Natalie Nelson: Data Analytics and Integrative Modeling in Aquatic Ecosystems

Natalie Nelson

Dr. Natalie Nelson recently joined the faculty at NC State in the Department of Biological and Agricultural Engineering. Having spent significant time conducting research, Dr. Nelson now uses her experience to mentor NC State students in their research projects, specifically pertaining to aquatic systems. We spoke to Dr. Nelson to learn about her background and her eagerness to help her students pursue research projects in data analytics and integrative modeling to make a difference for water-based ecosystems.  

NC State: Tell me briefly about your academic background. Why did you decide to pursue this field? What brought you to NC State?

Natalie Nelson: My fondest memories from my childhood all center around the water. I grew up in Florida and had opportunities to explore the wide diversity of water resources present in my home state – from the rivers of grass in the Everglades to the artesian springs of North and Central Florida. This love of water and the outdoors, combined with a knack for math and biology, led to my pursuing a field that centers around applying engineering principles to develop solutions to land and water resource issues.

My degrees are in agricultural and biological engineering from the University of Florida, where I also pursued an interdisciplinary concentration in hydrologic sciences as a doctoral student. During my doctoral studies, I utilized a range of data analytic and integrated modeling approaches to investigate harmful algal bloom dynamics across freshwater and coastal systems in Florida. The main goal of my doctoral research was to shed light on the underlying causes of these blooms and to improve researchers’ and practitioners’ abilities to prevent blooms from occurring in our irreplaceable water resources.

I love research and mentoring students and knew that I wanted to build a career as an academic researcher. This career goal led me to NC State. Here, I have endless opportunities to work with bright and motivated students to develop strategies for natural resources management and contribute to the “Think and Do” mission of the university.

NC State: Generally, what is the focus of your research? Please describe one particular research project, including intent and anticipated outcomes.

NN: I lead the Biosystems Analytics Lab, studies from which take a data-intensive, management-focused and interdisciplinary approach to the study of complex biological system dynamics. “Biosystems” are systems in which biological processes play a consequential role (e.g., ecosystems). Biosystems studied in the lab range from agricultural to aquatic, though most investigations presently focus on estuarine resources.

One project that I’m particularly excited about is being carried out by my Ph.D. student, Lise Montefiore. Lise is analyzing large public datasets to identify estuaries in the Southeast United States that are at risk of becoming degraded as a function of future climate and land use change. From this work, Lise will highlight projected “hotspots” of expected estuarine change, results from which will inform regional planning related to urban and natural resources management.

NC State: How do you use data analytics and integrative modeling in your research on aquatic ecosystems? How does it work? Why do you think it is effective?

NN: From extra-terrestrial satellites to sensors that are installed in the field, our natural resources are increasingly outfitted with novel instruments designed for high-resolution monitoring. The advent of cost-efficient sensors now allows for a huge variety of biological, physicochemical and socioeconomic factors to be observed at unprecedented rates and scales, but these sensors are producing data at rates that often exceed what we’re able to process using traditional approaches for data analysis.

New statistical methods (e..g, data analytics) have been developed to extract useful information from these data. These approaches are at the center of my research program. Data analytic methods identify patterns and relationships in data, and we can use this information to make inferences about the dynamics of the system from which the data were collected. We can also use similar approaches (e.g., integrated models) to simulate the relationships and patterns that we uncover from observational data, thus allowing us to make predictions about how a system’s dynamics will change under different scenarios (e.g., various environmental conditions).

NC State: How do you engage students in your research?

NN: My research is driven by student involvement. In addition to Lise, I have another Ph.D. student starting in Fall 2018 and three undergraduate research assistants who are analyzing a variety of datasets. I am always eager to recruit enthusiastic and motivated students into this team of up-and-coming researchers!

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