Environmental Monitoring and Assessment

, Volume 186, Issue 2, pp 1167–1182 | Cite as

Relations between macroinvertebrates, nutrients, and water quality criteria in wadeable streams of Maryland, USA

  • Matthew J. Ashton
  • Raymond P. MorganII
  • Scott Stranko


In an ongoing effort to propose biologically protective nutrient criteria, we examined how total nitrogen (TN) and its forms were associated with macroinvertebrate communities in wadeable streams of Maryland. Taxonomic and functional metrics of an index of biological integrity (IBI) were significantly associated with multiple nutrient measures; however, the highest correlations with nutrients were for ammonia-N and nitrite-N and among macroinvertebrate measures were for Beck’s Biotic Index and its metrics. Since IBI metrics showed comparatively less association, we evaluated how macroinvertebrate taxa related to proposed nutrient criteria previously derived for those same streams instead of developing nutrient–biology thresholds. We identified one tolerant and three intolerant taxa whose occurrence appeared related to a TN benchmark. Individually, these taxa poorly indicated whether streams exceeded the benchmark, but combining taxa notably improved classification rates. We then extracted major physiochemical gradients using principal components analysis to develop models that assessed their influence on nutrient indicator taxa. The response of intolerant taxa was predominantly influenced by a nutrient-forest cover gradient. In contrast, habitat quality had a greater effect on tolerant taxa. When taxa were aggregated into a nutrient sensitive index, the response was primarily influenced by the nutrient-forest gradient. Multiple lines of evidence highlight the effects of excessive nutrients in streams on macroinvertebrate communities and taxa in Maryland, whose loss may not be reflected in metrics that form the basis of biological criteria. Refinement of indicator taxa and a nutrient-sensitive index is warranted before thresholds in aquatic life to water quality are quantified.


