Executive Summary • Ocean circulation is a dominant controller of the locations and abundances of important marine ecosystem resources. • Changing circulation has already led to political disputes among the UK, Iceland, Norway, the EU and Greenland. • These changes are likely to continue. • Climate models do not capture the full range of variability in the North-East Atlantic, so continued observations and improved biological understanding are both needed to assess oceanographic change and its ecological implications.
Poster presentation at ATLAS 3rd General Assembly. Understanding marine biogeography and, in particular, vulnerable marine ecosystems (VMEs) will lead to better ocean governance in a future ocean challenged by rapid rates of climate change and the exploitation of living and non-living resources in the deep ocean. Most of the deep-seabed and VMEs, however, lie in areas beyond national jurisdiction (ABNJ), where the study of VME biogeography has received far less attention and where there is very limited governance. Biogeographic classifications have been used to date to analyse patterns of marine biodiversity and advancing knowledge of evolutionary and ecosystem processes (Rice et al., 2011). These classifications can also assist governments in designing management tools such as marine protected areas. The Global Open Oceans and Deep Seabed (GOODS) biogeographic classification system (UNESCO, 2009; Watling et al., 2013) was developed to provide technical support to planning and policy decisions related to open ocean and deep-seabed areas. GOODS divides the deep ocean into pelagic and benthic biogeographic provinces based on biological data such as primary production, and a range of environmental variables. The classification is based entirely on physical proxies, presumed to reflect species biogeography. Physical-proxy based schemes are available now for managers and they are based on data that are more easily compiled and updated. Thus, a main purpose of my thesis is to validate GOODS using species data and refine where necessary to overcome three limitations of GOODS to delineate biogeographic provinces in the deep ocean. Firstly, GOODS has not been validated for complex habitats formed by VME indicator taxa, which underpins the need of testing the biogeography of VME indicator species. Secondly, it does not account for projected future climate change scenarios, and thus is currently only a static product. Finally, it represents a high-level classification system, with both pronounced heterogeneity and a ...
Ferromanganese crusts occurring on seamounts are a potential resource for rare earth elements that are critical for low-carbon technologies. Seamounts, however, host vulnerable marine ecosystems (VMEs), which means that spatial management is needed to address potential conflicts between mineral extraction and the conservation of deep-sea biodiversity. Exploration of the Tropic Seamount, located in an Area Beyond National Jurisdiction (ABNJ) in the subtropical North Atlantic, revealed large amounts of rare earth elements, as well as numerous VMEs, including high-density octocoral gardens, Solenosmilia variabilis patch reefs, xenophyophores, crinoid fields and deep-sea sponge grounds. This study focuses on the extensive monospecific grounds of the hexactinellid sponge Poliopogon amadou (Thomson, 1878). Deep-sea sponge grounds provide structurally complex habitat, augmenting local biodiversity. To understand the potential extent of these sponge grounds and inform spatial management, we produced the first ensemble species distribution model and local habitat suitability maps for P. amadou in the Atlantic employing Maximum Entropy (Maxent), General Additive Models (GAMs), and Random Forest (RF). The main factors driving the distribution of the sponge were depth and maximum current speed. The sponge grounds occurred in a marked bathymetric belt (2,500 – 3,000 m) within the upper North Atlantic Deep Water mass (2.5◦C, 34.7 psu, O2 6.7–7 mg ml−1), with a preference for areas bathed by moderately strong currents (0.2 – 0.4 ms−1). GAMs, Maxent and RF showed similar performance in terms of evaluation statistics but a different prediction, with RF showing the highest differences. This algorithm only retained depth and maximum currents whereas GAM and Maxent included bathymetric position index, slope, aspect and backscatter. In these latter two models, P. amadou showed a preference for high backscatter values and areas slightly elevated, flat or with gentle slopes and with a NE orientation. The lack of significant ...
Acknowledgements: The Blue Growth Data Workshop was organised by the University of Edinburgh through the INSITE Data Initiative funded by the INSITE (INfluence of man-made Structures In the Ecosystem, www.insitenorthsea.org) research programme. The authors thank participants from BP, British Geological Survey, Gardline, DeepTek, theDataLab, Hartley Anderson, Marine Scotland Science, Heriot-Watt University, BMT Cordah, Shell, BEIS OPRED and Marathon Oil for their contributions. INSITE follows the 2012 Oil and Gas UK led "Decommissioning Baseline Study" joint industry project that identified data gaps in our understanding in the influence of man-made structures on the ecology of the North Sea. J. Murray Roberts and Katherine Needham acknowledge further support from the European Union's Horizon 2020 Research and Innovation Programme under grant agreement No. 678760 (ATLAS). David Billett was supported by funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 689518 (MERCES: Marine Ecosystem Restoration in Changing European Seas). Lea-Anne Henry was supported by the INSITE Project "Appraisal of Network Connectivity between North Sea subsea oil and gas platforms". Kieran Hyder was supported by INSITE project "Assessing the ecological connectivity between man-made structures in the North Sea". Silvana Birchenough was supported by the INSITE project "Understanding the influence of man-made structures on the ecosystem functions of the North Sea and the European Union's Horizon 2020 Project COLUMBUS (652690) "Knowledge Transfer for Blue Growth". 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. ; Peer reviewed ; Publisher PDF
The deep sea is the largest biome on Earth but the least explored. Our knowledge of it comes from scattered sources spanning different spatial and temporal scales. Implementation of marine policies like the European Union's Marine Strategy Framework Directive (MSFD) and support for Blue Growth in the deep sea are therefore hindered by lack of data. Integrated assessments of environmental status require tools to work with different and disaggregated datasets (e.g. density of deep-sea habitat-forming species, body-size distribution of commercial fishes, intensity of bottom trawling) across spatial and temporal scales. A feasibility study was conducted as part of the four-year ATLAS project to assess the effectiveness of the open-access Nested Environmental status Assessment Tool (NEAT) to assess deep-sea environmental status. We worked at nine selected study areas in the North Atlantic focusing on five MSFD descriptors (D1-Biodiversity, D3-Commercial fish and shellfish, D4-Food webs, D6-Seafloor integrity, D10-Marine litter). The objectives of the present study were to i) explore and propose indicators that could be used in the assessment of deep-sea environmental status, ii) evaluate the performance of NEAT in the deep sea, and iii) identify challenges and opportunities for the assessment of deep-sea status. Based on data availability, data quality and expert judgement, in total 24 indicators (one for D1, one for D3, seven for D4, 13 for D6, two for D10) were used in the assessment of the nine study areas, their habitats and ecosystem components. NEAT analyses revealed differences among the study areas for their environmental status ranging from "poor" to "high". Overall, the NEAT results were in moderate to complete agreement with expert judgement, previous assessments, scientific literature on human-pressure gradients and expected management outcomes. We suggest that the assessment of deep-sea environmental status should take place at habitat and ecosystem level (rather than at species level) and at relatively ...
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 ...
