Landscape Ecology

, Volume 15, Issue 1, pp 63–74 | Cite as

Predicting broad-scale occurrences of vertebrates in patchy landscapes

  • Randall B. Boone
  • William B. Krohn

Abstract

Spatially explicit landscape-scale models that predict species distributions, where patches of habitat are shown as having potential to be occupied or unoccupied, are increasingly common. To successfully use such data, one should understand how these predicted distributions are created and how their relative accuracies are assessed. Geographic ranges, defined upon observations (e.g., atlases), literature review, and expert review, are a primary data layer. A map of land cover is created, often from interpretation of satellite imagery or other remotely-sensed data. Species/habitat associations are defined based upon a literature review and expert review, describing associations for habitats derived from the cover map. Included as ancillary associations are how species relate to physical features, where appropriate, such as elevation and hydrography. The three layers of information (range, land cover, and associations) are merged, often using raster-based algebraic statements that exclude unused habitats or patches outside the range of a species. The accuracy of predictions for a suite of species is typically assessed with surveys by comparing the species predicted to occur in an area to the species observed. Omission (i.e., present in species lists but not predicted) and commission (i.e., predicted but not present in lists) errors are reported. Errors may be due to many sources. For example, ranges of species change, cover types may be misidentified, species/habitat associations may be incorrect or change, or species may be rare and unlikely to be seen in surveys and judged in-error even though the species may be present. An example is given of an appropriate use of broad-scale species predicted distributions, in which patterns and threats to Maine terrestrial vertebrate diversity are summarized.

fragmentation heterogeneous landscapes patch occupancy predicted distributions ranges species model assessment species richness species/habitat associations sprawl 

