1. 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 Quality Assurance Implementation Plan.

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

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

4. 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

5. 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

6. 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

7. 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

8. 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

9. 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

10. 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

11. 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