Suchergebnisse

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 ...

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 ...