Bio‐ORACLE v3.0. Pushing marine data layers to the CMIP6 Earth System Models of climate change research

Author:

Assis Jorge12ORCID,Fernández Bejarano Salvador Jesús3ORCID,Salazar Vinícius W.4ORCID,Schepers Lennert3ORCID,Gouvêa Lidiane1ORCID,Fragkopoulou Eliza1ORCID,Leclercq Frederic3ORCID,Vanhoorne Bart3ORCID,Tyberghein Lennert3ORCID,Serrão Ester A.1ORCID,Verbruggen Heroen5ORCID,De Clerck Olivier6

Affiliation:

1. Centre of Marine Sciences (CCMAR/CIMAR LA) Universidade do Algarve Faro Portugal

2. Faculty of Bioscience and Aquaculture Nord Universitet Bodø Norway

3. Flanders Marine Institute Ostend Belgium

4. Melbourne Integrative Genomics, School of Mathematics and Statistics University of Melbourne Melbourne Victoria Australia

5. School of BioSciences University of Melbourne Parkville Victoria Australia

6. Department of Biology, Phycology Research Group Ghent University Ghent Belgium

Abstract

AbstractMotivationImpacts 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.Main Types of Variable ContainedSurface and benthic layers for, chlorophyll‐a, diffuse attenuation coefficient, dissolved iron, dissolved oxygen, nitrate, ocean temperature, pH, phosphate, photosynthetic active radiation, total phytoplankton, total cloud fraction, salinity, silicate, sea‐water direction, sea‐water velocity, topographic slope, topographic aspect, terrain ruggedness index, topographic position index and bathymetry, and surface layers for air temperature, mixed layer depth, sea‐ice cover and sea‐ice thickness.Spatial Location and GrainGlobal at 0.05° resolution.Time Period and GrainDecadal from present‐day to the end of the 21st century (2000–2100).Major Taxa and Level of MeasurementMarine biodiversity associated with surface and epibenthic habitats.Software FormatA package of functions developed for Python and R software.

Funder

HORIZON EUROPE Framework Programme

Fundação para a Ciência e a Tecnologia

European Marine Biological Resource Centre Belgium

University of Melbourne

Publisher

Wiley

Reference58 articles.

1. Incorporating climate velocity into the design of climate‐smart networks of marine protected areas

2. Ensemble forecasting of species distributions

3. Post-2020 biodiversity targets need to embrace climate change

4. Assis J.(2023).Bio‐ORACLE Marine data layers for ecological modelling.https://www.bio‐oracle.org

5. Major shifts at the range edge of marine forests: The combined effects of climate changes and limited dispersal;Assis J.;Scientific Reports,2017

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