Application of species richness estimators for the assessment of fungal diversity. 2008

Martin Unterseher, and Martin Schnittler, and Carsten Dormann, and Andreas Sickert
Department of Botany and Plant Systematics, Institute of Botany and Landscape Ecology, Ernst-Moritz-Arndt-University Greifswald, Greifswald, Germany. martin.unterseher@uni-greifswald.de

Species richness and distribution patterns of wood-inhabiting fungi and mycetozoans (slime moulds) were investigated in the canopy of a Central European temperate mixed deciduous forest. Species richness was described with diversity indices and species-accumulation curves. Nonmetrical multidimensional scaling was used to assess fungal species composition on different tree species. Different species richness estimators were used to extrapolate species richness beyond our own data. The reliability of the abundance-based coverage estimator, Chao, Jackknife and other estimators of species richness was evaluated for mycological surveys. While the species-accumulation curve of mycetozoans came close to saturation, that of wood-inhabiting fungi was continuously rising. The Chao 2 richness estimator was considered most appropriate to predict the number of species at the investigation site if sampling were continued. Gray's predictor of species richness should be used if statements of the number of species in larger areas are required. Multivariate analysis revealed the importance of different tree species for the conservation and maintenance of fungal diversity within forests, because each tree species possessed a characteristic fungal community. The described mathematical approaches of estimating species richness possess great potential to address fungal diversity on a regional, national, and global scale.

UI MeSH Term Description Entries
D005658 Fungi A kingdom of eukaryotic, heterotrophic organisms that live parasitically as saprobes, including MUSHROOMS; YEASTS; smuts, molds, etc. They reproduce either sexually or asexually, and have life cycles that range from simple to complex. Filamentous fungi, commonly known as molds, refer to those that grow as multicellular colonies. Fungi, Filamentous,Molds,Filamentous Fungi,Filamentous Fungus,Fungus,Fungus, Filamentous,Mold
D012494 Sampling Studies Studies in which a number of subjects are selected from all subjects in a defined population. Conclusions based on sample results may be attributed only to the population sampled. Probability Sample,Probability Samples,Sample, Probability,Samples, Probability,Sampling Study,Studies, Sampling,Study, Sampling
D013045 Species Specificity The restriction of a characteristic behavior, anatomical structure or physical system, such as immune response; metabolic response, or gene or gene variant to the members of one species. It refers to that property which differentiates one species from another but it is also used for phylogenetic levels higher or lower than the species. Species Specificities,Specificities, Species,Specificity, Species
D014197 Trees Woody, usually tall, perennial higher plants (Angiosperms, Gymnosperms, and some Pterophyta) having usually a main stem and numerous branches. Tree
D014644 Genetic Variation Genotypic differences observed among individuals in a population. Genetic Diversity,Variation, Genetic,Diversity, Genetic,Diversities, Genetic,Genetic Diversities,Genetic Variations,Variations, Genetic
D017753 Ecosystem A functional system which includes the organisms of a natural community together with their environment. (McGraw Hill Dictionary of Scientific and Technical Terms, 4th ed) Ecosystems,Biome,Ecologic System,Ecologic Systems,Ecological System,Habitat,Niche, Ecological,System, Ecological,Systems, Ecological,Biomes,Ecological Niche,Ecological Systems,Habitats,System, Ecologic,Systems, Ecologic
D018709 Statistics, Nonparametric A class of statistical methods applicable to a large set of probability distributions used to test for correlation, location, independence, etc. In most nonparametric statistical tests, the original scores or observations are replaced by another variable containing less information. An important class of nonparametric tests employs the ordinal properties of the data. Another class of tests uses information about whether an observation is above or below some fixed value such as the median, and a third class is based on the frequency of the occurrence of runs in the data. (From McGraw-Hill Dictionary of Scientific and Technical Terms, 4th ed, p1284; Corsini, Concise Encyclopedia of Psychology, 1987, p764-5) Kolmogorov-Smirnov Test,Kruskal-Wallis H Statistic,Mann-Whitney U Test,Rank-Sum Tests,Spearman Rank Correlation Coefficient,Wilcox Test,Wilcoxon Rank Test,Non-Parametric Statistics,Nonparametric Statistics,Statistics, Non-Parametric,Kolmogorov Smirnov Test,Mann Whitney U Test,Non Parametric Statistics,Rank Sum Tests,Rank Test, Wilcoxon,Rank-Sum Test,Statistics, Non Parametric,Test, Kolmogorov-Smirnov,Test, Mann-Whitney U,Test, Rank-Sum,Test, Wilcox,Test, Wilcoxon Rank,Tests, Rank-Sum,U Test, Mann-Whitney

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