Development of a benthic macroinvertebrate multimetric index for large semiwadeable rivers in the Mid-Atlantic region of the USA

  • Dustin R. ShullEmail author
  • Zachary M. Smith
  • Gordon M. Selckmann


To meet the objective of protecting water quality standards outlined in the US Clean Water Act, many agencies and organizations have created standardized biological assessment methods to evaluate aquatic ecosystem integrity. However, few Mid-Atlantic states have assessment methods specifically designed for rivers with drainage areas ≥ 2600 km2. Most rivers in this region fall into a semiwadeable category, where both wadeable and nonwadeable biological collection methods are difficult to implement. Additionally, these rivers often transcend state boundaries, which hinder consistent assessment determinations between states. Consequently, we developed a benthic macroinvertebrate assessment tool using a modified wadeable collection method for large semiwadeable rivers that can be used across state lines. Our results indicate that the two multimetric indices we developed (summer and autumn) are uniquely effective at distinguishing between least disturbed and stressed environmental conditions.


Large river Water quality Biological assessment 



This project was made possible through financial support provided by the US Environmental Protection Agency. We would like to sincerely thank those who contributed to collecting transect and macroinvertebrate data over the years. Without their efforts and collaboration, this study would not have been possible. Specifically, we sincerely thank Aaron Henning and other members of the Susquehanna River Basin Commission who collected samples north of Pennsylvania. This work would not have been possible without the training support and thoughtful review of Greg Pond and Louis Reynolds of United States Environmental Protection Agency, and Bob Limbeck of the Delaware River Basin Commission. We also greatly appreciate the thoughtful review, comments, and recommendations of our referees.


