Anisotropy analyses of population distribution patterns

Abstract

Direction-dependence, or anisotropy, of spatial distribution patterns of vegetation is rarely explored due to neglect of this ecological phenomenon and the paucity of methods dealing with this issue. This paper proposes a new approach to anisotropy analysis of spatial distribution patterns of plant populations on the basis of the data resampling technique (DRT) combined with Ripley s L index. Using the ArcView Geographic Information System (GIS) platform, a case study was carried out by selecting the population of Pinus massoniana from a needle- and broad-leaved mixed forest community in the Heishiding Nature Reserve, Guangdong Province. Results showed that the spatial pattern of the P. massoniana population was typically anisotropic with different patterns in different directions. The DRT was found to be an effective approach to the anisotropy analysis of spatial patterns of plant populations. By employing resampling sub-datasets from the original dataset in different directions, we could overcome the difficulty in the direct use of current non-angular methods of pattern analysis.

Keywords

population, spatial distribution pattern, anisotropy analysis, data resampling technique, Ripley& / rsquo / s L index