Exploring an Ichthyoplankton Database from a Freshwater Reservoir in Legal Amazon.

The purpose of this study is to use data mining techniques for the exploratory analysis of a database of ichthyoplankton samples from a freshwater reservoir in Legal Amazon. This database has already been analyzed using statistical techniques, but these did not find a relationship between biotic and abiotic factors. The application of the Apriori algorithm allows us to generate association rules that yield an understanding of the process of fish spawning in Tocantins River. In this case, we demonstrate the effective use of data mining for the discovery of patterns and processes in ecological systems, and suggest that statistical methods often used by ecologists can be coupled with data mining techniques to generate hypotheses.