Student Carnegie Mellon University Titusville, New Jersey, United States
The World Economic Forum lists water scarcity as a major global risk, leaving us more dependent on surface water for drinking. This requires more filtration infrastructure, and monitoring of surface water sources. Current methods rely on expensive and technically challenging manual biological sample identification by morphology. Macroinvertebrates spend their larval lives within a small area of water, showing cumulative effects of habitat alteration and pollutants that chemical testing and field sensors do not. Molecular methods enhance biomonitoring programs. This research explores deoxyribonucleic acid (DNA) barcoding, to measure waterway health, particularly with the most widespread macroinvertebrate families. DNA Barcoding makes sample identification significantly more accessible. A statistical sampling plan was designed representing variation in geological, ecological, and land use factors. Four methods of isolation and amplification were compared. Statistical analysis shows DNA Barcoding results in more accurate and precise waterway health data, adding significant value for monitoring scarce water resources. Learnings were applied to design and build a microbiology and genetics lab at a nonprofit water study institute. The method successfully tracked nonpoint source pollution on waterways used as municipal drinking water sources. Project data were used in community land use decision making, protecting wetlands as well as threatened species. This concept was advanced to create the Genetics Entomological Monitoring Station (GEMS), a lab extension to perform environmental assessment with insect bioindicators. This method can be applied at low cost to enhance citizen science water monitoring programs and community education.