Associations between Benthic Cover and Habitat Complexity Metrics Obtained from 3D Reconstruction of Coral Reefs at Different Resolutions

Dead but not forgotten: complexity of Acropora palmata colonies increases with greater composition of dead coral

Coral reefs are highly biodiverse ecosystems that have declined due to natural and anthropogenic stressors. Researchers often attribute reef ecological processes to corals' complex structure, but effective conservation requires disentangling the contributions of coral versus reef structures. Many studies assessing the relationships between reef structure and ecological dynamics commonly use live coral as a proxy for reef complexity, disregarding the contribution of dead coral skeletons to reef habitat provision or other biogeochemical reef dynamics. This study aimed to assess the contribution of dead coral to reef complexity by examining structural variations in live and dead Acropora palmata colonies. We used photogrammetry to reconstruct digital elevation models (DEMs) and orthomosaics of the benthic region immediately surrounding 10 A. palmata colonies. These reconstructions were used to quantify structural metrics, including surface rugosity, fractal dimension, slope, planform curvature, and profile curvature, as a function of benthic composition (i.e., live A. palmata, dead A. palmata, or non-A. palmata substrate). The results revealed that dead coral maintained more varied profile curvatures and higher fractal dimensions than live or non-coral substrate. Conversely, A. palmata colonies with a higher proportion of live coral displayed more uniform structure, with lower fractal dimensions and less variability in profile curvature measures. Other metrics showed no significant difference among substrate types. These findings provide novel insights into the structural differences between live and dead coral, and an alternative perspective on the mechanisms driving the observed structural complexity on reefs. Overall, our results highlight the overlooked potential contributions of dead coral to reef habitat provision, ecological processes, and other biogeochemical reef dynamics, and could have important implications for coral reef conservation.

Using 3D photogrammetry to quantify the subtle differences of coral reefs under the impacts of marine activities

Marine activities may cause the degradation of coral reefs. The composition of benthic communities and seawater quality have been commonly used as the proxies to assess the impacts of marine activities. However, these proxies may not be able to detect the subtle differences within homogeneous environment. We used photogrammetry to quantify the subtle differences of structural complexity between heavily and lightly trafficked sites at Wanlitong, southern Taiwan. Our study demonstrated that the impacts of marine activities can be detected within tens of meters through quantifying structural complexity of coral reefs. Vector ruggedness measure (VRM) is a more suitable metric than conventional linear rugosity to detect such impacts. The correlations between structural complexity and coral cover have variances while comparing with previous studies. The results show that using photogrammetry to quantify the structure of coral reefs can provide a novel aspect to evaluate the subtle differences caused by marine activities.

Photogrammetry as a tool to improve ecosystem restoration

Ecosystem restoration has been practiced for over a century and is increasingly supported by the emergent applied science of restoration ecology. A prerequisite for successful ecosystem restoration is determining meaningful and measurable goals. This requires tools to monitor success in a standardized way. Photogrammetry uses images to reconstruct landscapes and organisms in three dimensions, enabling non-invasive measurement of key success indicators with unprecedented accuracy. We propose photogrammetry can improve restoration success by: (i) facilitating measurable goals; (ii) innovating and standardizing indicators of success; and (iii) standardizing monitoring. While the case we present is specific to coral reefs, photogrammetry has enormous potential to improve restoration practice in a wide range of ecosystems.

3D assessment of a coral reef at Lalo Atoll reveals varying responses of habitat metrics following a catastrophic hurricane

Extreme disturbances such as hurricanes can cause reductions in coral cover and three-dimensional (3D) structural complexity of coral reefs. We examined changes in structural complexity utilizing 3D reconstruction of a coral-reef site before and after Hurricane Walaka passed through Lalo of the Northwestern Hawaiian Islands. This event resulted in complete destruction of the coral-reef habitat, with dramatic changes in benthic cover from pre-hurricane tabulate coral to post-hurricane rubble. Rugosity and mean slope decreased after the hurricane, while structural complexity, captured by vector ruggedness measure (VRM), showed resolution-specific responses. This metric captured the structural complexity of rubble at a high raster resolution of 1 cm and that of tabulate coral at lower resolutions, resulting in decreases in mean VRM values at 2- and 4-cm resolutions but an increase at 1-cm resolution. Variability in profile and planform curvature was reduced after the hurricane due to a disappearance of extreme curvature values created by the tabulate coral after the hurricane. This study highlights the varying responses of habitat complexity metrics to the complete destruction of a coral reef and provides us with insights into how choices of habitat complexity metrics can affect quantitative assessments of 3D habitat structure.

