USFS Office/Lab and Location: A research opportunity is available at the U.S. Department of Agriculture (USDA) Forest Service (USFS), located in Corvallis or Portland, Oregon. 

At the heart of the U.S. Forest Service’s mission is their purpose. Everything they do is intended to help sustain forests and grasslands for present and future generations. Why? Because their stewardship work supports nature in sustaining life. This is the purpose that drives the agency’s mission and motivates their work across the agency. It’s been there from the agency’s very beginning, and it still drives them. To advance the mission and serve their purpose, the U.S. Forest Service balances the short and long-term needs of people and nature by: working in collaboration with communities and our partners; providing access to resources and experiences that promote economic, ecological, and social vitality; connecting people to the land and one another; and delivering world-class science, technology and land management.

Research Project: The agency’s monitoring of sequestration and emissions of carbon from forest lands has led to a need for managers and policy-makers to evaluate alternative approaches to managing and regulating forests on the West Coast. The selected participant will collaborate with staff to identify the strengths, weaknesses, and data requirements of alternative simulation models of forest carbon; compare the projections from alternative models with current status and dynamics of regional forests from Forest Inventory and Analysis (FIA) measurements; and help formulate recommendations for a modeling framework that builds on the extensive carbon inventories in the region. 

Under the guidance of a mentor, the participant will be given the opportunity to (1) continue their professional development through immersion in carbon projections to meet regional land management challenges, (2) inform and contribute to decisions regarding forest, watershed, soil, and fire evaluation and management, (3) gain an understanding of complex natural systems and their representation in models, and (4) pursue research related to the intersection of natural resource management and carbon storage in forests and forest products.

Learning Objectives: The learning objectives for the project include: understanding the implicit goals and data requirements of alternative state-of-the-art forest ecosystem carbon models, learning to run one or more vegetation dynamics models in contrasting landscapes, and gaining experience in the analysis of large-scale multi-attribute temporal data from permanent inventory plots. 

Anticipated Appointment Start Date: September 1, 2022.  Start date is flexible and negotiable, and will depend on a variety of factors.

Appointment Length: The appointment will initially be for one year and eight months, but may be extended upon recommendation of USFS and is contingent on the availability of funds.

Level of Participation: The appointment is full-time.

Participant Stipend: The participant will receive a monthly stipend commensurate with educational level and experience.

ORISE Information: This program, administered by ORAU through its contract with the U.S. Department of Energy (DOE) to manage the Oak Ridge Institute for Science and Education (ORISE), was established through an interagency agreement between DOE and USFS. Participants do not become employees of USDA, USFS, DOE or the program administrator, and there are no employment-related benefits. Proof of health insurance is required for participation in this program. Health insurance can be obtained through ORISE.

Qualifications

The qualified candidate should have received a master’s or doctoral degree in one of the relevant fields (e.g. Forestry, Natural Resource Science/Management), or be currently pursuing one of the degrees with completion by December 2022.

Candidates with demonstrated experience in quantitative analysis of data from forest ecosystems are preferred. 

Preferred skills:

• Experience in analyzing forest ecosystem vegetation dynamics
• Demonstrated computing skills for analyzing complex datasets and interpreting output.
• Strong written and verbal communication skills
• Experience in sharing technical natural resource information with decision-makers and researchers through print and presentations