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References

  1. Avery, M.L. and Van Riper, C. II. 1990. Evaluation of wildlifehabitat relationships data based for predicting bird community composition in central California chaparral and blue oak woodlands. California Fish Game 76: 103-117.Google Scholar
  2. Block, W.M., Morrison, M.L., Verner, J. and Manley, P.N. 1994. Assessing wildlife-habitat-relationships models: a case study with California oak woodlands. Wildlife Soc. Bull. 22: 549-561.Google Scholar
  3. Boone, R.B. 1996. An assessment of terrestrial vertebrate diversity in Maine. Ph.D. Dissertation, University of Maine, Orono, Maine, USA.Google Scholar
  4. Boone, R.B. and Krohn, W.B. 1998a. Maine gap analysis vertebrate data -- part I: distribution, habitat relations, and status of amphibians, reptiles, and mammals in Maine. Maine Cooperative Fish and Wildlife Research Unit, University of Maine, Orono, Maine, USA.Google Scholar
  5. Boone, R.B. and Krohn, W.B. 1998b. Maine gap analysis vertebrate data -- part II: distribution, habitat relations, and status of breeding birds in Maine. Maine Cooperative Fish and Wildlife Research Unit, University of Maine, Orono, Maine, USA.Google Scholar
  6. Boone, R.B. and Krohn, W.B. 1999a. A technique for representing diminishing habitat occupation: feathering predicted species distributions near range limits in Maine. Gap Anal. Bull. 7: 41-43.Google Scholar
  7. Boone, R.B. and Krohn, W.B. 1999b. Modeling the occurrence of bird species -- are the errors predictable? Ecol. Appl. 9: 835–848.Google Scholar
  8. Brown, J.H. 1995. Macroecology. University of Chicago Press, Chicago, Illinois, USA.Google Scholar
  9. Butterfield, B.R., Csuti, B. and Scott, J.M. 1994. Modeling vertebrate distributions for Gap Analysis. In Mapping the diversity of nature. pp. 53–68. Edited by R.I. Miller. Chapman and Hall, London, UK.Google Scholar
  10. Chapin, T.G., Harrison, D.J. and Katnik, D.D. 1998. Influence of landscape pattern on habitat use by American marten in an industrial forest. Cons. Biol. 12: 1327–1337.Google Scholar
  11. Congalton, R.G. and Green, K. 1999. Assessing the accuracy of remotely sensed data: principles and practices. Lewis Publishers, Boca Raton, Florida, USA.Google Scholar
  12. Conroy, M.J. and Noon, B.R. 1996. Mapping of species richness for conservation of biological diversity: conceptual and methodological issues. Ecol. Appl. 6: 763–773.Google Scholar
  13. Couture, R. and Babin, M. 1993. Survey of woodcock habitat with Landsat: possibilities and limitations of remote sensing. In USDI Fish and Wildlife Service Biological Report 16. pp. 49–56. Edited by J.R. Longcore and G.F. Sepik.Google Scholar
  14. Csuti, B. 1996. Mapping animal distribution areas for gap analysis. In Gap analysis: a landscape approach to biodiversity planning. pp. 135–145. J.M. Scott, T.H. Tear, and F.W. Davis. American Society for Photogrammetry and Remote Sensing, Bethesda, Maryland, USA.Google Scholar
  15. DeGraaf, R.M. and Rudis, D.D. 1986. New England willdife: habitat, natural history, and distribution. Northeastern Forest Experiment Station, General Technical Report NE-108.Google Scholar
  16. Dobson, A.P., Rodriguez, J.P., Roberts, W.M. and Wilcove, D.S. 1997. Geographic distributions of endangered species in the United States. Science 275: 550–553.Google Scholar
  17. Dubec, L.J., Krohn, W.B. and Owen, R.B. Jr. 1990. Predicting occurrence of river otters by habitat on Mount Desert Island, Maine. J. Wildlife Manag. 54: 594–599.Google Scholar
  18. Edwards, T.C., Jr., Deshler, E.T., Foster, D. and Moisen, G.G. 1996. Adequacy of wildlife habitat relation models for estimating spatial distributions of terrestrial vertebrates. Cons. Biol. 10: 263–270.Google Scholar
  19. Edwards, T.C., Jr., Moisen, G.G. and Cutler, D.R. 1998. Assessing map accuracy in a remotely sensed ecoregion-scale cover map. Remote Sensing Env. 63: 73–83.Google Scholar
  20. Elliot, C.A. 1987. Songbird species diversity and habitat use in relation to vegetation structure and size of forest stands and forestclearcut edges in north-central Maine. Ph.D. Thesis, University of Maine, Orono, Maine, USA.Google Scholar
  21. Finley, R.W. 1976. The original vegetation of Wisconsin compiled from US General Land Office survey notes. North Central Forest Experiment Station, US Forest Service, St. Paul, Minnesota, USA.Google Scholar
  22. Gap Analysis Program. 1998. Gap Analysis Program: program description. USGS Biological Resources Division Gap Analysis Program, Moscow, Idaho, USA. (http://www.gap.uidaho.edu/gap/AboutGap/GapDescription/index.htm#updating).Google Scholar
