Global Environmental Science Theses

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https://hdl.handle.net/10125/60447

The Bachelor of Science Degree Program in Global Environmental Science (GES) is administered by the department of Oceanography in the School of Ocean and Earth Science and Technology of the University of Hawai‘i.

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Iron and Cobalt Limitation in Atlantic Prochlorococcus MIT9301
(2024) van Dijken, Carlo; Hawco, Nicholas
Prochlorococcus is an abundant marine microorganism playing a vital role in the Earth’s carbon cycle and therefore climate. This organism is a cyanobacteria meaning it obtains energy through photosynthesis. A large portion of the ocean’s phytoplankton populations are limited by low concentrations of trace metals such as iron and cobalt. Future climate change will likely alter ocean circulation and supply of trace metals to the surface ocean, and may impact Prochlorococcus populations, which can affect marine food webs. We only have information on iron and cobalt requirements for a few strains of Prochlorococcus. Therefore, we performed culturing experiments to understand the growth and decay of Prochlorococcus in a lab environment with changes in levels of iron and cobalt. Iron limitation on Atlantic Prochlorococcus did not have a significant impact on growth rates, while cobalt limitation experiments did significantly impact the growth of these phytoplankton when lowered. The growth rates resulting from these experiments can be used to model future changes in Prochlorococcus populations as the impacts of climate change become more prevalent. Keywords: Prochlorococcus, trace metal, cobalt, iron, growth rate, limitation
ZOOSCANNING THE CCZ: A BASELINE STUDY OF ZOOPLANKTON ASSEMBLAGES IN THE CLARION CLIPPERTON ZONE
(2024) Yamada, Michael; Goetze, Erica
Zooplankton, small animals that inhabit the water column, are the dominant secondary producers of the global ocean. They serve several important roles in food web dynamics and ecosystem function but may be at risk due to the emerging industry of deep-sea mining. This study examines deep-sea plankton within the Clarion Clipperton Zone (CCZ), a region of the eastern tropical Pacific (ETP) that is rich in polymetallic nodules, as part of a baseline survey of ecosystem function prior to mining impact. Samples were collected over the NORI-D exploration mining claim using a 1m² Multiple Opening and Closing Net and Environmental Sensing System (MOCNESS) on two cruises in 2021, and samples were analyzed using a Hydroptic ZooScan MIV system. Zooplankton abundance was highest in the well-oxygenated upper 100 m of the water column, with lower abundance within the midwater oxygen minimum zone (OMZ) as well as below the OMZ. The expected migratory behavior for zooplankton is to move from the mesopelagic into the upper ocean at night. Most of the samples analyzed from the fall (DG5C cruise) exhibited this trend in all size fractions, but the large size fraction from the spring (DG5B cruise) did not. Seasonal variability in zooplankton abundance was observed in all regions of the water column (Upper, OMZ, Below OMZ) at the preservation reference zone (PRZ) site, with more small (0.2-1.0 mm) and large (1.0-5.0 mm) animals in the spring compared to the fall. At the collector test area (CTA) site, significant seasonality was observed only within the core of the OMZ in the small and large size fractions, with higher zooplankton abundance in spring. These site-specific differences in the strength of seasonality may have been due to higher oxygen concentrations in the upper portion of the OMZ during spring (100-300 m). This study provides some of the first information on zooplankton seasonality across midwater in the Eastern Tropical Pacific: In providing baseline observations, this work also enables subsequent study of how zooplankton are impacted by commercial mining in this region. The information gathered with the study could be used to help set industry regulations to protect zooplankton communities from deep-sea mining impacts. Keywords: Zooplankton, ZooScan, Deep-sea mining, eastern tropical Pacific (ETP), Clarion Clipperton Zone (CCZ), oxygen minimum zones (OMZ), seasonality
