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Selection of scale for Everglades landscape models

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Abstract

This article addresses the problem of determining the optimal “Model Grain” or spatial resolution (scale) for landscape modeling in the Everglades. Selecting an appropriate scale for landscape modeling is a critical task that is necessary before using spatial data for model development. How the landscape is viewed in a simulation model is dependent on the scale (cell size) in which it is created. Given that different processes usually have different rates of fluctuations (frequencies), the question of selection of an appropriate modeling scale is a difficult one and most relevant to developing spatial ecosystem models.

The question of choosing the appropriate scale for modeling is addressed using the landscape indices (e.g., cover fraction, diversity index, fractal dimension, and transition probabilities) recently developed for quantifying overall characteristics of spatial patterns. A vegetation map of an Everglades impoundment area developed from SPOT satellite data was used in the analyses. The data from this original 20 × 20 m data set was spatially aggregated to a 40 × 40 m resolution and incremented by 40 meters on up to 1000 × 1000 m (i.e., 40, 80, 120, 160 … 1000) scale. The primary focus was on the loss of information and the variation of spatial indices as a function of broadening “Model Grain” or scale.

Cover fraction and diversity indices with broadening scale indicate important features, such as tree islands and brush mixture communities in the landscape, nearly disappear at or beyond the 700 m scale. The fractal analyses indicate that the area perimeter relationship changes quite rapidly after about 100 m scale. These results and others reported in the paper should be useful for setting appropriate objectives and expectations for Everglades landscape models built to varying spatial scales.

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References

  • Barnsley, M., 1988. Fractals Everywhere. Academic Press, N.Y.

    Google Scholar 

  • Bradbury, R.H., R.E. Reichelt, and D.G. Green, 1984. Fractals in Ecology: Methods and Interpretation. Mar. Ecol. Prog. Ser. 14: 295–296.

    Google Scholar 

  • Burrough, P.A. 1981. Fractal Dimensions of Landscapes and Other Environmental Data. Nature, 294: 240–242.

    Article  Google Scholar 

  • Burrough, P.A., 1983. Multiscale Sources of Spatial Variation in Soil. I. The Application of Fractal Concepts to Nested Levels of Soil Variation. J. of Soil Sci. 34: 577–587.

    Article  Google Scholar 

  • Burrough, P.A., 1984. The Application of Fractal Ideas of Geophysical Phenomena. Bull. Inst. Math. Appl. 20(3/4): 36–42.

    Google Scholar 

  • Burrough, P.A., 1986. Principles of Geographical Information Systems for Land Resources Assessment. Clarendon Press, Oxford.

    Google Scholar 

  • Costanza, R., C.H. Fitz, J.A. Bartholomew, and E. DeBellevue, 1992. The Everglades Landscape Model (ELM): Summary Report of Task 1 Model Feasibility Assessment. Institute for Ecological Economics, Center of Environmental and Estuarine Studies, University of Maryland, Solomons, MD.

    Google Scholar 

  • Craighead, F.C., Sr. 1971. The Trees of South Florida, Vol I: The Natural Environments and Their Succession, University of Miami Press, Coral Cables, FL.

    Google Scholar 

  • Cullinan, V.I., and J.M. Thomas, 1992. A Comparison of Methods for Examining Landscape Pattern and Scale. Landscape Ecology, 7(3): 211–227.

    Article  Google Scholar 

  • Davis, S.M., 1991. Growth, Decomposition and Nutrient Retention ofCladium jamaicense Crantz andTypha domingensis Pers. in the Florida Everglades. Aquat. Bot. 40: 203–224.

    Article  Google Scholar 

  • Davis, S.M., 1994. Phosphorus Inputs and Vegetation Sensitivity in the Everglades. In: Everglades — The Ecosystem and Its Restoration, ed. by S.M. Davis and John C. Ogden, St Lucie Press, Florida.

    Google Scholar 

  • Davis, S.M., 1994. Landscape Dimension, Composition, and Function in a Changing Everglades Ecosystem. In: Everglades — The Ecosystem and Its Restoration, ed. by S.M. Davis and John C. Ogden, St Lucie Press, Florida.

