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Published VersionCC BY V4.0, Open Access
Journal article
Structural Complexity of Coral Reefs in Guam, Mariana Islands
Remote Sensing, Vol.15(23), pp.1-15
2023
Abstract
The complexity of tropical reef habitats affects the occurrence and diversity of the organisms residing in these ecosystems. Quantifying this complexity is important to better understand and monitor reef community assemblages and their roles in providing ecological services. This study employed structure-from-motion photogrammetry to produce accurate 3D reconstructions of eight reefs in Guam and quantified the structural complexity of these sites using seven terrain metrics: rugosity, slope, vector ruggedness measure (VRM), multiscale roughness (magnitude and scale), plan curvature, and profile curvature. The relationships between terrain complexity, benthic community diversity, and coral cover were investigated with generalized linear models. While the average structural complexity metrics did not differ between most sites, there was significant variation within sites. All surveyed transects exhibited high structural complexity, with an average rugosity of 2.28 and an average slope of 43 degrees. Benthic diversity was significantly correlated with the roughness magnitude. Coral cover was significantly correlated with slope, roughness magnitude, and VRM. This study is among the first to employ this methodology in Guam and provides additional insight into the structural complexity of Guam's reefs, which can become an important component of holistic reef assessments in the future.
Details
- Title
- Structural Complexity of Coral Reefs in Guam, Mariana Islands
- Authors
- Matthew S. Mills (Corresponding Author) - University of the Sunshine Coast, Queensland, School of Science, Technology and EngineeringTom Schils (Author) - University of GuamAndrew D. Olds (Author) - University of the Sunshine Coast, Queensland, School of Science, Technology and EngineeringJavier X. Leon (Author) - University of the Sunshine Coast, Queensland, School of Science, Technology and Engineering
- Publication details
- Remote Sensing, Vol.15(23), pp.1-15; 15
- Publisher
- MDPI AG
- Date published
- 2023
- DOI
- 10.3390/rs15235558
- ISSN
- 2072-4292
- Copyright note
- © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
- Data Availability
- The data computed and analyzed in this study are summarized in Table S1. However, the spatial datasets (DSMs) generated and/or analyzed during this study are available from the corresponding author upon reasonable request. These data are not publicly available due to the substantial file sizes.
- Grant note
- This research was funded by the National Aeronautics and Space Administration (NASA) and the National Science Foundation (NSF) under grant numbers 80NSSC17M0052 and OIA-1946352 awarded to T.S. and managed through the Guam EPSCoR offices of NASA and NSF. The work for this paper was also partly funded as an award to M.S.M. by an HDR Support Grant provided by the University of the Sunshine Coast.
- Organisation Unit
- School of Science, Technology and Engineering; Sustainability Research Cluster
- Language
- English
- Record Identifier
- 99986598702621
- Output Type
- Journal article
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- Domestic collaboration
- International collaboration
- Web Of Science research areas
- Environmental Sciences
- Geosciences, Multidisciplinary
- Imaging Science & Photographic Technology
- Remote Sensing
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