Society is becoming increasingly aware of climate change and its consequences for us. Examples of likely impacts are changes in food production, increases in mortality rates due to heat waves, and changes in our marine environment. Despite such emerging knowledge, precise predictions of future climate are (and will remain) unattainable owing to the fundamental chaotic nature of the climate system and to imperfections in our understanding, our climate simulation models and our observations of the climate system. This situation limits our ability to take effective adaptation actions. However, effective adaptation is still possible, particularly if we assess the level of precision associated with predictions, and thus quantify the risk posed by climate change. Coupled with assessments of the limitations on our knowledge, this approach can be a powerful tool for informing decision makers. Clearly, then, the quantification of uncertainty in the prediction of climate and its impacts is a critical issue. Considerable thought has gone into this issue with regard to climate change research, although a consensus on the best methods is yet to emerge. Climate impacts research, on the other hand, has focussed primarily on a different set of problems: what are the mechanisms through which climate change is likely to affect for example, agriculture and health, and what are the non-climatic influences that also need to be accounted for? Thus the research base for climate impacts is sound, but tends to be less thorough in its quantification of uncertainty than the physical climate change research that supports it. As a result, statements regarding the impacts of climate change often take a less sophisticated approach to risk and uncertainty. The logical next stage for climate impacts research is therefore to learn from the methods used for climate change predictions. Since climate and its impacts both exist within a broader earth system, with many interrelated components, this next stage is not a simple transfer of technology. Rather, it means taking an 'end-to-end' integrated look at climate and its impacts, and assessing risk and uncertainty across whole systems. These systems include not only physical and biological mechanisms, but also the decisions taken by users of climate information. The climate impacts chosen in EQUIP have been chosen to cover this spectrum from end to end. As well as aiding impacts research, end-to-end analyses are also the logical next stage for climate change research, since it is through impacts that society experiences climate change. The project focuses primarily on the next few decades, since this is a timescale of relevance for societies adapting to climate change. It is also a timescale at which our projections of greenhouse gas emissions are relatively well constrained, thus uncertainty is smaller than for, say, the end of the century. Work on longer timescales will also be carried out in order to gain a greater understanding of uncertainty. EQUIP research will build on work to date on the mechanisms and processes that lead to climate change and its impacts, since it is this understanding that forms the basis of predictive power. This knowledge is in the form of observations and experiments (e.g. experiments on crops have demonstrated that even brief episodes of high temperatures near the flowering of the crop can seriously reduce yield) and also simulation models. It is through effective use and combination of climate science and impacts science, and the models used by each community, that we will be able to quantify uncertainty, assess risk, and thus equip society to deal with climate change.

This project will use ocean-viewing satellites together with weather forecasts in order to help monitor the quality of water surrounding shellfish farms. These tools will help the shellfish farmers make decisions, for example when to harvest their crop to avoid contamination in nearby water. The farming or cultivation of seafood (e.g. shellfish) termed 'aquaculture' is an important worldwide source of protein. As global populations continue to rise the need for aquaculture as an important source of food will only increase. So increasing aquaculture output will help to provide food security for future generations. So approaches to help ensure efficient and sustainable aquaculture farming (e.g. towards reducing farm costs and energy use, and ensuring supply) will clearly help the industry to expand to feed future populations. Pollution events that reduce the quality of the water within an aquaculture farm, both from humans and naturally occurring, can significantly impact aquaculture farms. These events can cause the loss of stock (ie shellfish have to be disposed of), harvesting to stop (causing a loss in supply to the customer), illness or in extreme cases death (through humans eating contaminated food). Water quality in and around the aquaculture farms in the UK and Europe are monitored using a series of tests based on collecting water samples and analyzing the flesh of the seafood being farmed. This sampling is carried out by government agencies. Due to financial constraints and complexity of this sampling, it is not possible to take samples everyday and there is a delay between the samples being collected and the results being given to the farmer. The farmers themselves often do not have any way of measuring the water quality within their own farms, so they have to rely on the monitoring provided by the agencies, even if it is sporadic and the results are delayed. Whereas up to date information on water quality would help farmers make decisions about when and how much to harvest. Information about the quality of the water offshore from their farm would help warn farmers of possible future water quality problems within their farm. There are many approaches that have been developed by scientists to use satellites to provide salmon and trout farmers with information on their local water quality. Scientists have also looked at the links between reduced water quality and changes in the weather conditions. For instance satellites are routinely used for monitoring water quality in and around Salmon farms in Scotland, and simple models that relate environmental conditions like rainfall and sunlight to reduced water quality have been developed for the south west UK. These approaches and tools have yet to be made available to shellfish farms in a way that is simple for farmers to use and exploit. This project will extend the approaches developed for Salmon farmers to be specific for shellfish farmers. It will develop and extend existing methods for using satellites for studying water quality in offshore and coastal farms. It will also extend and develop simple tools that shellfish farmers can use to predict short-term variations in water quality, based on their local weather conditions and forecasts. A simple method to provide this information in a timely manner through regular 'news bulletins' to farmers using text messages and emails will also be tested. Importantly, all of this work will be carried out in conjunction with shellfish farmers, allowing them to provide feedback on the project and ensure that the results are highly relevant to their needs.

