Community composition predicts photogrammetry-based structural complexity on coral reefs

The capacity of coral reefs to provide ecosystem services is directly related to their three-dimensional structural complexity. This parameter is also correlated with total fish biomass, reef resilience to external stresses and the dissipation of wave energy. However, information on structural complexity (i.e., reef rugosity) has not always been assessed in historical monitoring programs, and long-term trends are sometimes unavailable. In this study, we show that it is possible to predict and hindcast the three-dimensional complexity of coral reefs by combining photogrammetry, statistical modeling and historical benthic community data. We calibrated lasso generalized linear models and boosted regression trees to predict structural complexity from photogrammetry transects around Moorea (French Polynesia). Our models were able to predict structural complexity with high accuracy (cross-validated R2 ranges between 0.81 and 0.9). We then used our models to hindcast historical trends in 3D structural complexity using community composition data collected in Moorea from 2004 to 2017. The temporal analysis highlighted the severe impact of a crown-of-thorns (COTS) outbreak from 2006 to 2009 and Cyclone Oli in 2010. In conjunction, these two events reduce coral cover from ~ 50% to almost zero. While the collection of actual data is always to be preferred, our model captured these effects, confirming the capacity of this modeling technique to predict structural complexity on the basis of assemblage composition.