Forest Ecology Field & Data Manager
Position in the FOCAL Lab and Latimer Lab, UC Davis
January or February - September 2023 (minimum), with option for extension through at least December (preferred)
Davis, California (UC Davis campus); first 1-2 months may be remote
Office (65-80%) and field (20-35%). Up to half of office work may optionally be performed remotely, but an in-person component is required. A desktop computer is available if desired.
50 - 100% depending on preference
For candidates with a bachelor’s or master’s degree: $27.09/hour
For candidates with a Ph.D., this position may be converted into a postdoc position, with commensurate compensation (approx. $58,000-$62,000/year) and additional opportunities for analysis and publication.
Coordinate the collection, management, and initial analysis of field-based and drone-based forest vegetation data to support forest ecology research projects.
This position will manage/co-manage several field technicians collecting data from California conifer forests, including burned and unburned sites. In collaboration with the PI, the position will help to recruit and train field crew members; prioritize data collection sites (based on GIS analysis and field scouting) and direct crews to sites; ensure high standards in data collection, data management, and field safety; and organize collected field data. The position will also assist in compiling and processing datasets in preparation for statistical analysis and may assist with some statistical analysis. The position will also include processing, quality control, and analysis of drone and other aerial imagery using automated workflows (with training provided). The position will support the following efforts: assessment of early (1-2 years) post-fire forest regeneration patterns, assessment of longer-term (~20 years) post-fire forest regeneration, development of drone-based forest mapping tools for the Open Forest Observatory, and assessment of large tree densities in unburned Sierra Nevada forests.
- Coordinate field data collection (in collaboration with PI)
- Examine existing data and use GIS to plan survey plot locations and prepare crew maps
- When necessary, independently perform field reconnaissance to confirm selected survey locations are suitable (e.g., accessible and appropriate forest type) prior to crew visit
- Interview, select, and train field crew members (approx. 3 students)
- Test and revise field survey methods
- Perform crew data quality control periodically throughout season
- Manage crew schedules
- Organize and prepare crew gear and vehicles
- Serve as emergency contact for crews
- Coordinate data entry
- Manage datasets and prepare them for analysis
- Clean field data (e.g., identify outliers, duplicated or missing plot IDs)
- Organize and assign plot IDs to collected photos (optionally using a scripted analysis)
- Compile multiple vegetation plot datasets from PI and collaborators into a standardized format; communicate with collaborators for clarification on data parameters if necessary
- Perform geospatial interpretation of aerial (including drone-derived) imagery to support validation of automated analysis methods (e.g., delineate vegetation types, record tree presence/absence in images)
- Inspect drone-derived imagery and use automated tools to process imagery into downstream products. Perform preliminary analysis of downstream products (e.g., compare drone-derived elevation to USGS DEM elevation).
- General research and lab assistance (as time allows)
- Analyze forest vegetation plot data to address research questions (with option to contribute to paper authorship)
- Search for journal articles relevant to post-fire forest recovery, and extract values to support a meta-analysis (with option to contribute to paper authorship).
- Assist other lab members with field and lab work
- Experience working on and leading ecology field crews
- Experience organizing ecological datasets
- Experience using GIS software for plot layout (map making) or other geospatial analysis
- Experience writing R and/or Python code for data processing and analysis
- Willingness to work both independently and collaboratively in the office and field
- Comfort with dispersed camping in remote locations without facilities
- Willingness to drive University or personal vehicle on remote forest roads independently to perform plot reconnaissance, meet crew, and check data quality
- Strong interpersonal skills for crew management
- Experience working successfully with individuals from diverse backgrounds
- Experience managing and organizing data in cloud storage such as Google Drive or Box
- Experience collaborating on code development using a platform such as GitHub
Please combine a statement of interest (including preferred start date and preferred time commitment), CV, and contact information for three references into a single PDF and email to Derek Young, firstname.lastname@example.org. Use the following subject line: Field & Data Manager. Application review will begin on December 9, 2022, and continue until the position is filled.