Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
Skip to main content
SpringerLink
Log in

Scale detection in real and artificial landscapes using semivariance analysis

  • Published:
Landscape Ecology Aims and scope Submit manuscript

Abstract

Semivariance analysis is potentially useful to landscape ecologists for detecting scales of variability in spatial data. We used semivariance analysis to compare spatial patterns of winter foraging by large ungulates with those of environmental variables that influence forage availability in northern Yellowstone National Park, Wyoming. In addition, we evaluated (1) the ability of semivariograms to detect known scales of variability in artificial maps with one or more distinct scales of pattern, and (2) the influence of the amount and spatial distribution of absent data on semivariogram results and interpretation. Semivariograms of environmental data sets (aspect, elevation, habitat type, and slope) for the entire northern Yellowstone landscape clearly identified the dominant scale of variability in each map layer, while semivariograms of ungulate foraging data from discontinuous study areas were difficult to interpret. Semivariograms of binary maps composed of a single scale of pattern showed clear and interpretable results: the range accurately reflected the size of the blocks of which the maps were constructed. Semivariograms of multiple scale maps and hierarchical maps exhibited pronounced inflections which could be used to distinguish two or three distinct scales of pattern. To assess the sensitivity of semivariance analysis to absent data, often the product of cloud interference or incomplete data collection, we deliberately masked (deleted) portions of continuous northern Yellowstone map layers, using single scale artificial maps as masks. The sensitivity of semivariance analysis to random deletions from the data was related to both the size of the deleted blocks, and the total proportion of the original data set that was removed. Small blocks could be deleted in very high proportions without degrading the semivariogram results. When the size of deleted blocks was large relative to the size of the map, the corresponding variograms became sensitive to the total proportion of data removed: variograms were difficult or impossible to interpret when the proportion of data deleted was high. Despite success with artificial maps, standard semivariance analysis is unlikely to detect multiple scales of pattern in real ecological data. Semivariance analysis is recommended as an effective technique for quantifying some spatial characteristics of ecological data, and may provide insight into the scales of processes that structure landscapes.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  • Allen, T.F.H. and Starr, T.B. 1982. Hierarchy. University of Chicago Press, Chicago, Illinois.

    Google Scholar 

  • Ball, S.T., Mulla, D.J. and Konzak, C.F. 1993. Spatial heterogeneity affects variety trial interpretation. Crop Science 33: 931-935.

    Google Scholar 

  • Barmore, W.J. 1980. Population characteristics, distribution and habitat relationships of six ungulates in northern Yellowstone Park. Final report. National Park Service, Yellowstone National Park, Wyoming.

    Google Scholar 

  • Bell, G., Lechowicz, M.J., Appenzeller, A., Chandler, M., De-Blois, E., Jackson, L., Mackenzie, B., Preziosi, R., Schallenberg, M. and Tinker, N. 1993. The spatial structure of the physical environment. Oecologia 96: 114-121.

    Google Scholar 

  • Burrough, P.A. 1986. Principles of geographical information systems for land resources assessment. Clarendon Press, Oxford.

    Google Scholar 

  • Carlile, D.W., Skalski, J.R., Batker, J.I., Thomas, J.M. and Cullinan, V.I. 1989. Determination of ecological scale. Landscape Ecology 2: 203-214.

    Article  Google Scholar 

  • Craighead, J.J., Atwell, G. and O'Gara, B.W. 1972. Elk migrations in and near Yellowstone National Park.Wildlife Monographs 29.

  • Cullinan, V.I. and Thomas, J.M. 1992. A comparison of quantitative methods for examining landscape pattern and scale. Landscape Ecology 7: 211-227

    Google Scholar 

  • Danielson, B.J. 1991. Communities in a landscape: the influence of habitat heterogeneity on the interactions between species.American Naturalist 138: 1105-1120.

    Google Scholar 

  • David, M. 1977. Geostatistical ore reserve estimation. New York, Elsevier Scientific.

    Google Scholar 

  • Delcourt, H.R. and Delcourt, P.A. 1988. Quaternary landscape ecology: relevant scales in space and time. Landscape Ecology 2: 23-44.

    Google Scholar 

  • Despain, D.G. 1991. Yellowstone vegetation: consequences of environment and history. Roberts Rinehart Publishing Co, Boulder, Colorado.

