Meeting energy demands in the most sustainable way is a major challenge for society. Offshore wind farms - groupings of wind turbines on submerged sediments - offers part of the solution for the energy transition that is needed to mitigate climate change, and the UK has committed to a dramatic and rapid expansion of wind farms in the seas around the UK. However, shelf sea sediments host diverse and productive communities that play a very important role in processing nutrients and carbon that underpin the entire food web. Many species are also important prey items for higher trophic levels, including sea mammals and birds. At the same time, many sediment-dwelling species, such as clams, worms, shrimp and some fish are so intimately associated with the sediment environment that they are particularly susceptible to disturbance. This raises concern as the expansion of offshore wind currently underway means that marine ecosystems are highly likely to experience a large proportional change in biodiversity and ecosystem functioning if marine policy and the management of increasing pressures on UK marine ecosystems is not correctly guided. In this project, we have assembled marine ecologists, engineers and computational scientists to work together to understand ecosystem responses to the cumulative pressures of a large increase in deployment of offshore wind, considered in combination with other pressures that marine ecosystems are facing caused by human activity (bottom fishing, shipping) and the effects of climate change (acidification, warming, low oxygen). To do this, we will collate available data on many aspects of the marine environment and fill in gaps in these data by collecting targeted information about how species interact and behave around offshore wind structures using autonomous vehicles and use artificial intelligence algorithms to identify any associations and patterns. This analysis will also tell us which species are vulnerable to change and highlight areas of concern. Next, we will carry out a series of experiments that will test whether representative species are susceptible to certain types of noise and vibration, electromagnetism and localised heating which are common sources of disturbance associated with wind farms. We will also bring back intact assemblages from areas experiencing different levels of fishing intensity and expose them to the same pressures to see whether species that are experiencing one set of pressures will respond in the same way as those that are not experiencing other pressures. This will tell us how species respond under current conditions, but the pace of climate change means that an additional set of pressures will also effects these species. Hence, we will carry out the same experiments under simulated future conditions (warmer and with altered seawater chemistry). The results of these experiments will tell us whether species benefit or are compromised by certain combinations of pressures, and our expectation is that some species and communities will fair better than others. We will use this information to develop models that allow us to predict how other species that we have not considered, but which share similar traits, may respond. To do this we will use sophisticated statistical models that take into account wider information and make predictions about what marine systems in the future might look like in the future under different scenarios of habitat use, human activity and climate change. In a final step, we will develop a decision support tool that will allow the complexities, including positive and negative feedbacks, to be taken into account by decision and policy makers so they can see the likely consequences of consenting offshore wind in specific locations. Our tool will support the sustainable growth of the offshore wind industry by helping decision makers to make informed decisions that minimise pressure on our marine ecosystems.

The coasts and shelf seas that surround us have been the focal point of human prosperity and well-being throughout our history and, consequently, have had a disproportionate effect on our culture. The societal importance of the shelf seas extends beyond food production to include biodiversity, carbon cycling and storage, waste disposal, nutrient cycling, recreation and renewable energy. Yet, as increasing proportions of the global population move closer to the coast, our seas have become progressively eroded by human activities, including overfishing, pollution, habitat disturbance and climate change. This is worrying because the condition of the seabed, biodiversity and human society are inextricably linked. Hence, there is an urgent need to understand the relative sensitivities of a range of shelf habitats so that human pressures can be managed more effectively to ensure the long-term sustainability of our seas and provision of societal benefits. Achieving these aims is not straightforward, as the capacity of the seabed to provide the goods and services we rely upon depends on the type of substrate (rock, gravel, sand, mud) and local conditions; some habitats are naturally dynamic and relatively insensitive to disturbance, while others are comparatively stable and vulnerable to change. This makes it very difficult to assess habitat sensitivities or make general statements about what benefits we can expect from our seas in the future. Recently, NERC and DEFRA have initiated a major new research programme on Shelf Sea Biogeochemistry that will improve knowledge about these issues. In response to this call, we have assembled a consortium of leading scientists that includes microbiologists, ecologists, physical oceanographers, biogeochemists, mathematical modellers and policy advisors. With assistance from organisations like CEFAS, Marine Scotland and AFBI, they will carry out a series of research cruises around the UK that will map the sensitivity and status of seabed habitats based on their physical condition, the microbial and faunal communities that inhabit them, and the size and dynamics of the nitrogen and carbon pools found there. The latest marine technologies will measure the amount of mixing and flow rates just above the seabed, as well as detailed seabed topography. These measurements will allow better understanding of the physical processes responsible for movement and mixing of sediment, nutrient, and carbon. At the same time, cores will be retrieved containing the microbial and faunal communities and their activity and behaviour will be linked to specific biogeochemical responses. Highly specialised autonomous vehicles, called landers, will also measure nutrient concentrations and fluxes at the seabed. Components of the system can then be experimentally manipulated to mimic scenarios of change, such as changing hydrodynamics, disturbance or components of climate change. This will be achieved in the field by generating different flow regimes using a submerged flume or, in the laboratory, using intact sediment communities exposed to different levels of CO2, temperature and oxygen. By measuring the biogeochemical response and behaviour of the microbial and faunal communities to these changes, we will generate an understanding of what may happen if such changes did occur across our shelf seas. We will use all of this information to assess the relative vulnerability of areas of the UK seabed by overlaying the observation and experimental results over maps of various human pressures, which will be of value to planners and policymakers. Mathematical models will test future scenarios of change, such as opening or closing vulnerable areas to fishing or anticipated changes in the factors that control nutrient and carbon stocks. This will be valuable in exploring different responses to external pressures and for deciding which management measures should be put in place to preserve our shelf seas for future generations.

