Self-Organizing Maps applied to ecological sciences

Ecological data are considered to be difficult to analyze because numerous biological and environmental factors are involved in a complex manner in environment–organism relationships. The Self-Organizing Map (SOM) has advantages for information extraction (i.e., without prior knowledge) and the efficiency of presentation (i.e., visualization). It has been implemented broadly in ecological sciences across different hierarchical levels of life. Recent applications of the SOM, which are reviewed here, include the molecular, organism, population, community, and ecosystem scales. Further development of the SOM is discussed regarding network architecture, spatio-temporal patterning, and the presentation of model results in ecological sciences.