    Google Scholar 

  • Deutsch, C.V. and Journel, A.G. 1992. GSLIB: Geostatistical software library and user's guide. Oxford University Press, New York.

    Google Scholar 

  • Gardner, R.H. 1998. Pattern, process and the analysis of spatial scales. In Ecological scale: theory and applications. Edited by Peterson, David L. and Parker, V. Thomas. Columbia University Press, New York, New York.

    Google Scholar 

  • Gardner, R.H. RULE: A spatial analysis program. In Landscape ecological analysis: issues and applications. Edited by Klopatek, J.M. and Gardner, R.H. Springer-Verlag, New York.

  • Gardner, R.H., Milne, B.T., Turner, M.G. and O'Neill, R.V. 1987.Neutral models for the analysis of broad-scale landscape pattern. Landscape Ecology 1: 19-28.

    Google Scholar 

  • Gardner, R.H. and O'Neill, R.V. 1991. Pattern, process and predictablility: the use of neutral models for landscape analysis. In Quantitative methods in landscape ecology. pp. 289-307. Edited by Turner, M.G. and Gardner, R.H. Springer-Verlag, New York.

    Google Scholar 

  • Greig-Smith, P. 1983. Quantitative plant ecology. University of California Press, Berkeley.ai]Hansen, A.J. and Urban, D.L. 1992. Avian response to landscape pattern: the role of species' life histories. Landscape Ecology 7: 163-181.

    Google Scholar 

  • Holling, C.S. 1992. Cross-scale morphology, geometry and dynamics of ecosystems. Ecological Monographs 62: 447-502.

    Google Scholar 

  • Houston, D.B. 1982. The northern Yellowstone elk: ecology and management. Macmillan, New York.

    Google Scholar 

  • Isaaks, E.H. and Srivastava, R.M. 1989. An introduction to applied geostatistics. Oxford University Press, New York.

    Google Scholar 

  • Istok, J.D., Smythe, J.D. and Flint, A.L. 1993. Multivariate geostatistical analysis of ground-water contamination: a case history. Ground Water 31: 63-74.

    Google Scholar 

  • Kareiva, P. and Wennergren, U. 1995. Connecting landscape patterns to ecosystem and population processes. Nature 373: 299-302.

    Google Scholar 

  • Kemeny, J.G. and Kurtz, T.E. 1993. TrueBasic: Macintosh version 2.61. TrueBasic, Inc., West Lebanon, New Hampshire, 03784.

    Google Scholar 

  • Kotliar, N.B. and Wiens, J.A. 1990. Multiple scales of patchiness and patch structure: a hierarchical framework for the study of heterogeneity. Oikos 59: 253-260.

    Google Scholar 

  • Korner, T.W. 1989. Fourier analysis. New York, Cambridge University Press.

    Google Scholar 

  • Krummel, J.R., Gardner, R.H., Sugihara, G., O'Neill, R.V. and Coleman, P.R. 1987. Landscape patterns in a disturbed environment. Oikos 48: 321-324.

    Google Scholar 

  • Lacaze, B., Rambal, S. and Winkel, T. 1994. Identifying spatial patterns of Mediterranean landscapes from geostatistical analysis of remotely-sensed data. International Journal of Remote Sensing 15: 2437-2450.

    Google Scholar 

  • Legendre, P. and Fortin, M.J. 1989. Spatial pattern and ecological analysis. Vegetatio 80: 107-138.

    Google Scholar 

  • Levin, S.A. 1992. The problem of pattern and scale in ecology.Ecology 73: 1943-67.

    Google Scholar 

  • Matheron, G. 1963. Principles of geostatistics. Economic Geology 58: 1246-1266.

    Google Scholar 

  • McBradney, A.B. and Webster, R. 1986. Choosing functions for semi-variograms of soil properties and fitting them to sampling estimates. Journal of Soil Science 37: 617-639.

    Google Scholar 

  • O'Neill, R.V., DeAngelis, D.L., Waide, J.B. and Allen, T.F.H. 1986. A hierarchical concept of ecosystems. Princeton, Princeton University Press.

    Google Scholar 

  • O'Neill, R.V., Turner, S.J., Cullinan, V.I., Coffin, D.P., Cook, T., Conley, W., Brunt, J., Thomas, J.M., Conley, M.R. and Gosz, J. 1991. Multiple landscape scales: an intersite comparison. Landscape Ecology 5: 137-144.

