Environmental Monitoring and Assessment

, Volume 172, Issue 1–4, pp 643–661 | Cite as

Structuring expert input for a knowledge-based approach to watershed condition assessment for the Northwest Forest Plan, USA

  • Sean N. Gordon
  • Kirsten Gallo


Assessments of watershed condition for aquatic and riparian species often have to rely on expert opinion because of the complexity of establishing statistical relationships among the many factors involved. Such expert-based assessments can be difficult to document and apply consistently over time and space. We describe and reflect on the process of developing a computer-based decision support application from expert judgments for assessing aquatic and riparian conditions over the 100,000 km2 managed by the US federal government under the Northwest Forest Plan. The decision support system helped structure and document the assessment process and provided consistency and transparency to the evaluation methodology. However, many decisions and trade-offs were required in the expert engagement and model-building processes. Knowledge elicitation in an interactive group had a number of benefits over nominal group or Delphi processes, but efficient knowledge capture required considerable planning and expertise in the subject matter and modeling process. Communicating model results for validation was problematic and only effectively accomplished via in-person workshops. The choice to use different expert groups for each biophysical province provided more opportunities for participation and promoted greater ownership in the assessment, but it also led to increased variation among the resulting model structures. We propose three possible approaches for better managing the consistency of assessment models when multiple expert groups are involved.


Watershed assessment Composite indicators Expert judgment Fuzzy logic Modeling Stream condition assessment Stream habitat 


