Predicting the Distribution of Mesophotic Coral Ecosystems in the Chagos Archipelago

To support conservation efforts, accurate mapping of marine organism community' distribution has become more critical than ever before. While previous mapping endeavours have primarily focused on easily accessible shallow-water habitats, there remains limited knowledge about the ecosystems lying beyond SCUBA diving depths, such as mesophotic coral ecosystems (MCEs, ~30-150 m). MCEs are important habitats from an ecological and conservation perspective, yet little is known about the environmental factors that shape these ecosystems and their distribution, particularly in the Indian Ocean region. The goals of this study are to (1) predict the spatial distribution and extent of distinct benthic communities and MCEs in the Chagos Archipelago, central Indian Ocean, (2) test the effectiveness of a range of environmental and topography derived variables to predict the location of MCEs around Egmont Atoll and the Archipelago, and (3) independently validate the models produced. In addition, we compared the MCEs predicted extent in the Archipelago for the models derived from high-resolution multibeam and low-resolution GEBCO bathymetry data. Using maximum entropy modelling, all models resulted in excellent (> 0.9) performances, for AUC and threshold-dependent metrics, predicting extensive and previously undocumented MCEs across the entire Archipelago with, however, differences in the predicted extent between the high- and low-resolution models. Independent validation resulted in fair (> 0.7 AUC) and poor (> 0.6 AUC) performances for the high-resolution and low-resolution models, respectively. Photosynthetically active radiation (PAR), temperature, chlorophyll-a, and topographically derived variables were identified as the most influential predictors. In conclusion, this study provides the first prediction of the distribution of MCEs and their distinct benthic communities in the Archipelago. It highlights their significance in terms of potential extent and response to various environmental factors, supporting decision making for prioritising future survey sites to study MCEs across the Archipelago and targeting ecologically important areas for conservation.