The UK is committed to quantifying and managing its emissions of greenhouse gases (GHG, i.e. CO2, CH4, N2O) to reduce the threat of dangerous climate change. Sinks and sources of GHGs vary in space and time across the UK because of the landscape's mosaic of managed and semi-natural ecosystems, and the varying temporal sensitivities of each GHG's emissions to meteorology and management. Understanding spatio-temporal patterns of biogenic GHG emissions will lead to improvements in flux estimates, allow inventories with greater sensitivity to management and climate, and advance the modelling of feedbacks between climate, land use and GHG emissions. Addressing Deliverable C of the NERC Greenhouse Gas (GHG) Emissions and Feedbacks Research Programme, we will use extensive existing UK field data on GHG emissions, supplemented with targeted new measurements at a range of scales, to build accurate GHG inventories and improve the capabilities of two land surface models (LSMs) to estimate GHG emissions. Our measurements will underpin state-of-the-art temporal and spatial upscaling frameworks. The temporal framework will evaluate diurnal, seasonal and inter-annual variation in emissions of CO2, CH4 and N2O over dominant UK land-covers, resolving management interventions such as ploughing, fertilizing and harvesting, and the effects of weather and climate variability. The spatial framework will evaluate landscape heterogeneity at patch (m), field (ha) and landscape (km2) scales, in two campaigns combining chambers, tower and airborne flux measurements in arable croplands of eastern England, and grazing and forest landscapes of northern Britain. For modelling, we will update two LSMs, JULES and C-tessel, so that both generate estimates of CO2, CH4 and N2O fluxes from managed landscapes. The models will be updated to include the capabilities to represent changes in land use over time, to represent changes in land management over time (crop sowing, fertilizing, harvesting, ploughing etc), and the capacity to simulate forest rotations. With these changes in place, we will determine parameterisations for dominant UK land-covers and management interventions, using our spatio-temporal data. The work is organized in five science work-packages (WP). WP1: Data assembly and preliminary analysis. We will create a database of GHG emissions data and ancillary data for major UK landcovers/landuses in order to calibrate and evaluate the LSMs' capabilities, and generate spatial databases of environmental and management drivers for the models. WP2. GHG measurement at multiple scales. We deploy advanced technology to generate new information on spatial GHG processes from simultaneous measurement from chamber (<1 m) to landscape (40 km) length scales, and on temporal flux variation from minutes to years. WP3. Earth observation (EO) to support upscaling. EO data will provide: i) driving data for LSM upscaling, from flux tower to aircraft campaign scales; and ii) spatial data for testing LSM outputs at these larger scales. WP4 Upscaling GHG processes. Firstly, the two LSMs will be updated to allow the impacts of management activities on GHG emissions to be simulated, with calibration against an array of temporal flux data. Then, we will use the LSMs to model the fluxes of GHGs at larger spatial scales, based on a rigorous understanding of how the nonlinearity of responses and the non-Gaussian distribution of environmental input variables interact, for each GHG, using all available field data at finer scales. WP5 Application at the regional scale. The LSMs will upscale GHG emissions for both campaign regions (E. England, N. Britain) using a 1-km2 resolution simulations with a focus on the airborne campaign periods of 4 weeks. We will determine how regional upscaling error can be reduced with intensive spatial soil and land management data.

