This winter, after I graduate from my master’s program, I will make the transition from school into the working world just as I did 10 years ago after completing my bachelor’s degree. The transition feels like a familiarly vulnerable time, wondering what jobs may be available to me and wondering if I understood my classes well enough to translate my new knowledge into practice. During grad school, I focused on learning data analysis techniques that would be relevant to my future employment. My DFP position gave me a glimpse into the working world and an opportunity to practice my new skills in a supportive environment. My experience has shown me that I can translate my foundational knowledge in statistics into practice and that my learning process may continue for the rest of my career.
My motivation to return to school was mainly to learn to analyze data. At the time I was working for the California Department of Fish and Wildlife, collecting data on desert fishes and their habitat to inform management decisions. My supervisor gave me opportunities to conduct my own projects from start to finish as a way to help me move up in my career. I was able to design and implement projects and manage databases but I didn’t know how to find meaning in the data that I was collecting. During my time as a graduate student, I made some progress towards my goal by taking a few statistics courses and analyzing data for my thesis research. Leading into this summer, however, I still wasn’t very confident in my abilities. It seemed like the more stats courses I took, the more I realized how little I knew.
My DFP position this summer gave me a huge boost of confidence in my abilities to analyze data. My project asked me to conduct a comparative population analysis of steelhead trout living in different drainages across the Central Valley of California. My supervisors encouraged me to dig into the literature and develop a research question that I found interesting and would be informative to management. I decided to investigate variables that influenced steelhead migration to determine if there were differences in fish movement between drainages. I found a couple of papers that described techniques to use for answering my questions and I proposed using a logistic regression model. I had never worked with a logistic regression model but I had worked with multi-variate models in one of my statistics courses and so I had some familiarity with what I needed to do. My supervisors looked over my methods, gave me some suggestions, and were available for answering questions throughout the process.
I spent the bulk of my time compiling the data from each drainage. I used the programming language R to scripts that paired fish catch data with environmental data for each river over the corresponding time frames. This part was tricky because not all of the data was available over the same time ranges for each river. Once I finally had a data set that was ready for analysis, I used a model selection technique to determine which variables explained fish movement best and how those variables differed between streams and over time. Once I selected the best model, I created figures that illustrated how each environmental variable related to fish movement. The output of the model provided insight into how dam regulation on each river may be creating differences in steelhead migration cues between rivers. The results of my analysis can be used by the Fish and Wildlife Service to inform water management strategies, and the coding language that I used to conduct the analysis can be used as a template for adding new rivers to create a basin-wide comparison.
Working on this project has given me the sense that I really have learned useful skills in graduate school. Prior to my DFP, I thought that I could only use statistics in a work environment if I was the expert on the content. I now see that working in an environment with mentorship from my supervisors can help me continue to grow my abilities and to learn how to use new techniques to answer new questions. I’m grateful to have had a DFP position and I’m especially thankful to my wonderful supervisors who encouraged me to be excited about my work and to learn new techniques.
Agency: U.S. Fish and Wildlife Service
Program: US Fish & Wildlife Service - DFP
Location: Lodi Fish and Wildlife Office