    Google Scholar 

  • Debusk, W.F., K.R. Reddy, M.S. Koch, and Y. Wang, 1994. Spatial Distribution of Soil Nutrients in a Northern Everglades Marsh: Water Conservation Area 2A. Soil Sci. Am. J., vol 58(2).

  • De Cola, L., 1989. Fractal Analysis of a Classified Landsat Scene. Photogrammetric Engineering and Remote Sensing, 55(5): 601–610.

    Google Scholar 

  • Dineen, J.W., 1972. Life in the Tenacious Everglades. In Depth Report: Central and Southern Florida Flood Control District, 1(5).

  • Dineen, J.W., 1974. Examination of Water Management Alternatives in Conservation Area 2A. In Depth Report: Central and Southern Florida Flood Control District, 2(3).

  • Feder, J., 1988 Fractals. Plenum, N.Y.

  • Fitz, C.H., R. Costanza, and E. Reyes, 1993. The Everglades Landscape Model: Summary Report 2, Model Development. Institute for Ecological Economics, Center of Environmental and Estuarine Studies, University of Maryland, Solomons, MD.

    Google Scholar 

  • Frontier, S., 1987. Applications of Fractal Theory to Ecology. NATO ASI Series, Vol. G14.

  • Gardner, R.H., B.T. Milne, M.G. Turner, and R.V. O’Neil, 1987. Neutral Models for the Analysis of Broad Scale Landscape Pattern. Landscape Ecology, 1(1): 19–28.

    Article  Google Scholar 

  • Gunderson, L.H., J.R. Stenberg, and A.K. Herndon. 1988. Tolerance of Five Hardwood Species to Flooding Regimes in South Florida. In: Interdisciplinary Approaches to Fresh-water Wetlands Research, ed. by D.J. Wilcox, Michigan State University Press, Ann Arbor.

    Google Scholar 

  • Holling, C.S., 1992. Cross-Scale Morphology, Geometry and Dynamics of Ecosystems. Ecological Monographs, 62(4): 447–502.

    Article  Google Scholar 

  • Jensen, J.J., K. Rutchey, M.S. Koch, and S. Narumalani, 1995. Inland Wetland Change Detection in the Everglades Water Conservation Area 2A Using a Time Series of Normalized Remotely Sensed Data. Photogrammetric Engineering and Remote Sensing, 61: 199–209.

    Google Scholar 

  • King, A.W., 1987. Translating Models Across Scales in the Landscape. In: Quantitative Methods in Landscape Ecology, ed. by M.G. Turner and R.H. Gardner, Springer-Verlag, New York.

    Google Scholar 

  • Krummel, J.R., R.H. Gardner, G. Sugihara, R.V. O’Neill, and P.R. Coleman, 1987. Landscape Patterns in a Disturbed Environment. OIKOS, 48(3): 321–324.

    Article  Google Scholar 

  • Li, H., and J.F. Reynolds, 1993. A New Contagion Index to Quantify Spatial Patterns of Landscapes. Landscape Ecology, 8(3): 155–162.

    Article  Google Scholar 

  • Lovejoy, S., 1982. Area-Perimeter Relation for Rain and Cloud Areas. Science, 216(9): 185–187.

    Article  Google Scholar 

  • Ludwig, J.A., and J.F. Reynolds, 1988. Statistical Ecology, A Premier on Methods and Computing, John Wiley and Sons, New York.

    Google Scholar 

  • Mandelbrot, B.B., 1977. Fractals, Form Chance and Dimension. Freeman Press, San Francisco.

    Google Scholar 

  • Meettemeyer, V., and E.O. Box, 1987. Scale Effects in Landscape Studies. In Landscape Heterogeneity and Disturbance, ed. M.G. Turner, Springer-Verlag, New York.

    Google Scholar 

  • Milne, B.T., 1988. Measuring the Fractal Geometry of Landscapes. Applied Mathematics and Computation, 27: 67–79. Elsevier Science, New York.

    Google Scholar 

  • Milne, B.T., 1991. Lessons from Applying Fractal Models to Landscape Patterns. In: Quantitative Methods in Landscape Ecology, Ed. by M.G. Turner and R.H. Gardner, Springer-Verlag, New York.