SIMULATING THE IMPACTS OF CLIMATE CHANGE ON UH MĀNOA LETTUCE (LACTUCA SATIVA L.) GROWTH BY MODIFYING AIR TEMPERATURE, SOIL WATER AVAILABILITY, AND ATMOSPHERIC CO₂ CONCENTRATION
(2023) Yos, Nicholas; Mora, Camilo
Plant species are adapted to survive under specific ranges of air temperature, soil water availability, and atmospheric CO₂ concentration. Climate change-induced shifts in these environmental conditions have the potential to significantly affect nearly all terrestrial plants. Many studies have explored the impacts of changing one or two of the conditions listed above, but few have examined the combined effects of all three. To study the interactive effects of the three environmental conditions, 350 UH Mānoa lettuce (Lactuca sativa L.) plants were grown in indoor growth chambers. Within the chambers, plants were grown under ambient (~430-520 ppm) or elevated (700 ppm) atmospheric CO₂ concentration, 60-100% of maximum soil water content, and 20-36 °C air temperature for 21 days. At the end of this period, the leaves of each plant were removed, dried, and weighed. Percent plant mortality and leaf nitrogen content percentage were also measured. Across all combinations of temperature and water availability, elevated CO₂ concentrations resulted in increased leaf mass production and decreased percent mortality. Percent mortality increased and leaf mass production decreased under high temperatures and both high and low water availability. The combination of environmental conditions that produced the largest amount of biomass was 700 ppm CO₂, 80% of soil water capacity, and 24 °C, while the treatment that produced the least amount was ambient CO₂, 60% of soil water capacity, and 36 °C. Nitrogen content percentage increased under high temperatures and high water availability. These results suggest that although increased atmospheric CO₂ levels have the potential to promote lettuce growth, lettuce yield is still likely to decrease in many regions due to the negative effects of high temperatures, drought, and flooding. Keywords: Lettuce, heat stress, water stress, CO₂ enrichment
ANALYSIS OF ENVIRONMENTAL PARAMETERS CORRELATING WITH THE PRESENCE OF LEPTOSPIRACEAE IN HE‘EIA FISHPOND
(2023) Rochette-Yu Tsuen, Keanu G.; Alegado, Rosanna ‘Anolani
Leptospirosis is a zoonotic disease caused by the bacteria Leptospira interrogans and is disseminated in the urine of mammalian hosts (rats, swine). Mild cases involve flu-like symptoms, vomiting, and jaundice while severe cases may involve renal failure and pulmonary hemorrhage. Hawaiʻi has the highest incidence of leptospirosis in the United States due to its warm and humid climate, yet cases are likely under-diagnosed due to the non-specific nature of clinical symptoms. Taro farmers are at highest risk as freshwater habitats are near mammalian carriers. In the Heʻeia watershed in windward Oʻahu, Indigenous agriculture (loʻi) and mariculture (loko iʻa), channelized streams, and established populations of feral pigs may facilitate transmission of leptospirosis. We hypothesized that precipitation and storms increase dispersal of Leptospira. We carried out water quality sampling at the Heʻeia loko iʻa (HFP) between 2014-2015 and 2017-2019. Precipitation data were retrieved from the Hawai‘i Climate Data Portal. Metabarcoding of the 16S rDNA gene was performed on water samples. Leptospiraceae relative abundance co-varied with the seasonal precipitation and was highest in the wet season. Leptospiraceae presence is strongly correlated with storm events (R² = 0.68, p = 0.086). Relative abundance was inversely correlated with salinity within HFP (R² = 0.69, p < 0.05) and correlated to the freshwater input (R² = 0.27, p < 0.05) suggesting a riverine origin. Quantification of pathogenic Leptospira by qPCR, targeting the lipL32, which is conserved across pathogenic strains of Leptospira, showed no amplification of the target gene. Results of this project provide a better understanding of the presence of Leptospiraceae in HFP and indicate relative risks of infection for communities working in the fishpond. Keywords: Leptospirosis, Zoonotic disease, Microbial Source Tracking
