Editors: Rick Paik-Schoenberg & Nicolas Christou ISSN 1945-1296
Published by the UCLA Department of Statistics

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Authors: | Tamanna Islam, Mikinori Tsuiki |

Title: | [download] (1167) Analysis of Spatial Heterogeneity Using Power Law |

Reference: | Vol. 7, Issue 2, Sep 2015 Submitted 2014-12-03, Accepted 2015-09-22 |

Type: | Article |

Abstract: | We tried to find out the spatial heterogeneity of plant species using power law. A field study was conducted on four grasslands each grazed by a single cow. Grasslands were Dactylis glomerata L. dominated grassland without feces (DgF-), Dactylis glomerata L. dominated grassland with feces (DgF+), Veronica arvensis dominated grassland without feces (VaF-) and Veronica arvensis dominated grassland with feces (VaF+). In each grassland, a 50 m line transect was drawn. Each of the four grasslands was surveyed by placing (=100) equal spaced large quadrats (L-quadrats) along the line transect. Each L-quadrats was divided into equal spaced small quadrats (S-quadrats). For each S-quadrat the occurrence of all plant species were recorded. Using the frequency distribution table these data were summarized. The percentage of S-quadrats containing a given species and the variance of each species were estimated. Using the power law the spatial heterogeneity of each species together with community heterogeneity were calculated. We compared degree of heterogeneity index calculated from beta-binomial distribution and from the regression analysis using the power law. The heterogeneity index from the regression analysis was found to be superior to that of the beta-binomial distribution with respect to evaluate the spatial heterogeneity of each species. The per L-quadrat diversity for DgF+ and VaF+ were higher compared to those of the DgF- and VaF-. |

Paper: | [download] (1167)Analysis of Spatial Heterogeneity Using Power Law (application/pdf, 497.7 KB) |

Resources: | BibTeX | OAI |

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Code: Commons GNU General Public License License

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