Predictive habitat mapping has shown great promise to improve the understanding of the spatial distribution and complexity of benthic habitats and is a valuable means to highlight species-environment relationships where field data are limited. However, reliable predictions are hard to obtain in deep-sea environments, mainly owing to the usual paucity of high-resolution maps in these settings.

This study aimed to apply and test different spatial models to statistically predict the distribution of two Cold-Water Coral (CWC) species (Madrepora oculata, Dendrophyllia cornigera) in the Cap de Creus Canyon (NW Mediterranean), based on high-resolution swath-bathymetry (5 m resolution) and video observations through the manned submersible JAGO. Along the Cap de Creus Canyon, presence/absence of CWC was estimated in each 5m resolution pixel based on video imagery.

The results of the models show that CWC were most likely to be found on the steep walls of the southern flank which face the head and the thalweg of the canyon, aligning with the known CWC ecology acquired from previous studies. It was found that the drivers of distribution were slope and aspect for Madrepora oculata and rugosity for Dendrophyllia cornigera, although in some cases the three models identified different variables controlling each species.

The study highlights the need to adopt high-resolution spatial scales to produce reliable predictions of suitability for benthic communities, reducing the risk of bias due to mismatch between spatial scales.

It is concluded that ensemble prediction maps can represent a way forward to increase the solidity of habitat distribution models. A final up-scaled map maintaining that fine-scale information, can represent a valuable and solid spatial tool for stakeholders and end-users, which need to manage large areas and define science-based policies for the management of natural resources.

Lo Iacono et al. (2018) Predicting cold-water coral distribution in the Cap de Creus Canyon (NW Mediterranean): Implications for marine conservation planning. Progress in Oceanography 169:169-180.