A technique for conducting point pattern analysis of cluster plot stem-maps

Abstract

Point pattern analysis of forest inventory stem-maps may aid interpretation and inventory estimation of forest attributes. To evaluate the techniques and benefits of conducting point pattern analysis of forest inventory stem-maps, Ripley’s K( t) was calculated for simulated tree spatial distributions and for over 600 USDA Forest Service Forest Inventory and Analysis (FIA) plots in Minnesota and Wisconsin. A new technique for calculation of Ripley’s K( t) for cluster plot stem-maps was proposed that involves the truncation and combination of clustered, circular sub-plots (0.01 ha) into one square (0.04 ha) for each inventory plot. For Poisson and uniform simulated tree spatial distributions, combined sub-plots may possess nearly the same spatial properties as the entire plot area from which they were sampled. Although sub-plots may be too small for meaningful spatial analysis, combined sub-plots may permit spatial analysis regardless of how sub-plots are combined. The step-size ( t) at which stem-map point patterns were most discernible as either clustered or uniform varied by forest type. Additionally, stand disturbances may increase K( t). Although limitations exist, point pattern analysis of forest inventory stem-maps may permit refined ecological analysis of forest inventories.