SEA LEVEL RISE IMPACTS AND ADAPTATION IN YAP PROPER, FEDERATED STATES OF MICRONESIA
(2023) Einfalt, Nadia; Fletcher, Charles
Sea level rise (SLR) poses a significant threat to coastal communities, resulting in various impacts such as flooding, aquifer salinization, and coastal erosion. Small island nations, like Yap in the Federated States of Micronesia, are particularly vulnerable due to their low elevation, isolated geographic location, and above-average rates of sea-level rise. Yap, being one of the four member states in free association with the United States, faces heightened risks, yet lacks localized SLR data, making it a critical area for study. This research aims to address this gap by employing ArcGIS to model areas in Yap that will be inundated under one meter of SLR, providing valuable insights and potential place-based solutions. The choice of one meter as the benchmark aligns with the IPCC AR6 projection of a sea-level rise of 0.6 to 1.1 meters by 2100 under the high emissions scenario (Fox-Kemper et al., 2023). The results of this project reveal the exposure of Yap's infrastructure: four pieces of critical infrastructure, nine government or non-governmental organization facilities, 16 businesses, 29 cultural sites, and 248 buildings or other structures are projected to be inundated under one meter of SLR. Notably, the mapping results highlight Colonia as the most vulnerable area in Yap. Colonia serves as the primary center for governance and commerce for the entire state, emphasizing the urgency of understanding and addressing the potential impacts of SLR in this critical location. This research not only sheds light on the exposure of Yap but also underscores the importance of localized data for effective climate resilience planning and policy development in vulnerable coastal regions. Keywords: Sea level rise, coastal flooding, erosion, saltwater intrusion, adaptation, Yap, FSM.
THE LĀHAINĀ WILDFIRES FROM A METEOROLOGICAL PERSPECTIVE IN THE CONTEXT OF CLIMATE CHANGE
(2024) Dyer, Kyra; Torri, Giuseppe
The Effects of Environmental Forcing on the Water Quality in Ke‘ehi Lagoon O‘ahu, Hawai‘i
(2024) Felicijan, Peter Elmer Jakob; McManus, Margaret Anne
MICROBIAL METABOLISM OF DIESEL FUEL IN A TROPICAL ISLAND AQUIFER
(2024) Inn, Skye; Nelson, Craig E.
ISOTOPIC ANALYSIS OF A CATCHMENT IN MĀNOA, HAWAIʻI
(2024) Koeroessy, Rebecca; Torri, Giuseppe; Nugent, Alison
DEVELOPING AND ASSESSING A DIVERSE PLANKTON IMAGERY TRAINING SET FOR MACHINE-LEARNING PLANKTON CLASSIFICATION IN THE NORTH PACIFIC SUBTROPICAL REGION
(2024) Mathews, Nicole Celine Sulla; White, Angelicque; Henderikx-Freitas, Fernanda
ABSTRACT The Imaging FlowCytobot (IFCB) has a continually growing role in oceanographic research, particularly in the exploration of microbial life within the North Pacific Subtropical Gyre (NPSG). However, the vast amount of data generated by the IFCB poses a challenge for manual sorting and taxonomic classification. This study addresses this challenge by developing a Convolutional Neural Network (CNN) training set to efficiently categorize IFCB images into taxonomic groups. Specifically focusing on the diatom Hemiaulus and ciliate phylum Ciliphora during a research cruise within the NPSG in the summer of 2021, the study aims to quantify the CNN's performance compared to manual annotations of IFCB images taken on this cruise, providing insights into the CNN’s accuracy and precision over time. Statistical analyses of the CNN’s machine learning-based classifications indicate a high accuracy in the automated identification of Hemiaulus and Ciliophora. Analysis of biovolume and particle number concentration reveals trends in taxonomic abundance over the course of the cruise. Despite morphological changes of Hemiaulus as it loses structure over time, the CNN demonstrates an overall improvement in accuracy as the cruise progresses, particularly for Hemiaulus. This study highlights the development of a robust training set of roughly 76,000 images, allowing the CNN to accurately classify images collected within the NPSG. Keywords: Taxonomic sorting, machine learning, zooplankton, Imaging FlowCytoBot (IFCB), North Pacific Subtropical Gyre (NPSG), ocean microbiology.

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