, Volume 36, Issue 1, pp 111–120 | Cite as

Developing a Field-Tested Wetland Indicator Rating for Blue Spruce (Picea Pungens) in the Southern Rocky Mountains

  • Edward A. GageEmail author
  • David J. Cooper
  • Betsy Bultema
  • Cristina McKernan
  • Robert Lichvar
Original Research


To be identified as a wetland under U.S. Federal regulations, a site must, under normal circumstances, support vegetation dominated by hydrophytes. A list of hydrophytes and their wetland indicator rating is published by the U.S. Army Corps of Engineers as the National Wetland Plant List (NWPL) and is the basis for assessing the vegetation criteria of Federal wetland delineation manuals. Ratings are primarily based on expert opinion and few empirical studies have been done, particularly at landscape scales. In this study, we developed an approach for quantifying plant indicator ratings at broad spatial scales and used it to estimate the frequency that Picea pungens Engelm. (Colorado blue spruce) occurs in wetlands across a 22,921 km2 study area in the southern Rocky Mountains. Species distribution models were developed and used to inform a multistage field sampling design. Wetland soil and hydrology indicators were assessed around 423 randomly selected trees in 22 HUC12 watersheds. Only 16.5 % of trees occurred in wetlands, suggesting that a rating of facultative upland (FACU) is more appropriate than the currently published rating of facultative (FAC) for our study area. This study demonstrates that it is feasible to quantitatively evaluate ratings for species even at broad landscape scales.


Wetland delineation Hydrophyte National Wetland Plant List Regulation Picea pungens 



Funding for this study was provided by the U.S. Environmental Protection Agency, U.S. Fish and Wildlife Service, and the U.S. Army Corps of Engineers under the Wetland Regulatory Assistance Program (WRAP). Special thanks to Dr. Anthony Olson of EPA, Western Ecology Division, for discussions related to our sampling design and methods. Thanks to Joanna Harter, Sven Bultema, Dan Kotter, and Amanda Snyder for assistance in the field and to Mary Butterwick for input on study objectives and design. Thanks also to Catherine Jarnevich for help with species distribution modeling.

Supplementary material

13157_2015_721_MOESM1_ESM.docx (2.6 mb)
ESM 1 (DOCX 2683 kb)


