AbstractIn shipping and aquaculture, respectively, the fouling of hulls and cages by barnacles is a considerable problem. Barnacles can also block power station water intakes, and sharp Balanus shells can pose a health risk to humans. This study highlights the use of non-supervised neural networkstostudy the zonation of barnacles found in intertidal zones at various sampling sites on the Penang Island. Barnacles were studied at each zonation of the intertidal areas at 14 sampling sites; i.e. upper, middle, and lower zonations for every sampling site. From the results, three species were identified, including Euraphiawithersi and Chthamalusmalayensis from the Chthamalidae family, and Balanus amphitrite amphitrite from the Balanidae family. Chthamalusmalayensis was found to be the most abundant of the three species at 44.24% of the total population. The distribution of the three barnacle species also varied within the sampling locations. Based ona Self Organizing Map (SOM), also known as Non-Supervised Neural Network, a distinct zonation was observed where Chthamalusmalayensis was more dominant in the upper zonation; Euraphiawithersi on the middle zonation; and Balanus amphitrite amphitrite on the lower zonation. The distribution of these barnacles was found to be vertically distributed and affected by several factors including abiotic factors such as temperature, light intensity, salinity, and biotic factors. The interaction between barnacles leads to competitive exclusion and niche partitioning which created zonations among the species. Apart from that, the distributions were possibly affected by anthropogenic activities such as embankment, land reclamation, and residential development.
Keywords: Barnacles, Clustering, Distribution, Intertidal, Self Organizing Maps, Zonation.