Measuring surface complexity in ecological studies

Habitat complexity is a potential structuring force in benthic communities. Different studies often estimate complexity in different ways, and it is not always clear how precise the separate techniques are. Here we review three methods of estimating surface complexity: stereo photography, profile gauges, and lengths of chain contoured over the substratum. We derived fractal dimensions for the quadrats in the rocky intertidal zone using each technique. Complexity estimates from chains and profile gauges were related, but neither technique was correlated with the results from stereo photographs. Stereo photographs appeared to overestimate complexity on smooth surfaces. The variance of fractal dimension estimates increased nonlinearly with the mean fractal dimension in each quadrat. Recommendations for the number of replicates needed for a reliable estimate of fractal dimension from a quadrat, therefore, vary as a function of surface complexity. Within the range of complexities typically encountered on rocky shores, as few as three profiles or sets of chains can produce relatively reliable estimates of fractal dimension. The most robust and time effective method, however, would be to sample using as many chain profile sets per quadrat as is logistically feasible. Given the changes in precision with surface complexity, comparisons between studies need to take careful note of the number of replicates and the average level of surface complexity. A null result (no relationship between surface complexity and an ecological variable) could be produced by imprecise estimates of surface complexity based on too few replicate measurements per quadrat.

[1]  S. Hartley,et al.  Uses and abuses of fractal methodology in ecology , 2004 .

[2]  J. Davenport Fractal Dimension Estimation in Studies of Epiphytal and Epilithic Communities: Strengths and Weaknesses , 2003 .

[3]  B. Baily,et al.  Comparative assessment of analytical and digital photogrammetric methods in the construction of DEMs of geomorphological forms , 2003 .

[4]  Stephen J. Hawkins,et al.  The area‐independent effects of habitat complexity on biodiversity vary between regions , 2003 .

[5]  J. Videler,et al.  University of Groningen A simple field method for stereo-photographic length measurement of free-swimming fish , 2003 .

[6]  L. Barmuta,et al.  Using fractal geometry to make rapid field measurements of riverbed topography at ecologically useful spatial scales , 2002 .

[7]  S. Williams,et al.  Spatial scale, species diversity, and habitat structure: small mammals in Australian tropical rain forest , 2002 .

[8]  G. Jenkins,et al.  Elements of habitat complexity that influence harpacticoid copepods associated with seagrass beds in a temperate bay , 2002, Oecologia.

[9]  G. Floater HABITAT COMPLEXITY, SPATIAL INTERFERENCE, AND “MINIMUM RISK DISTRIBUTION”: A FRAMEWORK FOR POPULATION STABILITY , 2001 .

[10]  Commito,et al.  Structural complexity in mussel beds: the fractal geometry of surface topography. , 2000, Journal of experimental marine biology and ecology.

[11]  M. Beck,et al.  Separating the elements of habitat structure: independent effects of habitat complexity and structural components on rocky intertidal gastropods. , 2000, Journal of experimental marine biology and ecology.

[12]  J.-P. Agnard,et al.  High‐resolution remote sensing of intertidal ecosystems: A low‐cost technique to link scale‐dependent patterns and processes , 2000 .

[13]  J. Hills,et al.  Settlement of barnacle larvae is governed by Euclidean and not fractal surface characteristics , 1999 .

[14]  H. Olff,et al.  Spatial scaling laws yield a synthetic theory of biodiversity , 1999, Nature.

[15]  Stuart N. Lane,et al.  Assessment of Dem Quality for Characterizing Surface Roughness Using Close Range Digital Photogrammetry , 1998 .

[16]  Michael W. Beck,et al.  Comparison of the measurement and effects of habitat structure on gastropods in rocky intertidal and mangrove habitats , 1998 .

[17]  R. Norris,et al.  Prediction of benthic macroinvertebrate composition using microhabitat characteristics derived from stereo photography , 1997 .

[18]  Jim H. Chandler,et al.  Automated Digital Photogrammetry on a Shoestring , 1996 .

[19]  John J. Videler,et al.  A simple field method for stereo-photographic length measurement of free-swimming fish: Merits and constraints , 1996 .

[20]  V. Kostylev Spatial heterogeneity and habitat complexity affecting marine littoral fauna. , 1996 .

[21]  M. McCormick,et al.  Comparison of field methods for measuring surface topography and their associations with a tropical reef fish assemblage , 1994 .

[22]  B. L. Cox,et al.  Fractal Surfaces: Measurement and Applications in the Earth Sciences , 1993 .

[23]  C. Pennycuick,et al.  Newton rules biology. A physical approach to biological problems , 1992 .

[24]  C. Pennycuick Newton rules biology , 1992 .

[25]  Earl D. McCoy,et al.  Habitat Structure: The Evolution and Diversification of a Complex Topic , 1991 .

[26]  G Sugihara,et al.  Applications of fractals in ecology. , 1990, Trends in ecology & evolution.

[27]  M. Chapman,et al.  Experimental analyses of the influences of topography of the substratum on movements and density of an intertidal snail, Littorina unifasciata , 1989 .

[28]  Heinz-Otto Peitgen,et al.  The science of fractal images , 2011 .

[29]  E. Bourget,et al.  Shore topography and spatial partitioning of crevice refuges by sessile epibenthos in an ice disturbed environment , 1986 .

[30]  B. Luckhurst,et al.  Analysis of the influence of substrate variables on coral reef fish communities , 1978 .

[31]  A. Dahl Surface area in ecological analysis: Quantification of benthic coral-reef algae , 1973 .

[32]  L. R. Taylor,et al.  Aggregation, Variance and the Mean , 1961, Nature.

[33]  L F Richardson,et al.  The problem of contiguity : An appendix to statistics of deadly quarrels , 1961 .