Uncovering phenology patterns of old-growth forests in webcam images
Faculty mentor/Supervisor: 
Christopher Still
Department Affiliation: 
Forest Ecosystems & Society
Job Location: 
Work is planned to be entirely on a computer so can be done anywhere the student prefers.
Description of project or research opportunity: 
We are looking for a motivated undergraduate student who will be responsible for helping to collect, organize, and analyze camera images for a study exploring the phenology of vegetation at the HJ Andrews Experimental Forest. Phenology is the scientific study of periodic events in biological life cycles and understanding how these events (like leaf-on and leaf-off) are influenced by variations in climate. The student will be responsible for assisting with organizing images collected by approximately 3 dozen phenocams (webcams and timelapse cameras) installed around the Andrews watershed (https://andrewsforest.oregonstate.edu/about/webcams). The student will also be trained in the analysis of camera images and gain exposure to basic image processing and data analysis methods. The student will be mentored by Prof. Still and Prof. Mark Schulze (and affiliate faculty Dr. Julia Jones) and also work closely with a graduate student (Adam Sibley). The student will additionally benefit from interaction with other post-docs and graduate students within the Still lab through attendance of regular lab meetings over Zoom.
Tasks student will perform: 
The student will learn how to conduct basic image analyses. In the process of doing this, the student will focus on these specific tasks (with the help and guidance of Drs. Still and Schulze): 1. The student will conduct basic QA/QC of images in order to remove blurry images and to extract subsets of midday images from the full period of record from each camera site to use in analysis and extract basic information on weather conditions 2. The student will conduct basic image analysis of webcam data to understand how image patterns relate to phenology (like bud break, leaf-on, and leaf-off events)
Special skills required: 
I anticipate that the student will be familiar with basic computer tasks and some programing language and/or software packages, such as MS Excel, MATLAB, or R. As the planned research tasks are based entirely on working with computers, basic or intermediate levels of computer skills and data analysis are helpful for this position. Enthusiasm for exploring data will be helpful.
Hourly rate of pay: 
Proposed dates of employment: 
Monday, October 12, 2020 to Friday, June 4, 2021
Anticipated hours worked per week: 
Proposal Type: 
Mentored Employment Program
COVID-19 Pandemic Response: 
As this work is entirely computer based, it does not require being on campus or meeting in person. As part of this project I plan set up a shared virtual workspace on Slack and connect with the student regularly for check-ins and updates using Zoom.