Species abundance in a forest community in South China: A case of poisson lognormal distribution
Journal of Integrative Plant Biology
By: Z.-Y. Yin, H. Ren, Q.-M. Zhang, S.-L. Peng, Q.-F. Guo, and G.-Y. Zhou
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Abstract
Case studies on Poisson lognormal distribution of species abundance have been rare, especially in forest communities. We propose a numerical method to fit the Poisson lognormal to the species abundance data at an evergreen mixed forest in the Dinghushan Biosphere Reserve, South China. Plants in the tree, shrub and herb layers in 25 quadrats of 20 m??20 m, 5 m??5 m, and 1 m??1 m were surveyed. Results indicated that: (i) for each layer, the observed species abundance with a similarly small median, mode, and a variance larger than the mean was reverse J-shaped and followed well the zero-truncated Poisson lognormal; (ii) the coefficient of variation, skewness and kurtosis of abundance, and two Poisson lognormal parameters (?? and ??) for shrub layer were closer to those for the herb layer than those for the tree layer; and (iii) from the tree to the shrub to the herb layer, the ?? and the coefficient of variation decreased, whereas diversity increased. We suggest that: (i) the species abundance distributions in the three layers reflects the overall community characteristics; (ii) the Poisson lognormal can describe the species abundance distribution in diverse communities with a few abundant species but many rare species; and (iii) 1/?? should be an alternative measure of diversity.
| Publication type | Article |
|---|---|
| Publication Subtype | Journal Article |
| Title | Species abundance in a forest community in South China: A case of poisson lognormal distribution |
| Series title | Journal of Integrative Plant Biology |
| DOI | 10.1111/j.1744-7909.2005.00095.x |
| Volume | 47 |
| Issue | 7 |
| Year Published | 2005 |
| Language | English |
| Publisher | Wiley |
| Contributing office(s) | Northern Prairie Wildlife Research Center |
| Description | 10 p. |
| First page | 801 |
| Last page | 810 |
| Google Analytic Metrics | Metrics page |