  1. Applegate, J. M., Baumann, P. C., Emery, E. B., & Wooten, M. W. (2007). First steps in developing a multimetric macroinvertebrate index for the Ohio River. River Research and Applications, 23, 683–697.CrossRefGoogle Scholar
  2. Astin, L. E. (2007). Developing biological indicators from diverse data: The Potomac Basin-wide Index of Benthic Integrity (B-IBI). Ecological Indicators, 7, 895–908.CrossRefGoogle Scholar
  3. Baptista, D. F., de Souza, R. G., Vieira, C. A., Mugnai, R., Souza, A. S., & de Oliveira, R. S. (2011). Multimetric index for assessing ecological condition of running waters in the upper reaches of the Piabanha-Paquequer-Preto Basin, Rio de Janeiro, Brazil. Zoologia, 28, 619–628.CrossRefGoogle Scholar
  4. Barbour, M. T., Gerritsen, J., Snyder, B. D., & Stribling, J. B. (1999). Rapid bioassessment protocols for use in streams and wadeable rivers: Periphyton, benthic macroinvertebrates and fish, second edition. EPA 841-B-99-002. DC: U.S. Environmental Protection Agency. Office of Water. Washington.Google Scholar
  5. Becher, A., & Root, S. (1981). Ground water and geology of the Cumberland Valley, Cumberland County, Pennsylvania. Pennsylvania geological survey. In Available from Scholar
  6. Blocksom, K. A., & Johnson, B. R. (2009). Development of a regional macroinvertebrate index for large river bioassessment. Ecological Indicators, 9, 313–328.CrossRefGoogle Scholar
  7. Botts, W. (2009). An index of biological integrity (IBI) for “true” limestone streams. Pennsylvania Department of Environmental Protection. Pennsylvania: Harrisburg Available from: Scholar
  8. Bray, J. R., & Curtis, J. T. (1957). An ordination of the upland forest communities of southern Wisconsin. Ecological Monographies, 27, 325–349.CrossRefGoogle Scholar
  9. Calinski, T., & Harabasz, J. (1974). A dendrite method for cluster analysis. Communications in Statistics, 3, 1–27.Google Scholar
  10. Chalfant, B. A. (2012). A benthic index of biotic integrity for wadeable freestone streams in Pennsylvania. Pennsylvania Department of Environmental Protection. Pennsylvania: Harrisburg Available from: Scholar
  11. Chalfant, B. A. (2013). Wadeable riffle-run stream macroinvertebrate data collection protocol. Chapter 3. In D. R. Shull & M. J. Lookenbill (Eds.), Water quality monitoring protocols for streams and rivers (pp. 2–7). Pennsylvania: Pennsylvania Department of Environmental Protection. Harrisburg Available from: Scholar
  12. Chutter, F. M. (1972). An empirical biotic index of the quality of water in South African streams and rivers. Water Research, 6, 19–30.CrossRefGoogle Scholar
  13. Collier, K. J., Clapcott, J. E., Duggan, I. C., Hamilton, D. P., Hamer, M., & Young, R. G. (2013). Spatial variation of structural and functional indicators in a large New Zealand river. River Research and Applications, 29, 1277–1290.CrossRefGoogle Scholar
  14. Davies, S. P., & Jackson, S. K. (2006). The biological condition gradient: A descriptive model for interpreting change in aquatic ecosystems. Ecological Applications, 16, 1251–1266.CrossRefGoogle Scholar
  15. Davis, W. S., & Simon, T. P. (1995). In W. S. Davis & T. P. Simon (Eds.), Introduction to Biological assessment and criteria: tools for water resource planning and decision making (pp. 3–6). Boca Raton: CRC Press.Google Scholar
  16. Emery, E. B., Simon, T. P., McCormick, F. H., Angermeier, P. L., Deshon, J. E., Yoder, C. O., Sanders, R. E., Pearson, W. D., Hickman, G. D., Reash, R. J., & Thomas, J. A. (2003). Development of a multimetric index for assessing the biological condition of the Ohio River. Transactions of the American Fisheries Society, 132, 791–808.CrossRefGoogle Scholar
  17. Esri. (2017). World Imagery Basemap. (Available from:
  18. Gerritsen, J., & Jessup, B. (2007). Identification of the biological condition gradient for freestone (noncalcareous) streams of Pennsylvania. Prepared for United States Environmental Protection Agency and Pennsylvania Department of Environmental Protection. Tetra Tech, Inc. Owings Mills, Maryland.Google Scholar
  19. Gerritsen, J., Burton, J., & Barbour, M. T. (2000). A stream condition index for West Virginia wadeable streams. Tetra Tech, Inc. Owings Mills, Maryland.Google Scholar
