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Bio-ORACLE v2.0: extending marine data layers for bioclimatic modelling
Assis, J.; Tyberghein, L.; Bosch, S.; Verbruggen, H.; Serrão, E.A.; De Clerck, O. (2018). Bio-ORACLE v2.0: extending marine data layers for bioclimatic modelling. Glob. Ecol. Biogeogr. 27(3): 277-284. https://dx.doi.org/10.1111/geb.12693
In: Global Ecology and Biogeography. Blackwell Science: Oxford. ISSN 1466-822X; e-ISSN 1466-8238
Peer reviewed article  

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Keyword
    Marine/Coastal
Author keywords
    Bio-ORACLE; bioclimatic modelling; environmental data; global; kriging;macroecology; marine; species distribution modelling

Authors  Top 
  • Assis, J.
  • Tyberghein, L.
  • Bosch, S.
  • Verbruggen, H.
  • Serrão, E.A.
  • De Clerck, O.

Abstract
    Motivation: The availability of user-friendly, high-resolution global environmental datasets is crucial for bioclimatic modelling. For terrestrial environments, WorldClim has served this purpose since 2005, but equivalent marine data only became available in 2012, with pioneer initiatives like Bio-ORACLE providing data layers for several ecologically relevant variables. Currently, the available marine data packages have not yet been updated to the most recent Intergovernmental Panel on Climate Change (IPCC) predictions nor to present times, and are mostly restricted to the top surface layer of the oceans, precluding the modelling of a large fraction of the benthic diversity that inhabits deeper habitats. To address this gap, we present a significant update of Bio-ORACLE for new future climate scenarios, present-day conditions and benthic layers (near sea bottom). The reliability of data layers was assessed using a cross-validation framework against in situ quality-controlled data. This test showed a generally good agreement between our data layers and the global climatic patterns. We also provide a package of functions in the R software environment (sdmpredictors) to facilitate listing, extraction and management of data layers and allow easy integration with the available pipelines for bioclimatic modelling. Main types of variable contained: Surface and benthic layers for water temperature, salinity, nutrients, chlorophyll, sea ice, current velocity, phytoplankton, primary productivity, iron and light at bottom. Spatial location and grain: Global at 5 arcmin (c.0.08 degrees or 9.2 km at the equator). Time period and grain: Present (2000-2014) and future (2040-2050 and 2090-2100) environmental conditions based on monthly averages. Major taxa and level of measurement: Marine biodiversity associated with sea surface and epibenthic habitats. Software format: ASCII and TIFF grid formats for geographical information systems and a package of functions developed for R software.

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