Bluetongue virus (BTV) is an arboviral pathogen of ruminants spread by Culicoides biting midges, which causes the disease bluetongue (BT) in sheep (particularly certain fine wool and mutton breeds). During the 1980's clinical BT began to appear in flocks of native Indian breeds of sheep, particularly in the southern states, possibly as a result of exotic strains of the virus introduced via sheep-breeding programmes. This change in epidemiology led to outbreaks among family-based subsistence farming communities in these areas, and BTV has since been become a significant constraint in both the rearing and productivity of indigenous flocks. In addition, in rain-fed agricultural areas, massive periodic outbreaks of disease occur that are thought to be related to the influence of timing and intensity of monsoon conditions on populations of vectors responsible for spreading BTV. Due to the circulation of 21 serotypes of BTV in southern India and the prohibitive costs of vaccination to the vast majority of the population, vector control remains the only feasible way of combating BTV transmission in the field. Despite this, virtually no quantitative data concerning the efficiency of available techniques in this role is available to inform control strategies. We will adopt a multidisciplinary approach involving mathematical modelling, entomology and chemical ecology to examine the epidemiology of BTV in the southern Indian states and to produce prediction, monitoring and mitigation techniques that can reduce the impact of BT in this region. Initially we will characterise southern India using mapping techniques that delineate land areas according to climate and land use patterns. We will then establish field sites across the region that are representative of both these factors and also the types of husbandry employed (with an emphasis on small holdings and landless husbandry workers). Having characterised these sites, we will then use light trapping to define adult seasonality and distribution and ground truth this survey with direct collection of Culicoides from livestock. These studies will be combined with detection of BTV within collected individual midges to define regional variation in which species are involved in transmission in southern India for the first time. The larval development sites of major vector species identified will then also be characterised via field investigations. Using data generated on adult seasonality, larval habitat preference and historic surveys of BT cases across southern India, we will then model the relationship between monsoon conditions and adult Culicoides/BT activity to assess the potential to produce an early warning system for major BTV epidemics based on meteorological variables. The provision of fundamental epidemiological knowledge will also enable an assessment of husbandry-based control techniques for Culicoides that could be employed to reduce BTV transmission by subsistence farmers in a cost-neutral fashion. We will examine traditional and novel means of control, both in the laboratory and in the field. The former will include the use of larval site modification, or targeted treatment with traditional, low environmental impact, insecticidal products available to villagers and additionally the use of stabling. In addition, information regarding host location by identified vector Culicoides will allow novel intervention strategies based upon the application of masking semiochemicals that could also reduce the use of synthetic insecticides by these communities in the medium term. The effect of combinations of these techniques will be examined via monitoring viral infection in livestock, as a gold standard for evidence of impact in the field. These data will then be assessed for integration into the everyday lives of user groups as part of wider dissemination frameworks for improvement of ruminant productivity and control of vectors of human and veterinary pathogens.

Combustion of fossil fuels and use of fertilisers in agriculture has increased the amount of nitrogen compounds present in the atmosphere and the biosphere. More atmospheric nitrogen is converted into reactive nitrogen by anthropogenic activities than by all natural processes combined. This phenomenal historical increase in nitrogen deposition is responsible for several serious environmental problems, such as soil acidification and nitrogen saturation, nitrate leaching in water courses and eutrophication and changes in the composition of natural ecosystems. In its most extreme forms, it can also cause plant mortality. The added nitrogen also contributes to forming active ozone in the troposphere (where it is damaging) and to producing the greenhouse gases methane and nitrous oxide. To partially counterbalance all these negative effects, nitrogen deposition is also known to increase the sequestration of carbon by forests, which helps to slow down climate change. However, the magnitude of this indirect positive service provided by a pollutant is uncertain, with many estimates suggesting that the effect if rather small. In a previous paper in Nature however, we reported new data showing the effect to be very large for forests of the boreal and temperate regions. This work raised several questions in the community and stimulated a debate which is still ongoing on the real magnitude of this effect. In this project we propose to test whether our findings stand to scientific scrutiny by using two complentary tests: a) an experimental manipulation which artificially elevates the levels of nitrogen deposition over one experimental forest, where we have been measuring carbon sequestration for the past 10 years. Many fertilisation experiments have been carried out in the past, but we contend that they did not realistically simulate the process of nitrogen deposition, as the many ways that nitrogen can interact with the canopy of trees are entirely eliminated when the fertiliser is applied directly on the ground (nitrogen deposition obviously occurs from above the canopy either dissolved in rainfall or as dry deposition over the foliage). b) comparative observations of tree growth across known regional gradients in nitrogen deposition across the UK. Surprisingly few empirical observations have been carried out using this second method, on the assumption that changes in climate, soil fertility, etc. would mask any residual effect due to nitrogen deposition. However, the available literature strongly suggests that high levels of nitrogen deposition have increased tree growth during the 20th century across much of Europe, in support of our theory. Finally, we will use three models to compare our observations against the model predictions. This will also help to determine the mechaism(s) which may promote high rates of carbon sequestration in response to nitrogen deposition.

