Plankton Biomass Models Based on GIS and Remote Sensing Technique for Predicting Marine Megafauna Hotspots in the Solor Waters. [ Presented at 2nd International Conference of Indonesian Society for Remote Sensing (ICOIRS) 2016].

Abstract

Geographic information system and remote sensing techniques can be used to assist with distribution modelling; a useful tool that helps with strategic design and management plans for MPAs. This study built a pilot model of plankton biomass and distribution in the waters off Solor and Lembata, and is the first study to identify marine megafauna foraging areas in the region. Forty-three samples of zooplankton were collected every 4 km according to the range time and station of aqua MODIS. Generalized additive model (GAM) we used to modelling zooplankton biomass response from environmental properties.Thirty one samples were used to build a model of inverse distance weighting (IDW) (cell size 0.01°) and 12 samples were used as a control to verify the models accuracy. Furthermore, Getis-Ord Gi was used to identify the significance of the hotspot and cold-spot for foraging area. The GAM models was explain 88.1% response of zooplankton biomass and percent to full moon, phytopankton biomassbeing strong predictors. The sampling design was essential in order to build highly accurate models. Our models 96% accurate for phytoplankton and 88% accurate for zooplankton. The foraging behaviour was significantly related to plankton biomass hotspots, which were two times higher compared to plankton cold-spots. In addition, extremely steep slopes of the Lamakera strait support strong upwelling with highly productive waters that affect the presence of marine megafauna. This study detects that the Lamakera strait provides the planktonic requirements for marine megafauna foraging, helping to explain why this region supports such high diversity and abundance of marine megafauna.