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 ...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 resam-pling 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 popula-tion 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 resam-pling sub-datasets from the original dataset in different direc-tions,we could overcome the difficulty in the direct use of current non-angular methods of pattern analysis.展开更多
基金This paper was supported by the National Natural Science Foundation of China(Grant No.30370254).
文摘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 resam-pling 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 popula-tion 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 resam-pling sub-datasets from the original dataset in different direc-tions,we could overcome the difficulty in the direct use of current non-angular methods of pattern analysis.
