Assessing Spatial Variation in Algal Productivity in a Tropical River Floodplain Using Satellite Remote Sensing

• Published in: Remote sensing (Basel, Switzerland) Switzerland), 2021-05, Vol.13 (9), p.1710
• Main Authors: Molinari, Bianca, Stewart-Koster, Ben, Malthus, Tim, Bunn, Stuart
• Format: Article
• Language: English
• Subjects: Accuracy; Algae; Aquatic ecosystems; Aquatic habitats; Aquatic plants; Biomass; Classification; epiphyton; Flood predictions; Floodplains; Food; Habitats; Mathematical models; phytoplankton; Productivity; Remote sensing; River ecology; Rivers; Satellites; Seasons; Spatial variations; statistical modelling; Statistical models; Submerged plants; tropical rivers; Turbidity; Vegetation; wetland management; Wetlands
• ISSN: 2072-4292; 2072-4292
• DOI: 10.3390/rs13091710

Studies of tropical floodplains have shown that algae are the primary source material for higher consumers in freshwater aquatic habitats. Thus, methods that can predict the spatial variation of algal productivity provide an important input to better inform management and conservation of floodplains. In this study, a prediction of the spatial variability in algal productivity was made for the Mitchell River floodplain in northern Australia. The spatial variation of aquatic habitat types and turbidity were estimated using satellite remote sensing and then combined with statistical modelling to map the spatial variation in algal primary productivity. Open water and submerged plants habitats, covering 79% of the freshwater flooded floodplain extent, had higher rates of algal production compared to the 21% cover of emergent and floating aquatic plant habitats. Across the floodplain, the predicted average algal productivity was 150.9 ± 95.47 SD mg C m−2 d−1 and the total daily algal production was estimated to be 85.02 ± 0.07 SD ton C. This study provides a spatially explicit representation of habitat types, turbidity, and algal productivity on a tropical floodplain and presents an approach to map ‘hotspots’ of algal production and provide key insights into the functioning of complex floodplain–river ecosystems. As this approach uses satellite remotely sensed data, it can be applied in different floodplains worldwide to identify areas of high ecological value that may be sensitive to development and be used by decision makers and river managers to protect these important ecological assets.