Species abundance distribution patterns of <I>Pinus tabulaeformis</I> forest in Huoshan Mountain of Shanxi Province, China

Abstract

Aims Determination of species abundance distribution is important in research on species diversity. Our major objective was to determine species abundance distribution models to advance understanding of distribution mechanisms and to assist preservation of biological diversity. Methods Based on data collected from field surveys, we examined the species abundance patterns of tree, shrub and herb layers in Pinus tabulaeformis forest in Huoshan Mountain, Shanxi Province. We used niche preemption (NPM), broken stick (BSM) and overlapping niche (ONM) models and two species abundance statistical models (log-series distribution model (LSD) and log-normal distribution model (LN)) and neutral theory model (NT). The simulation effects were verified by Chi-square tests, Likelihood-ratios (L-R) tests, Kolmogorov-Smirnov (K-S) tests and Akaike Information Criterion (AIC). Important findings The best niche model for the tree layer is NPM, because it had the smallest AIC value and no significant difference (p > 0.05) between the theory predictions and observed species abundance distributions. The next best is ONM; BSM does not fit the tree layer. All three niche models are suitable for the shrub layer. ONM is the best for the herb layer, followed by BSM and NPM. LSD is good for understanding distribution mechanisms in Pinus tabulaeformis forest. LN can fit both the herb and shrub layers, but not the tree layer. NT cannot explain any layer. These findings indicate that the community has relatively few dense species and more sparse species, the species richness and diversity indices of the tree and shrub layers are much smaller than those of the herb layer, and the community evenness is relatively smaller. We conclude that one model cannot fit differ- ent data but that more than one model can fit the same data even for the same layer. Therefore, we should choose different models to study the species abundances of forest communities. We suggest that these methods might be useful for the protection of the biodiversity of forest dominated by Pinus tabulaeformis.