Abstract
Energy fluxes throughout ecosystems can be predicted by scaling relationships linking metabolic rates with the structural attributes of organisms and habitats. Coral reef ecosystems are structurally complex and highly productive, yet quantitative links between habitat structure and productivity have not been identified. Here we use benthic metabolic chambers to quantify rugosity–productivity relationships across shallow reef plots in Australia and Hawaiʻi. In each region, habitat rugosity explained 56–58% of variation in daytime community metabolic rates, despite naturally varying light, temperature and benthic composition (for example, coral versus algae cover). Allometric scaling with habitat rugosity was found for gross photosynthesis and respiration (scaling exponents 1.23 ± 0.19 and 1.45 ± 0.23, respectively), and sites with higher rugosity produced a greater surplus of photosynthetic carbon after meeting community respiration demands (higher net community production). Nevertheless, the proportion of gross photosynthesis allocated to net community production was diminished on high-rugosity reefs (lower carbon use efficiency), possibly because of increased respiration from cryptic, heterotrophic organisms. Our study shows that habitat complexity is a strong predictor of energy fluxes in a variable reef environment, with consistent scaling properties in two distinct regions. Moreover, reefs with complex habitat structure fix more net organic carbon for biomass accumulation and export to other organisms.
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Data availability
Data are available via GitHub at https://github.com/mikemcwilliam/metabolism3D and via Zenodo at https://doi.org/10.5281/zenodo.19463715 (ref. 70).
Code availability
Code is available via GitHub at https://github.com/mikemcwilliam/metabolism3D and via Zenodo at https://doi.org/10.5281/zenodo.19463715 (ref. 70).
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Acknowledgements
This research was supported by a Lizard Island Postdoctoral Fellowship courtesy of the Maple-Brown Family Foundation and Australian Museum’s Lizard Island Research Station. M.M. was supported by a Leverhulme Early Career Fellowship (ECF-2021-512). M.D. was funded by the European Union (CoralINT, GA 101044975). Views and opinions expressed are, however, those of the author(s) only and do not necessarily reflect those of the European Union or the European Research Council. Neither the European Union nor the granting authority can be held responsible for them.
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M.M. and J.S.M. conceived the study. M.M., J.S.M., M.D. and M.O.H. designed the study. M.M., N.R. and E.A.W. collected the data. M.O.H., M.S.P. and M.D. provided support on analyses and concept development. M.M. analysed the data and wrote the first draft of the article. All authors contributed to the revising and editing of the final article.
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Extended data
Extended Data Fig. 1 Benthic chamber used to measure community productivity.
(a) Diagram of materials used to construct benthic metabolic chambers. (b) Example of 3D mosaics extracted from chambers used to quantify habitat rugosity. (c) Example of logger reading extracted from chambers, including oxygen, light, and temperature. Green areas indicated readings used to calculate NCP (in light conditions) and blue areas indicate readings used to calculate R (in dark conditions).
Extended Data Fig. 2 Map of reef plots.
Locations of plots (yellow points) sampled at Lizard Island (left) and Kaneohe Bay, Hawaii (right) are shown. An ANOVA of site versus GPP, NCP and R indicated no significant effect of site location on community metabolic rates (p = 0.183 for GPP, p = 0.182 for NCP, p = 0.277 for R). Imagery from Google Maps © 2025.
Extended Data Fig. 3 Composition of assemblages within benthic chambers.
Bar plots show the % cover of different benthic groups (colours) at each plot in the analysis. The identity of the dominant taxon used to explore the influence of benthic composition is shown above each bar.
Extended Data Fig. 4 Rugosity-productivity relationships in each region.
Linear relationships between log(habitat rugosity) and log(metabolic rates) shown separately for each region (n = 70 GBR, n = 25 Hawai’i). Relationships are shown for (a) Gross Primary Production, (b) Respiration, (c) Net Community Production, and (d) Carbon Use Efficiency.
Extended Data Fig. 5 Rugosity-productivity relationships across dominant benthic taxa.
Linear relationships between log(habitat rugosity) and log(metabolic rates) are shown for each dominant benthic taxon excluding sand and seagrass, coloured by taxon as per Fig. 2. Sample sizes for each dominant taxon are shown in Fig. 2.
Extended Data Fig. 6 Variation in metabolic rates across sites.
Each bar (site) is ranked by rugosity (with rugosity increasing from left to right), with separate panels for the two regions. The upper panel shows absolute rates of NPP and R, such that the total height of the panel is reflective of GPP. The lower panel shows the proportion of the GPP allocated into NPP versus R.
Extended Data Fig. 7 Relationships between rugosity and carbon use efficiency across dominant taxa.
Linear relationships between log(habitat rugosity) and the carbon use efficiency (CUE) are shown for each dominant benthic taxon (excluding sand and seagrass). Taxa are presented separately in the upper panels, and combined in the lower panel. Sample sizes for each dominant taxon are shown in Fig. 2.
Extended Data Fig. 8 Effects of including or omitting water pumps on chamber NCP.
(a) Relationship between rugosity and NCP for all chambers (grey points or lines) and for chambers that were tested with and without battery-powered pumps (n = 13, coloured points or lines). A mixed-effects model of NCP versus rugosity, light, and pump presence/absence produced an insignificant effect of pumps (p = 0.45) while maintain a significant effect of rugosity (p = 0.042). (b) Variation in NCP across sites for which metabolism was quantified with and without water pumps are shown along with the full distribution of net photosynthesis values across the study. (c) Histogram of change in NCP with the addition of pumps. The red line indicates the mean change.
Extended Data Fig. 9 A test of adequate water mixing within chambers.
The test was conducted using two oxygen sensors placed in different locations within the same chamber. (a) Differences in measured NCP across each chamber (n = 20), ranked by NCP. (b) Relationship between rugosity and NCP with differences in measurements within chambers plotted.
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McWilliam, M., Dornelas, M., Hoogenboom, M.O. et al. Habitat complexity enhances primary productivity on coral reefs.
Nat Ecol Evol (2026). https://doi.org/10.1038/s41559-026-03093-3
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DOI: https://doi.org/10.1038/s41559-026-03093-3
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