A wide range of man-made chemicals has the ability to interfere with the endocrine system that controls amongst other functions, sexual development. These are called endocrine disruptors (EDs). Steroidal oestrogens are often implicated in the causation of the widely observed sexual disruption in fish and are of both natural and synthetic origin (e.g. ethinyl-oestradiol, which is the active ingredient of the human contraceptive pill). As well as posing potential risks to humans (there are several studies that attempt to link exposure to EDs with the decline of sperm counts, the increased incidence of testicular and prostate cancers, male congenital reproductive abnormalities and infertility rates), EDs are of particular concern for fish as the aquatic environment is often the most important sink for man-made chemicals and sewage waste. There is clearly a need to develop tools for the detection of such chemicals and fish have been recognised as providing the ideal biological system for this purpose, leading to the development of a number of tests by the OECD, including the fish sexual development test (FSDT) The species that have entered a validation phase for the FSDT to date are the zebrafish and the fathead minnow, both of which are routinely used in aquatic ecotoxicological studies. However, we argue that they are not the ideal test subjects for the FSDT. The main disadvantage of these fish species is the lack of a genetic sex marker, which could unequivocally assign sex, leading to an enormous wastage of experimental fish. This is because the main endpoint employed by the FSDT is sex ratio, which in the case of the stickleback can be assigned genetically using a simple test. In the case of alternative models, sex is assigned by means of gonadal histology, a strategy that presents many drawbacks. Firstly, if the stickleback is used, an acceptable sex ratio for the control groups does not need to be defined waiving the risk of test failure. Secondly, the mode of action of a chemical can be better defined as an oestrogen or an androgen for example because any differences between genetic and histological sex can be attributed to the chemical exposure. Thirdly, but most importantly the ability to assign genetic sex increases the power of the test and can dramatically reduce the number of animals used in scientific procedures for both research and regulatory purposes.

Shelf seas are of major societal importance providing a diverse range of goods (e.g. fisheries, renewable energy, transport) and services (e.g. carbon and nutrient cycling and biodiversity). Managing UK seas to maintain clean, healthy, safe, productive and biologically diverse oceans and seas is a key governmental objective, as evidenced by the obligations to obtain Good Environmental Status (GES) under the UK Marine Strategy Framework, the Convention on Biological Diversity and ratification of the Oslo-Paris Convention (OSPAR) .. The delivery of these obligations requires comprehensive information about the state of our seas which in turn requires a combination of numerical models and observational programs. Computer modelling of marine ecosystems allows us to explore the recent past and predict future states of physical, chemical and biological properties of the sea, and how they vary in 3D space and time. In an analogous manner to the weather forecast, the Met Office runs a marine operational forecast system providing both short term forecast and multi-decadal historical data products. The quality of these forecasts is improved by using data assimilation; the process of predicting the most accurate ocean state using observations to nudge model simulations, producing a combined observation and model product. Marine autonomous vehicles (MAVs) are a rapidly maturing technology and are now routinely deployed both in support of research and as a component of an ocean observing system. When used in conjunction with fixed point observatories, ships of opportunity and satellite remote sensing, the strategic deployment of MAVs offers the prospect of substantial improvement in our observing network. Marine Gliders in particular have the capability to provide depth resolved data sets of high resolution from deployments that can endure several months and cover 100s kms, allowing the collection of sufficient information to be useful for assimilation into models. We will improve the exchange of data between model systems and observational networks to inform an improved strategy for the deployment of the UK's high-cost marine observing capability. In particular we will utilise mathematical and statistical models to develop and test "smart" autonomy - autonomous systems that are enabled to selectively search and monitor explicit features within the marine system. By developing data assimilation techniques to utilise autonomous data, our model systems will be able to better characterise episodic events such as the spring bloom, harmful algal blooms and oxygen depletion, which are currently not well captured and are key to understanding ecosystem variability and therefore quantifying GES. In doing so CAMPUS will provide a step change in the combined use of observation and modelling technologies, delivered through a combination of autonomous technologies (gliders), other observations and shelf-wide numerical models. This will provide improved analysis of key ocean variables, better predictions of episodic events, and 'smart' observing systems in order to improve the evidence base for compliance with European directives and support the UK industrial strategy.

We propose a programme of observations, combined with analysis of past and ongoing time series, to discover the magnitude of surface pH variations at seasonal-up-to-decadal time scales. We will address the Atlantic, UK shelf and slope waters, and selected locations in the Southern Ocean and Nordic Seas, using data from time series stations and volunteer observing ships (VOS), measuring three parameters of the marine carbonate system. The programme will be integrated with the efforts of colleagues in other European countries, and with the Surface ocean carbon atlas project (SOCAT) which aims to produce the most comprehensive and up to date data base to access all the quality data relevant to ocean carbon uptake and pH. Estimation of change will be set against the background of intra- and inter-annual variation.