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  1. Delbecq, A. L., Van de Ven, A. H., & Gustafson, D. H. (1986). Group techniques for program planning: A guide to nominal group and Delphi processes. Middleton: Green Briar.Google Scholar
  2. Fall, A., Daust, D., & Morgan, D. (2001). A framework and software tool to support collaborative landscape analysis: Fitting square pegs into square holes. Transactions in GIS, 5, 67–86.CrossRefGoogle Scholar
  3. Gallo, K., Moyer, C., & Lanigan, S. (2002). Northwest Forest Plan Aquatic And Riparian Effectiveness Monitoring Program: 2001 pilot summary report. USDA Forest Service Regional Ecosystem Office, Portland, OR. Retrieved from
  4. Gallo, K., Lanigan, S. H., Eldred, P., Gordon, S. N., & Moyer, C. (2005). Northwest Forest Plan—The first 10 years (1994–2003): Preliminary assessment of the condition of watersheds. Report PNW-GTR-647. Portland: USDA Forest Service Pacific Northwest Research Station.Google Scholar
  5. Girvetz, E., & Shilling, F. (2003). Decision support for road system analysis and modification on the Tahoe National Forest. Environmental Management, 32, 218–233.CrossRefGoogle Scholar
  6. Gordon, S. N. (2006). Decision support systems for forest biodiversity management: A review of tools and an analytical-deliberative framework for understanding their successful application. Doctoral dissertation, Dept. of Forest Resources, Oregon State University, Corvallis, OR. Retrieved from
  7. Herger, L. G., Weiss, A., Augustine, S., & Hayslip, G. (2003). Modeling fish distributions in the Pacific Northwest Coast Range Ecoregion using EMAP data. Report EPA/910/R-03/000. U.S. Environmental Protection Agency, Region 10, Seattle, WA.Google Scholar
  8. Hubler, S. (2008). PREDATOR: Development and use of RIVPACS-type macroinvertebrate models to assess the biotic condition of wadeable Oregon streams. Hillsboro: Oregon Department of Environmental Quality, Laboratory and Environmental Assessment Division.Google Scholar
  9. Hubler, S., Miller, S., Merrick, L., Leferink, R., & Borisenko, A. (2009). High level indicators of Oregon’s forested streams. Hillsboro: Oregon Department of Environmental Quality, Laboratory and Environmental Assessment Division.Google Scholar
  10. Hughes, R. M., Howlin, S., & Kaufmann, P. R. (2004). A biointegrity index (IBI) for coldwater streams of western Oregon and Washington. Transactions of the American Fisheries Society, 133, 1497–1515.CrossRefGoogle Scholar
  11. Jensen, M. E., Reynolds, K., Andreasen, J., & Goodman, I. A. (2000). A knowledge-based approach to the assessment of watershed condition. Environmental Monitoring and Assessment, 64, 271–283.CrossRefGoogle Scholar
  12. Johnson, K. N., Swanson, F., Herring, M., & Greene, S. (Eds.) (1999). Bioregional assessments: Science at the crossroads of management and policy. Washington: Island.Google Scholar
  13. Johnson, K. N., Gordon, S. N., Duncan, S., Lach, D., McComb, B., & Reynolds, K. (2007). Conserving creatures of the forest: A guide to decision making and decision models for forest biodiversity. Corvallis: College of Forestry, Oregon State University. Retrieved from
  14. Kaufmann, P. R., & Hughes, R. M. (2006). Geomorphic and anthropogenic influences on fish and amphibians in Pacific Northwest coastal streams. In R. M. Hughes, L. Wang, & P. W. Seelbach (Eds.), American fisheries society symposium: Landscape influences on stream habitats and biological assemblages. Bethesda: American Fisheries Society.Google Scholar
  15. Krueger, R. A., & Casey, M. A. (2000). Focus groups: A practical guide for applied research. Thousand Oaks: Sage.Google Scholar
  16. Lloyd, R. (1999). Metric mishap caused loss of NASA orbiter. Retrieved from
  17. Manno, J. P., Smardon, R., DePinto, J. V., Cloyd, E. T., & Del Granado, S. M. (2008). The use of models in Great Lakes decision making: An interdisciplinary synthesis. Report 16. Syracuse: Randolph G. Pack Environmental Institute.Google Scholar
  18. Marakas, G. M. (1999). Decision support systems in the 21st century. Upper Saddle River: Prentice Hall.Google Scholar
  19. Marcot, B. G. (2006). Characterizing species at risk I: Modeling rare species under the Northwest Forest Plan. Ecology and Society, 11, 10.Google Scholar
  20. Mendoza, G. A., & Prabhu, R. (2003). Qualitative multi-criteria approaches to assessing indicators of sustainable forest resource management. Forest Ecology and Management, 174, 329–343.CrossRefGoogle Scholar
  21. Mitchell, R. B., Clark, W. C., Cash, D. W., & Dickson, N. M. (Eds.) (2006). Global environmental assessments: Information, institutions, and influence. Cambridge: MIT.Google Scholar
  22. Mulvey, M., Leferink, R., & Borisenko, A. (2009). Willamette basin rivers and streams assessment. Hillsboro: Oregon Department of Environmental Quality, Laboratory and Environmental Assessment Division.Google Scholar