  23. Gawler, S.C., Albright, J.J., Vickery, P.D. and Smith, F.C. 1996. Biological diversity in Maine: an assessment of the status and trends in the terrestrial and freshwater landscape. Maine Forest Biodiversity Project, Maine Natural Areas Program, Department of Conservation, Augusta, Maine, USA.Google Scholar
  24. Greater Laurentian Wildlands Project. 1998. Maine Wildlands Reserve Project -- Draft Proposal. Greater Laurentian Wildlands Project, South Burlington, Vermont, USA.Google Scholar
  25. Hall, L.S., Krausman, P.R. and Morrison, M.L. 1997. The habitat concept and a plea for standard terminology. Wildlife Soc. Bull. 25: 173–182.Google Scholar
  26. Hengeveld, R. 1992. Dynamic biogeography. Cambridge University Press, Cambridge.Google Scholar
  27. Jennings, M.D. 1993. Natural terrestrial cover classification: assumptions and definitions. USDI Fish and Wildlife Service GAP Analysis Technical Bulletin 2, Washington, DC, USA.Google Scholar
  28. Kellett, M.J. 1989. A new Maine woods reserve -- options for protecting Maine's northern woodlands. The Wilderness Society, Washington, DC, USA.Google Scholar
  29. Krohn, W.B. 1992. Sequence of habitat occupancy and abandonment: potential standards for testing habitat models. Wildlife Soc. Bull. 20: 441–444.Google Scholar
  30. Krohn, W.B. 1996. Predicted vertebrate distributions from gap analysis: considerations in the designs of statewide accuracy assessments. In Gap analysis: a landscape approach to biodiversity planning. pp. 147–162. Edited by J.M. Scott, T.H. Tear and F.W. Davis. American Society for Photogrammetry and Remote Sensing, Bethesda, Maryland, USA.Google Scholar
  31. Krohn, W.B. and Kelley, R.D. 1997. A conservation and public lands database for Maine: project history and database documentation. Maine Cooperative Fish and Wildlife Research Unit, Orono, and the Maine State Planning Office, Augusta, Maine, USA.Google Scholar
  32. Krohn, W.B., Boone, R.B., Sader, S.A., Hepinstall, J., Painton, S. and Schaefer, S. 1998. Maine Gap Analysis Final Report. Maine Cooperative Fish and Wildlife Research Unit, Orono, Maine, USA.Google Scholar
  33. Land Acquisition Priorities Advisory Committee. 1997. Final report and recommendations of the Land Acquisition Priorities Advisory Committee. Maine State Planning Office, Augusta, Maine, USA.Google Scholar
  34. Litvaitis, J.A. 1993. Response of early successional vertebrates to historic changes in land use. Cons. Biol. 7: 866–873.Google Scholar
  35. Livingston, S.A., Todd, C.S., Krohn, W.B. and Owen, R.B. Jr. 1990. Habitat models for nesting bald eagles in Maine. J. Wildlife Manag. 54: 644–653.Google Scholar
  36. Liu, J., Dunning, J.B. Jr. and Pulliam, H.R. 1995. Potential effects of a forest management plan on Bachman's Sparrows (Aimophila aestivalis): linking a spatially explicit model with GIS. Cons. Biol. 9: 62–75.Google Scholar
  37. Maine Audubon Society. 1996. Solutions for the future of Maine's woods, water, wildlife, and hard-working forest communities. Maine Audubon Society, Falmouth, Maine, USA.Google Scholar
  38. Maine Forest Service. 1990. Forest regeneration and clearcutting standards: MFS rules Chapter 20. Maine Forest Service, Augusta, Maine, USA.Google Scholar
  39. Marschner, F.J. 1974. The original vegetation of Minnesota compiled from US General Land Office survey maps. Map. US Department of Agriculture, Washington, DC, USA.Google Scholar
  40. Master, L.L. and Jennings, M. 1993. Hexagons: a new way to display predicted distributions of vertebrate species. Gap Anal. Bull. 3: 6–7.Google Scholar
  41. Master, L. 1996. Predicting distributions for vertebrate species: some observations. In Gap analysis: a landscape approach to biodiversity planning. pp. 171–176. Edited by J.M. Scott, T.H. Tear and F.W. Davis. American Society for Photogrammetry and Remote Sensing, Bethesda, Maryland, USA.Google Scholar
  42. Maurer, B.A. 1994. Geographic population analysis: tools for the analysis of biodiversity. Blackwell Scientific, Oxford.Google Scholar
  43. McMahon, J.S., Jacobson, G.L., Jr. and Hyland, F. 1990. An atlas of the native woody plants of Maine: a revision of the Hyland maps. Maine Agricultural Experiment Station, University of Maine, Orono, Maine, USA.Google Scholar
