Biogeographic patterns in the deep ocean: a revision of the Global Open Oceans and Deep-Seabed classification system Berta Ramiro Sánchez1*, Lea-Anne Henry1, J. Murray Roberts1, Telmo Morato2, Gérald Hechter Taranto2, Marina Carreiro-Silva2, Íris Sampaio2, Sophie Arnaud-Haond3, Bramley Murton4 1School of GeoSciences, The University of Edinburgh, 2IMAR-Uaz, 3MARBEC-Ifremer, 4NOC Berta Ramiro Sánchez Introduction Biogeographic classifications are used to analyse patterns of marine biodiversity; advance knowledge of evolutionary and ecosystem processes; and assist governments in designing management tools. The Global Open Oceans and Deep Seabed (GOODS) biogeographic classification system for the deep ocean1,2 was developed to aid management efforts and minimize impacts of activities in the high seas, where governance is limited. Vulnerable marine ecosystems3 (VMEs) provide essential ecosystem services (e.g. nursery grounds4; nutrient cycling5) and are protected through international initiatives6. Most of the VMEs, however, lie in the high seas, receiving little attention. Based entirely on physical proxies presumed to reflect species biogeography, the GOODS tool is not grounded in species data. of GOODS is currently only a static product, as the classification does not account either for projected future climate change scenarios Berta.ramiro@ed.ac.uk Objectives (1) To validate the GOODS classification for complex habitats formed by VME indicator taxa. (2) To test biogeographic boundaries at present and under future ocean climate change projections for the year 21007, based on the output of the Intergovernmental Panel on Climate Change Fifth Assessment Report models. Figure 1. Current proposed GOODS benthic provinces in the North Atlantic. A. Shows three lower bathyal (801-3500 m) provinces, BY1: Arctic; BY2: Northern Atlantic Boreal; BY4: North Atlantic (included MAR hydrothermal vents). B. Shows one abyssal (3501-6500 m) province, AB2: North Atlantic. Modified from Watling et al. (2013). Methodology Data compilation Existing environmental variables (depth, temperature, salinity, dissolved oxygen, POC flux and silicate) and presence and absence point data of VME indicator species in the North Atlantic will be compiled. Data analysis Metacommunity structure analysis will be used to quantify the spatial structure of VME species distribution and obtain distinct faunal provinces. VME indicator species will be assigned to the environmental and historical cluster with which they spatially co-occur. Validation of GOODS for complex habitats formed by VME indicator taxa 1. A B Testing biogeographic boundaries at present and under future climate change scenarios 2. Data compilation Data will consist of species distribution models (SDMs) from 6-8 VME taxa in the North Atlantic and modelled changes in environmental variables for the year 21005. Data analysis SDMs will be correlated with the environmental and historical clusters producing faunal breaks in the projected conditions. Through Procrustes rotation the projected GOODS for the year 2100 will be contrasted with the present-day GOODS. Figure 3. Modelled environmental changes at the deep seafloor (>200) in the year 2100 relative to present-day conditions, following the IPCC card reports. Modified from Sweetman et al. (2017). Challenges References The spatial resolution of available environmental datasets is broad enough to encompass areas that may not have sufficient data, but equally to miss detailed information. Similarly, VME indicator species point data is abundant on continental waters, however, despite ATLAS case studies contribution, there is still a lack of data covering the high seas 1UNESCO, 2009. Global Open Oceans and Deep Seabed (GOODS) - biogeographic classification. IOC Technical Series 84, 84. 2Watling, L., et al., 2013. A proposed biogeography of the deep ocean floor. Progress in Oceanography 111, 91–112. 3UNGA resolution 61/1052, 2006 4Henry, L.-A., et al., 2016. Seamo