Applying data mining techniques for spatial distribution analysis of plant species co-occurrences

摘要: We used association rules for extracting patterns of co-occurrences.We obtained pairs and groups species with positive negative correlation.One multiscale, spatially explicit multi-species method was proposed.Data mining can be useful to produce lists co-occurrences. The continuous growth biodiversity databases has led a search techniques that assist researchers. This paper presents the analysis occurrences aims identify in co-occurrences through application data mining. propose, implement evaluate tool help ecologists formulate validate hypotheses regarding co-occurrence between two or more species. To our approach, we analyzed occurrence dataset from 50-ha Forest Dynamics Project on Barro Colorado Island (BCI). Three case studies were developed based this tropical forest correlation. Our point multi-scale form multi-species, simultaneously, accelerating identification process Spatial Point Pattern Analysis. demonstrates mining, which been successfully applications such as business consumer profile analysis, resource ecology.