Iodine is a vital element. For example, human growth hormones contain iodine so it is an essential part of our diet and a deficiency in this will severely affect how we grow and our brains develop. Also, in the atmosphere iodine is involved in chemical processes that contribute to climate change such as ozone depletion and cloud formation. The persistence of life on earth depends upon the constant recycling of essential elements that occurs via the major biogeochemical cycles that are maintained by the activities of microorganisms. It is crucial that we know how iodine is cycled between the oceans, air and land. The oceans contain a large proportion of the total iodine on the planet and the transfer of this element from seawater to the atmosphere is known to be an important part of its global cycle. One group of compounds that play a major role in transferring iodine across the sea surface are the volatile iodocarbons, this includes CH3I, CH2I2 and CH2ClI. Although we can measure the iodocarbons in seawater we do not fully understand what controls their concentrations in seawater and crucial parts of the jigsaw are still to be discovered. INSPIRE will compare iodocarbon concentration distributions with measurements that indicate biological, chemical and photochemical processes, and carry out experiments in the laboratory and during two research cruises to work out what the main controls on the concentrations of these compounds are. For example, the project will examine how the exposure of water samples to sunlight, zooplankton grazing of phytoplankton, plankton death and decay and bacterial growth influences the concentrations of the iodocarbons we measure in seawater. Once we have identified this we will then produce a mathematical model to simulate iodocarbon production to allow us to predict how much iodine is transferred from the oceans to the atmosphere. This will help us to understand how the iodine biogeochemical cycle operates much better and how it might alter with future climatic change.

Coastlines are illuminated with artificial light at night (ALAN) from piers, promenades, ports harbours, and dockyards. Artificial sky glow created by lighting from coastal settlements can now be detected above 22% of the world's coasts nightly, and will dramatically increase as coastal human populations more than double by year 2060. Life history adaptations to the moon and sun are near ubiquitous in the upper 200m of the sea, such that cycle's and gradients of light intensity and colour are major structuring factors in marine ecosystems. The potential for ALAN to reshape the ecology of coastal habitats by interfering with natural light cycles and the biological processes they inform is increasingly recognised. Marine invertebrates are extremely sensitive to natural light throughout their life cycle. Examples include synchronised broadcast spawning in reef corals informed by moonlight cycles, zooplankton sensitivity to moonlight at >100m depth, and phototaxis of larvae under light equivalent to moonless overcast nights. The reproductive, larval and adult phases of marine invertebrates are all affected by night-time lighting of equivalent illuminances to those found in ports and harbours. Further, direct impacts on organism behaviour can indirectly affect other species in coastal food web's, changing ecosystem structure. The potential for coastal ALAN to disrupt marine organisms, species interactions, population dynamics, and organism distributions is clear. The growing use of white Light Emitting Diodes (LEDs) (69% of global lighting by 2020) will exacerbate ALAN's impacts. LEDs emit more blue wavelength light that: i) penetrates deeper into seawater compared to older lighting technologies; and ii) many marine organism responses are most sensitive to. Tailoring LEDs to avoid blue wavelengths represents one mitigation option trialled on land that can be improved by investigating the spectral dependence of biological responses. ALICE will tackle fundamental gaps in our understanding of marine ecosystem responses to ALAN, by carrying out the following research: - 1. Laboratory experiments to determine the impacts of ALAN on coastal organisms: Parallel experiments will quantify the impacts of ALAN interference with natural light cycles on the life history responses of marine invertebrates. These relationships will be used to model the growth rate of marine invertebrate populations exposed to different intensities of cool white LED light assuming optimal conditions with no predators or competitors. 2. Laboratory experiments to determine the impact of ALAN on species interactions: The relationships between white LED light intensity, and species interactions (predation,competition and mutualism) will be simultaneously quantified during the above experiments, and used to model the impacts of ALAN on marine invertebrate populations accounting for their relationships with one another in nature. 3. Mapping and modelling the distribution of ALAN in coastal marine habitats: The intensity of colour composition of ALAN in coastal waters will be mapped across three contrastingly urbanised UK estuaries. These data, and associated optical modelling, will be used with satellite data to globally map ALAN intensity from the sea surface to a depth of 100m. 4. Modelling ALAN impacts on species distributions: The population models (1,2) and the ALAN distribution model (3), will allow a synthesis assessment of long term changes in species distributions that may result from ALAN impacts. 5. Quantifying the benefits of avoiding ALAN wavelengths: we will quantify the ecological benefits of: i) removing blue light form LEDs blue using optical filters; ii) replacing white, with longer wavelength Amber LEDs. In addition we will quantify the responses of marine invertebrate larvae to different colours of light, so that the design of ecologically friendly LED lighting can be better informed.