Forest Inventory and Analysis Program tree plots for 20 species in the western USA

The Forest Iinventory and Analysis (FIA) Program collects, analyzes, and reports information on the status  and trends of America’s forests. This information can be used in many ways, such as in evaluating wildlife habitat conditions, assessing the sustainability of ecosystem management practices, and supporting planning and decision-making activities undertaken by public and private enterprises. The FIA Program combines this information with related data on insects, diseases, and other types of forest damages and stressors to assess the health condition and potential future risks to forests. The program also projects what the forests are likely to be in 10 to 50 years under various scenarios. This information is essential for evaluating whether current forest management practices are sustainable in the long run and whether current policies will allow future generations to enjoy America’s forests.
 
To assist users in utilizing the FIA data while preserving owner privacy, FIA uses a technique whereby the plot coordinate data are slightly altered (fuzzed) and some of the plot data are exchanged (swapped). The purpose is to maintain the functional value, or “ecological signal” of the data while introducing enough uncertainty to decouple the plot-landowner relationship. The ‘fuzzing’ procedure consists of randomly relocating most plot latitude and longitude coordinates within one-half mile of their actual coordinates, with the remainder relocated up to 1 mile. This means that the actual plot location is generally masked within a 500-acre area.

“Swapping” consists of exchanging the plot coordinates for a small number of similar plots within the same county. Swapping only occurs on private forested plots and depends on the region of the country. Between 0 and 10 percent of the forested plots are randomly selected for swapping with plots from the remaining data for a total swapping of between 0 and 25 percent. The primary criterion for swapping is based on a measure of ecological similarity. Plots with the smallest ecological difference are swapped. The variables for swapping—e.g., x and y coordinates, forest type group, and stand size—vary by region. This induces enough uncertainty as to the actual property owner to satisfy the legal requirements without introducing an unacceptable amount of error in the population estimates computed for analyses.