Stream nutrients Nutrient criteria MBSS Macroinvertebrates 


  1. APHA. (1998). Standard methods for the examination of water and wastewater (20th ed.). Washington, DC: American Public Health Association.Google Scholar
  2. 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. Washington, DC: EPA 841-B-99-002, USEPA, Office of Water.Google Scholar
  3. Bernhardt, E. S., Palmer, M. A., Allan, J. D., Alexander, G., Barnas, K., Brooks, S., et al. (2005). Synthesizing US river restoration efforts. Science, 308, 636–637.CrossRefGoogle Scholar
  4. Bovee, K. D. (1986). Development and evaluation of habitat suitability criteria for use in the Instream Flow Incremental Methodology. Washington, DC: USDOI Fish and Wildlife Service Instream Flow Information Paper #21 FWS/OBS-86/7.Google Scholar
  5. Bowman, M. F., Chambers, P. A., & Schindler, D. W. (2007). Constraints on benthic algal response to nutrient addition in oligotrophic mountain rivers. River Research and Applications, 23, 858–876.CrossRefGoogle Scholar
  6. Burnham, S. E., & Anderson, D. R. (2002). Model selection and multimodel inference: a practical information-theoretic approach. New York: Springer.Google Scholar
  7. Cade, N. S., Terrell, J. W., & Schroeder, R. L. (1999). Estimating effects of limiting factors with regression quartiles. Ecology, 80, 311–323.CrossRefGoogle Scholar
  8. Camgaro, J. A., & Alonso, A. (2006). Ecological and toxicological effects of inorganic nitrogen pollution in aquatic ecosystems: a global assessment. Environment International, 32, 831–849.CrossRefGoogle Scholar
  9. Castro, M. S., Driscoll, C. T., Jordan, T. E., Reay, W. G., & Boyton, W. R. (2003). Sources of nitrogen to estuaries in the United States. Estuaries, 26, 803–814.CrossRefGoogle Scholar
  10. Chambers, P. A., Vis, C., Brua, R. B., Guy, M., & Culp, J. M. (2008). Eutrophication of agricultural streams: defining nutrient concentrations to protect ecological condition. Water Science and Technology, 58, 2203–2210.CrossRefGoogle Scholar
  11. Cole, R. A. (1973). Stream community response to nutrient enrichment. Journal of the Water Pollution Control Federation, 45, 1874–1888.Google Scholar
  12. Cooper, C. M. (1993). Biological effects of agriculturally-derived surface water pollutants on aquatic systems—a review. Journal of Environmental Quality, 22, 402–408.CrossRefGoogle Scholar
  13. Cross, W. F., Wallace, J. B., Rosemond, A. D., & Eggert, S. L. (2006). Whole-system nutrient enrichment increases secondary production in a detritus-based ecosystem. Ecology, 87, 1556–1565.CrossRefGoogle Scholar
  14. Dodds, W. K., & Welch, E. B. (2000). Establishing nutrient criteria in streams. Journal of the North American Benthological Society, 19, 186–196.CrossRefGoogle Scholar
  15. Dodds, W. K., Bouska, W. W., Eitzmann, J. L., Pilger, T. L., Pitts, K. L., Riley, A. J., et al. (2009). Eutrophication of U.S. freshwaters: analysis of potential economic damages. Environmental Science and Technology, 43, 12–19.CrossRefGoogle Scholar
  16. Driscoll, C., Whithall, D., Aber, J., Boyer, E., Castro, M., Cronan, C., et al. (2003). Nitrogen pollution: sources and consequences in the US Northeast. Environment, 45, 9–21.CrossRefGoogle Scholar
  17. Easton, G. S., & McCulloch, R. E. (1990). A multivariate generalization of quantile–quantile plots. Journal of the American Statistical Association, 85, 376–386.CrossRefGoogle Scholar
  18. Evans-White, M. A., Dodds, W. K., Huggins, D. A., & Baker, D. S. (2009). Thresholds in macroinvertebrate biodiversity and stoichiometry across water-quality gradients in Central Plains (USA) streams. Journal of the North American Benthological Society, 28, 855–868.CrossRefGoogle Scholar
  19. Galloway, J. N., Aber, J. D., Erisman, J. W., Seitziner, S. S., Howarth, R. W., Cowling, E. B., et al. (2003). The nitrogen cascade. BioScience, 53, 341–356.CrossRefGoogle Scholar
  20. Heisler, J., Glibert, P. M., Burkholder, J. M., Anderson, D. M., Cochlan, W., Dennison, W. C., et al. (2008). Eutrophication and harmful algal blooms: a scientific consensus. Harmful Algae, 8, 3–13.CrossRefGoogle Scholar
  21. Hilsenhoff, W. L. (1987). An improved biotic index of organic stream pollution. The Great Lakes Entomologist, 20, 31–40.Google Scholar
  22. Homer, C. C., Dewitz, J., Fry, J., Coan, M., Hossain, N., Larson, C., et al. (2007). Completion of the 2001 National Landcover database for the conterminous United States. Photogrammetric Engineering and Remote Sensing, 73, 337–341.Google Scholar
  23. Jackson, D. A. (1993). Stopping rules in principal components analysis: a comparison of hueristical and statistical approaches. Ecology, 74, 2204–2214.CrossRefGoogle Scholar
  24. Karr, J. R., & Chu, E.W. (1997). Biological monitoring and assessment: using multimetric indexes effectively. University of Washington.Google Scholar
  25. Kazyak, P. F. (2000). Maryland biological stream survey sampling manual. Monitoring and Non-Tidal Assessment Division, Maryland Department of Natural Resources.Google Scholar
