Spatial pattern analysis of forest trees based on the vectorial mark

Abstract Analysis of spatial patterns to describe the correlation between a tree location and marks (i.e., structural variables), can reveal stand history, population dynamics, competition symbiosis. However, most studies have concentrated on sizes rather than crown asymmetry especially with direct analysis among characterizing facilitation trees, thus cannot cause distributions locations quantitative marks. To explore vectorial their implication we extracted vertical horizontal (tree height projection area) size, mark (crown displacement vector asymmetry) using an airborne laser scanning point cloud obtained from two forest stands in Oxfordshire, UK. Quantitatively vectorially marked were developed, corresponding null models established for significance test. We analyzed eight types univariate bivariate patterns, after first proposing four types. The accuracy pattern based algorithm-segmented was compared that truly segmented cloud. managed detect 70–86% correctly. distribution size facilitated or competitive interactions sycamore other species. These jointly showed that, at smaller scales, trees tend be clustered, taller, larger crowns due detected facilitations study area. found scales there are taller more species, while is mostly homogeneous across scales. results indicate interspecific mainly affect This work further confirms connection individual competition, revealing potential structure previously hard detect.