Monitoring efforts strive to generate high quality information. Quality assurance (QA) and quality control (QC) are processes that ensure data integrity and minimize errors. Examples of good QA and QC practices include receiving proper training in monitoring methods, calibration, using electronic data capture tools that have built-in checks for errors, and reviewing data before leaving a point and at the end of the season. QA and QC occur throughout the monitoring process. Everyone involved in a monitoring effort is responsible for some portion of QA and QC. Make sure that everyone on your monitoring team is familiar with their QA and QC responsibilities. The Terrestrial AIM Data Management Protocol_V2.0 carefully explains QA and QC responsibilities for everyone involved with the process.
|Figure 1. Data collection in Colorado. Credit: BLM||Figure 2. Hesperostipa comata in Lander, WY. Credit: Ashley Woolman||Figure 3. Data Collection in Alaska. Credit: BLM|