  26. Kemp, W. M., Boyton, W. R., Adolf, J. E., Doesch, D. E., Boicourt, W. C., Brush, G., et al. (2005). Eutrophication of Chesapeake Bay: historical trends and ecological interactions. Marine Ecology Progress Series, 303, 1–29.CrossRefGoogle Scholar
  27. King, R. S., & Richardson, C. J. (2003). Integrating bioassessment and ecological risk assessment: an approach to developing numerical water-quality criteria. Environmental management, 31, 795–809.CrossRefGoogle Scholar
  28. King, R. S., Baker, M. E., Kazyak, P. F., & Weller, D. E. (2011). How novel is too novel? Stream community thresholds at exceptionally low levels of catchment urbanization. Ecological applications, 21, 1659–78.CrossRefGoogle Scholar
  29. Klauda, R., Kazyak, P., Stranko, S., Souterland, M., Roth, N., & Chaillou, J. (1998). Maryland Biological Stream Survey: a state agency program to assess the impact of anthropogenic stress on stream habitat quality and biota. Environmental Monitoring and Assessment, 51, 299–316.CrossRefGoogle Scholar
  30. MacCullagh, P., & Nelder, J. A. (1989). Generalized linear models (2nd ed.) CRC.Google Scholar
  31. McCune, B., & Grace, J. B. (2002). Analysis of ecological communities. MJM Software Design.Google Scholar
  32. MDLS. (2008). Chesapeake Bays and Atlantic Coastal Bays 2010 trust fund and non-point source fund. Annapolis: Maryland General Assembly, Senate Bill 213.Google Scholar
  33. Meador, M. R. (2012). Nutrient enrichment and fish nutrient tolerance: assessing biologically relevant nutrient criteria. Journal of the American Water Resources Association, 49, 253–263.CrossRefGoogle Scholar
  34. Miltner, R. J. (2010). A method and rationale for deriving nutrient criteria for small rivers and streams in Ohio. Environmental Management, 45, 842–845.CrossRefGoogle Scholar
  35. Miltner, R. J., & Rankin, E. T. (1998). Primary nutrients and the biotic integrity of rivers and streams. Freshwater Biology, 40, 145–158.CrossRefGoogle Scholar
  36. Morgan, R. P., & Kline, K. M. (2011). Nutrient concentrations in Maryland non-tidal streams. Environmental Monitoring and Assessment, 178, 221–235.CrossRefGoogle Scholar
  37. Palmer, M. A. (2009). Reforming watershed restoration: science in need of application and applications in need of science. Estuaries and Coasts, 32, 1–17.CrossRefGoogle Scholar
  38. Paul, J. F., & McDonald, M. E. (2005). Development of empirical, geographically specific water quality criteria: a conditional probability analysis approach. Journal of the American Water Resources Association 41, 1211–1223.Google Scholar
  39. Peterson, B., Fry, B., Deegan, L., & Hershey, A. (1993). The trophic significance of epilithic algal production in a fertilized tundra river ecosystem. Limnology and Oceanography, 28, 872–878.CrossRefGoogle Scholar
  40. Peterson, B., Wollheim, W., Mulholland, P., Webster, J., Meyer, J., Tank, J., et al. (2001). Control of nitrogen export from watersheds by headwater streams. Science, 292, 86–90.CrossRefGoogle Scholar
  41. Poff, N. L. (1997). Landscape filters and species traits: towards mechanistic understanding and prediction in stream ecology. Journal of the North American Benthological Society, 16, 391–409.CrossRefGoogle Scholar
  42. Poff, N. L., & Ward, J. V. (1989). Implications of streamflow variability and predictability for lotic community structure: a regional analysis of streamflow patterns. Canadian Journal of Fisheries and Aquatic Sciences, 46, 1805–1818.CrossRefGoogle Scholar
  43. Poff, N. L., & Ward, J. V. (1990). The physical habitat template of lotic systems: recovery in the context of historical pattern of spatio-temporal heterogeneity. Environmental Management, 14, 629–646.CrossRefGoogle Scholar
  44. Poff, N. L., Olden, J. D., Vieira, N. K., Finn, D. S., Simmons, M. P., & Kondratieff, B. C. (2006). Functional trait niches of North American lotic insects: traits-based ecological applications in light of phylogenetic relationships. Journal of the North American Benthological Society 25, 730–755.Google Scholar
  45. R Development Core Team. (2012). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. http://www.R-project.org/. Accessed 25 Oct 2012
  46. Richards, C., Host, G. E., & Arthur, J. W. (1993). Identification of predominant environmental factors structuring stream macroinvertebrate communities within a large agricultural catchment. Freshwater Biology, 29, 285–294.CrossRefGoogle Scholar
  47. Richards, C., Johnson, L. B., & Host, G. E. (1996). Landscape-scale influences on stream habitats and biota. Canadian Journal of Fisheries and Aquatic Sciences, 53(S1), 295–311.CrossRefGoogle Scholar
  48. Smith, V. H., Tilman, G. D., & Nekola, J. C. (1999). Eutrophication: impacts of excess nutrient inputs on freshwater, marine, and terrestrial ecosystems. Environmental Pollution, 100, 179–196.CrossRefGoogle Scholar