  44. Merrill, E.H., Kohley, T.W., Herdenorf, M.E., Reiners, W.A., Driese, K.L., Marrs, R.W. and Anderson, S.H. 1996. Wyoming gap analysis: a geographic analysis of biodiversity. Final report submitted to US Geological Survey, Biological Resources Division by the University of Wyoming, Laramie, Wyoming, USA.Google Scholar
  45. Mladenoff, D.J. and Sickley, T.A. 1998. Assessing potential gray wolf restoration in the northeastern United States: a spatial prediction of favorable habitat and potential population levels. J. Wildlife Manag. 62: 1–10.Google Scholar
  46. Miller, R.I. 1994. Mapping the diversity of nature. Chapman and Hall, London.Google Scholar
  47. Morrison, M.L., Marcot, B.G. and Mannan, R.W. 1992. Wildlifehabitat relationships: concepts and applications. University of Wisconsin Press, Madison, Wisconsin, USA.Google Scholar
  48. Northern Forest Lands Council. 1994. Finding common ground: conserving the northern forest. Maine State Library, Augusta, Maine, USA.Google Scholar
  49. O'Hara, F. 1997. The cost of sprawl. Maine State Planning Office, Augusta, Maine, USA.Google Scholar
  50. RESTORE. 1994. Maine Woods -- proposed national park and preserve: a vision of what could be. RESTORE: The North Maine Woods, Concord, Massachusetts, USA.Google Scholar
  51. Robbins, C.S., Bystrak, D. and Geissler, P.H. 1986. The Breeding Bird Survey: its first fifteen years, 1965–1979. USDI Fish and Wildlife Service Resource Publication 157, Washington, DC, USA.Google Scholar
  52. Root, T. 1988. Energy constraints on avian distributions and abundances. Ecology 69: 330–339.Google Scholar
  53. Schamberger, M., Farmer, A.H. and Terrell, J.W. 1982. Habitat suitability index models: introduction. USDI Fish and Wildlife Service FWS/OBS-82/10, Washington, DC, USA.Google Scholar
  54. Schamberger, M. and Krohn, W.B. 1982. Status of the habitat evaluation procedures. Transactions of the 47th North American Wildlife and Natural Resources Conference 47: 154–164.Google Scholar
  55. Schulz, T.T. and Joyce, L.A. 1992. A spatial application of a marten habitat model. Wildlife Soc. Bull. 20: 74–83.Google Scholar
  56. Scott, J.M., Csuti, B., Jacobi, J.D. and Estes, J.E. 1987. Species richness: a geographic approach to protecting future biological diversity. Bioscience 37: 782–788.Google Scholar
  57. Scott, J.M., Davis, F., Csuti, B., Noss, R., Butterfield, B., Groves, C., Anderson, H., Caicco, F., D'erchia, F., Edwards, T.C. Jr., Ulliman, J. and Wright, R.G. 1993. Gap analysis: a geographic approach to protection of biological diversity. Wildlife Monog. 123: 1–41.Google Scholar
  58. Scott, J.M., Tear, T.H. and Davis, F.W. 1996. Gap Analysis: a landscape approach to biodiversity planning. American Society of Photogrammetry and Remote Sensing, Bethesda, Maryland, USA.Google Scholar
  59. Smith, K.G. and Catanzaro, D.G. 1996. Predicting vertebrate distributions for gap analaysis: potential problems in constructing the models. In Gap analysis: a landscape approach to biodiversity planning. pp. 163–169. Edited by J.M. Scott, T.H. Tear and F.W. Davis. American Society for Photogrammetry and Remote Sensing, Bethesda, Maryland, USA.Google Scholar
  60. Straw, J.A., Jr., Krementz, D.G., Olinde, M.W and Sepik, G.F. 1994. American Woodcock. In The International Association of Fish and Wildlife Agencies, Washington, DC, USA. pp. 96–114. Edited by T.C. Tacha and C.E. Braun.Google Scholar
  61. Thomas, J.W. 1979. Wildlife habitats in managed forests: the Blue Mountains of Oregon and Washington. USDA Forest Service Agricultural Handbook No. 553.Google Scholar
  62. Van Horne, B. and Wiens, J.A. 1991. Forest bird habitat suitability models and the development of general habitat models. US Department of Interior Fish and Wildlife Service, Fish and Wildlife Research 8.Google Scholar
  63. Vickerman, S. 1996. Using gap analysis data for statewide biodiversity planning: case studies of applied gap analysis for planning of land use and biological resources. In Gap analysis: a landscape approach to biodiversity planning. pp. 195–208. Edited by J.M. Scott, T.H. Tear, and F.W. Davis. American Society for Photogrammetry and Remote Sensing, Bethesda, Maryland, USA.Google Scholar
  64. White, D., Kimmerling, A.J. and Overton, W.S. 1992. Cartographic and geometric components of a global sampling design for environmental monitoring. Cartography Geographic Information Systems 19: 5–22.Google Scholar

Copyright information

© Kluwer Academic Publishers 2000

Authors and Affiliations

  • Randall B. Boone
    • 1
  • William B. Krohn
    • 1
  1. 1.Department of Wildlife EcologyUniversity of MaineOronoUSA

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