    Google Scholar 

  • Pearson, S.M., Turner, M.G., Wallace, L.L. and Romme, W.H. 1995. Winter habitat use by large ungulates following fire in northern Yellowstone National Park. Ecological Applications 5(3): 744-755.

    Google Scholar 

  • Pearson, S.M., Turner, M.G., Gardner, R.H., and O'Neill, R.V. 1996. An organism-based perspective of habitat fragmentation. In Biodiversity in managed landscapes: theory and practice. pp. 77-95. Edited by Szaro, R.C. Oxford University Press, Covelo, CA.

    Google Scholar 

  • Plotnick, R.E., Gardner, R.H. and O'Neill, R.V. 1993. Lacunarity indices as measures of landscape texture. Landscape Ecology 8: 201-211.

    Google Scholar 

  • Plotnick, R.E., Gardner, R.H., Hargrove, W.W., Prestegaard, K. and Perlmutter, M. 1996. Lacunarity analysis: a general technique for the analysis of spatial patterns. Physical Review E 53: 1-8.

    Google Scholar 

  • Rossi, R.E., Mulla, D.J., Journel, A.G. and Franz, E.H. 1992. Geostatistical tools for modeling and interpreting ecological dependence. Ecological Monographs 62: 277-314.

    Google Scholar 

  • Schneider, D.C. and Piatt, J.F. 1986. Scale-dependent correlation of seabirds with schooling fish in a coastal ecosystem. Marine Ecology – Progress Series 32: 237-246.

    Google Scholar 

  • Senft, R.L., Coughenour, M.B., Bailey, D.W., Rittenhouse, L.R., Sala, O.E. and Swift, D.M. 1987. Large herbivore foraging and ecological hierarchies. BioScience 39: 716-722.

    Google Scholar 

  • Swanson, F.J., Kratz, T.K., Caine, N. and Woodmansee, R.G. 1988. Landform effects on ecosystem patterns and processes. BioScience 38: 92-98.

    Google Scholar 

  • Sugihara, G. and May, R.M. 1990. Applications of fractals in ecology. Trends in Ecology and Evolution 5: 79-86.

    Google Scholar 

  • Tobler, W.R. 1970. A computer movie simulating urban growth in the Detroit region. Economic Geography 46(supplement): 234-240.

    Google Scholar 

  • Turner, S. J., O'Neill, R.V., Conley, W., Conley, M.R. and Humphries, H.C. 1991. Pattern and scale: statistics for landscape ecology. In Quantitative Methods in Landscape Ecology. pp. 17-50. Edited by Turner, M.G. and Gardner, R.H. Springer-Verlag, New York.

    Google Scholar 

  • Turner, M.G., Pearson, S.M., Romme, W.H. and Wallace, L. L. 1997. Landscape heterogeneity and ungulate dynamics: what spatial scales are important? In Landscape ecology: A primer for wildlife biologists. pp. 331-348. Edited by J. A. Bissonette. Springer-Verlag, New York.

    Google Scholar 

  • USA CERL. 1991. Geographic resources analysis support system, version 4.0. U.S. Army Corps of Engineers, Construction Engineering Research Laboratory, Champaign, Illinois, USA.

    Google Scholar 

  • Webster, R. and Oliver, M.A. 1992. Sample adequately to estimate variograms of soil properties. Journal of Soil Science 43: 177-192.

    Google Scholar 

  • Ward, D. and Saltz, D. 1994. Foraging at different spatial scales: dorcas gazelles foraging for lilies in the Negev desert. Ecology 75: 45-58.

    Google Scholar 

  • Watt, A.S. 1947. Pattern and process in the plant community. Journal of Ecology 35: 1-22.

    Google Scholar 

  • With, K.A. and A.W. King. 1997. The use and misuse of neutral landscape models in ecology. Oikos 79: 219-229.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Zoology, Birge Hall, University of Wisconsin, Madison, WI, 53706, USA

    Joe E. Meisel & Monica G. Turner

Authors
  1. Joe E. Meisel
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Monica G. Turner
    View author publications

    You can also search for this author in PubMed Google Scholar

Rights and permissions

Reprints and permissions

About this article

Cite this article

Meisel, J.E., Turner, M.G. Scale detection in real and artificial landscapes using semivariance analysis. Landscape Ecology 13, 347–362 (1998). https://doi.org/10.1023/A:1008065627847

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1023/A:1008065627847

Search

Navigation