Exergy is a measure of the free energy of a system with contributions from all components including the energy of organisms, and it is used as an ecological indicator. In this study, we implemented a self-organizing map (SOM) for patterning exergy of benthic macroinvertebrate communities. The datasets were extracted from the database EKOO consisting of 650 sampling sites in the Netherlands including 855 species. Using these datasets, exergy of five trophic functional groups (carnivores, detritivores, detritivore¿herbivores, herbivores, and omnivores) were calculated for each sampling site on the basis of the biomass data. Exergy of each trophic group was used as input data of the SOM. By training the SOM the sampling sites were classified into five clusters and the classification was mainly related to water types of the sampling sites. Exergy of different trophic groups responded differently to different water types displaying characteristics of target ecosystems. Finally, the results show that exergy is an effective ecological indicator and patterning changes of exergy is an effective way to evaluate target ecosystems.
- artificial neural-networks