Marine coastal areas are important for the ecosystem functioning because they provide a wealth of goods and services. Hence, it is a major challenge nowadays to understand and predict how human activities will affect marine sediment communities, benthic biogeochemical cycling and the link between them. It is known that bioturbation activities affect the ecosystem functioning. In this study, we are going one step further by studying biogeochemical cycling in a range of natural sediment and disturbed sediment, and by assessing the contribution of macrofaunal activities (bioturbation and bio-irrigation) to the ecosystem cycling. We conducted closed-core incubations of sediment sampled along a gradient from fine to coarse sediments, including sediments subjected to fining. Nutrients and oxygen concentration were followed by sampling the overlying water every 2 hours. Bio- and physical irrigation has been quantified by adding a bromide tracer to the overlying water and following the decreasing concentration over time. At the end of the incubation, the sediment was sieved and the organisms retrieved to calculate the bioturbation potential of the community (BPc). With those data, we will estimate the total flux of degradable organic carbon deposited at the sediment surface, its degradation rate and transformation, and the nitrification/denitrification rates. The aim is to assess the effect of fining and the effect of bioturbation and bio irrigation on benthic ecosystem functioning. The research plan and the preliminary results will be reported.
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RBINS Staff Publications 2017
inance is one of the main critical issues for the development of a low carbon society especially during times of economic recession. Closing this green investment gap will require policy intervention. The ALPI project will concentrate on analysing and designing relevant instruments to accelerate the transition towards a low carbon society. Five case studies were set-up to cover different economic sectors (electricity, housing, transport, green public procurement and geothermal energy), with a common methodology. As a showcase of emerging technologies in Belgium, the Hasselt University and the Geological Survey of Belgium are investigating the regional potential for geothermal electricity production. Deep geothermal energy appears to be currently on the edge of a takeoff. But the actual emergence of this technology is subject to developments in legislation and incentives from regional governments. Different risk/return expectations across stages of the investment continuum exist and the financial structures that are employed at each stage may require different types of public support. The investigation starts with a broad stakeholder consultation (policy makers, sector federations, industry, researchers, banking sector, investors, etc.). A techno-economic evaluation then is realized by real options valuation. As the development of deep geothermal energy is a complex process, a detailed stochastic calculation is made of a project decision tree. The decision tree replicates the consequent development of different deep geothermal energy projects, with their different success rates and interdependencies in terms of technological knowledge accumulation, decreasing uncertainty for single basins, and increasing public acceptance. This approach allows to investigate measures, such as insurances or government guaranteed, to reduce project risk, in order to increase the interest of investors in this sector. Secondly, this approach is combined with an evolutionary step development to analyze the potential growth of the sector over the coming decades. Finally, different fiscal measures are designed in collaboration with stakeholders, and their effectiveness to stimulate the transition to a low carbon society is evaluated. Giving the high geological uncertainty, this combined geologicaleconomic analysis is arguably the most realistic way to calculate project performance, and simulate the future development trajectory of the geothermal sector subjected to different policy measures.
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RBINS Staff Publications 2016