Flooding is the deadliest and most costly natural hazard on the planet, affecting societies across the globe. Nearly one billion people are exposed to the risk of flooding in their lifetimes and around 300 million are impacted by floods in any given year. The impacts on individuals and societies are extreme: each year there are over 6,000 fatalities and economic losses exceed US$60 billion. These problems will become much worse in the future. There is now clear consensus that climate change will, in many parts of the globe, cause substantial increases in the frequency of occurrence of extreme rainfall events, which in turn will generate increases in peak flood flows and therefore flood vast areas of land. Meanwhile, societal exposure to this hazard is compounded still further as a result of population growth and encroachment of people and key infrastructure onto floodplains. Faced with this pressing challenge, reliable tools are required to predict how flood hazard and exposure will change in the future. Existing state-of-the-art Global Flood Models (GFMs) are used to simulate the probability of flooding across the Earth, but unfortunately they are highly constrained by two fundamental limitations. First, current GFMs represent the topography and roughness of river channels and floodplains in highly simplified ways, and their relatively low resolution inadequately represents the natural connectivity between channels and floodplains. This restricts severely their ability to predict flood inundation extent and frequency, how it varies in space, and how it depends on flood magnitude. The second limitation is that current GFMs treat rivers and their floodplains essentially as 'static pipes' that remain unchanged over time. In reality, river channels evolve through processes of erosion and sedimentation, driven by the impacts of diverse environmental changes (e.g., climate and land use change, dam construction), and leading to changes in channel flow conveyance capacity and floodplain connectivity. Until GFMs are able to account for these changes they will remain fundamentally unsuitable for predicting the evolution of future flood hazard, understanding its underlying causes, or quantifying associated uncertainties. To address these issues we will develop an entirely new generation of Global Flood Models by: (i) using Big Data sets and novel methods to enhance substantially their representation of channel and floodplain morphology and roughness, thereby making GFMs more morphologically aware; (ii) including new approaches to representing the evolution of channel morphology and channel-floodplain connectivity; and (iii) combining these developments with tools for projecting changes in catchment flow and sediment supply regimes over the 21st century. These advances will enable us to deliver new understanding on how the feedbacks between climate, hydrology, and channel morphodynamics drive changes in flood conveyance and future flooding. Moreover, we will also connect our next generation GFM with innovative population models that are based on the integration of satellite, survey, cell phone and census data. We will apply the coupled model system under a range of future climate, environmental and societal change scenarios, enabling us to fully interrogate and assess the extent to which people are exposed, and dynamically respond, to evolving flood hazard and risk. Overall, the project will deliver a fundamental change in the quantification, mapping and prediction of the interactions between channel-floodplain morphology and connectivity, and flood hazard across the world's river basins. We will share models and data on open source platforms. Project outcomes will be embedded with scientists, global numerical modelling groups, policy-makers, humanitarian agencies, river basin stakeholders, communities prone to regular or extreme flooding, the general public and school children.

Globally, human societies face a burgeoning challenge of achieving sustainable use of natural resources to provide food, fuel, water and amenities for an increasing population under the context of climate change. At its most fundamental, this will require achieving food and water security of supply without threatening the ability of the environment to support future generations. An increasingly urbanized and wealthy population is driving a growing and changing demand for food, water, land and other natural resources and contributing to environmental degradation. These demands combined with climate change, and its associated natural hazards, were critical considerations in the development of the UN's Sustainable Development Goals (SDGs, 2015). The challenges posed by the SDGs require long term national scale research-based solutions. SUNRISE seeks to improve livelihoods and wellbeing through reduced environmental risk, improved environmental quality and improved reliability of the supply of food, water and other natural resources by providing the evidence and advice needed to improve management of the wider environment. SUNRISE will address local issues and research needs in China, India, Indonesia / Malaysia, Kenya and other countries in sub Saharan Africa and address SDGs 1, 2, 3, 6, 13 and 15. SUNRISE builds on the research themes that formed the basis of the approved NC-ODA Foundation Award with activity currently in progress: (1) developing hydro-climate services for improved water resource management and flood and drought forecasting and preparedness; (2) restoration and remediation of degraded resources and environments to improve people's health and economic security, and; (3) management of land resources to ensure environmental sustainability and economic growth and resilience. These will be developed and delivered in partnership with in-country partners and stakeholders to address their most pressing environmental needs. Hydro-climate services are tools and methods that translate data and knowledge of current and potential future hydrological conditions into information that will inform better water policy, planning, management and decision-making. The science challenge is to adapt CEH's models and understanding to perform at an acceptable level of uncertainty in data sparse regions. In meeting this challenge we will both advance UK research capabilities and provide tools, methodologies and assessments to reduce the impact of extreme events on people and their livelihoods and increase the reliability and resilience of water supplies for people, livestock and businesses on a day to day basis. Restoration and remediation options require research aimed at understanding and quantifying the key factors and processes that cause environmental degradation and upon which mitigation measures rely. This theme will seek to fill a knowledge gap by determining the key factors that affect the rate and stability of recovery as systems are restored, and the resilience of restored systems to future change. In investigating this knowledge gap in real-world situations the findings will advance science knowledge and inform new policy and management approaches needed in India, China, Indonesia, Malaysia and Kenya but with global relevance. Increasing agricultural productivity sustainably is a clear priority both for food provision and also as a pathway to alleviating poverty, particularly for the 83% of the global agricultural population who rely on smallholder agriculture. Small holder agriculture is often not as productive as it could be: working with local agronomists we will investigate new approaches to achieve ecological intensification, through diversification of smallholder land, water and livestock management to deliver improved productivity, resilience and sustainability.