Spatial patterns of trees in oak stands can be analyzed using the Morisita Index, but the results can vary based on the size of the sampling area. Researchers found that the Morisita Index values change with different quadrat sizes, making it hard to compare sites. They developed a new method to determine the best quadrat size for each site and to interpret clustering patterns consistently across multiple sites. By looking at the maximum clustering intensity and the rate of change of clustering intensity, they could identify the scale of clustering and the best quadrat size for analyzing spatial patterns in different environments.