genetic diversity based on RAPD analysis ranged from 0.24 to 0.34 within populations to 0.36 among all strains from all populations. Phytophthora parasitica var. nicotianae populations were genotypically and phenotypically variable, but no distinct genotypic differences were identified among populations from the seven locations. [source] | ||||||||||