Research Experience for Undergraduates (REU) Summer 2020: An environmental justice approach to data-intensive lake research
By Jessica Díaz Vázquez
I joined the Data Intensive Landscape Limnology Lab in October 2018 to gain research experience in the general field of ecology. As I learned more about the database LAGOS and the openness of the lab for interdisciplinary research, I saw an opportunity to incorporate my interest in environmental justice.
I grew up in Northeast Houston, Texas in a predominantly latinx and low-income community that is adjacent to petrochemical plants and oil refineries. Living in a ‘frontline’ or environmental justice community means that the topics of health, racial/ethnic identity, economic status, and natural environment are extremely interconnected. Just like any other community, we love our backyard gardens, neighborhood parks, and local bayous. However, the disproportionate burden of air and water pollution make outdoor activities much less pleasant or healthy. From my lived experiences and as a rising senior in MSU’s Department of Fisheries & Wildlife, I seek to improve the habitat of wildlife and expose and correct environmental injustices. I am excited to apply my combined knowledge in fisheries & wildlife and environmental justice through this REU position.
The overall goals of this REU position are to integrate information about lake watersheds and lake water quality with human demographics and apply an environmental justice lens. I hope to answer the question: Are people and communities within marginalized demographics (e.g., low income, people of color, younger/older people) disproportionately affected by low water quality lakes and their watersheds?
For my research, I am using lake and watershed data from the LAGOS database that covers the conterminous U.S. Therefore, the human demographic data used must be compatible with this large scale. I am using tract-level data from the 2010 Decennial Census and the American Community Survey (ACS). The main variables that I will focus on for lakes are those that together serve as a measure of water quality: water clarity, phosphorus, and nitrogen. For the human demographic variables, I will choose those of interest in the environmental field, such as median household income, race/ethnicity, population, and sex. Figure 1 is an example of a visual output resulting from linking watersheds and median household income for LAGOS-NE.
Although I expect challenges to arise from working with two unique databases (LAGOS and ACS), I look forward to bringing a new perspective to the research group. Stay tuned for an update at the conclusion of my summer 2020 REU!