How has the state-of-the-art for quantification of landscape pattern advanced in the twenty-first century?
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Landscape ecology was founded on the idea that there is a reciprocal relationship between spatial pattern and ecological processes. I provide a retrospective look at how the state-of-the-art of landscape pattern analysis has changed since 1998.
My objective is to show how pattern analysis techniques have evolved and identify some of the key lessons learned.
The state-of-the-art in 1998 was derived from information theory, fractal geometry, percolation theory, hierarchy theory and graph theory, relying heavily on the island-patch conceptual model using categorical maps, although point-data analysis methods were actively being explored. We have gradually winnowed down the list of fundamental components of spatial pattern, and have clarified the appropriate and inappropriate use of landscape metrics for research and application. We have learned to let the objectives choose the metric, guided by the scale and nature of the ecological process of interest. The use of alternatives to the binary patch model (such as gradient analysis) shows great promise to advance landscape ecological knowledge.
The patch paradigm is often of limited usefulness, and other ways to represent the pattern of landscape properties may reveal deeper insights. The field continues to advance as illustrated by papers in this special issue.
KeywordsSpatial pattern Metrics Indices Landscape ecology Scale Spatial heterogeneity
I thank Kurt Riitters, Marie-Josée Fortin, Nancy McIntyre and an anonymous reviewer for critical reviews of earlier drafts of the manuscript.
- Bormann F, Likens G (1979) Catastrophic disturbance and the steady state in northern hardwood forests: a new look at the role of disturbance in the development of forest ecosystems suggests important implications for land-use policies. Am Sci 67:660–669Google Scholar
- Gao P, Li Z (in review) Computation of the Boltzmann entropy of a landscape pattern: the state of the art. Landscape EcolGoogle Scholar
- Kedron P, Zhao Y, Frazier A (in review) 3D volumetrics for spatial pattern analysis of landscape structure. Landscape EcolGoogle Scholar
- Keitt TH, Urban DL, Milne BT (1997) Detecting critical scales in fragmented landscapes. Conserv Ecol 1, article 4. www.consecol.org/vol1/iss1/art4
- Kindlmann P, Burel F (2008) Connectivity measures: a review. Landscape Ecol 23:879–890Google Scholar
- Levins R (1966) The strategy of model building in population biology. Am Sci 54:421–431Google Scholar
- Loehle C (1983) The fractal dimension and ecology. Specul Sci Technol 6:131–142Google Scholar
- McGarigal K, Marks BJ (1995) FRAGSTATS: spatial pattern analysis program for quantifying landscape structure. Gen. Tech. Rep. PNW-GTR-351. U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station, Portland, ORGoogle Scholar
- Milne BT (1988) Measuring the fractal geometry of landscapes. Appl Math Comput 27:67–79Google Scholar
- Nowosad J, Stepinski TF (in review) Information-theoretical approach to measuring landscape complexity. Landscape EcolGoogle Scholar
- O’Neill RV (1989) Perspectives in hierarchy and scale. In: Roughgarden J, May RM, Levin SA (eds) Perspectives in ecological theory. Princeton University Press, Princeton, NJ, pp 140–156Google Scholar
- O’Neill RV, DeAngelis DL, Allen TFH, Waide JB (1986) A hierarchical concept of ecosystems. Monographs in population biology 23. Princeton University Press, Princeton, NJGoogle Scholar
- Peterman W, Winiarski K, da Silva Carvalho C, Moore C, Gilbert A, Spear S (in review). Understanding how landscape features affect gene flow: advances in resistance surface optimization for landscape genetic studies. Landscape EcolGoogle Scholar
- Riitters K (in review) Revisiting the fundamental components of landscape pattern. Landscape EcolGoogle Scholar
- Shannon C, Weaver W (1949) The mathematical theory of communication. University of Illinois Press, UrbanaGoogle Scholar
- Shelberg MC, Moellering H, Lam N (1982) Measuring the fractal dimensions of empirical cartographic curves. In: Proceedings of 5th international symposium on computer-assisted cartography, vol 5, pp 481–490Google Scholar
- USDA Forest Service (2016) Future of America’s forests and rangelands: update to the 2010 Resources Planning Act Assessment. Gen. Tech. Report WO-GTR-94. Washington, DCGoogle Scholar