Advertisement

Wetlands

, Volume 27, Issue 4, pp 846–854 | Cite as

Mapping wetlands: A comparison of two different approaches for New Brunswick, Canada

  • Paul N. C. Murphy
  • Jae Ogilvie
  • Kevin Connor
  • Paul A. Arp
Article

Abstract

Wetlands have an important role in ecosystem function and biodiversity. Effective management of wetlands requires accurate and comprehensive spatial information on location, size, classification, and connectivity in the landscape. Using a GIS, two provincial wetland maps were compared with regard to their areal correspondence across different ecoregions of New Brunswick. The first consisted of discrete wetland units (vector data) derived from aerial photo interpretation. The second consisted of wet areas modeled by a newly developed depth-to-water index with continuous coverage across the landscape (raster data). This index was derived from a digital elevation model and hydrographic data. The relative advantages and disadvantages of the two approaches were assessed. The two maps were generally consistent with most discrete wetland areas (51%–67%) embedded in the 0– 10 cm depth-to-water class, verifying the continuous modeling approach. The continuous model identified a larger wetland area. Much of this additional area consisted of riparian zones and numerous small wetlands (< 1 ha) that were not captured by aerial photo interpretation. Unlike the discrete map, the continuous model showed the hydrological connectivity of wetlands across the landscape. Both approaches revealed that topography was a major control on wetland distribution between ecoregions, with more wetland in ecoregions with flatter topography.

Key Words

GIS riparian zones soil mapping soil wetness index topographic modeling topography wetland management 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Literature Cited

