Parameterizing PNW tree species for simulation modeling
Faculty mentor/Supervisor
Emily Conklin
Email Address
Department Affiliation
Forest Ecosystems & Society
Project Location
Mentor is based in Corvallis, but work location can be flexible/remote
Project Description
This project addresses our need to understand post-fire trajectories of moist temperate forests in the Western Cascades. These landscapes were historically exposed to a mixed-severity fire regime, with more frequent low- to moderate-severity fires interspersed with rarer large, high-severity fires driven by severe drought and fire weather. Contemporary fires are increasing in both frequency and average severity following a century of fire exclusion in conjunction with climate change. As a result, there is substantial uncertainty about how to apply existing fire-focused forest management knowledge that was developed in drier western ecosystems, and about the impacts of these management decisions on ecosystem processes and services in moist northwestern forests. Using the individual-based model iLand alongside long-term data collected at the H.J. Andrews Experimental Forest, we will explore how projected fire, climate, and management regimes affect future forest resilience and ecosystem processes. As part of this project, researchers at the University of Washington and Oregon State University are working to parameterize and benchmark the iLand model to improve its accuracy for Pacific Northwest landscapes.
Describe the type of work and tasks you anticipate the student will perform
The student will work to parameterize Pacific Northwest tree species currently missing from the iLand model. In particular, the work will focus on the species Arbutus menziesii (Pacific madrone), Calocedrus decurrens (incense cedar), Chamaecyparis nootkatensis (spach cedar), Pinus jeffreyi (Jeffrey pine), Pinus lambertiana (sugar pine), and Quercus garryana (Oregon white oak). Work will involve reviewing plant trait databases, peer-reviewed literature, and ‘grey’ literature, as well as consultation with domain experts, to compile species traits related to growth, biomass allocation, reproduction, and other aspects of life history. The student will be trained on literature review, data extraction, and data management techniques, and will follow a published protocol for parameterizing species in iLand. Following species parameterization, there is also the opportunity to become more involved in the simulation modeling project particularly in terms of ‘benchmarking,’ or comparing the new species’ model performance to field data. There is additional opportunity to learn R skills in data wrangling, visualization, and analysis.
Hourly rate of pay
15.05
Certification
Yes
What is the expected timeline of this project?
The anticipated start date for this project is Nov 12th, 2025 (or whenever the student applications are processed and students are notified) and may extend as long as June 12th, 2026. This end date is flexible and can be modified according to student needs. The expected weekly work schedule will take place M-F, between 9-5pm, part-time (maximum of 24 hours per week during academic terms). Outside of these guidelines, the exact timing for scheduling work is very flexible and can be modified based on student class schedules. There will also be a half-hour check in weekly.
Are special skills or knowledge required to work on this project?
No
Will training be provided?
Yes
How many hours per week do you anticipate a student to work?
Anticipated 8-10, but flexible
How many hours per week do you anticipate engaging in direct mentorship?
At the start of the project while the student needs more training and support, 2-3 hours per week. As the student becomes more independent, 1 hour per week.
Overall expectations for the mentor:
Provide literature review and data collection instructions and time for questions as mentee learns the new procedures.
Provide opportunities to be involved with the research process after parameterization, including data curation, figure prep, writing and editing.
Provide opportunities to network with other researchers, including invitations to Betts Lab meetings and iLand North America meetings.
Invite mentee to join for scientific talks in forestry and other departments.
Respond to questions in a timely manner and give mentee time to discuss any issues related to the projects.
On a weekly basis, meet to discuss questions about the research project or any questions the student has about being a researcher and the academic career path.
Provide literature review and data collection instructions and time for questions as mentee learns the new procedures.
Provide opportunities to be involved with the research process after parameterization, including data curation, figure prep, writing and editing.
Provide opportunities to network with other researchers, including invitations to Betts Lab meetings and iLand North America meetings.
Invite mentee to join for scientific talks in forestry and other departments.
Respond to questions in a timely manner and give mentee time to discuss any issues related to the projects.
On a weekly basis, meet to discuss questions about the research project or any questions the student has about being a researcher and the academic career path.