Powerpoint template for scientific posters (Swarthmore College)

1
Development and Application of a
Performance-based System Approach Framework Using
Comparisons of Macroinvertebrate Field and
Laboratory Protocols Mike Miller and Alison
Colby, Wisconsin Dept. of Natural Resources,
Madison, WI Jerry Diamond, Sam Stribling, and
Colin Hill, Tetra Tech, Inc. Owing Mills, MD and
Kurt Schmude, Univ. of WI-Superior, Superior, WI

• For this study a total of 300 macroinvertebrate
  samples were collected from 48 streams. Of
  these, 36 samples have been processed and are
  used in the analyses presented here.
• To Evaluate Laboratory Sample Processing
  Procedures, Sub-samples Were Analyzed by a Second
  Lab to Measure
• Sub-sample sorting bias
• Specimen enumeration precision
• Taxonomic identification precision
• To Measure the Precision Within and Between Field
  Sample-Collectors
• 2 people each collected 2 replicate samples
  within the same reaches of multiple small and
  large least-impacted reference streams.
• To Measure the Precision of Single Habitat Vs
  Multiple Habitat Sampling Methods
• 2 people each collected 2 riffle samples and 2
  multi-habitat samples from a number of small
  and large least-impacted reference streams

Preliminary Results (Con.)
Preliminary Results (Con.)

• A performance-based system (PBS) approach is a
  process that can be used to measure quality
  control characteristics of various aspects of
  field sampling and laboratory analyses. This
  information can then be used to identify sources
  of error in these processes, and if necessary,
  take corrective actions to improve resulting data
  quality. The National Water Quality Monitoring
  Councils (NWQMC) Methods and Data Comparability
  Board has been promoting the use of a PBS
  approach to objectively set data quality
  objectives (DQOs) and document the rigor of field
  and laboratory methods. While the utility of PBS
  has been described (Refs 2, 3), there are few
  published examples of the application of PBS to
  field or lab biological sampling and analytical
  methods (Ref 1, 4). The Wisconsin Department of
  Natural Resources in cooperation with the Methods
  Board is piloting the use of a PBS-approach to
  evaluate, and if necessary, refine field and lab
  methods for the collection, sub-sampling, and
  identification of aquatic macroinvertebrate
  samples used to assess the condition of streams
  in Wisconsin. The findings of this pilot project
  will be used to provide a framework and example
  of how a PBS-approach can be applied to
  biological sampling and aquatic resource
  assessment.

Materials and Methods
Introduction
The Influence of Laboratory Sub-Sample Size
(100-, 300-, 500-organism) on Sample Variance
Taxonomic Identification Enumeration Precision
-Determined by
Percent Difference in Enumeration (PDE)
Percent Taxonomic Disagreement (PTD)
Field sampling precision, Sampler A, multihabitat
(n8 pairs of samples and replicates)
Subsample size
Coefficient of variability (CV)
Field sampling precision, Sampler B, multihabitat
(n10 pairs of samples and replicates )
Subsample size
Coefficient of variability (CV)
Target MQO PTD 15 Target MQO PDE 5
Study Area Wisconsin Driftless Area Ecoregion
Preliminary Results Laboratory Sorting Bias -
Determined by Percent Sorting Efficiency (PSE)
Comparison of Variance Within and Between Field
Sample Collectors and Single and Multi-Habitat
Samples

• Additional Analyses
• Measure the sensitivity of single and
  multi-habitat sampling in detecting stream
  stressors sedimentation and eutrophication
• Evaluate the sensitivity of laboratory sub-sample
  size in detecting stream quality 100, 300, and
  500 organism sub-samples are being processed
• Evaluate the level of taxonomic identification
  family level versus lowest practical level
  (genus-species).

Within-sampler variability (precision), Sampler
A, 300-organism subsamples (n4 sample pairs)
Coefficient of variability (CV)

• Literature cited
• Barbour, M. T., J. Gerritsen, G. E. Griffith, R.
  Frydenborg, E. McCarron, J. S. White, M. L.
  Bastian. 1996. A framework for biological
  criteria for Florida streams using benthic
  macroinvertebrates. J. N. Am. Benthol. Soc.
  15179-184.
• Diamond, J. M., M. T. Barbour, J. B. Stribling.
  1996. Characterizing and comparing bioassessment
  methods and their results a perspective. J. N.
  Am. Benthol. Soc. 15(4)713-727.
• ITFM. 1995. The strategy for improving
  water-quality monitoring in the United States.
  Final report of the Intergovernmental Task Force
  on Monitoring Water Quality (ITFM). Office of
  Water Dara Coordination, U.S. Geological Survey,
  Reston, VA. OFR 95-742.
• Stribling, J. B., S. R. Moulton II, G. T.
  Lester. 2003. Determining the quality of
  taxonomic data. J. N. Am. Benthol. Soc.
  22(4)621-631.

Within-sampler variability (precision), Sampler
B, 300-organism subsamples (n5 sample pairs)

Coefficient of variability (CV)
Target Measurement Quality Objective (MQO) PSE
90
Target MQO To be determined
Members of the NWQMC-Methods Board