Tracking skeletal change in dead coral colonies: A non-invasive 3D photogrammetry workflow and case-study application
Year: 2026
Type: preprint
Abstract: The breakdown of coral structures by bioeroding organisms is a key reef process. Understanding how reef material is lost over time is increasingly important as reefs degrade under climate change. Quantifying bioerosion at the colony scale requires repeated observations of recently dead coral skeletons through time. Large-area photogrammetry offers a reliable, non-invasive approach, allowing thousands of colonies to be tracked simultaneously across repeated surveys. Here, we present a protocol to quantify structural changes from surficial bioerosion and overgrowth in coral skeletons using 3D reconstructions from large-area photogrammetry. The workflow identifies recently dead colonies, extracts the corresponding image subsets, and reconstructs sub-millimetre-resolution 3D models of individual skeletons. Models from the first survey (2022) were aligned with those from the second (2023) and compared using the Geomagic 3D compare tool. To assess precision, we randomly selected 10 skeletons and generated 10 independent reconstructions of each, then compared variation in estimated volume and surface area. Precision varied among morphologies. For surface area, relative standard error (RSE) was lowest for tabular Acropora (0.22–0.31%) and highest for branching non-Acropora (1.20–5.07%). Volume estimates followed the same pattern, with RSE of 0.22–1.78% for tabular Acropora and 2.48–5.97% for branching non-Acropora. We applied the protocol to 60 skeletons from the southern Great Barrier Reef between May 2022 and May 2023. Erosion and deposition rates differed among morphotaxa, with branching non-Acropora skeletons eroding significantly faster. This approach enables repeatable quantification of change in coral skeleton structure and provides a scalable tool for assessing reef degradation.
Source: Research Square
Institution: Australian Institute of Marine Science
Language: English
Subfield: Ecology
Field: Environmental Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7225820655
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