  20. Griffith, M. B. (2014). Natural variation and current reference for specific conductivity and major ions in wadeable streams of the conterminous USA. Freshwater. Science, 33, 1–17.Google Scholar
  21. Hawkins, C. P. (2006). Quantifying biological integrity by taxonomic completeness: Its utility in regional and global assessments. Ecological Applications, 16, 1277–1294.CrossRefGoogle Scholar
  22. Hawkins, C. P., Norris, R. H., Hogue, J. N., & Feminella, J. W. (2000). Development and evaluation of predictive models for measuring the biological integrity of streams. Ecological Applications, 10, 1456–1477.CrossRefGoogle Scholar
  23. Hilsenhoff, W. L. (1977). Use of arthropods to evaluate water quality of streams. Technical Bulletin Number 100. Wisconsin Department of Natural Resources 15 pp. Madison, Wisconsin.Google Scholar
  24. Hilsenhoff, W. L. (1987). An improved biotic index of organic stream pollution. Great Lakes Entomol, 20, 31–39.Google Scholar
  25. Hilsenhoff, W. L. (1988). Rapid field assessment of organic pollution with a family-level biotic index. Journal of the North American Benthological Society, 7, 65–68.CrossRefGoogle Scholar
  26. Hering, D., Feld, C. K., Moog, O., & Ofenbock, T. (2006). Cook book for the development of a multimetric index for biological condition of aquatic ecosystems: Experiences from the European AQEM and STAR projects and related initiatives. Hydrobiologia, 566, 311–324.CrossRefGoogle Scholar
  27. Hoger, M. S. (2017). In-situ field meter and transect data collection protocol. Chapter 4. In D. R. Shull & M. J. Lookenbill (Eds.), Water quality monitoring protocols for streams and rivers (pp. 2–7). Pennsylvania: Pennsylvania Department of Environmental Protection. Harrisburg Available from: Scholar
  28. Hoger, M. S., Shull, D. R., & Lookenbill, M. J. (2017). Continuous physicochemical data collection protocol. Chapter 4. In D. R. Shull & M. J. Lookenbill (Eds.), Water quality monitoring protocols for streams and rivers (pp. 22–87). Pennsylvania: Pennsylvania Department of Environmental Protection. Harrisburg Available from: Scholar
  29. Homer, C. G., Dewitz, J. A., Yang, L., Jin, S., Danielson, P., Xian, G., Coulston, J., Herold, N. D., Wickham, J. D., & Megown, K. (2015). Completion of the 2011 National Land Cover Database for the conterminous United States—Representing a decade of land cover change information. Photogrammetric Engineering and Remote Sensing, 81, 345–354.Google Scholar
  30. Hughes, R. M. (1995). Defining acceptable biological status by comparing with reference conditions. Chapter 4. In W. S. Davis & T. P. Simon (Eds.), Biological assessment and criteria: tools for water resource planning and decision making (pp. 31–47). Boca Raton: CRC Press.Google Scholar
  31. Hunsaker, C. T., & Levine, D. A. (1995). Hierarchical approaches to the study of water quality in rivers. Bioscience, 45, 193–203.CrossRefGoogle Scholar
  32. Hurd, T. M. (2012). Determination of preferential groundwater flow patterns to Cumberland County springs with fluorescent dye tracing. Pennsylvania Geology, 42, 3–11.Google Scholar
  33. Johnson, B. L., Richardson, W. B., & Naimo, T. J. (1995). Past, present, and future concepts in large river ecology: How rivers function and how human activities influence river processes. BioScience, 45, 134–141.CrossRefGoogle Scholar
  34. Karr, J. R., & Chu, E. W. (1999). Restoring life in running waters: Better biological monitoring. Island Press, Washington, DC.Google Scholar
  35. Klemm, D. J., Blocksom, K. A., Fulk, F. A., Herlihy, A. T., Hughes, R. M., Kaufmann, P. R., Peck, D. V., Stoddard, J. L., Thoeny, W. T., Griffith, M. B., & Davis, W. S. (2003). Development and evaluation of a macroinvertebrate Biotic Integrity Index (MIBI) for regionally assessing Mid-Atlantic Highland streams. Environ Manag, 31, 656–669.CrossRefGoogle Scholar
  36. King, N. R., Mctammany, M. E., Wilson, M. J., Chakany, J. C., Coffin, H. N., & Reilly, M. E. (2014). Variability in macroinvertebrate communities of the Susquehanna River in Central Pennsylvania. J Pa Acad Sci, 88, 67–75.Google Scholar
