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Ecological Research

, Volume 33, Issue 2, pp 427–434 | Cite as

A timesaving estimation of per-quadrat species number in grassland communities based on a Poisson-like model

  • Jun Chen
  • Masae Shiyomi
  • Huimin Bai
Original Article

Abstract

In estimating the number of species per quadrat with a given area, we usually need much time and labor, because we have no simple ways to easily count it using hardware. We devised here a software method to estimate the mean number of species by counting them only partially in the survey, and estimating it mathematically. We classify quadrats into three classes composed of k, k + 1 and more than k + 1 species; or classify quadrats into four classes composed of k, k + 1, k + 2, and more than k + 2 (referred to as “censored sampling”), where k is the minimum number of species per quadrat. We do not need to count more than k + 2 or k + 3 species, respectively. Using only these 3 or 4 numerals we can estimate the mean of number of species per quadrat, the 95% confidence intervals for the mean and know the spatial pattern value such as aggregated, random or uniform pattern of the number of species per quadrat. Using this method, 10–20% time and labor in counting will be saved compared to the full census. The estimates are obtained through the maximum likelihood calculation. Computer programs to estimate the mean number of species per quadrat are attached as ESMs.

Keywords

Censored sample Labor-saving Small-scale Spatial pattern Species richness 

Supplementary material

11284_2017_1544_MOESM1_ESM.pdf (167 kb)
Supplementary material 1 (PDF 166 kb)
11284_2017_1544_MOESM2_ESM.pdf (160 kb)
Supplementary material 2 (PDF 160 kb)
11284_2017_1544_MOESM3_ESM.pdf (158 kb)
Supplementary material 3 (PDF 157 kb)
11284_2017_1544_MOESM4_ESM.xlsm (33 kb)
Supplementary material 4 (XLSM 32 kb)

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Copyright information

© The Ecological Society of Japan 2018

Authors and Affiliations

  1. 1.College of Animal Science and TechnologyNorthwest A&F UniversityYanglingChina
  2. 2.Ibaraki University, Professor EmeritusMitoJapan

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