ASSESSMENT OF ECOLOGICAL CONDITION IN STREAMS OF THE CENTRAL PLAINS: Multimetric and Predictive Modeling Techniques

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1 ASSESSMENT OF ECOLOGICAL CONDITION IN STREAMS OF THE CENTRAL PLAINS: Multimetric and Predictive Modeling Techniques R. William Bouchard Jr. & Donald G. Huggins Central Plains Center for BioAssessment, Kansas Biological Survey, University of Kansas, 2021 Constant Ave., Lawrence, KS P C C B

2 Introduction Compare macroinvertebrate multimetric and predictive modeling approaches for assessing the health of headwater streams in the WCBP ecoregion. Discuss some strengths and weaknesses of the multimetric and predictive modeling techniques. Discuss future considerations for biological assessment of streams in the Great Plains.

3 Data Data from two studies were used to assess multimetric and predictive modeling techniques in 3 rd and 4 th order streams. - Tristate study ( ): 1995): A multi-state study designed to assess the effects of agricultural NPSP in the WCBP ecoregion. - Regional Reference study (1999-): An ongoing study of nutrient enrichment and nutrient benchmark development. Tristate and Regional Reference sites were sampled for numerous water quality, geomorphology/habitat, and biological parameters.

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5 Methods Stream condition was predicted using a watershed assessment procedure, which employed measures independent of the biota (water quality, in-/near /near- stream habitat, and land use/land cover). An Invertebrate Community Index (ICI) was developed from standard methods (Gibson et al. 1996, and Barbour et al. 1999). Predictive modeling approaches were developed from numerous sources (Wright 1995, Smith et al. 1999, and Hawkins et al. 2000). However, due to a limited number of reference sites, multivariate steps were removed and an ecoregion classification was used. Both approaches were calculated for macroinvertebrates using family and generic resolutions.

6 Testing of Approaches Approaches were tested by their ability to correctly identify sites as reference or impacted based on the Watershed Index. Classifications were based on the reference site 25 th percentile. For these tests, Tristate test, Tristate reference replicate, and Regional Reference sites were tested.

7 Results Tristate test and reference sites samples were most accurately assessed by predictive modeling. There was no difference among models when Regional Reference sites were assessed. Classification accuracy for multimetric and predictive models for various taxonomic resolutions and taxa groups. Taxonomy Approach Tristate Test Site Assessment (N = 22) Accuracy % Accuracy Tristate Reference Site Assessment (N = 17) Accuracy % Accuracy 9 of 17 53% 13 of 17 77% Regional Reference Site Assessment (N = 8) Accuracy % Accuracy Multimetric 8 of 22 36% 6 of 8 75% Family Predictive 11 of 22 50% 6 of 8 75% Multimetric 10 of 22 45% 13 of 17 77% 6 of 8 75% Genus Predictive 17 of 22 77% 14 of 17 82% 6 of 8 75%

8 Bioassessment Approach Conclusions Predictive modeling performed as good or better than the multimetric approach. Generic resolution models were as or more accurate than family resolution. The positive results of the predictive modeling technique indicate that this approach deserves more attention. However, no single assessment approach is likely to perform consistently better in all situations, as these techniques have strengths and weaknesses.

9 Comparison of predictive modeling and multimetric attributes important in this study (modified from Karr & Chu (2000) and Norris & Hawkins (2000)). Required Dataset Sampling Period Faunal Group Large Predictive Modeling Multiple or single season Macroinvertebrates (although other groups should be applicable) Multimetric Smaller than predictive modeling, but still considerable Defined sampling period Macroinvertebrates, fishes, algae Reference Sites Site Classification Development of Reference Criteria and Model Calculation Sites without serious human disturbance Suite of environmental factors (stream size, geography, water chemistry, substrate, date) minimally influenced by human activities Standardized multivariate techniques which are complicated and difficult initially Sites with little or no human disturbance Ecoregion (geology, land use, stream size, temperature, altitude) Straightforward although fine tuning of reference criteria can be complicated and variable Rare Species Basis for Assessing Impact Communication Excluded Presence/absence of taxa Concept easy to explain Included Structure and function of community Concept less clear

10 Approach Similarities Both multimetric and predictive modeling techniques use the reference condition approach to compare test sites to a group of reference sites with similar environmental characteristics. These approaches also require similar biological, physical, and chemical data.

11 Development of Reference Condition Both approaches use similar methods to select reference sites (e.g. professional judgment and existing data). Predictive modeling employs standardized techniques to develop a reference condition, which can be applied across broad regions. Multimetric methods tend to vary across regions. Candidate metric selection can vary among agencies, stream size, region, etc. Metric scoring can also be highly variable. Multivariate techniques used to fine tune criteria also vary among programs.

12 Basis for Assessing Impact Predictive Modeling Uses the presence and absence of individual taxa. Less well tested than the multimetric approach. Multimetric Incorporates structural and functional measures of biotic communities, which are well understood direct measures of biotic integrity. Uses rare taxa in assessments. Requires fewer reference sites.

13 Model Calculation The predictive modeling approach is often associated with a widespread and easily accessible computer program for the calculation of the O/E. No such program is generally available for multimetric indices. Advantages of computer program: Ease of index calculation. Standardization of sampling methods and approach development. Improved testing of methods (classification schemes, taxonomic resolution, sampling periods, assessment approaches, etc).

14 Summary There is no bioassessment silver bullet, but the approaches developed thus far have strengths that can be utilized to develop successful stream assessment programs. Despite methodological differences between multimetric and predictive modeling approaches, both techniques use the reference condition approach, which provides a basis for their incorporation. Combinations of multimetric and predictive modeling techniques should be tested to improve techniques and increase the tools available to bioassessment practitioners. Development of computer programs will allow better testing of approaches and enhance the assessment capabilities of bioassessment programs.

15 Acknowledgements My thesis committee: Dr. Donald Huggins, Dr. James Thorp, and Dr. Jerry denoyelles. Past and current Central Plains Center for BioAssessment and Kansas Biological Survey staff for collecting the data used in this study as well as providing support and advise throughout this study.