Vegetation - Pickel Meadow Wildlife Area [ds3197]

The California Department of Fish and Wildlife (CDFW) created a fine-scale vegetation map of the Pickel Meadows meadow complex and adjacent uplands. CDFW conducted field reconnaissance assistance for this project, as well as accuracy assessment (AA) field data collection. CDFW’s Vegetation Classification and Mapping Program (VegCAMP) provided in-kind service to allocate and score the AA. The mapping study area consists of approximately 2,169 acres of Mono County. Work was performed on the project between 2021 and 2025. Field samples were collected between June 21 and June 25, 2021. The primary purpose of the project was to further CDFW’s goal of developing fine-scale digital vegetation maps as part of the California Biodiversity Initiative Roadmap of 2018.CDFW's VegCAMP developed the floristic vegetation classification used for the project based on existing vegetation types described in the Manual of California Vegetation Online (CNPS 2021) and the classification for the Modoc ecoregion (Boul et al. 2021). The floristic classification follows protocols compliant with the Federal Geographic Data Committee (FGDC) and National Vegetation Classification Standards (NVCS). The vegetation classification and mapping report with the vegetation key can be downloaded here: https://nrm.dfg.ca.gov/FileHandler.ashx?DocumentID=237989.The vegetation map was produced applying heads-up digitizing techniques using a 2018 base of one-meter National Agricultural Imagery Program (NAIP) imagery (true-color and color infrared), in conjunction with ancillary data and imagery sources, including 1" UAS imagery from June 2018. Map polygons are assessed for Vegetation Type, Percent Cover, Exotics, Development Disturbance, and other attributes. The minimum mapping unit (MMU) is 1 acre, with the exception of wetland and riparian types, which have an MMU of ½ acre. Field reconnaissance and accuracy assessment enhanced map quality. There were a total of 33 mapping classes. The overall users' map accuracy was 89.3% and overall producers' accuracy was 89.6%.