  1. Aiello-Lammens ME, Boria RA, Radosavljevic A, Vilela B, Anderson RP (2015) spThin: an R package for spatial thinning of species occurrence records for use in ecological niche models. Ecography 38(5):541–545CrossRefGoogle Scholar
  2. Anderson L (2012) Rocky mountain hydroclimate: holocene variability and the role of insolation, ENSO, and the North American monsoon. Glob Planet Chang 92–93:198–208CrossRefGoogle Scholar
  3. Bailey RG (1980) Description of the Ecoregions of the United States. USDA Forest Service, Washington, D.CGoogle Scholar
  4. Breiman L (2001) Random forests. Mach Learn 45:5–32CrossRefGoogle Scholar
  5. Cooper DJ (1990) Ecology of Wetlands in Big Meadows, Rocky Mountain National Park, Colorado. U.S. Fish and Wildlife Service, Washington, D.CGoogle Scholar
  6. Daly C, Halbleib M, Smith JI, Gibson WP, Doggett MK, Taylor GH, Curtis J, Pasteris PP (2008) Physiographically sensitive mapping of climatological temperature and precipitation across the conterminous United States. Int J Climatol 28(15):2031–2064CrossRefGoogle Scholar
  7. Daubenmire RF (1943) Vegetational zonation in the Rocky Mountains. Bot Rev 9(6):325–393CrossRefGoogle Scholar
  8. Daubenmire R (1972) On the relation between Picea pungens and Picea engelmannii in the Rocky Mountains. Can J Bot 50(4):733–742CrossRefGoogle Scholar
  9. De Reu J, Bourgeois J, Bats M, Zwertvaegher A, Gelorini V, De Smedt P, Chu W, Antrop M, De Maeyer P, Finke P (2013) Application of the topographic position index to heterogeneous landscapes. Geomorphology 186:39–49CrossRefGoogle Scholar
  10. Dorn RD (2001) Vascular plants of Wyoming. Mountain West Publishing, CheyenneGoogle Scholar
  11. Elith J, Leathwick JR (2009) Species distribution models: ecological explanation and prediction across space and time. Annu Rev Ecol Evol Syst 40(1):677–697CrossRefGoogle Scholar
  12. Elith J, Leathwick JR, Hastie T (2008) A working guide to boosted regression trees. J Anim Ecol 77(4):802–813CrossRefPubMedGoogle Scholar
  13. Elith J, Phillips SJ, Hastie T, Dudík M, Chee YE, Yates CJ (2011) A statistical explanation of MaxEnt for ecologists. Divers Distrib 17(1):43–57CrossRefGoogle Scholar
  14. Fall PL (1997) Timberline fluctuations and late quaternary paleoclimates in the southern Rocky Mountains, Colorado. Geol Soc Am Bull 109(10):1306–1320CrossRefGoogle Scholar
  15. Franklin J (2010) Mapping species distributions: spatial inference and prediction. Cambridge University Press, CambridgeCrossRefGoogle Scholar
  16. Gibson J, Moisen G, Frescino T, Edwards T Jr (2014) Using publicly available forest inventory data in climate-based models of tree species distribution: examining effects of true versus altered location coordinates. Ecosystems 17(1):43–53CrossRefGoogle Scholar
  17. Graham CH, Ferrier S, Huettman F, Moritz C, Peterson AT (2004) New developments in museum-based informatics and applications in biodiversity analysis. Trends Ecol Evol 19(9):497–503CrossRefPubMedGoogle Scholar
  18. Gutzler DS (2004) An index of interannual precipitation variability in the core of the North American monsoon region. J Clim 17(22):4473–4480CrossRefGoogle Scholar
  19. Higgins RW, Yao Y, Wang XL (1997) Influence of the North American monsoon system on the U.S. summer precipitation regime. J Clim 10(10):2600–2622CrossRefGoogle Scholar
  20. Hijmans RJ (2012) Cross-validation of species distribution models: removing spatial sorting bias and calibration with a null model. Ecology 93(3):679–688CrossRefPubMedGoogle Scholar
  21. Jarnevich CS, Stohlgren TJ, Kumar S, Morisette JT, Holcombe TR (2015) Caveats for correlative species distribution modeling. Ecol Inform 29:6–15CrossRefGoogle Scholar
  22. Jenness J, Brost B, Beier P (2013) Land facet corridor designer: extension for ArcGIS. Jenness enterprises. Available at:
  23. Kittel TG, Thornton PE, Royle JA, Chase TN (2002) Rocky mountain climates: historical and future patterns. In: Baron J, Ehrlich PR (eds) Rocky mountain futures: an ecological perspective. Island Press, Washington, D.CGoogle Scholar
  24. Laboratory E (1987) Corps of engineers wetlands delineation manual. U.S. Army corps of engineers. Waterways Experiment Station, VicksburgGoogle Scholar
  25. Lichvar RW (2013) The National Wetland Plant List: 2013 wetland ratings. Phytoneuron 49:1–241Google Scholar
  26. Lichvar RW, Minkin P (2008) Concepts and procedures for updating the National Wetland Plant List. U.S. Army Engineer Research and Development Center and Cold Regions Research and Engineering Laboratory, HanoverGoogle Scholar
  27. Lichvar RW, Butterwick M, Melvin NC, Kirchner WN (2014) The National Wetland Plant List: 2014 update of wetland ratings. Phytoneuron 41:1–42Google Scholar
  28. Little EJ (1971) Atlas of United States Trees. Volume 1, Conifers and Important Hardwoods. US Department of Agriculture, Washington DCGoogle Scholar
