Fig 1.
Thirty temperate reefs, including natural (blue circles) and artificial (red triangles) reefs, surveyed on the continental shelf of NC.
Point size is proportional to mean digital reef rugosity (DRR) from transects on the particular reef. Symbols overlap for two artificial reefs located in northern Onslow Bay.
Fig 2.
Habitat complexity of temperate reefs.
a-d) Representative images of temperate reef morphologies. e-h) Representative depth contours of each reef morphology along the surveyed transect length. i-l) Representative semivariograms of each reef for half the distance of the surveyed transect length. Columns refer to different reef morphologies as follows, from left to right: naturally occurring pavement-and-rubble reef, naturally occurring ledge outcrop, artificial reef composed of concrete pipes, and a ship representative of historic shipwrecks and vessels intentionally sunk to enhance fish habitat.
Fig 3.
Relationship between digital reef rugosity (DRR) and fish community metrics on natural (blue) and artificial (red) temperate reefs.
A) Kernel density of digital reef rugosity (DRR) by reef type (Nnatural = 67, Nartificial = 56). B-G) Three-dimensional surface plot of GLM between fish community metrics and environmental predictor variables for natural reefs (left column) and artificial reefs (right column). Perspective grid surface represents GLM predictions. Points are raw data. Perpendicular segments attached to points depict whether the raw data are above (positive, dark color) or below (negative, light color) the surface predicted by GLM. Abundance (fishes / 120 m2) was modeled with a negative-binomial error distribution (b-c), biomass (kg / 120 m2) with a gamma distribution (d-e), and species richness with a Poisson distribution (f-g).
Table 1.
GLM results for the relationship between fish community metrics (abundance, biomass, richness) and environmental predictor variables by reef type.
Environmental variables include digital reef rugosity (DRR (m)), squared digital reef rugosity (DRR 2 (m)), average reef depth (m), average water temperature (°C), and standard deviation of sediment cover (m) approximating sediment dynamics. Coefficients, standard error (SE), Z-values and P-values are provided for each environmental parameter. Bold values indicate significance or marginal significance. Interpretation of the pattern (unimodal or non-significant (NS)) between rugosity and the fish community metric are displayed for each model. Model results displayed here were from the best models that we evaluated.
Fig 4.
Fish community metrics by morphological category for natural reefs (blue; Npavement&rubble = 38, Nledge = 29) and artificial reefs (red; Nconcrete = 17, Nship = 39).
A) Fish abundance (fishes per 120 m2). B) Fish biomass (kg / 120 m2). C) Fish species richness. Data displayed are untransformed, whereas ANOVAs were conducted on log-transformed data for abundance and biomass to meet assumptions of homogeneity of variance.
Fig 5.
Biplot of nonmetric multidimensional scaling (nMDS) ordination for fish community at the family level overlaid with indicators of reef morphologies.
Ellipses are 50% confidence intervals for samples classified by each reef morphology. Family names correspond to weighted averages of indicator families, colored according to morphology or reef type (artificial or natural).