Journal article Open Access

Climate-induced changes in the suitable habitat of cold-water corals and commercially important deep-sea fishes in the North Atlantic

Morato, Telmo; González-Irusta, José-Manuel; Dominguez-Carrió, Carlos; Wei, Chih-Lin; Davies, Andrew; Sweetman, Andrew K; Taranto, Gerald H; Beazley, Lindsay; García-Alegre, Ana; Grehan, Anthony; Laffargue, Pascal; Murillo, Francisco Javier; Sacau, Mar; Vaz, Sandrine; Kenchington, Ellen; Arnaud-Haond, Sophie; Callery, Oisín; Chimienti, Giovanni; Cordes, Erik; Egilsdottir, Hronn; Freiwald, André; Gasbarro, Ryan; Gutiérrez-Zárate, Cristina; Gianni, Matthew; Gilkinson, Kent; Wareham Hayes, Vonda E; Hebbeln, Dierk; Hedges, Kevin; Henry, Lea-Anne; Johnson, David; Koen-Alonso, Mariano; Lirette Cam; Mastrototaro, Francesco; Menot, Léniack; Molodtsova, Tina; Durán Munoz, Pablo; Orejas, Covadonga; Pennino, Maria Grazia; Puerta, Patricia; Ragnarsson, Stefán Á; Ramiro-Sánchez, Berta; Rice, Jake; Rivera, Jesús; Roberts, J Murray; Ross, Steve W; Rueda, José L; Sampaio, Íris; Snelgrove, Paul; Stirling, David; Treble, Margaret A; Urra, Javier; Vad, Johanne; van Oevelen, Dick; Watling, Les; Walkusz, Wojciech; Wienberg, Claudia; Woillez, Mathieu; Levin, Lisa A; Carreiro-Silva, Marina

ABSTRACT. The deep sea plays a critical role in global climate regulation through uptake and storage of heat and carbon dioxide. However, this regulating service causes warming, acidification and deoxygenation of deep waters, leading to decreased food availability at the seafloor. These changes and their projections are likely to affect productivity, biodiversity and distributions of deep-sea fauna, thereby compromising key ecosystem services. Understanding how climate change can lead to shifts in deep-sea species distributions is critically important in developing management measures. We used environmental niche modelling along with the best available species occurrence data and environmental parameters to model habitat suitability for key cold-water coral and commercially important deep-sea fish species under present-day (1951–2000) environmental conditions and to project changes under severe, high emissions future (2081–2100) climate projections (RCP8.5 scenario) for the North Atlantic Ocean. Our models projected a decrease of 28%–100% in suitable habitat for cold-water corals and a shift in suitable habitat for deep-sea fishes of 2.0°–9.9° towards higher latitudes. The largest reductions in suitable habitat were projected for the scleractinian coral Lophelia pertusa and the octocoral Paragorgia arborea, with declines of at least 79% and 99% respectively. We projected the expansion of suitable habitat by 2100 only for the fishes Helicolenus dactylopterus and Sebastes mentella (20%–30%), mostly through northern latitudinal range expansion. Our results projected limited climate refugia locations in the North Atlantic by 2100 for scleractinian corals (30%–42% of present-day suitable habitat), even smaller refugia locations for the octocorals Acanella arbuscula and Acanthogorgia armata (6%–14%), and almost no refugia for P. arborea. Our results emphasize the need to understand how anticipated climate change will affect the distribution of deep-sea species including commercially important fishes and foundation species, and highlight the importance of identifying and preserving climate refugia for a range of area-based planning and management tools.

FUNDING INFORMATION. Global Ocean Biodiversity Initiative, Grant/ Award Number: 16-IV-049; Icelandic Research Fund, Grant/Award Number: 174552-052; Fundación Séneca, Grant/ Award Number: 20632/IV/18; PO2020, Grant/Award Number: Acores-01-0145- FEDER-000056; Fundação para a Ciência e a Tecnologia Naumann, Grant/Award Number: FCT/UID/MAR/04292/2013 and IF/01194/2013; H2020 Environment, Grant/Award Number: 678760 and 679849; RF State Assignment, Grant/Award Number: 0149-2019-0009; IFCT, Grant/ Award Number: IF/01194/2013/CP1199/ CT0002; NSF OCE, Grant/Award Number: OCE-1829623. ACKNOWLEDGMENTS. This work contributes to the European Union's Horizon 2020 re- search and innovation programme under grant agreement No 678760 (ATLAS) and No 679849 (SponGES). This output reflects only the authors' views and the European Union cannot be held responsible for any use that may be made of the information contained therein. TM was supported by Program Investigador FCT (IF/01194/2013), IFCT Exploratory Project (IF/01194/2013/CP1199/CT0002) from the Fundação para a Ciência e Tecnologia (POPH and QREN), PO2020 MapGes (Acores-01-0145-FEDER-000056). TM, CDC, JMGI, GHT and MCS also acknowledge funds provided by the Fundação para a Ciência e a Tecnologia (FCT) through the strategic project (FCT/UID/MAR/04292/2013) granted to MARE. LAL is supported by NSF OCE OCE-1829623 and a DOOS subcontract from the Consortium for Ocean Leadership. HE and SR acknowledge funds by the Icelandic Research Fund (174552-052) and SR for grant from Fundación Séneca (20632/IV/18). DJ acknowledges the Global Ocean Biodiversity Initiative, part of the International Climate Initiative (grant no. 16-IV-049-Global-A-Global Ocean Biodiversity Initiative GOBI). T Molodtsova acknowledges RF State Assignment 0149-2019-0009. We acknowledge all of those involved in data col- lection and modelling, namely Anna Rengstorf, Inge van den Beld and Tim Siferd, among many others. Finally, we thank the Food and Agriculture Organization ABNJ Deep-Seas Program, the Deep Ocean Stewardship Initiative, Tony Thompson and Maria Baker for their contributions towards this work. DATA AVAILABILITY STATEMENT. The bathymetry data supporting the analyses are publicly avail- able from the EMODnet Digital Terrain Model and the General Bathymetric Chart of the Oceans portals (https://portal.emodnet- bathymetry.eu/ and https://www.gebco.net/data_and_products/ gridded_bathymetry_data/, respectively). The environmental data used in this study are publicly available from the Earth System Grid Federation (ESGF) Peer-to-Peer (P2P) enterprise system (https:// esgf.llnl.gov/). All analyses were conducted using publicly available packages from the Comprehensive R Archive Network (https://cran. r-project.org/), namely the R packages MOPA, Raster, Dismo, mgcv, randomForest, MuMIn, EnMEVAL, and boot. The Benthic Terrain Model 3.0 tool is available from the ESRI Oceans GitHub repository (https://github.com/EsriOceans/btm). The processed environmen- tal data layers used in this study are publicly available through the PANGAEA data publisher portal (https://doi.org/10.1594/PANGA EA.911117). The model outputs are also available for download from PANGAEA (https://doi.org/10.1594/PANGAEA.910319).
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