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Water quality monitoring is essential for the wellbeing of humans, animals, and the environment. Monitoring coastal water quality is critical for the sustainable management and development of coastal resources as over one-third of the human population live in coastal areas. The health of our coasts, oceans, and cities highly depends on our changing climate and anthropogenic activities. Creating robust solutions to climate change and achieving coastal resilience requires interdisciplinary research by leveraging various datasets and techniques. The water quality monitoring techniques encompassed by this body of work aim to leverage satellite remote sensing to monitor water clarity and sea surface temperature for coral health and the second are a suite of microbiological techniques to monitor antibiotic resistance. The first two studies utilize remote sensing imagery to monitor water clarity and sea surface temperature (SST) in coastal Belize. The third and fourth studies use culture, amplification, and sequencing techniques to elucidate levels of antibiotic resistance genes (ARGs) and antibiotic resistant bacteria (ARB) in two major cities—Los Angeles, CA, USA and Belize City, Belize. The final chapter captures the impact remote sensing modules and a course-based undergraduate research experience (CURE) can have on the confidence and self-efficacy of STEM and non-STEM students.The first chapter investigates water clarity changes using Aqua MODIS imagery during the COVID-19 anthropause. Here satellite derived Kd(490) (proxy for water clarity), marine traffic data, and climate model data were used to uncover significant improvements in water clarity during 2020 compared to the baseline period from 2002-2019 in areas with typically heavy marine traffic.In the second chapter, a Google Earth Engine and RStudio based toolkit is devised to combine Aqua MODIS-derived Kd(490) and SST into a coral vulnerability index for marine protected areas (MPAs) in Belize. Using the coral vulnerability index, Belizean MPAs were ranked based on the number of heat stress days and index scores to draw attention to MPAs that may need more intervention.Chapter three elucidates the impacts of land use and water reclamation plants on ARGs and ARB in the Los Angeles River watershed. The developed sampling sites were 2-3 orders of magnitude higher ARG concentrations compared to beaches and undeveloped areas.The fourth chapter uses multiple microbiology techniques to measure ARG and ARB levels in the Belize River, coastal lagoon, and Belize Barrier Reef. Belize City, in particular the sewage treatment lagoons and fish market, were found to contribute most to the resitome.The final chapter allowed students the opportunity to learn remote sensing to investigate environmental change and was found to increase their understanding of remote sensing and coding.

The rising level of antibiotic resistance worldwide is a critical public health challenge. Antibiotic resistance genes (ARGs) and mobile genetic elements allow for bacteria to confer resistance to antibiotics in as little as a year. Antibiotics utilized for growth promotion in confined animal feeding operations (CAFOs) generates manure that is an anthropogenic source of ARGs into the environment. In this study, 10 potting soils, 7 garden soils, 4 food amendments, 4 lawn amendments, 6 manure-based soils, 5 natural soils, 3 community soils, and 3 compost soils were surveyed for antibiotic resistance gene ermF, mobile genetic element intI1, and proxy for bacterial content 16S rRNA. The ARGs were quantified through quantitative polymerase chain reaction (qPCR) to per gram of fertilizer and per gene copies of 16S rRNA. Most soils contained detectable levels of ermF and intI1, ranging from 9.66 x 10-7 to 8.31 x 10-2 gene copies ermF/copies of 16S rRNA and 8.92 x 10-7 to 6.21 x 10-2 gene copies intI1/copies of 16S rRNA. Natural soils were significantly lower in ermF and intI1 than the other soil types. Natural soils ranged from 10-7 to 10-5 gene copies per copies of 16S rRNA while the other types ranged from 10-7 to 10-2 gene copies per copies of 16S rRNA. There was no strong correlation between intI1 and ermF.