12 - The gradient concept of landscape structure  pp. 112-119

The gradient concept of landscape structure

By Kevin McGarigal and Samuel A. Cushman

Image View Previous Chapter Next Chapter

The goal of landscape ecology is to determine where and when spatial and temporal heterogeneity matter, and how they influence processes (Turner, 1989). A fundamental issue in this effort revolves around the choices a researcher makes regarding how to depict and measure heterogeneity, specifically, how these choices influence the “patterns” that will be observed and what mechanisms may be implicated as potential causal factors. Indeed, it is well known that observed patterns and their apparent relationships with response variables often depend upon the scale that is chosen for observation and the rules that are adopted for defining and mapping variables (Wiens, 1989). Thus, success in understanding pattern–process relationships hinges on accurately characterizing heterogeneity in a manner that is relevant to the organism or process under consideration.

In this regard, landscape ecologists have generally adopted a single paradigm – the patch mosaic model of landscape structure (Forman, 1995). Under the patch-mosaic model, a landscape is represented as a collection of discrete patches. Major discontinuities in underlying environmental variation are depicted as discrete boundaries between patches. All other variation is subsumed by the patches and either ignored or assumed to be irrelevant. This model has proven to be quite effective. Specifically, it provides a simplifying organizational framework that facilitates experimental design, analysis, and management consistent with well-established tools (e.g., FRAGSTATS; McGarigal and Marks, 1995) and methodologies (e.g., ANOVA). Indeed, the major axioms of contemporary landscape ecology are built on this perspective (e.g., patch structure matters, patch context matters, pattern varies with scale).

Barbato, G., Carneiro, K., Cuppini, D., et al., (1995). Scanning Tunneling Microscopy Methods for the Characterization of Roughness and Micro Hardness Measurements. Synthesis report for research contract with the European Union under its programme for applied metrology. CD-NA-16145 EN-C. Brussels, Luxembourg: European Commission.
Barnsley, M. F. (2000). Fractals Everywhere. San Diego, CA: Elsevier.
Bradshaw, G. A. and Spies, T. A. (1992). Characterizing canopy gap structure in forests using wavelet analysis. Journal of Ecology, 80, 205–215.
Chui, C. K. (1992). An Introduction to Wavelets: Wavelet Analysis and its Applications. San Diego, CA: Academic Press.
Cohen, A. (1995). Wavelets and Multiscale Signal Processing. New York, NY: Chapman and Hall.
Forman, R. T. T. (1995). Land Mosaics: The Ecology of Landscapes and Regions. Cambridge: Cambridge University Press.
Gleason, H. A. (1926). The individualistic concept of the plant association. Bulletin of the Torrey Botanical Club, 53, 7–26.
Kahane, J. P. and Lemarie, P. G. (1995). Fourier Series and Wavelets. Studies in the Development of Modern Mathematics, vol. 3. London: Taylor and Francis.
Kaiser, G. (1994). A Friendly Guide to Wavelets. Boston, MA: Birkhauser.
Mandelbrot, B. B. (1982). The Fractal Geometry of Nature. New York, NY: Freeman.
McGarigal, K. and Marks, B. J. (1995). FRAGSTATS: Spatial Analysis Program for Quantifying Landscape Structure. USDA Forest Service General Technical Report PNW-GTR-351. Portland, OR: USDA Forest Service.
McGarigal, K., Cushman, S. A., Neel, M. C., and Ene, E. (2002). FRAGSTATS: Spatial Pattern Analysis Program for Categorical Maps. Amherst, MA: University of Massachusetts.
Pentland, A. P. (1984). Fractal-based description of natural scenes. IEEE Transactions on Pattern Analysis and Machine Intelligence, 6, 661–674.
Peterson, D. L., and Parker, V. T. (1998). Ecological Scale: Theory and Applications. New York, NY: Columbia University Press.
Plotnick, R. E., Gardner, R. H., and O'Neill, R. V. (1993). Lacunarity indices as measures of landscape texture. Landscape Ecology, 8, 201–211.
SPIP (2001). The Scanning Probe Image Processor. Lyngby, Denmark: Image Metrology APS.
Stout, K. J., Sullivan, P. J., Dong, W. P., et al. (1994). The Development of Methods for the Characterization of Roughness on Three Dimensions. EUR 15178 EN. Luxembourg: European Commission.
Turner, M. G. (1989). Landscape ecology: the effect of pattern on process. Annual Review of Ecology and Systematics, 20, 171–197.
Turner, M. G., Gardner, R. H., and O'Neill, R. V. (2001). Landscape Ecology in Theory and Practice. New York, NY: Springer
Villarrubia, J. S. (1997). Algorithms for scanned probe microscope, image simulation, surface reconstruction and tip estimation. Journal of the National Institute of Standards and Technology, 102, 435–454.
Webster, R. and Oliver, M. (2001). Geostatistics for Environmental Scientists. Chichester: Wiley.
Whittaker, R. H. (1967). Gradient analysis of vegetation. Biological Review, 42, 207–264.
Wiens, J. A. (1989). Spatial scaling in ecology. Functional Ecology, 3, 385–397.