complexity, can be modeled and quantified using surface morphometrics from the
fields of digital terrain modeling and industrial surface metrology. In these fields,
morphometrics are used to quantify geomorphological surface features and
irregularities or roughness in engineered surfaces, such as for quality control or
examination of damage (Pike 2001a, b). Pittman et al. (2009) examined seven
surface morphometrics and found that topographic complexity, particularly the
slope-of-slope (a measure of the maximum rate of maximum slope change),
emerged as the most useful predictor of faunal diversity and abundance across
Caribbean coral reef seascapes. Although some co-linearity existed between
morphometrics, the differences between them, even if only subtle, appeared to
matter when predicting faunal distributions (Fig. 6.4). Subsequently, Pittman and
Brown (2011) examined the interaction between topographic complexity and
across-shelf location in SW Puerto Rico and found improved predictive performance in mapped habitat suitability for several key fish species associated with
Caribbean coral reef seascapes. LiDAR derived topographic complexity, for
example, contributed most to the spatial model of habitat suitability for threespot
damselfish (Stegastes planifrons), an important indicator species of live coral
cover, producing a highly reliable prediction (Fig. 6.5). Studies by Wedding and
Friedlander (2008) in Hawaii, and Walker et al. (2009) in Florida, have also found
useful predictability between LiDAR topographic complexity and fish metrics.
Variance in depth (within a 75 m radius) demonstrated the strongest relationships
with fish abundance and species richness, while depth and slope were also found to
be useful spatial pattern metrics (Wedding and Friedlander 2008). Walker et al.
(2008) reported a depth dependent relationship between topographic complexity
and species richness, which was more pronounced in shallow coral reefs, as well as
a correlation between topographic complexity and fish abundance, which was
strongest in deeper offshore coral reefs. With increasing concern over the structural collapse of coral reefs, studies are now underway using LiDAR bathymetry to
forecast the impact of declining reef complexity on habitat suitability for fish
species and diversity to provide advance warning on the potential consequences
for fish and fisheries that depend on coral reef structure (Pittman et al. 2011b).
Variations in topographic complexity can also be used to characterize differences between benthic habitat classes. Pittman et al. (2009) showed that in SW
Puerto Rico aggregated patch reefs had the greatest proportion of high slope-ofslope, followed by spur and groove; whereas the largest areal extent of high slopeof-slope was quantified for the more common class of colonized pavement with
sand channels. These habitat classes were correspondingly found to support the
highest live coral cover and fish species richness values (Pittman et al. 2009). For
the Florida reef tract, Zawada and Brock (2009) quantified topographic complexity
using the fractal dimension (D) and found spatial patterns in D were positively
correlated with known reef zonation in the area, and consistent with physical
processes operating on the reef geomorphology, such as erosion and sea-level
dynamics. In similar studies using multibeam data from the Caribbean island of
152
S. J. Pittman et al.
fields of digital terrain modeling and industrial surface metrology. In these fields,
morphometrics are used to quantify geomorphological surface features and
irregularities or roughness in engineered surfaces, such as for quality control or
examination of damage (Pike 2001a, b). Pittman et al. (2009) examined seven
surface morphometrics and found that topographic complexity, particularly the
slope-of-slope (a measure of the maximum rate of maximum slope change),
emerged as the most useful predictor of faunal diversity and abundance across
Caribbean coral reef seascapes. Although some co-linearity existed between
morphometrics, the differences between them, even if only subtle, appeared to
matter when predicting faunal distributions (Fig. 6.4). Subsequently, Pittman and
Brown (2011) examined the interaction between topographic complexity and
across-shelf location in SW Puerto Rico and found improved predictive performance in mapped habitat suitability for several key fish species associated with
Caribbean coral reef seascapes. LiDAR derived topographic complexity, for
example, contributed most to the spatial model of habitat suitability for threespot
damselfish (Stegastes planifrons), an important indicator species of live coral
cover, producing a highly reliable prediction (Fig. 6.5). Studies by Wedding and
Friedlander (2008) in Hawaii, and Walker et al. (2009) in Florida, have also found
useful predictability between LiDAR topographic complexity and fish metrics.
Variance in depth (within a 75 m radius) demonstrated the strongest relationships
with fish abundance and species richness, while depth and slope were also found to
be useful spatial pattern metrics (Wedding and Friedlander 2008). Walker et al.
(2008) reported a depth dependent relationship between topographic complexity
and species richness, which was more pronounced in shallow coral reefs, as well as
a correlation between topographic complexity and fish abundance, which was
strongest in deeper offshore coral reefs. With increasing concern over the structural collapse of coral reefs, studies are now underway using LiDAR bathymetry to
forecast the impact of declining reef complexity on habitat suitability for fish
species and diversity to provide advance warning on the potential consequences
for fish and fisheries that depend on coral reef structure (Pittman et al. 2011b).
Variations in topographic complexity can also be used to characterize differences between benthic habitat classes. Pittman et al. (2009) showed that in SW
Puerto Rico aggregated patch reefs had the greatest proportion of high slope-ofslope, followed by spur and groove; whereas the largest areal extent of high slopeof-slope was quantified for the more common class of colonized pavement with
sand channels. These habitat classes were correspondingly found to support the
highest live coral cover and fish species richness values (Pittman et al. 2009). For
the Florida reef tract, Zawada and Brock (2009) quantified topographic complexity
using the fractal dimension (D) and found spatial patterns in D were positively
correlated with known reef zonation in the area, and consistent with physical
processes operating on the reef geomorphology, such as erosion and sea-level
dynamics. In similar studies using multibeam data from the Caribbean island of
152
S. J. Pittman et al.