Project Description: 

Camera traps are a valuable tool for wildlife ecologists to be able to remotely collect data on the distribution and behavior of wildlife species. Students will assist with camera trap data processing and analysis for one of two projects:

  1. Carnivore Community Response to a Novel Prey, the Magellanic Penguin: Rewilding efforts across the world are often predicated on restoring predator-prey relationships, which in theory will result in various ecological benefits. In Patagonia, rewilding has led to the increase of herbivores like guanacos and rhea, and their predator, the puma. However, along the Patagonia coast, pumas have switched to predating penguins. For this project, we are interested in using camera trap data already collected to estimate how the penguin colony is shaping the movement of pumas and other carnivores in Monte León National Park. Students will primarily classify and identify species in camera trap photos from our array in the park.
  2. Monitoring Wildlife Communities in South Africa: Wildlife reserves in South Africa are important for the conservation of a high diversity of predator and prey species. Obtaining accurate information on the distribution and abundance of species within reserves can be challenging because many species are cryptic or nocturnal. However, camera traps are a useful tool for collecting data on the entire wildlife community, which then can be used to help infom management decisions. Students will work to help identify species in camera trap photos.

Applicants should indicate in their Personal Statement which of the two projects they are interested in.

Undergraduate's Role: 

The students will be responsible for identifying animal species or behaviors in photos taken by remote camera traps. For self-motivated students, there may be additional opportunities to use the resulting data for subsequent analyses using Program R. 

Undergraduate's Qualifications: 

Looking for hardworking and self-motivated students 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.

On Campus
To be negotiated