Terrain variables used for ensemble distribution modelling of vulnerable marine ecosystems indicator taxa on data-limited seamounts of Cabo Verde (NW Africa)

Aim: Seamounts are conspicuous geological features with an important ecological role and can be considered Vulnerable Marine Ecosystems (VMEs). Since many deep-sea regions remain largely unexplored, investigating the occurrence of VME taxa on seamounts is challenging. Our study aimed to predict the distribution of four cold-water coral (CWC) taxa, indicators for VMEs, in a region where occurrence data is scarce.
Location: Seamounts around the Cabo Verde Archipelago (NW Africa).
Methods: We used species presence-absence data obtained from Remotely Operated Vehicle (ROV) footage collected during two research expeditions. Terrain variables calculated using a multiscale approach from a 100 m resolution bathymetry grid, as well as physical oceanographical data from the VIKING20X model, at a native resolution of 1/20°, were used as environmental predictors. Two modelling techniques (Generalized Additive Model (GAM) and Random Forest (RF)) were employed and single-model predictions were combin..., Terrain variables were derived from a 100 m resolution bathymetry grid, created from a compilation of all available bathymetry data collected by multibeam echosounder (MBES) in the Cabo Verde region. We used an analytical multiscale approach to calculate terrain variables by considering, when possible, different neighbourhood sizes (i.e., number of grid-cells (n)) for calculations. In this study, slope, aspect (converted to eastness and northness), and three types of terrain curvature (plan, profile and mean) were calculated following a Fibonacci sequence of four increasing n values (n = 3, 9, 17, 33) (Dolan et al., 2008). For this, the functions ‘SlpAsp’ and ‘Qfit’ of the “Multiscale DTM” library (Ilich et al., 2023) were used in R Studio. Topographic Position Index (TPI) and Vector Ruggedness Measure (VRM) were calculated at two scales, both fine- and broad-scales (n = 3, 33), using the ‘tpi’ and ‘vrm’ functions, respectively, of the “spatialEco” R Package (Evans and Ram, 2021). Rough..., , # Terrain variables used for ensemble distribution modelling of Vulnerable Marine Ecosystems indicator taxa on data-limited seamounts of Cabo Verde (NW Africa)

[https://doi.org/10.5061/dryad.0vt4b8h5g](https://doi.org/10.5061/dryad.0vt4b8h5g)

Dataset and code to calculate terrain variables used in the manuscript entitled \"Ensemble modelling to predict the distribution of Vulnerable Marine Ecosystems indicator taxa on data-limited seamounts of Cabo Verde (NW Africa)\" published in \"Diversity and Distributions\".

We have submitted a shapefile to mask the spatial extent considered in our study (“Seamounts_Mask.zip”); a raster file of a Multibeam Echosounder (MBES) bathymetry data for the Cabo Verde region, at 100 m resolution (“00_Caboverde_bathy_100m_UTM26N.tif”) and a R script (“DataProcessing_R_code.Rmd”) used to calculate terrain variables using a multi-scale approach and to prepare oceanographical data (available in Schwarzkopf, 2024) for modelling.

## Description of the data and fi...