Patterning limnological characteristics of the Chilika lagoon (India) using a self-organizing map

Abstract

In this study, a self-organizing map (SOM) was utilized to classify habitats in the Chilika lagoon located in India, the largest lagoon ecosystem in Asia (maximum length, 64.3 km; mean width, 20.1 km). The lagoon was marginally eutrophic (nitrate, 0.25 ± 0.22 mg L -1 ; orthophosphate, 0.26 ± 0.22 mg L -1 ; n = 1,980, respectively) for six years (1999)(2000)(2001)(2002)(2003)(2004), and it used to be warm, shallow, turbid and predominantly brackish. The SOM model successfully identified the changing patterns of limnology in the lagoon using the monthly limnological dataset from 30 study sites (July 1999-December 2004. Comparative re-sectoring evaluation of current monitoring sites was accomplished based on the outcome of the modeling. The new site clustering that emerged from the model was similar to conventional ones, and several sites were reorganized. Water physicochemistry was affected by freshwater inflow during monsoon and the new lagoon mouth constructed in September 2000, which resulted in variations in site characteristics in terms of limnology. The results of this study may provide information on the limnological patterns in Chilika lagoon, and they leave room for further study into functional changes in the lagoon ecology with respect to changes in climatic factor, freshwater flow and lagoon morphology.

The Use of Artificial Neural Networks (ANNs) in Aquatic Ecology

“…In most cases the SOM has been used to classify sampling sites according to different environmental variables or faunal assemblages from their species composition. Jeong et al (2008b), for instance, classified the different habitats present in a lagoon from a set of 21 limnological characteristics, whereas Cho first to define hydro-morphological patterns of the sampling sites based on four environmental variables, and then to reveal temporal changes in the macro-invertebrate communities inhabiting the sites clustered by SOM. Concerning the classification of faunal communities, the SOM has been mainly used to pattern invertebrate (Chon et al, 1996;Cereghino et al, 2001;Park et al, 2006) and fish (Brosse et al, 2001;Hyun et al, 2005) assemblages.…”

Monsoon-driven Dynamics of water quality by multivariate statistical methods in Daya Bay, South China Sea

“…The monsoon is a characteristic climate variation in Asian A large amount of rainfall occurs, usually during the southwest monsoon period (Jeong et al 2008). There is plenty of rainfall in Daya Bay during the southwest monsoon period from May to October, and there is relatively less rainfall during the northeast monsoon period from November to the next April .…”

“…Better understanding of these complex ecological and environmental processes is of the utmost importance. Identification of key factors governing the ecological dynamics and environmental pollution is strongly required to establish the basis for the ecological and environmental research needed to undertake the efficient management and biodiversity conservation of coastal bay ecosystems (Jeong et al 2008). One critical step in controlling coastal pollution and maintaining the sustainability of the biodiversity is the development of coastal water monitoring programs to track ecological and environmental conditions and spatiotemporal trends.…”

Identification of temporal and spatial variations of water quality in Sanya Bay, China by three-way principal component analysis

“…8). A large amount of rainfall occurs usually during the southwest monsoon period (Jeong et al 2008). There is plenty of rainfall in Sanya Bay during the southwest monsoon period from May to October, and there is less during the northeast monsoon period from November to the next April.…”