Advancing Optical Imaging and Classification to Enhance Biodiversity Monitoring

Foundational to assessing biodiversity is an effective and cost-efficient method to identify and quantify the components of biodiversity. While a substantial proportion of present and proposed biofuel production systems are terrestrially based, the environmental impacts wash down the watershed into the aquatic ecosystem. Biodiversity monitoring can therefore be efficiently focused on surface waters draining the watershed, but it is first necessary to design and build modern sampling methodologies with which to collect data on biodiversity status and trends. The objective of this Phase I project is to modernize methods for identification and enumeration of organisms sampled from surface waters by advancing the design and operational range of an optical image acquisition and classification (OIC) system. Despite its potential to increase sample precision, reduce processing time and better manage costs, OIC has not achieved its potential in most sectors for which commercial opportunity exists. This opportunity will be addressed by designing, building, and testing a portable OIC system that will support spatially and temporally resolved sample collection and real-time identification and enumeration, allowing adaptive sampling to ensure acquisition of statistically robust data for the milieu of common and rare organisms of which biodiversity is composed. A portable OIC unit capable of imaging and classifying lentic and lotic organisms ranging in maximum cross-section from ~1-25 mm will be designed and built. Unit capabilities will include remote operation, internal data logging, a portable power supply, and robust construction to ensure operability in hostile field environments. External but complementary to the unit will be a sampling apparatus capable of extracting organisms from complex benthic environments in a predictable manner while preventing entry of potentially damaging non-biological items. Domestically and globally, thousands of streams and lakes are monitored to characterize biodiversity status and trends. In most cases, sampling is conducted using archaic net sampling techniques that require expensive manual sorting and identification and that result in poorly resolved and time-delayed data outcomes. Industry, government agencies, and commercial organizations that conduct these sampling efforts will benefit from reduced sample processing costs and more rapid data acquisition resulting from an OIC-based tool. The public will benefit from enhanced temporal and spatial data outcomes, allowing improved understanding of biodiversity status and trends and thereby better environmental decision-making. A successful Phase I project will lead to the development of a Phase II commercialization plan to achieve a supportable price point resulting in a multi-million-dollar revenue stream based on unit sales, system upgrades, and service.