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January 22nd, 2025

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National Autonomous University of Mexico Faculty of Science: Universidad Nacional Autonoma de Mexico Facultad de Ciencias

ecology

biorxiv

Multiscale Rugosity Assessment of Coral Reefs Using Underwater Photogrammetry

Barrera Falcon, E.Open in Google Scholar•Rioja-Nieto, R.Open in Google Scholar•Hernandez Landa, R. C.Open in Google Scholar

Understanding the structural complexity of coral reefs is essential for assessing their condition, biodiversity, and resilience. Traditional methods commonly use a rugosity index, based on the chain method, that overlooks the underlaying structure of coral reefs. However, digital underwater photogrammetry allows to build models of coral structures which can then be used to decompose reef topography across multiple layers. This study introduces a wavelet-based method for the multiscale analysis of reef rugosity, considering reefs surface and underlying characteristics. Data were collected from six reefs within the Cozumel Reefs National Marine Park (CRNP) at depths ranging from 6 to 14 m. High-resolution Digital Elevation Models (DEMs) and orthomosaics were constructed using digital underwater photogrammetry (UWP). The elevation profiles extracted from the DEMs were analyzed using a Maximum Overlap Discrete Wavelet Transform (MODWT), with a Daubechies mother wavelet to decompose the reef topography into local rugosity (related to live coral coverage) and underlying rugosity (related to the historical context of the formation of the reef matrix). The wavelet-based method effectively decomposed the DEMs into components representing rugosity at different scales, with the reconstructed DEMs being statistically equivalent to the data source (p> 0.05). Underlying reef characteristics contributed the most to the rugosity estimates. Significant differences in rugosity were observed between reefs (p< 0.05), where interpretations differed based on the contribution of surface and underlying characteristics. For the CRNP, Agariciid and branching corals are the primary drivers of surface rugosity (p<0.05), rather than the mound & boulder, and meandroid corals. Our results highlight that traditional methods to estimate rugosity can underestimate the importance of local rugosity in maintaining rugosity over time.

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