  23. Oregon DEQ (2004). Oregon’s 2004 water quality assessment section 305(b) report. Hillsboro: Oregon Department of Environmental Quality, Water Quality Division.Google Scholar
  24. Oreskes, N., Shrader-Frechette, K., & Belitz, K. (1994). Verification, validation, and the confirmation of numerical models in the earth sciences. Science, 263, 641–646.CrossRefGoogle Scholar
  25. Pess, G. R., Montgomery, D. R., Steel, E. A., Bilby, R. E., Feist, B. E., & Greenberg, H. M. (2002). Landscape characteristics, land use, and coho salmon (Oncorhynchus kisutch) abundance, Snohomish River, Wash., USA. Canadian Journal of Fisheries and Aquatic Sciences, 59, 613–623.CrossRefGoogle Scholar
  26. Rauscher, H. M. (2000). Application scientific knowledge to decision-making in managing forest ecosystems: Forward. Computers and Electronics in Agriculture, 27, 1–6.CrossRefGoogle Scholar
  27. Reeves, G. H., Hohler, D. B., Larsen, D. P., Busch, D. E., Kratz, K., Reynolds, K., et al. (2004). Aquatic and riparian effectiveness monitoring plan for the northwest forest plan. Report PNW-GTR-577. Portland: USDA Forest Service Pacific Northwest Research Station.Google Scholar
  28. Reeves, G. H., Williams, J. E., Burnett, K. M., & Gallo, K. (2006). The aquatic conservation strategy of the Northwest Forest Plan. Conservation Biology, 20, 319–329.CrossRefGoogle Scholar
  29. Reynolds, K., & Peets, S. (2001). Integrated assessment and priorities for protection and restoration of watersheds. In: Proceedings of the IUFRO 4.11 conference on forest biometry, modelling and information science. UK: University of Greenwich.Google Scholar
  30. Reynolds, K. M., Jensen, M. E., Andreasen, J., & Goodman, I. (2000). Knowledge-based assessment of watershed condition. Computers and Electronics in Agriculture, 27, 315–333.CrossRefGoogle Scholar
  31. Reynolds, K. M., Rodriguez, S., & Bevans, K. (2002). Ecosystem management decision support 3.0 user guide. Corvallis: USDA Forest Service Pacific Northwest Research Station.Google Scholar
  32. Rieman, B. E., Hessburg, P. F., Lee, D. C., Thurow, R. F., & Sedell, J. R. (2000). Toward an integrated classification of ecosystems: Defining opportunities for managing fish and forest health. Environmental Management, 25, 425–444.CrossRefGoogle Scholar
  33. Rieman, B. E., Peterson, J. T., Clayton, J., Howell, P., Thurow, R., Thompson, W., et al. (2001). Evaluation of potential effects of federal land management alternatives on trends of salmonids and their habitats in the interior Columbia River basin. Forest Ecology and Management, 153, 43–62.CrossRefGoogle Scholar
  34. Rouwette, E. A. J. A., Vennix, J. A. M., & van Mullekom, T. (2002). Group model building effectiveness: A review of assessment studies. System Dynamics Review, 18, 5–45.CrossRefGoogle Scholar
  35. Schmoldt, D. L., & Peterson, D. L. (2000). Analytical group decision making in natural resources: Methodology and application. Forest Science, 46, 62–75.Google Scholar
  36. Sedell, J. R., Lee, D. C., Rieman, B. E., Thurow, R. F., & Williams, J. E. (1997). Effects of proposed alternatives on aquatic habitats and native fishes. In T. M. Quigley, K. M. Lee, & S. J. Arbelbide (Eds.), Evaluation of EIS alternatives by the science integration team (pp. 435–535). Portland: USDA Forest Service Pacific Northwest Research Station.Google Scholar
  37. Shifley, S. R., Thompson Iii, F. R., Dijak, W. D., & Fan, Z. (2008). Forecasting landscape-scale, cumulative effects of forest management on vegetation and wildlife habitat: A case study of issues, limitations, and opportunities. Forest Ecology and Management, 254, 474–483.CrossRefGoogle Scholar
  38. Turban, E., & Aronson, J. E. (2001). Decision support systems and intelligent systems. Upper Saddle River: Prentice Hall.Google Scholar
  39. USDA & USDI (1994). Record of decision for amendments to Forest Service and Bureau of Land Management planning documents within the range of the northern spotted owl. Washington: USDA Forest Service and Department of Interior Bureau of Land Management.Google Scholar
  40. van Den Belt, M. (2004). Mediated modeling: A system dynamics approach to environmental consensus building. Washington: Island.Google Scholar
  41. Whittier, T. R., Hughes, R. M., Lomnicky, G. A., & Peck, D. V. (2007). Fish and amphibian tolerance values and an assemblage tolerance index for streams and rivers in the western USA. Transactions of the American Fisheries Society, 136, 254–271.CrossRefGoogle Scholar

Copyright information

© US Government 2010

Authors and Affiliations

  1. 1.Pacific Northwest Research StationUSDA Forest ServicePortlandUSA
  2. 2.Resource Planning and Monitoring, Pacific Northwest RegionUSDA Forest ServiceCorvallisUSA
  3. 3.Chihuahuan Desert Inventory and Monitoring NetworkNational Park ServiceLas CrucesUSA

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