Fish Assemblage Structure in the Northwestern Hawaiian Islands Is Associated with the Architectural Complexity of Coral-Reef Habitats

The architectural complexity of coral-reef habitat plays an important role in determining the assemblage structure of reef fish. We investigated associations between the reef habitats and fish assemblages in the Northwestern Hawaiian Islands (NWHI) using in situ fish counts and data on habitat metrics and benthic community composition that were obtained from three-dimensional (3D) photogrammetric reconstructions of the surveyed sites. The structure of fish assemblage as a whole on the basis of Bray–Curtis dissimilarity, species richness and the abundances of herbivores and piscivores were associated with habitat metrics, with higher levels of architectural complexity generally supporting greater numbers of fish species and individuals. Benthic cover did not explain additional variation in these variables after the effects of habitat metrics were taken into account. Corallivorous fish was the only group that showed positive associations with both habitat metrics and benthic cover (Acropora and Pocillopora corals). The total fish abundance and the abundances of planktivores and invertivores did not show associations with either habitat metrics or benthic cover. This study suggests that an appropriate combination of habitat metrics can be used to account sufficiently for the effects of habitat architecture on fish assemblages in reef monitoring efforts in the NWHI.

Metrics of Coral Reef Structural Complexity Extracted from 3D Mesh Models and Digital Elevation Models

Underwater photogrammetry has been increasingly used in coral-reef research in recent years. Habitat metrics extracted from resulting three-dimensional (3D) reconstructions can be used to examine associations between the structural complexity of the reef habitats and the distribution of reef organisms. We created simulated 3D models of bare surface structures and 3D reconstructions of coral morphologies to investigate the behavior of various habitat metrics that were extracted from both Digital Elevation Models (DEMs) and 3D mesh models. Analyzing the resulting values provided us with important insights into how these metrics would compare with one another in the characterization of coral-reef habitats. Surface complexity (i.e., reef rugosity), fractal dimension extracted from DEMs and vector dispersion obtained from 3D mesh models exhibited consistent patterns in the ranking of structural complexity among the simulated bare surfaces and coral morphologies. The vector ruggedness measure obtained from DEMs at three different resolutions of 1, 2, and 4 cm effectively captured differences in the structural complexity among different coral morphologies. Profile curvature and planform curvature, on the other hand, were better suited to capture the structural complexity derived from surface topography such as walls and overhanging ledges. Our results indicate that habitat metrics extracted from DEMs are generally suitable when characterizing a relatively large plot of a coral reef captured from an overhead planar angle, while the 3D metric of vector dispersion is suitable when characterizing a coral colony or a relatively small plot methodically captured from various angles.

3D Fine-scale Terrain Variables from Underwater Photogrammetry: A New Approach to Benthic Microhabitat Modeling in a Circalittoral Rocky Shelf

The relationship between 3D terrain complexity and fine-scale localization and distribution of species is poorly understood. Here we present a very fine-scale 3D reconstruction model of three zones of circalittoral rocky shelf in the Bay of Biscay. Detailed terrain variables are extracted from 3D models using a structure-from-motion (SfM) approach applied to ROTV images. Significant terrain variables that explain species location were selected using general additive models (GAMs) and micro-distribution of the species were predicted. Two models combining BPI, curvature and rugosity can explain 55% and 77% of the Ophiuroidea and Crinoidea distribution, respectively. The third model contributes to explaining the terrain variables that induce the localization of Dendrophyllia cornigera. GAM univariate models detect the terrain variables for each structural species in this third zone (Artemisina transiens, D. cornigera and Phakellia ventilabrum). To avoid the time-consuming task of manual annotation of presence, a deep-learning algorithm (YOLO v4) is proposed. This approach achieves very high reliability and low uncertainty in automatic object detection, identification and location. These new advances applied to underwater imagery (SfM and deep-learning) can resolve the very-high resolution information needed for predictive microhabitat modeling in a very complex zone.