A Study On Species-area Relationship Of Subalpine Meadowplant Community

The species-area relationship (SARs) characterizes the variation in the observed number of species with increased sample area. It plays an important role in understanding the generation and maintenance of biodiversity. SARs are used for estimating species richness at different scales and for estimating species extinction probability due to habitat loss. The shapes of the species-area relationships vary according to sampling methods, spatial scales and regional differences. In this paper, I studied three plant communities in different habitats (north-facing slop, south-facing slop and flat field) of subalpine meadow, and three commonly used species-area models (exponential curve, power curve, logistic curve) were fitted to the data respectively. In the experiment, two different sampling methods, nested plots and quadrates combination method, were used to investigate the species-area relationship respectively. A community analysis software PC-ORD was used to analysis the data of the quadrates combination. I found that the logistic model satisfactorily describes the species-area data for all the samples of the nested plots (with the lowest P value of the F test and Ra2), and the logistic model also describes the species-area data for all the samples of the quadrates combination very well except that the data of the flat field was fitted by the exponential curve a little better. I concluded that the logistic model will work best if the species are randomly distributed in space, and tested it by calculating Poisson index of dispersion (Id).