A Multiscale Analysis of Coral Reef Topographic Complexity Using Lidar-Derived Bathymetry

Zawada, David G.; Brock, John C.

doi:10.2112/si53-002.1

Cited by 54 publications

(55 citation statements)

References 41 publications

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“…These studies, however, did not address the vertical relief of coral reefs, in part because of the difficulty of obtaining high-resolution, submerged topographic data at a high spatial density over the seascape. Such constraints are being eliminated by the growing availability of lidar and multibeam-sonar bathymetric data at spatial resolutions as fine as 1 m. Initial work using lidar or sonar datasets has only focused on specific areas within a seascape, yet revealed zonation patterns in fractal dimension that were consistent with the geomorphic domains of the known benthic cover types [Purkis and Kohler, 2008;Zawada and Brock, 2009]. Here, we show the substantial variability in topographic complexity over an entire seascape and the correlations with different benthic zones.…”

Section: Introductionmentioning

confidence: 63%

Topographic complexity and roughness of a tropical benthic seascape

Zawada

Piniak²,

Hearn³

2010

Geophysical Research Letters

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[1] Topographic complexity is a fundamental structural property of benthic marine ecosystems that exists across all scales and affects a multitude of processes. Coral reefs are a prime example, for which this complexity has been found to impact water flow, species diversity, nutrient uptake, and wave-energy dissipation, among other properties. Despite its importance, only limited assessments are available regarding the distribution or range of topographic complexity within or between benthic communities. Here, we show substantial variability in topographic complexity over the entire inner-shelf seascape of a tropical island. Roughness, estimated in terms of fractal dimension, served as a proxy for topographic complexity, and was computed for linear transects (D T ), as well as the benthic surface (D S ). Spatial variability in both D T and D S was correlated with the known distribution of benthic cover types in the seascape. Transect roughness values ranged from 1.0 to 1.7, with features along the shelf edge being markedly anisotropic with an along-shore bias, whereas regions with high scleractinian coral cover were nearly isotropic and exhibited minimal directional bias. Surface-roughness values ranged from 2.0 in predominantly hardbottom areas with low coral cover to 2.5 in areas with high coral cover. Quantifying roughness across the substrates and biological communities for an entire seascape provides a synoptic view of its spatial variability at scales appropriate for numerous research efforts, including ecosystem studies, parameterizing hydrodynamic models, and designing monitoring programs. Citation: Zawada, D. G., G. A. Piniak, and C. J. Hearn (2010), Topographic complexity and roughness of a tropical benthic seascape, Geophys.

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Section: Introductionmentioning

confidence: 63%

Topographic complexity and roughness of a tropical benthic seascape

Zawada

Piniak²,

Hearn³

2010

Geophysical Research Letters

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“…For ecological applications, it would be desirable to compare this fine-scale complexity metric to a measure of useable space, because some surfaces may be inaccessible to many macro organisms. In large-scale surveys of marine benthic structure, LiDAR (light detection and ranging) technology was demonstrated to be a useful method for measuring surface rugosity (Wedding et al, 2008;Zavada & Brock, 2009 , Fig. 4D); however, due to its large grid size, the resulting measures of habitat complexity would only be relevant for larger organisms such as fish.…”

Section: Coralsmentioning

confidence: 99%

Habitat complexity: approaches and future directions

2011

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Habitat complexity is one of the most important factors structuring biotic assemblages, yet we still lack basic understanding of the underlying mechanisms. Although it is one of the primary targets in conservation management, no methods are available for comparing complexity across ecosystems, and system-specific qualitative assessment predominates. Despite its overwhelming importance for faunal diversity and abundance, there has been surprisingly little interest in examining its effects on other community and ecosystem attributes. We discuss possibilities of such effects, outlining potentially fruitful areas for future research, and argue that complexity may be implicated in community persistence and ecosystem stability by acting as a decoupling mechanism in predator-prey interactions. We provide a brief overview of methods used to quantify complexity in different ecosystems, highlighting contributions of the current issue of Hydrobiologia, and discuss potential application of these approaches for cross-ecosystem comparisons. Better understanding of the role of habitat complexity resulting from such comparisons is critically important for preservation of biodiversity and ecosystem function in an era of unprecedented habitat loss.

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“…When estimating the fractal dimension (D) of natural surfaces, such as rocky substrata, investigators should consider that a number of methods may be used and they may produce different results (Zhou & Lam 2005, Zawada & Brock 2009. It is therefore difficult to compare estimates of D where different measurement and calculation techniques have been used; this should be the subject of future studies.…”

Section: Static Habitat Structurementioning

confidence: 99%

“…varies with direction). In contrast, the fractal surface dimension (2 < D < 3) measures how completely a 3D surface fills a volume (Murdock & Dodds 2007, Zawada & Brock 2009) and corresponds closely to the human perception of surface roughness (Dubuc et al 1989). To our knowledge, fractal surface dimension has not yet been measured on rocky shores.…”

Section: Introductionmentioning

confidence: 99%