  1. Baker, C., R. Lawrence, C. Montagne, and D. Patten. 2006. Mapping wetlands and riparian areas using landsat ETM+ imagery and decision-tree-based models. Wetlands 26: 465–74.CrossRefGoogle Scholar
  2. Bhatti, J. S. and C. M. Preston. 2006. Carbon dynamics in forest and peatland ecosystems: preface. Canadian Journal of Soil Science 86: 155–58.Google Scholar
  3. Boerner, R. E. J., S. J. Morris, E. K. Sutherland, and T. F. Hutchinson. 2000. Spatial variability in soil nitrogen dynamics after prescribed burning in Ohio mixed-oak forests. Landscape Ecology 15: 425–39.CrossRefGoogle Scholar
  4. Christensen, N. L., A. M. Bartuska, J. H. Brown, S. Carpenter, C. D’Antonio, R. Francis, J. F. Franklin, J. A. MacMahon, R. F. Noss, D. J. Parsons, C. H. Peterson, M. G. Turner, and R. G. Woodmansee. 1996. The report of the Ecological Society of America committee on the scientific basis for ecosystem management. Ecological Applications 6: 665–91.CrossRefGoogle Scholar
  5. Detenbeck, N. E., S. M. Galatowitch, J. Atkinson, and H. Ball. 1999. Evaluating perturbations and developing restoration strategies for inland wetlands in the Great Lakes Basin. Wetlands 19: 789–820.CrossRefGoogle Scholar
  6. DNR. 2006. New Brunswick wetland classification for 2003–2012 photo cycle. Department of Natural Resources New Brunswick, Fredericton, NB, Canada.Google Scholar
  7. Findlay, C. S. and J. Bourdages. 2000. Response time of wetland biodiversity to road construction on adjacent lands. Conservation Biology 14: 86–94.CrossRefGoogle Scholar
  8. Gomes Pereira, L. M. and R. J. Wicherson. 1999. Suitability of laser data for deriving geographical information: a case study in the context of management of fluvial zones. ISPRS Journal of Photogrammetry and Remote Sensing 54: 105–14.CrossRefGoogle Scholar
  9. Grunwald, S. 2006. What do we really know about the space-time continuum of soil-landscapes? p. 3–36. In S. Grunwald (ed.) Environmental Soil-landscape Modeling: Geographic Information Technologies and Pedometrics. CRC Press, New York, NY, USA.Google Scholar
  10. Güntner, A., J. Seibert, and S. Uhlenbrook. 2004. Modeling spatial patterns of saturated areas: an evaluation of different terrain indices. Water Resources Research 40: 1–19.CrossRefGoogle Scholar
  11. Haag, D. and M. Kaupenjohann. 2001. Landscape fate of nitrate fluxes and emissions in Central Europe: a critical review of concepts, data, and models for transport and retention. Agriculture, Ecosystems and Environment 86: 1–21.CrossRefGoogle Scholar
  12. Hornberger, G. M. and E. W. Boyer. 1995. Recent advances in watershed modelling. Review of Geophysics 33: 949–57.CrossRefGoogle Scholar
  13. Iverson, L. R., M. E. Dale, C. T. Scott, and A. Prasad. 1997. A GIS-derived integrated moisture index to predict forest composition and productivity of Ohio forests (U.S.A.). Landscape Hydrology 12: 331–48.CrossRefGoogle Scholar
  14. Iverson, L. R., A. M. Prasad, and J. Rebbeck. 2004. A comparison of the integrated moisture index and the topographic wetness index as related to two years of soil moisture monitoring in Zaleski State Forest, Ohio. 14th Central Hardwoods Forest Conference. Wooster, OH, USA.Google Scholar
  15. Johnston, C. A. and P. Meysembourg. 2002. Comparison of the Wisconsin and National Wetlands Inventories. Wetlands 22: 386–405.CrossRefGoogle Scholar
  16. Kent, B. J. and J. N. Mast. 2005. Wetland change analysis of San Dieguito Lagoon, California, USA: 1928–1994. Wetlands 25: 780–87.CrossRefGoogle Scholar
  17. Li, J. and W. Chen. 2005. A rule-based method for mapping Canada’s wetlands using optical, radar and DEM data. International Journal of Remote Sensing 26: 5051–69.CrossRefGoogle Scholar
  18. Lunetta, R. S. and M. E. Balogh. 1999. Application of multitemporal landsat 5 TM imagery for wetland identification. Photogrammetric Engineering and Remote Sensing 65: 1303–10.Google Scholar
  19. Mitsch, W. J. and J. G. Gosselink. 2000. Wetlands, third edition. John Wiley & Sons, Inc., New York, NY, USA.Google Scholar
  20. Moore, I. D., R. B. Grayson, and A. R. Ladson. 1991. Digital terrain modelling: a review of hydrological, geomorphological, and biological applications. Hydrological Processes 5: 3–30.CrossRefGoogle Scholar
  21. Murphy, P. N. C., J. Ogilvie, M. Castonguay, T. Connors, F.-R. Meng, and P. A. Arp. 2006. DEM-derived flow channel and wet area mapping: a new tool for forest operations planning. Sustainable Forest Management Network, Fourth International Conference. Edmonton, AB, Canada.Google Scholar
  22. NWWG. 1997. The Canadian Wetland Classification System. National Wetlands Working Group, Wetlands Research Centre, University of Waterloo, Waterloo, ON, Canada.Google Scholar
  23. Olivera, F. 1996. Spatial hydrology of the Urubamba river system in Peru using geographic information systems (GIS). Center for Research in Water Resources, The University of Texas at Austin, TX, USA. (www.ce.utexas.edu/prof/maidment/CE397/urubamba/peru.htm).Google Scholar
  24. Paine, J. G., W. A. White, R. C. Smyth, J. R. Andrews, and J. C. Gibeaut. 2004. Mapping coastal environments with lidar and EM on Mustang Island, Texas, U.S. Leading Edge 23: 894–98.CrossRefGoogle Scholar
  25. Parmuchi, M. G., H. Karszenbaum, and P. Kandus. 2002. Mapping wetlands using multi-temporal RADARSAT-1 data and a decision-based classifier. Canadian Journal of Remote Sensing 28: 175–86.Google Scholar
  26. Pegler, K. H., D. J. Coleman, and H. T. T. Nguyen. 2000. Comparing TIN random densification with the mean profile filter to minimize the ridging phenomenon in Service New Brunswick digital terrain models. Geomatica 54: 433–40.Google Scholar
  27. Ryan, P. J., N. J. McKenzie, D. O’Connell, A. N. Loughhead, P. M. Leppert, D. Jacquier, and L. Ashton. 2000. Integrating forest soils information across scales: spatial prediction of soil properties under Australian forests. Forest Ecology and Management 138: 139–57.CrossRefGoogle Scholar
  28. Saunders, W. K. and D. R. Maidment. 1996. A GIS assessment of nonpoint source pollution in the San Antonio-Nueces coastal basin. Center for Research in Water Resources, The University of Texas at Austin, TX, USA. (http://www.ce.utexas.edu/centers/crwr/reports/online.html).Google Scholar
  29. Simley, J. 2004. The geodatabase conversion. USGS National Hydrography Newsletter 3(4). USGS.Google Scholar
  30. Toeyrae, J., A. Pietroniro, L. W. Martz, and T. D. Prowse. 2002. A multi-sensor approach to wetland flood monitoring. Hydrological Processes 16: 1569–81.CrossRefGoogle Scholar
  31. Tomer, M. D., D. E. James, and T. M. Isenhart. 2003. Optimizing the placement of riparian practices in a watershed using terrain analysis. Journal of Soil and Water Conservation 58: 198–206.Google Scholar
  32. Turner, R. K., J. C. J. M. van den Bergh, T. Soderqvist, A. Barendregt, J. van der Straaten, E. Maltby, and E. C. van Ierland. 2000. Ecological-economic analysis of wetlands: scientific integration for management and policy. Ecological Economics 35: 7–23.CrossRefGoogle Scholar
  33. U.S.F.W.S. 2007. National Wetlands Inventory Metadata. United States Fish and Wildlife Service. (http://www.fws.gov/nwi/downloads/metadata/nwi_meta.txt).Google Scholar
  34. Watson, D. F. and G. M. Philip. 1985. A refinement of inverse distance weighted interpolation. Geoprocessing 2: 315–27.Google Scholar
  35. Wehr, A. and U. Lohr. 1999. Airborne laser scanningan introduction and overview. ISPRS Journal of Photogrammetry and Remote Sensing 54: 68–82.CrossRefGoogle Scholar

Copyright information

© Society of Wetland Scientists 2007

Authors and Affiliations

  • Paul N. C. Murphy
    • 1
  • Jae Ogilvie
    • 1
  • Kevin Connor
    • 2
  • Paul A. Arp
    • 1
  1. 1.Nexfor-Bowater Forest Watershed Research Centre Faculty of Forestry and Environmental ManagementUniversity of New BrunswickFrederictonCanada
  2. 2.Fish and Wildlife Branch New Brunswick Department of Natural ResourcesHugh John Flemming Forestry CentreFrederictonCanada

Personalised recommendations