Job Type: Full-time, Hybrid
Location: Olympia, WA
Salary: $67,716.00 - $91,068.00 Annually
Deadline: 12/26/2024
Want to join something GREAT and make a difference?
The Washington Department of Natural Resources’ Forest Resilience Division is seeking to hire a Forest Health Scientist to join our team of scientists and planners that assess, plan, coordinate, and monitor forest health-related activities that seek to restore and enhance the resilience of Washington’s forested landscapes.
If you are an analyst or scientist that has a passion for assessing and monitoring landscape-level forest conditions using remotely sensed datasets, tackling challenging ecological and forest management research questions, developing innovative analytical tools, communicating complex scientific topics, and working collaboratively with internal and external partners, we want to hear from you!
The Forest Health Scientist focuses on landscape-level evaluation and monitoring of forest conditions related to the goals of the 20-Year Forest Health Strategic Plan for Eastern Washington and Washington’s Forest Action Plan. This position leads analysis and development of remotely sensed datasets to monitor the effects of treatments, wildfires, drought, insects, and other disturbances on forest conditions and resilience indicators. The position performs analyses related to drought vulnerability, post-fire restoration. climate adaptation, fire modeling, and other forest health needs. This position collaborates closely with DNR scientists and analysts, external researchers, and other DNR partners to develop and implement methods for regional monitoring of forest health and participates in relevant research partnerships. This position reports monitoring results to a range of audiences in presentations, web apps, written reports, and scientific journals.
Responsibilities:
Utilize multiscale, remotely sensed and field-based datasets to detect, attribute, and analyze changes in forest conditions from treatments and other disturbances. Develop and run related accuracy assessments.
Analyze and assess the effects of treatments, fire, insect, and other disturbances on landscape-level forest health indicators and resilience objectives.
Model and map vegetation and biophysical conditions using a variety of datasets and methods. These include forest structure and composition, vegetation type, climate, and topo-edaphic conditions.
Maintain vegetation and other large-scale datasets and tools used for landscape evaluations and monitoring. Develop and improve where needed. Manage distribution and documentation of these datasets.
Collaborate with DNR scientists, external researchers and other partners to ensure that DNR is using current science for planning and monitoring. Serve on relevant internal and external technical working groups.
Lead or assist with analyses related to landscape evaluations, drought vulnerability, postfire restoration need, work of wildfire assessments, fire modeling, or other topics. Provide assistance related to study design, statistical methods, and display of results in figures and web apps.
Present results of forest health monitoring analysis and research efforts to technical and non-technical audiences at meetings and conferences.
Work with the forest health science team to publish results and document methods in reports and peer-reviewed publications. Opportunity to be a lead author, but not required.
Required Qualifications:
A bachelor’s degree with a major study in natural resource science (e.g. forestry, ecology, landscape ecology, fire science, wildlife biology, remote sensing) or a closely related field AND three years of professional work experience in remote sensing, ecology, fire science, landscape ecology, forest management, wildlife management or a closely related field. OR an equivalent combination of education and/or experience.
Experience in processing, analyzing, and managing large, remotely sensed and field-based datasets to address natural resource questions. Experience with LiDAR, aerial imagery, and satellite imagery is needed.
Proficiency in R, ArcPro, and Google Earth Engine.
Experience writing technical reports and documents, including creating maps, figures, and graphics that effectively and creatively communicate results of analyses and research.
Knowledge of vegetation change detection methods and datasets.
Knowledge of spatial and non-spatial modeling concepts and methods to model current conditions and predicted changes in forest conditions and forest health indicators over time. Knowledge of a variety of modeling approaches, including machine learning, is needed.
Working knowledge of the Scientific Method, including sound understanding and working knowledge of experimental design, sampling procedures, systematic literature reviews, error assessment methods, data analysis procedures, and both spatial and non-spatial statistical techniques.
Commitment to fostering and supporting an environment that honors diversity, equity, inclusion, and environmental justice practices.
Perform assigned duties in a manner consistent with applicable laws, regulations and public records retention and requests are followed.