  37. Le, S., Josse, J., & Husson, F. (2008). FactoMineR: An R package for multivariate analysis. J Stat Softw, 25, 1–18.CrossRefGoogle Scholar
  38. Maechler, M., Rousseeuw, P., Struyf, A., Hubert, M., & Hornik, K. (2014). Cluster: Cluster analysis basics and extensions. R package version 1., 15, 3.Google Scholar
  39. Mattson, K. M., & Angermeier, P. L. (2007). Integrating human impacts and ecological integrity into a riskbased protocol for conservation planning. Environmental Management, 39, 125–138.CrossRefGoogle Scholar
  40. McArdle, B. H., & Anderson, M. J. (2001). Fitting multivariate models to community data: A comment on distance-based redundancy analysis. Ecology, 82, 290–297.CrossRefGoogle Scholar
  41. Merritt, R. W., Cummins, K. W., & Berg, M. B. (editors). (2008). An Introduction to the aquatic insects of North America. 4 th edition. Kendall/Hunt Publishing Company, Dubuque, Iowa.Google Scholar
  42. Novotny, V. (2004). Linking pollution to water body integrity—Literature review. Center for Urban Environmental Studies, Northeastern University. Boston, Massachusetts.Google Scholar
  43. Oksanen, J. (2014). Cluster Analysis: Tutorial with R. University of Oulu, Oulu. Available from:
  44. Oksanen, J., Blanchet, G., Kindt, R., Legendre, P., Minchin, P. R., O'Hara, R. B., Simpson, G. L., Solymos, P., Stevens, H. H., & Wagner, H. (2016). vegan: Community ecology package. R package version, 2, 3–4 Available from: Scholar
  45. Olivero Sheldon, A., Barnett, A., & Anderson, M. G. (2015). A stream classification for the Appalachian region. The Nature Conservancy, Eastern Conservation Science, Eastern Regional Office. Boston, Massachusetts.Google Scholar
  46. PADEP. (2014). 2012–13 Susquehanna River sampling and assessment report. Pennsylvania Department of Environmental Protection, Harrisburg, Pennsylvania. Available from:
  47. Peterson, B. G., Carl, P., Boubt, K., Bennett, R., Ulrich, J., Zivot, E., Lestel, M., Balkissoon, K., & Wuertz, D. (2015). PerformanceAnalytics: Econometric tools for performance and risk analysis. Available from:
  48. Pond, G. P., Bailey, J. E., Lowman, B. M., & Whitman, M. J. (2013). Calibration and validation of a regionally and seasonally stratified macroinvertebrate index for West Virginia wadeable streams. Environmental Monitoring and Assessment, 185, 1515–1540.CrossRefGoogle Scholar
  49. Rao, C. R. (1995). A review of canonical coordinates and an alternative to correspondence analysis using Hellinger distance. Questiio, 19, 23–63.Google Scholar
  50. Revelle, W. (2017). psych: Procedures for psychological, psychometric, and personality research. Available from:
  51. Roth, N. E., Southerland, M. T., Chaillou, J. C., Vølstad, J. H., Weisberg, S. B., Wilson, H. T., Heimbuch, D. G., & Seibel, J. C. (1999). State of the streams: 1995-1997 Maryland biological stream survey results. Maryland Department of Natural Resources, Chesapeake Bay and Watershed Programs, Monitoring and Non-tidal Assessment, Annapolis, Maryland.Google Scholar
  52. Royer, T. V., Robinson, C. T., & Minshall, G. W. (2001). Development of macroinvertebrate-based index for bioassessment of Idaho Rivers. Environmental Management, 27, 627–636.CrossRefGoogle Scholar
  53. Ruspini, E. H. (1970). Numerical methods for fuzzy clustering. Information Sciences, 2, 319–350.CrossRefGoogle Scholar
  54. Scopel, C., (2014). Create watersheds and trace downstream in your ArcGIS Online web map. ArcGIS Blog. Environmental Systems Research Institute. Redlands, California. Available from:
  55. Shaw, T. (2002). Stream habitat data collection protocol. Chapter 5, pages 2–7. In Shull, D. R., and M. J. Lookenbill. (editors). Water quality monitoring protocols for streams and rivers. Pennsylvania Department of Environmental Protection. Harrisburg, Pennsylvania. Available from:
  56. Shull, D. R. (2013). Discrete water chemistry data collection protocol. Chapter 4, pages 8–21. In Shull, D. R., and M. J. Lookenbill. (editors). Water quality monitoring protocols for streams and rivers. Pennsylvania Department of Environmental Protection. Harrisburg, Pennsylvania. Available from:
