A generalized light-driven model of community transitions along coral reef depth gradients

Aim Coral reefs shift between distinct communities with depth throughout the world. Yet, despite over half a century of research on coral reef depth gradients, researchers have not addressed the driving force of these patterns. We present a theoretical, process-based model of light's influence on the shallow to mesophotic reef transition as a single quantitative framework. We also share an interactive web application. Moving beyond depth as an ecological proxy will enhance research conducted on deeper coral reefs. Location Global; subtropical and tropical coral reefs, oligotrophic and turbid coastal waters. Time period Present day (2020). Major taxa Scleractinia. Methods We constructed ordinary differential equations representing the preferred light environments of shallow and mesophotic Scleractinia. We projected these as depth bands using light attenuation coefficients from around the world, and performed a sensitivity analysis. Results We found light relationships alone are sufficient to capture major ecological features across coral reef depth gradients. Our model supports the depth limits currently used in coral reef ecology, predicting a global range for the shallow-upper mesophotic boundary at 36.1 m +/- 5.6 and the upper-lower mesophotic boundary at 61.9 m +/- 9.6. However, our model allows researchers to move past these fixed depth limits, and quantitatively predict the depths of reef zones in locations around the world. Main conclusions The use of depth as a proxy for changes in coral reef communities offers no guidance for environmental variation between sites. We have shown it is possible to use light to predict the depth boundaries of reef zones as a continuous variable, and to accommodate this variability. Predicting the depths of reef zones in unusual light environments suggests that shallow-water turbid reefs should be considered as mesophotic coral ecosystems. Nonetheless, the current depth-based heuristics are relatively accurate at a global level.