QUALITY ASSURANCE/QUALITY CONTROL PNW-FIA QUALITY ASSURANCE/QUALITY CONTROL (QA/QC) Phyllis C. Adams QA/QC Coordinator The Goal of the QA/QC program: “to ensure that all research data collected, synthesized, and utilized by or for the Forest Service are scientifically sound, of known quality and thoroughly documented.” USDA Forest Service, Research and Development. 1998. Quality Assurance Implementation Plan.

QA/QC for Data Collection Documenting Data Collection Methods Training Data Collectors Real-time Error Checking by Data Recorder Field Checks for Data Quality

Documenting the Data Collection Process Field Manual Special Studies Protocols Selection and Preparation of Plots for Data Collection

Training Data Collectors Basic & Advanced Data Collection Procedures Identification of Trees, Other Plants, Insects, & Diseases Safety First Aid Defensive Driving Professional Development – leadership – planning & organization – time management

Portable Data Recorder Information about plots loaded into PDR – ensures that crews have the information they need on site. PDR’s are programmed with data checks – helps determine if data are within certain bounds – a data item is entered for each required variable

Checks of Data Quality A training tool Evaluate specified tolerance and whether measurements meet the desired MQO’s Assure consistent & high quality data collection Measures variability

3 KINDS OF CHECK PLOTS Hot Check Cold Check Blind Plot QA Staff Conducts Check An informal inspection in which the QA measures behind the production crew and provides instant feedback regarding data quality. Hot Check An inspection done on production plots. The production crew is not present and has no knowledge beforehand that a plot is slated for inspection. Cold Check FIA Production Crew A plot revisited by a second crew during the same season; a second set of measurements is taken without data from the initial visit of that year. Blind Plot

Hot Check – A training tool OBJECTIVES: Identify and correct improper measurement techniques Answer questions Share techniques Clarify interpretation of the field manual OUTCOMES: Discrepancies are noted and discussed with the crew members on the spot Data errors are corrected in the field computer file The QA identifies and corrects problems with crew performance early in the field season; especially helpful for inexperienced crews Assures consistency

Cold Check – A quality control tool OBJECTIVES: Improve the quality of data collected through timely feedback to crews Guide training of the field crews Suggest clarifications for the FIA Manual Document the quality of data produced by crews OUTCOMES: Keep production crews on their toes Evaluates and corrects measurement techniques Improves clarity of field manual topics Identifies discrepancies: subsequent training addresses common errors

Blind Check – Quality Assessment & Evaluation OBJECTIVES: Estimate measurement variability Assess repeatability of measurements OUTCOMES: Two independent data sets provide a means to quantify variability Provides an indicator of data quality

Quality Assessment: What’s Next? 2005 Field Manual & Office Procedures 2-Tiered Training Program Certification Process for FIA Crews Consistency in Check Plot Protocol More detailed information tracking