  57. Shull, D. R. (2017). Macroinvertebrate laboratory subsampling and identification protocol. Chapter 3, pages 31–41. In Shull, D. R., and M. J. Lookenbill. (editors). Water quality monitoring protocols for streams and rivers. Pennsylvania Department of Environmental Protection. Harrisburg, Pennsylvania. Available from:
  58. Shull, D. R., & Lookenbill, M. J. (2017). Assessing the expansion of wadeable benthic macroinvertebrate collection methods in large semiwadeable rivers. Freshwater Science, 36, 683–691.CrossRefGoogle Scholar
  59. Shull, D. R., Stewart, R. L., Jr., Hurd, T., & Light, T. (2016). A case for unique habitat selection by Sigara mathesoni (Hemiptera: Corxidae) in South Central Pennsylvania. Northeastern Naturalist, 23, 174–183.CrossRefGoogle Scholar
  60. Sliva, L., & Williams, D. D. (2001). Buffer zone versus whole catchment approaches to studying land use impact on river water quality. Water Resources, 35, 3462–3472.Google Scholar
  61. Smith, Z. M., Buchanan, C., & Nagel, A. (2017). Refinement of the Basin-wide benthic index of biotic integrity for non-tidal streams and wadeable rivers in the Chesapeake Bay Watershed. Interstate Commission on the Potomac River Basin (ICPRB). Rockville, Maryland.Google Scholar
  62. Stoddard, J. L., Larsen, D. P., Hawkins, C. P., Johnson, R. K., & Norris, R. H. (2006). Setting expectations for the ecological condition of streams: The concept of reference condition. Ecological Applications, 16, 1267–1276.CrossRefGoogle Scholar
  63. Stranahan, S. Q. (1993). Susquehanna: River of dreams. Johns Hopkins University Press. Baltimore, Maryland.Google Scholar
  64. Stribling, J. B., Jessup, B. K., & Feldman, D. L. (2008). Precision of benthic macroinvertebrate indicators of stream condition in Montana. Journal of the North American Benthological Society, 27, 58–67.CrossRefGoogle Scholar
  65. USEPA. (2013). National rivers and streams assessment 2013–2014: Field operations manual—non-wadeable. EPA-841-B-12-009a. U.S. Environmental Protection Agency, Office of Water. Washington, DC.Google Scholar
  66. USEPA. (2016). National rivers and streams assessment 2008–2009: A collaborative study. EPA-841-R-16-007. U.S. Environmental Protection Agency, Washington, DC.Google Scholar
  67. USDT. (2015). National Transportation Atlas Database. Bureau of Transportation Statistics. Washington, DC. Available from:
  68. USGS. (2006). National Field Manual for the collection of water quality data. Chapter 4.1 - Surface Water Sampling: Collection methods at flowing-water and still-water sites. U.S. Geological Survey, Water Resources Office of Water Quality. Reston, Virginia. Available from:
  69. Vannote, R. L., Minshall, G. W., Cummins, K. W., Sedell, J. R., & Cushing, C. E. (1980). The river continuum concept. Canadian Journal of Fisheries and Aquatic Sciences, 37, 130–137.CrossRefGoogle Scholar
  70. Weigel, B. M., & Robertson, D. M. (2007). Identifying biotic integrity and water chemistry relations in nonwadeable rivers of Wisconsin: Toward the development of nutrient criteria. Environmental Management, 40, 691–708.CrossRefGoogle Scholar
  71. Weigel, B. M., & Dimick, J. J. (2011). Development, validation, and application of a macroinvertebrate based index of biotic integrity for nonwadeable rivers of Wisconsin. Journal of the North American Benthological Society, 30, 665–679.CrossRefGoogle Scholar
  72. Wessell, K. J., Merritt, R. W., Wilhelm, J. G. O., Allan, J. D., Cummins, K. W., & Uzarski, D. G. (2008). Biological evaluation of Michigan’s non-wadeable rivers using macroinvertebrates. Aquatic Ecosystem Health and Management, 11, 335–351.CrossRefGoogle Scholar
  73. Wickham, H. (2011). Plyr: The split-apply-combine strategy for data analysis. Journal of Statistical Software, 40(1), 1–29 Available from: Scholar
  74. Wickham, H., and R. Francois. (2016). dplyr: A grammar of data manipulation. Available from:

Copyright information

© This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply 2018

Authors and Affiliations

  1. 1.Pennsylvania Department of Environmental ProtectionHarrisburgUSA
  2. 2.Interstate Commission on the Potomac River BasinRockvilleUSA

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