Abstract:Ecological experiments are usually conducted on small scale,but the ecological and environmental issues are usually at large scale. Hence,,there is a clear need of scaling. Namely,when we deal with the patterns and processes at larger scale, a special connection needs to be established to the small scale that we are familiar with. Here we presented a wavelet analysis method that could build relationships between spatial distribution patterns at different scales. And with this method, we also studied the how spatial heterogeneity and patterns changed with scale. We investigated the distribution and the habitat of C.ewersmanniana in two plots (200m×20m, the distance between the plots is 15 km) at Mosuowan desert..The results demonstrated that spatial heterogeneity and distribution patterns were incorporated into larger scale when wavelet scale varied from one (5m) to four (20m). However, if the wavelet scale was above five (25m),the spatial distribution patterns varied placidly, oscillation period of landform stabilized at 110m, and the dynamic quantity period of C.ewersmanniana stabilized at 115-125m.We also identified signal catastrophe points with wavelets and verified heterogeneity degree of local space with position variance. We found that position variance decomposed the distribution patterns at large scale into small sampling plot, and the position with the largest variance also had strongest heterogeneity. In a word, wavelet analysis method could scale-up spatial distribution patterns and habit heterogeneity. With this method and other method derived from this one, such as, wavelet scale, wavelet variance, position variance, and extremely direct-viewing graphs, wavelet analysis could be widely applied in solving the scaling problem in ecological and environmental studies.