由于缺少简洁有效的分析方法,目前对植被空间格局各向异性特征研究的报道很少。该文提出基于数据重采样技术并结合R ip ley s L指数进行种群格局各向异性分析的新思路,并在ArcV iew G IS技术平台上,对广东省黑石顶自然保护区针阔叶混交...由于缺少简洁有效的分析方法,目前对植被空间格局各向异性特征研究的报道很少。该文提出基于数据重采样技术并结合R ip ley s L指数进行种群格局各向异性分析的新思路,并在ArcV iew G IS技术平台上,对广东省黑石顶自然保护区针阔叶混交林中的马尾松Pinus massoniana种群分布格局的各向异性特征进行实例研究。结果表明,马尾松种群分布格局具有典型的各向异性特征,在不同方向上表现不同的分布格局。实例研究表明,通过数据重采样技术在典型方向上的取样过程解决现有格局分析方法中缺少方向参数的问题,是进行种群格局各向异性分析的有效途径,具有一定的实用性。展开更多
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
文摘由于缺少简洁有效的分析方法,目前对植被空间格局各向异性特征研究的报道很少。该文提出基于数据重采样技术并结合R ip ley s L指数进行种群格局各向异性分析的新思路,并在ArcV iew G IS技术平台上,对广东省黑石顶自然保护区针阔叶混交林中的马尾松Pinus massoniana种群分布格局的各向异性特征进行实例研究。结果表明,马尾松种群分布格局具有典型的各向异性特征,在不同方向上表现不同的分布格局。实例研究表明,通过数据重采样技术在典型方向上的取样过程解决现有格局分析方法中缺少方向参数的问题,是进行种群格局各向异性分析的有效途径,具有一定的实用性。
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.
