Quantifying coral reef carbonate budgets: a comparison between ReefBudget and CoralNet

Abstract Calcium carbonate production constitutes one of the core processes that drive coral reef ecosystem functioning and can be assessed using in-water or image-based survey methods, which have not previously been compared. This study compares carbonate production estimates from in-water ReefBudget surveys and image-based CoralNet analyses in Puerto Rico, Indonesia, and Chagos Archipelago. Methods were compared for different regions (Western Atlantic and Indo-Pacific), reef settings (low and high coral cover), CoralNet calcification versions (v1 and v2), and input metrics (regional vs. local coral growth rates). We show similar gross carbonate production estimates between methods, indicating that area-normalised scaling of calcification rates and assumptions about colony size and rugosity employed in CoralNet produce comparable estimates to ReefBudget surveys. Divergences in carbonate production estimates are potentially driven by differences in survey methods (reef contour measurements vs. planar imagery) and survey effort, which affect calcifier cover estimates, particularly at low coral cover sites. Local versus regional growth rate comparisons suggest site-specific factors can influence accuracy more than method choice. Our findings suggest that image-based methods can allow rapid reef-scale calcification estimates from photo or video imagery. These methods, combined with machine learning substrate classification algorithms, can estimate both benthic cover and carbonate production over larger reef areas and can be applied to historically collect benthic cover data to track carbonate production trends. We encourage researchers to recognise situation-specific differences in methodologies and select the one most suitable for their specific study site, required level of accuracy, and time constraints for fieldwork and image analysis.

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Publication Details

Journal
Coral Reefs
Published
2025-03-17
DOI
https://doi.org/10.1007/s00338-025-02620-1
Citations
4
Primary Topic
Coral and Marine Ecosystems Studies
Type
article
Field-Weighted Citation Impact
6.87

Funders

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article

Quantifying coral reef carbonate budgets: a comparison between ReefBudget and CoralNet

John R. Turner, Andreas J. Andersson, Ines D. Lange, Travis A. Courtney et al.
4 citations
Coral Reefs
Coral and Marine Ecosystems Studies
6.87
article

Quantifying coral reef carbonate budgets: a comparison between ReefBudget and CoralNet

John R. Turner, Andreas J. Andersson, Ines D. Lange, Travis A. Courtney, Cut Aja Gita Alisa, Ronan Roche, Sivajyodee Sannassy Pilly, Tries B. Razak, Chris T. Perry, Joseph E. Townsend, Stephen Chan, David Kriegman
article en
4 citations

Abstract

Abstract Calcium carbonate production constitutes one of the core processes that drive coral reef ecosystem functioning and can be assessed using in-water or image-based survey methods, which have not previously been compared. This study compares carbonate production estimates from in-water ReefBudget surveys and image-based CoralNet analyses in Puerto Rico, Indonesia, and Chagos Archipelago. Methods were compared for different regions (Western Atlantic and Indo-Pacific), reef settings (low and high coral cover), CoralNet calcification versions (v1 and v2), and input metrics (regional vs. local coral growth rates). We show similar gross carbonate production estimates between methods, indicating that area-normalised scaling of calcification rates and assumptions about colony size and rugosity employed in CoralNet produce comparable estimates to ReefBudget surveys. Divergences in carbonate production estimates are potentially driven by differences in survey methods (reef contour measurements vs. planar imagery) and survey effort, which affect calcifier cover estimates, particularly at low coral cover sites. Local versus regional growth rate comparisons suggest site-specific factors can influence accuracy more than method choice. Our findings suggest that image-based methods can allow rapid reef-scale calcification estimates from photo or video imagery. These methods, combined with machine learning substrate classification algorithms, can estimate both benthic cover and carbonate production over larger reef areas and can be applied to historically collect benthic cover data to track carbonate production trends. We encourage researchers to recognise situation-specific differences in methodologies and select the one most suitable for their specific study site, required level of accuracy, and time constraints for fieldwork and image analysis.

Coral ReefsVol. 44(2)
Scripps Institution of Oceanography (US), Bangor University (GB), IPB University (ID), University of Exeter (GB), University of California San Diego (US), University of Puerto Rico-Mayaguez (PR)
Fondation Bertarelli, Fisheries Society of the British Isles
Openalex Percentile: Top 4%
Coral and Marine Ecosystems Studies
6.87
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