Date of Award
2024
Degree Type
Dissertation
Degree Name
Doctor of Philosophy in Oceanography
Specialization
Biological Oceanography
Department
Oceanography
First Advisor
Colleen Mouw
Abstract
Phytoplankton account for about half of all global net primary production. They are responsible for fueling marine fisheries, modulating the climate cycle, and forming the base of the marine food web. Some phytoplankton taxa play critical roles in coastal and lake ecosystems by forming harmful algal blooms (HABs), which can severely impact local communities’ economic revenue and human health. Given their importance, recent decades have seen a broad interest in understanding and predicting the variability of phytoplankton populations; however, there are limited resources that identify the relative strengths and weaknesses of analysis approaches used to study phytoplankton population dynamics. Research gaps include understanding when to use any particular approach, identifying the types of question that can be answered, and accounting for major philosophical assumptions.
In this dissertation, I explore some of the diverse quantitative methods used in oceanographic research to study phytoplankton ecology. Although the specific research questions differ by chapter, the overarching theme focuses on the various data sources and analytical tools used to study phytoplankton ecological processes in the natural environment. Chapter 1 relies on numerical modeling to answer questions about colony formation in phytoplankton. With careful parameter testing, this chapter highlights the creation of testable hypotheses and the formation of ecological theory. Chapter 2 uses empirical dynamic modeling to answer questions about the predictability of harmful algal blooms. It highlights the use of non-parametric methods to solve practical problems. Chapter 3 describes the creation of a novel data visualization technique. It represents the influence of ecological assumptions and extends the methodological toolset available to the scientific community. In Chapter 4, I use descriptive statistics to understand the interactions among phytoplankton populations. Lastly, Chapter 5 is a global geometric analysis on satellite remote sensing datasets, highlighting the challenges and opportunities of ecological “Big Data” and the unique methodological considerations of satellite oceanography.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Agarwal, Vitul, "AN EXPLORATION OF THE QUANTITATIVE METHODS USED IN THE STUDY OF PHYTOPLANKTON POPULATION DYNAMICS" (2024). Open Access Dissertations. Paper 1645.
https://digitalcommons.uri.edu/oa_diss/1645