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Bio-ORACLE v3.0. Pushing marine data layers to the CMIP6 Earth system models of climate change research Assis, J.; Fernández Bejarano, S.J.; Salazar, V.W.; Schepers, L.; Gouvêa, L.; Fragkopoulou, E.; Leclercq, F.; Vanhoorne, B.; Tyberghein, L.; Serrão, E.A.; Verbruggen, H.; De Clerck, O. (2024). Bio-ORACLE v3.0. Pushing marine data layers to the CMIP6 Earth system models of climate change research. Glob. Ecol. Biogeogr. 33(4): e13813. https://dx.doi.org/10.1111/geb.13813 In: Global Ecology and Biogeography. Blackwell Science: Oxford. ISSN 1466-822X; e-ISSN 1466-8238

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Beschikbaar in	Auteurs
VLIZ: Non-open access 400235 [ aanvragen ] VLIZ: Open Marine Archive 396412 [ download pdf ]

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Auteurs		Top
Assis, J. Fernández Bejarano, S.J. Salazar, V.W. Schepers, L.	Gouvêa, L. Fragkopoulou, E. Leclercq, F. Vanhoorne, B.	Tyberghein, L. Serrão, E.A. Verbruggen, H. De Clerck, O.

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Abstract

Motivation: Impacts of climate change on marine biodiversity are often projected with species distribution modelling using standardized data layers representing physical, chemical and biological conditions of the global ocean. Yet, the available data layers (1) have not been updated to incorporate data of the Sixth Phase of the Coupled Model Intercomparison Project (CMIP6), which comprise the Shared Socioeconomic Pathway (SSP) scenarios; (2) consider a limited number of Earth System Models (ESMs), and (3) miss important variables expected to influence future biodiversity distributions. These limitations might undermine biodiversity impact assessments, by failing to integrate them within the context of the most up-to-date climate change projections, raising the uncertainty in estimates and misinterpreting the exposure of biodiversity to extreme conditions. Here, we provide a significant update of Bio-ORACLE, extending biologically relevant data layers from present-day conditions to the end of the 21st century Shared Socioeconomic Pathway scenarios based on a multi-model ensemble with data from CMIP6. Alongside, we provide R and Python packages for seamless integration in modelling workflows. The data layers aim to enhance the understanding of the potential impacts of climate change on biodiversity and to support well-informed research, conservation and management.

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