Analyzing Avian Community Structure Using Biodiversity Monitoring Data
Mentor & Lab: Reza Goljani Amirkhiz, Zavaleta lab
Positions: 1 intern
Tentative dates: 6/23/25 – 8/29/25
Project Location: Lab on Coastal Campus
Project Background: Are you passionate about birds and biodiversity? Join our research project, Analyzing Avian Community Structure Using Biodiversity Monitoring Data! This project investigates how environmental factors shape avian communities across diverse ecosystems. You’ll work with real-world data, learn cutting-edge statistical and spatial analysis techniques, and contribute to understanding how bird populations respond to environmental change. Ideal for students interested in ecology, conservation, or data science, this opportunity offers hands-on research experience and mentorship in a collaborative environment.
Intern duties:
As an intern for this project, you will play a key role in advancing our understanding of avian community structure. Your primary duties will include obtaining and organizing biodiversity monitoring data from various sources, ensuring it is properly formatted and accessible for analysis. You will also create and manage Geographic Information System (GIS) layers to spatially map bird distributions and environmental variables. This work will be instrumental in identifying patterns and relationships across avian communities.
Additionally, you will perform basic statistical analyses to help interpret the data and draw meaningful conclusions. Throughout the internship, you will receive training and mentorship in data management, GIS tools, and statistical techniques, making this an excellent opportunity to develop valuable skills for a career in ecology, conservation, or environmental science.
Intern qualifications:
Enthusiasm for ecology, ornithology, or environmental science.
Experience with or willingness to learn GIS tools such as ArcGIS.
Basic understanding of statistics and data analysis; experience with software like R, Python, or Excel is a plus.
Strong organizational skills and attention to detail for managing and formatting datasets.
Ability to work independently and collaboratively in a research environment.
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