Project Description: 

Large carnivores have experienced population declines and range contractions worldwide, but restoration programs have been successful in reestablishing carnivore populations in previously inhabited areas. Following restoration, large carnivores can affect the larger wildlife community both directly through predation, and indirectly through changes in space use or activity patterns. Therefore, understanding community-level responses to large carnivore restoration is critical.

This project will focus on understanding wildlife community responses to lion (Panthera leo) and cheetah (Acinonyx jubatus) restoration in a reserve in South Africa. Using camera trap data collected over a 3-year period following large carnivore restoration, we will investigate changes in occupancy, distribution, and abundance of mesocarnivore and prey species. A primary component of this project will be conducting analyses in Program R and summarizing results. This is a great opportunity for a student interested in learning more about how data analysis can inform conservation practices.

The student will be supervised by Laura Gigliotti (postdoc in the Middleton Lab). This will be an entirely remote project for the fall - all the work can be accomplished without being on campus. 

Department: 
ESPM
Undergraduate's Role: 

The student will be responsible for identifying animal species in photos taken by remote camera traps. When data processing is complete, we will work to analyze the data using Program R. Specifically, we will be running basic descriptive statistics (e.g. species richness, relative abundance indices) as well as more complex analyses such as occupancy in relation to time since carnivore restoration. We will also work on summarizing the analysis results using figures, tables, and text.

Undergraduate's Qualifications: 

Looking for a hardworking and self-motivated student with interests in wildlife ecology and statistical analysis. Prior experience with Program R (or other programming languages), statistics, and data analysis is preferred but not required.

Location: 
Remote
Hours: 
To be negotiated