Journal of Applied Phycology, vol: 30,1 (2018)
Percentage cover, biomass, distribution, and potential habitat mapping of natural macroalgae, based on high-resolution satellite data and in situ monitoring, at Libukang Island, Malasoro Bay, Indonesia
Setyawidati N., Kaimuddin A.H., Wati I.P., Helmi M., Widowati I., Rossi N., Liabot P.O., Stiger-Pouvreau V.
Abstract
In this study, we combined remote sensing data and in situ observations to explore the potential habitats of macroalgae at Libukang Island, Indonesia. High-resolution satellite images from the GeoEye-1 were used to estimate and to map the geomorphological structures together with macroalgal species in the study area. Seasonal variations of percentage cover and biomass of macroalgae associated with substrates were investigated in May and November 2014, and June 2015, using quadrats as sampling unit. A total of nine common genera were found in the study area with three dominant genera: Sargassum, Padina, and Turbinaria. Most of macroalgae was observed in the eastern part of the Island, on several substrate types and particular oceanographic conditions (wave and current). Mean biomasses of Sargassum and Padina were high in May (1189.6 ± 455 and 166.7 ± 15.4 g DW.m−2, respectively), while the biomass of Turbinaria was high in November (3245 ± 599.8 g DW.m−2). The map accuracy of image classification for all typology substrates was 74.19%. Overall, approximately 62.3% of the total study area can be considered as potential for natural macroalgae habitats. Spectral response characteristic of shallow water substrates at study area based on GeoEye-1 is also presented. The results of this study exhibit a potential utilization of natural macroalgae in the study area, and provide information for a possible diversification of the use of macroalgae in Indonesia. The method could be useful for habitat management and future biomonitoring in the study area or other similar areas in Indonesia. © 2017, Springer Science+Business Media B.V.
Keyword: Biomass; Brown algae; Habitat structure; Remote sensing; Seaweed monitoring