标题：ESTUDO DA DISTRIBUIÇÃO ESPACIAL DO ANGICO (Anadenanthera peregrina) NA FLORESTA ESTADUAL "EDMUNDO NAVARRO DE ANDRADE" - RIO CLARO,SP, BRASIL, EMPREGANDO METODOLOGIA GEOESTATÍSTICA
出版社：Centro de Estudos Ambientais - UNESP/Rio Claro
摘要：Studies concerning application of geostatistical methodology to space distribution and mapping of plant species populations are rare. The main purpose of this study is to evaluate the application of geostatistics in detection and prediction of the space pattern of Anadenanthera peregrina "angico" at the "Edmundo Navarro de Andrade" State Forest (Rio Claro/SP). Simulations of the population data, previously mapped, were made in laboratory, by PCQ method. Using ordinary kriging interpolation technique, a map of "angicos" aggregation occurrence aggregation was generated for the area. Such method showed to be efficient to spatial analysis of the population agglomerates, as it could be observed by overlapping the population mapped with the map of the aggregation estimates originating from sampling. This case study can contribute to the discussion of the traditional methods of botanical data sampling, proposing a new methodology for analysis using space statistics.
其他摘要：Studies concerning application of geostatistical methodology to space distribution and mapping of plant species populations are rare. The main purpose of this study is to evaluate the application of geostatistics in detection and prediction of the space pattern of Anadenanthera peregrina "angico" at the "Edmundo Navarro de Andrade" State Forest (Rio Claro/SP). Simulations of the population data, previously mapped, were made in laboratory, by PCQ method. Using ordinary kriging interpolation technique, a map of "angicos" aggregation occurrence aggregation was generated for the area. Such method showed to be efficient to spatial analysis of the population agglomerates, as it could be observed by overlapping the population mapped with the map of the aggregation estimates originating from sampling. This case study can contribute to the discussion of the traditional methods of botanical data sampling, proposing a new methodology for analysis using space statistics.