    Google Scholar 

  • Milne, B.T., 1992. Spatial Aggregation and Neutral Models in Fractal Landscapes. The American Naturalist, 139(1): 32–57.

    Article  Google Scholar 

  • O’Neil, R.V., J.R. Krummel, R.H. Gardner, G. Sugihara, B. Jackson, D.L. DeAngelis, B.T. Milne, M.G. Turner, B. Zygmunt, S. Christensen, V.H. Dale, and R.L. Graham, 1988. Indices of Landscape Pattern. Landscape Ecology., 1: 153–162.

    Article  Google Scholar 

  • Pastor, J., and M. Broschart, 1990. The Spatial Pattern of a Northern Conifer-Hardwood Landscape. Landscape Ecology, 4(1): 55–68.

    Article  Google Scholar 

  • Pielou, E.C., 1975. Ecological Diversity. Wiley-Intersciences, New York, NY. 165 pp.

    Google Scholar 

  • Risser, P.G., J.K. Karr, and R.T.T. Forman, 1984. Landscape Ecology: Directions and Approaches. Spec. Publ. 2. Illinois Natural History Survey, Champaign, IL, 18 pp.

    Google Scholar 

  • Rutchey, K., and L. Vilchek, 1994. Development of An Everglades Vegetation Map Using A SPOT Image and the Global Positioning System. Photogrammetric Engineering and Remote Sensing, 60(6): 767–775.

    Google Scholar 

  • Shannon, C.E., and W. Weaver, 1949. The Mathematical Theory of Communication. University of Illinois Press, Urbana.

    Google Scholar 

  • SAS Institute, 1990. SAS/STAT User’s Guide, Version 6, SAS Institute, Cary, North Carolina.

    Google Scholar 

  • Turner, M.G., 1987. Spatial Simulation of Landscape Changes in Georgia: A Comparison of 3 Transition Models. Landscape Ecology, 1(1): 29–36.

    Article  Google Scholar 

  • Turner, M.G., and C.L. Rusher, 1988. Changes in Landscape Pattern in Georgia, USA. Landscape Ecology, 1(4): 241–251.

    Article  Google Scholar 

  • Turner, M.G., R.V. O’Neil, R.H. Gardner, and B.T. Milne, 1989a. Effects of Changing Spatial Scale on the Analysis of Landscape Pattern. Landscape Ecology, 3(3/4): 153–163.

    Article  Google Scholar 

  • Turner, M.G., R. Costanza, and F.H. Sklar, 1989b. Methods to Evaluate the Performance of Spatial Simulation Models. Ecological Modelling, 48:1–18.

    Article  Google Scholar 

  • Turner, M.G., 1990. Spatial and Temporal Analysis of Landscape Patterns. Landscape Ecology, 4(1): 21–30.

    Article  Google Scholar 

  • Turner, M.G., and R.H. Gardner, 1991. Quantitative Methods in Landscape Ecology: An Introduction. In: Quantitative Methods in Landscape Ecology, Ed. by M.G. Turner and R.H. Gardner, Springer-Verlag, New York.

    Google Scholar 

  • Urban, D.L., R.V. O’Neil, H.H. Shugart, 1987. Landscape Ecology, a Hierarchical Perspective. BioScience, 37(2): 119–127.

    Article  Google Scholar 

  • Urban, N.H., S.M. Davis, N.G. Aumen, 1993. Fluctuations in Sawgrass and Cattail Densities in Everglades Water Conservation Area 2A Under Varying Nutrient, Hydrologic and Fire regimens. Aquatic Botany, vol 46.

  • Worth, D.F., 1988. Environmental Response of WCA-2A to Reduction in Regulation Schedule and Marsh Drawdown (Technical Publication 88-2). West Palm Beach, FL: South Florida Water Management District.

    Google Scholar 

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Obeysekera, J., Rutchey, K. Selection of scale for Everglades landscape models. Landscape Ecol 12, 7–18 (1997). https://doi.org/10.1007/BF02698203

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