Data from: The influence of data resolution on predicted distribution and estimates of extent of current protection of three ‘listed’ deep-sea habitats

Modelling approaches have the potential to significantly contribute to the
spatial management of the deep-sea ecosystem in a cost effective manner.
However, we currently have little understanding of the accuracy of such
models, developed using limited data, of varying resolution. The aim of
this study was to investigate the performance of predictive models
constructed using non-simulated (real world) data of different resolution.
Predicted distribution maps for three deep-sea habitats were constructed
using MaxEnt modelling methods using high resolution multibeam bathymetric
data and associated terrain derived variables as predictors. Model
performance was evaluated using repeated 75/25 training/test data
partitions using AUC and threshold-dependent assessment methods. The
overall extent and distribution of each habitat, and the percentage
contained within an existing MPA network were quantified and compared to
results from low resolution GEBCO models. Predicted spatial extent for
scleractinian coral reef and Syringammina fragilissima aggregations
decreased with an increase in model resolution, whereas Pheronema
carpenteri total suitable area increased. Distinct differences in
predicted habitat distribution were observed for all three habitats.
Estimates of habitat extent contained within the MPA network all increased
when modelled at fine scale. High resolution models performed better than
low resolution models according to threshold-dependent evaluation. We
recommend the use of high resolution multibeam bathymetry data over low
resolution bathymetry data for use in modelling approaches. We do not
recommend the use of predictive models to produce absolute values of
habitat extent, but likely areas of suitable habitat. Assessments of MPA
network effectiveness based on calculations of percentage area protection
(policy driven conservation targets) from low resolution models are likely
to be fit for purpose.