Invasive aquatic plants, such as non-native hydrilla (Hydrilla verticillata), negatively impact waterway systems in the southeastern United States and on a global scale. Often, these aquatic weed species impede recreational activities, power generation, and disrupt native ecological systems. Costs associated with aquatic weed management include expenses accompanied with monitoring, mapping, and implementing control measures. Prompt detection and accurate mapping of submersed aquatic vegetation (SAV) are critical components when formulating management decisions and practices. Therefore, SAV management protocols are often reliant upon the perceived extent of invasion. Traditional biomass sampling techniques have been widely utilized, but often require significant labor inputs, which limits repeatability, the scale of sampling, and the rapidness of processing. Advances in consumer available hydroacoustic technology (sonar) and data post-processing offer the opportunity to estimate SAV biomass at scale with reduced labor and economic requirements.
The objectives of this research were to document the use of an off-the-shelf consumer sonar/gps chartplotter to: 1) describe and characterize a relationship between hydroacoustic biovolume signature to measured hydrilla biomass; 2) develop algorithm for on-the-fly assessment of hydrilla biomass from interpolated biovolume records; 3) define seasonal hydrilla growth patterns at two NC piedmont reservoirs; and 4) create a visual representation of SAV development over time. From these objectives, the expected outcome was to describe a protocol for passive data collection while reducing the economic inputs associated with labor efforts involved in biomass sampling and post-processing evaluations. In our research, a Lowrance HDS-7 Gen2 was utilized to correlate biomass from monospecific stands of hydrilla within two different North Carolina piedmont reservoirs using BioBase 5.2 (now marketed as EcoSound – www.biobasemaps.com), cloud-based algorithm to aid in post-processing.