Applying data mining techniques for spatial distribution analysis of plant species co-occurrences
| Autor: | Marinez Ferreira de Siqueira, Felipe S. M. Barros, Flávia dos Santos Pinto, Jano M. Souza, Luís Alexandre Estevão da Silva, Geraldo Zimbrão |
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| Rok vydání: | 2016 |
| Předmět: |
0106 biological sciences
Forest dynamics Association rule learning Computer science Process (engineering) Ecology (disciplines) General Engineering 02 engineering and technology computer.software_genre 010603 evolutionary biology 01 natural sciences Computer Science Applications Identification (information) Resource (project management) Knowledge extraction Artificial Intelligence 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Data mining computer |
| Zdroj: | Expert Systems with Applications. 43:250-260 |
| ISSN: | 0957-4174 |
| DOI: | 10.1016/j.eswa.2015.08.031 |
| Popis: | We used association rules for extracting patterns of co-occurrences.We obtained pairs and groups of species with positive and negative correlation.One multiscale, spatially explicit and multi-species method was proposed.Data mining can be useful to produce lists of species with co-occurrences. The continuous growth of biodiversity databases has led to a search for techniques that can assist researchers. This paper presents a method for the analysis of occurrences of pairs and groups of species that aims to identify patterns in co-occurrences through the application of association rules of data mining. We propose, implement and evaluate a tool to help ecologists formulate and validate hypotheses regarding co-occurrence between two or more species. To validate our approach, we analyzed the occurrence of species with a dataset from the 50-ha Forest Dynamics Project on Barro Colorado Island (BCI). Three case studies were developed based on this tropical forest to evaluate patterns of positive and negative correlation. Our tool can be used to point co-occurrence in a multi-scale form and for multi-species, simultaneously, accelerating the identification process for the Spatial Point Pattern Analysis. This paper demonstrates that data mining, which has been used successfully in applications such as business and consumer profile analysis, can be a useful resource in ecology. |
| Databáze: | OpenAIRE |
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