  29. Mitton JB, Andalora R (1981) Genetic and morphological relationships between blue spruce, Picea pungens, and Engelmann spruce, Picea engelmannii, in the Colorado Front Range. Can J Bot 59(11):2088–2094CrossRefGoogle Scholar
  30. Morisette JT, Jarnevich CS, Holcombe TR, Talbert CB, Ignizio D, Talbert MK, Silva C, Koop D, Swanson A, Young NE (2013) VisTrails SAHM: visualization and workflow management for species habitat modeling. Ecography 36(2):129–135CrossRefGoogle Scholar
  31. Nelson RA, Williams RL (1992) Handbook of Rocky Mountain Plants. Roberts Rinehart Publishers, NiwotGoogle Scholar
  32. Olsen AR, Kincaid TM, Payton Q (2012) Spatially balanced survey designs for natural resources. In: Gitzen RA, Millspaugh JJ, Cooper AB, Licht DS (eds) Design and Analysis of Long-Term Ecological Monitoring Studies. Cambridge University Press, Cambridge, pp 126–150CrossRefGoogle Scholar
  33. Pearce J, Ferrier S (2000) Evaluating the predictive performance of habitat models developed using logistic regression. Ecol Model 133(3):225–245CrossRefGoogle Scholar
  34. Peet RK (2000) Forests and meadows of the Rocky Mountains. In: North American Terrestrial Vegetation, vol 2. Cambridge University Press, New York, pp 75–122Google Scholar
  35. Phillips SJ, Dudík M (2008) Modeling of species distributions with Maxent: new extensions and a comprehensive evaluation. Ecography 31(2):161–175CrossRefGoogle Scholar
  36. Phillips SJ, Dudík M, Schapire RE (2004) A maximum entropy approach to species distribution modeling. In: Proceedings of the twenty-first international conference on Machine learning. ACM, p 83Google Scholar
  37. Phillips SJ, Anderson RP, Schapire RE (2006) Maximum entropy modeling of species geographic distributions. Ecol Model 190(3):231–259CrossRefGoogle Scholar
  38. PRISM Climate Group (2014) Data extracts of 30-year annual temperature and precipitation normals (1981–2010). Oregon State University PRISM Climate Group.
  39. Reed PB (1988) National list of plant species that occur in wetlands: National summary. USDI Fish and Wildlife Service, Washington D.CGoogle Scholar
  40. Schaefer PR, Hanover JW (1985) A morphological comparison of Blue and Engelmann Spruce in the Scotch Creek drainage, Colorado. Silvae Genet 34:2–3Google Scholar
  41. Sousa-Silva R, Alves P, Honrado J, Lomba A (2014) Improving the assessment and reporting on rare and endangered species through species distribution models. Glob Ecol Conserv 2:226–237CrossRefGoogle Scholar
  42. Swets, J (1988) Measuring the accuracy of diagnostic systems. Science 240: 1285–1293Google Scholar
  43. Talbert C, Talbert M (2012) User Documentation for the Software for Assisted Habitat Modeling (SAHM) package in VisTrails. US Geological Survey, Fort CollinsGoogle Scholar
  44. Taylor RJ (1993) Picea. In: Flora of North America Editorial Committee (ed) Flora of North America North of Mexico, vol 2. Oxford University Press, New YorkGoogle Scholar
  45. Theobald DM, Stevens DL Jr, White D, Urquhart NS, Olsen AR, Norman JB (2007) Using GIS to generate spatially balanced random survey designs for natural resource applications. Environ Manag 40(1):134–146CrossRefGoogle Scholar
  46. Tiner RW (1999) Wetland indicators : a guide to wetland identification, delineation, classification, and mapping. Lewis Publishers, Boca RatonCrossRefGoogle Scholar
  47. Tiner R (2006) Lists of potential hydrophytes for the United States: a regional review and their use in wetland identification. Wetlands 26(2):624–634CrossRefGoogle Scholar
  48. Tiner RW (2012) Defining hydrophytes for wetland identification and delineation. U.S. Army Corps of Engineers, U.S. Army Engineer Research and Development Center, Cold Regions Research and Engineering Laboratory, Washington, D.CGoogle Scholar
  49. USACE (2010) Regional supplement to the corps of engineers wetland delineation manual: western Mountains, Valleys, and Coast Region (Version 2.0). U.S. Army Engineer Research and Development Center Environmental Laboratory, VicksburgGoogle Scholar
  50. Weber WA, Wittmann RC (eds) (2012) Colorado Flora: eastern slope, 4th edn. University Press of Colorado, NiwotGoogle Scholar
  51. Weiss A (2001) Topographic position and landforms analysis (Poster Presentation). Paper presented at the ESRI Users Conference, San Diego, CAGoogle Scholar
  52. Wiens JA, Stralberg D, Jongsomjit D, Howell CA, Snyder MA (2009) Niches, models, and climate change: assessing the assumptions and uncertainties. Proc Natl Acad Sci U S A 106:19729–19736PubMedCentralCrossRefPubMedGoogle Scholar

Copyright information

© Society of Wetland Scientists 2015

Authors and Affiliations

  • Edward A. Gage
    • 1
    Email author
  • David J. Cooper
    • 1
  • Betsy Bultema
    • 1
  • Cristina McKernan
    • 1
  • Robert Lichvar
    • 2
  1. 1.Department of Forest and Rangeland StewardshipColorado State UniversityFort CollinsUSA
  2. 2.U.S. Army Corps of Engineers, Cold Regions Research and Engineering Laboratory (CRREL)HanoverUSA

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