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

Ross, Lauren K.; Ross, Rebecca E.; Stewart, Heather A.; Howell, Kerry L.. 2015 The influence of data resolution on predicted distribution and estimates of extent of current protection of three ‘listed’ deep-sea habitats. PLOS ONE, 10 (10), e0140061. https://doi.org/10.1371/journal.pone.0140061

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Official URL: http://journals.plos.org/plosone/article?id=10.137...

Abstract/Summary

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.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	https://doi.org/10.1371/journal.pone.0140061
Additional Keywords:	Habitats; Conservation science; coral reefs; data management; marine conservation; corals; terrain; sediment; predictive mapping
NORA Subject Terms:	Earth Sciences Ecology and Environment Marine Sciences Data and Information
Date made live:	03 Nov 2015 09:55 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/512111

Item Type:

Publication - Article

Digital Object Identifier (DOI):

https://doi.org/10.1371/journal.pone.0140061

Additional Keywords:

Habitats; Conservation science; coral reefs; data management; marine conservation; corals; terrain; sediment; predictive mapping

NORA Subject Terms:

Earth Sciences
Ecology and Environment
Marine Sciences
Data and Information

Date made live:

03 Nov 2015 09:55 +0 (UTC)

URI:

https://nora.nerc.ac.uk/id/eprint/512111