Unpaid internship/semester project in statistics and R software programming, USDA Forest Service, Forest Inventory and Analysis Unit.
The USDA Forest Service, Forest Inventory and Analysis Unit (FIA) is seeking a highly-motivated individual to participate in a technology transfer activity in support of the Peruvian National Forest Inventory. FIA conducts an inventory of the nation’s forests, and reports on the status of and trends in forest resources in our country (see www.fia.fs.fed.us for more information). Part of that role is supporting the Forest Service’s International Programs (IP) group (https://www.fs.fed.us/about-agency/international-programs). IP coordinates technology transfer and other activities in support of broader agency and federal government goals.
One such activity was support IP and FIA offers to the national forest inventory of Peru (http://cop20.minam.gob.pe/en/ck/el-inventario-nacional-forestal-constituye-un-pilar-central-en-el-monitoreo-de-bosques-del-peru/). This includes helping design a system to go from raw data (tables of information collected in the field and processed in the office) to final reports that detail the status of Peru’s forest resources. This system involves software that takes tables in a relational database, combines them, and applies a statistical estimator like that described at https://onlinecourses.science.psu.edu/stat506/node/44 to produce estimates of things like total number of trees by species, or total biomass by forest type. These tables are used by managers to help guide management and policy in this important, ecologically diverse country.
We are seeking a qualified applicant who knows R statistical software coding and ideally has a good understanding of statistics, and is willing to help produce R scripts that help apply the estimator to the raw data tables to produce estimates that managers can use. The work would entail learning about the estimator (the psu.edu website above), using a template stored in Microsoft Excel and duplicated in basic R code, and making this code more user-friendly and amenable to producing cross-tabulations analogous to Pivot Tables in Microsoft Excel. Work could be conducted remotely, and could be completed in approximately 150-200 hours, depending upon skill level with R and statistics. If work is completed sooner, additional tasks could be assigned.
This project would give the candidate valuable skills in R programming working on a real-world project, and contribute to conservation efforts in Peru. Interested candidates should contact Andrew Lister, Research Forester, Northern FIA Unit, at [email protected] or 610.557.4038.