  49. Smith, A. J., Bode, R. W., & Kleppel, G. S. (2007). A nutrient biotic index (NBI) for use with benthic macroinvertebrate communities. Ecological Indicators, 7, 371–386.CrossRefGoogle Scholar
  50. Southerland, M. T., & Stribling, J. P. (1995). Status of biological criteria development and implementation pp. In W. S. Davis & T. P. Simon (Eds.), Biological assessment and criteria: tools for water resource planning and decision making (pp. 81–96). Boca Raton: Lewis Publishers.Google Scholar
  51. Southerland, M. T., Rogers, G. M., Kline, K. M., Morgan, R. P., Boward, D. M., Kazyak, P. F., et al. (2007). Improving biological indicators to better assess the condition of streams. Ecological Indicators, 7, 751–767.CrossRefGoogle Scholar
  52. Southerland, M. T., Vǿlstad, J. H., Weber, E. D., Klauda, R. J., Poukish, C. A., & Rowe, M. C. (2009). Application of the probability-based Maryland Biological Stream Survey to the state’s assessment of water quality standards. Environmental Monitoring and Assessment, 150, 65–73.CrossRefGoogle Scholar
  53. Stone, M. L., Whiles, M. R., Webber, J. A., Willard, K. W. J., & Reeve, J. D. (2005). Macroinvertebrate communities in agriculturally impacted Southern Illinois streams: patterns with riparian vegetation, water quality, and in-stream habitat quality. Journal of Environmental Quality, 34, 907–917.CrossRefGoogle Scholar
  54. Stranko, S. A., Hurd, M. W., & Klauda, R. J. (2005). Applying a large, statewide database to the assessment, stressor diagnosis, and restoration of stream fish communities. Environmental Monitoring and Assessment, 108, 99–121.CrossRefGoogle Scholar
  55. Suplee, M. W., Varghese, A., & Cleland, J. (2007). Developing nutrient criteria for streams: an evaluation of the frequency distribution method. Journal of the American Water Resources Association, 43, 453–472.CrossRefGoogle Scholar
  56. Trebitz, A. S. (2012). Deriving criteria-supporting benchmark values from empirical response relationships: comparison of statistical techniques and effect of log-transforming the nutrient variable. Freshwater Science, 31, 986–1002.CrossRefGoogle Scholar
  57. USEPA. (1987). Handbook of methods for acid deposition studies: laboratory analyses for surface water chemistry. Washing, DC: USEPA, Office of Acid Deposition, Environmental Monitoring and Quality Assurance.Google Scholar
  58. USEPA. (1999). Update of ambient water quality criteria for ammonia. Washington, DC: EPA-822-R-99-014, USEPA, Office of Water, Office of Science and Technology.Google Scholar
  59. USEPA. (2000a). Nutrient criteria technical guidance manual: Rivers and streams. Washington, DC: EPA-822-B-00-002, USEPA, Office of Water, Office of Science and Technology.Google Scholar
  60. USEPA. (2000b). Ambient water quality recommendations, rivers and streams in nutrient ecoregion XI. Washington, DC: EPA-822-B-00-019, USEPA, Office of Water, Office of Science and Technology.Google Scholar
  61. USEPA. (2010a). Using Stressorresponse relationships to derive numeric nutrient criteria. Washington, DC: EPA-820-S-10-001, USEPA, Office of Water, Office of Science and Technology.Google Scholar
  62. USEPA. (2010b). Establishment of the total maximum daily load for the Chesapeake Bay. Washington, DC: EPA-R03-OW-2010-0736-0776, USEPA, Office of Water, Office of Science and Technology.Google Scholar
  63. Utz, R. M., Hildebrand, R. H., & Boward, D. A. (2009). Identifying regional differences in threshold responses of aquatic invertebrates to landcover gradients. Ecological indicators, 9, 556–567.CrossRefGoogle Scholar
  64. Wang, L., Roberston, D. M., & Garrison, S. F. (2007). Linkages between nutrients and assemblages of macroinvertebrates and fish in wadeable streams: implications to nutrient criteria development. Environmental Management, 39, 194–212.CrossRefGoogle Scholar
  65. Ward, J. V., & Stanford, J. A. (1992). Thermal responses in the evolutionary ecology of aquatic insects. Annual Review of Entomology, 27, 97–117.CrossRefGoogle Scholar
  66. Weigel, B. M., & Robertson, D. M. (2007). Identifying biotic integrity and water chemistry relations in non-wadeable rivers of Wisconsin: toward the development of nutrient criteria. Environmental Management, 40, 691–708.CrossRefGoogle Scholar
  67. Zheng, L., Gerritsen, J., Beckman, J., Ludwig, J., & Wilkes, S. (2008). Land use, geology, enrichment, and stream biota in the eastern ridge and valley ecoregion: implications for nutrient criteria development. Journal of the American Water Resources Association, 44, 1521–1536.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  • Matthew J. Ashton
    • 1
  • Raymond P. MorganII
    • 2
  • Scott Stranko
    • 1
  1. 1.Maryland Department of Natural Resources, Monitoring and Non-Tidal Assessment DivisionAnnapolisUSA
  2. 2.Appalachian LaboratoryUniversity of Maryland Center for Environmental ScienceFrostburgUSA

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