ORCID

Abstract

Marine spatial management requires accurate data on species and habitat distributions. For the deep sea, these data are lacking. Habitat suitability modelling offers a robust defensible means to fill data gaps, provided models are sufficiently reliable. We tested the performance of published models of 2 deep-sea habitat-forming taxa at low and high resolutions (~1 km and 200 m grid-cell size), across the extended exclusive economic zones of the UK and Ireland. We constructed new data-rich models and compared new and old estimates of the area of habitat protected, noting changes in the protected area network since 2015. Results of independent validation suggest that all published models perform worse than expected considering original cross-validation results, but model performance is still good or fair for Desmophyllum pertusum reef, with poorer performance for Pheronema carpenteri sponge models. High-resolution models using multibeam data out-perform low-resolution GEBCO-based models. Newly constructed models are good to excellent according to cross validation. New model spatial predictions reflect published models, but with a significant reduction in predicted extent. The current marine protected area network and the European Union ban on bottom trawling below 800 m protect 40 and 60% of D. pertusum reef-suitable habitat, respectively, and 11 and 100% of P. carpenteri-suitable habitat, respectively, within the model domain. We conclude that high-resolution models of D. pertusum reef distribution are a useful tool in spatial management. The poorer performing P. carpenteri model indicates areas for more detailed study. While low-resolution models can provide conservative estimates of percentage area-based conservation targets following the precautionary principle, high-resolution sea-floor mapping supports the development of better-performing models.

DOI

10.3354/meps14098

Publication Date

2022-08-25

Publication Title

MARINE ECOLOGY PROGRESS SERIES

Volume

695

ISSN

0171-8630

Embargo Period

2023-08-25

Organisational Unit

School of Biological and Marine Sciences

First Page

33

Last Page

51

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