There are three potential ways in which organisms can respond to changing environments: (1) they may disperse, or migrate, (2) they may evolve so that they adapt to the new environment, or (3) they may produce different phenotypes - in other words display phenotypic plasticity - as the environment changes. A contemporary example relates to understanding responses of populations to climate change. Work to date suggests that, despite the three mechanisms being non-exclusive, population responses to climate change usually involve phenotypic plasticity. Hence, understanding the evolutionary forces acting on plasticity is of central importance in our understanding of viability in the face of climate change. Understanding of phenotypic plasticity and its role in adaptation to changing environments is hampered by the fact that most studies simply correlate an average phenotype for the population with a single value for the environment, most often at the level of an entire year. This only makes sense if the environmental cues to which organisms respond are very large-scale cues, varying little from the perspective of individuals within populations. However, we know that many organisms experience only a limited part of the environment, and that the environment may vary over quite small spatial scales. Despite this, we don't understand how animals balance these small- and large-scale cues. The central aim of this research is thus to determine how the spatial scale of the environment is important in understanding the evolution of phenotypic plasticity. Our model system involves reproductive behaviour in small woodland birds - great tits, breeding in Wytham Woods near Oxford - which are under strong natural selection to time their reproduction to coincide with peaks in abundance of moth caterpillars (e.g. the winter moth) that are adapted to feed on newly emerged leaves of deciduous trees. At the population level there is a good match between the timing of birds' breeding and the peak of caterpillar abundance, but there is tremendous variation within each year in the timing of these events over quite a small spatial scale. Furthermore, we have evidence that, despite a common temperature trend, different parts of the population are responding at different rates. Hence, the population level summary statistics disguise several important levels of variation. We will use long term data on breeding behaviour and fitness, together with detailed environmental data to analyse the spatial scales at which variation in bird reproductive timing can best be explained, and to test hypotheses about the influence of scale on fitness and population dynamics. We will then supplement these data with new data collected across a regular grid of locations to determine phenology of bud-burst and caterpillar abundance, and hence characterise the extent to which birds are able to match the timing of events in their environment at different scales. Because we expect multiple scales to be important, we can make the prediction that the optimal phenotype is a balance between small- and large-scale plasticity, and hence that adaptation will not be perfect at either scale in isolation. Because the environment is patchy, we can further predict that adjusting to small- as well as large-scale cues will lead to some patches having higher productivity than others; hence the spatial scale of plasticity will lead to within population variation in population dynamics. Collecting environmental data on the ground is very time-consuming, and only limited areas can be covered; therefore we will test the extent to which satellite images can be used to estimate phenology at scales that are relevant to organisms in nature. Finally, we will carry out experimental tests of whether mis-matches in phenology between birds and the environment, which have been implicated in population declines in some species, are alleviated by being in more varied environments.

The Sustainable Development Goals (SDGs), a universal set of goals, targets and indicators that UN member states will be expected to use to frame their agendas and policies over the next 15 years, were agreed in New York earlier this year. One of the 17 goals is to "Protect, restore and promote sustainable use of terrestrial ecosystems, sustainably manage forests, combat desertification and halt and reverse land degradation, and halt biodiversity loss". According to the Global Carbon Project, carbon dioxide emissions from deforestation and other land-use change were 3.3 Gt carbon dioxide on average during 2004-2013, accounting for 8% of all emissions from human activity (fossil fuel, cement, land use change). There is a pressing need to support ongoing initiatives aimed at reducing emissions from deforestation and forest degradation, and participatory forest management strategies to reach sustainable management of forests and enhancement of forest carbon stocks in developing countries In the context of the UN Framework Convention on Climate Change, the international initiative "Reducing Emissions from Deforestation and forest Degradation" (REDD+) aims to protect carbon stocks and biodiversity in threatened ecosystems around the world. Policy makers, financiers and scientists have identified the need for robust and objective Measurement, Reporting and Verification (MRV) systems and it has been recognised that satellite technology is the only way to regularly monitor the world's forests on the timescales required. Within the context of REDD+, the University of Leicester is seeking to develop and demonstrate a prototype for a near-real-time forest cover change information service from Sentinel-1 and 2 satellite data that meets the relevant national forest definitions and is delivered directly in an easily accessible reporting format via a smartphone app to community forest associations and national agencies. Our initial focus is to address the management of tropical forests in Kenya, which has recently set out an ambitious climate change action plan. The service prototype will be delivered based on the University of Leicester's internationally renowned expertise in Earth Observation science in collaboration with a mobile technology developer in Kenya (UKALL Ltd). Market research has been conducted via a NERC Pathfinder grant to assess the potential uptake of a global near-real-time deforestation information service from satellites, commercialising the research results from the NERC CORSAR grant. This study has indicated Kenya to be a likely customer. The annual cost of climatic shocks to Kenya alone is estimated at US$ 0.5 billion (2% of GDP). If not addressed, climate change will hamper progress towards Kenya's aim of being a middle income country by 2030. A recent market visit has confirmed that Kenyan authorities have a huge interest in satellite enabled forest monitoring products/services delivered via a smartphone app with a variety of interested stakeholders, amongst which: - Ministry of Environment and Kenyan Forest Services (National level) - Community Forestry Associations (Local level) - UNEP and UN FAO / REDD+ (International level) Our objective is to develop a mobile app allowing customers in Kenya to access a near-real-time, detailed information about forest cover change for their local area of interest. The accessible provision of this service has real value at the local scale as well as the national scale. To unlock the considerable potential for this service and commercialise our know how, we will develop a prototype and demonstrate it in market. We aim to create a joint venture or spin out company in collaboration with identified commercial partners in the areas of satellite imagery and technology development.

Peru is one the world's worst COVID affected countries. Gaps in social welfare, poor infrastucture and living conditions and high levels of informal employment exacerbate the impact of this disease. Artisanal fisheries are an important and overlooked activity which provides employment and basic nutrition for some of the poorest in rural areas. Thousands of jobs in the seadood supply chain are affected by the pandemic. In the Piura region, the impact on fishing communities is expected to be higher due to the large number of people involved in fisheries-dependent activities and the lack of alternative economic opportunities. There has been no systematic effort to document the impact of COVID on these communities. The Regional Government has identified a need for this information in order to respond with appropiate social welfare measures and is leading an Inter-Agency Consortium (IAC) to re-establish artisanal fisheries activities. This project will support the IAC by collecting and disseminating data on the impact of COVID in fishing communities. It will assess key fisheries, rigorously estimate the impact of the pandemic througout the supply chain and look at the way that this has, or needs to adapt to become more resilient. Throught the timely provision of relevant socio-economic information through a virtual online platform, this project will support decision-making by fishers, government and society in general, By engaging stakeholders in affected communities the project will develop recommendations for a sustained re-activation of fishing and associated activities.

The world's major river deltas - hotspots of agricultural production that support rural livelihoods and feed much of the global population - are facing a major sustainability crisis. This is because they are under threat from being 'drowned' by rising sea levels, with potentially severe consequences for the 500 million people who live and work there. In particular, the process of 'drowning' means that deltas are rapidly losing land (up to 20% of land is projected to be lost to sea-level rise by 2100 in the major deltas of south and southeast Asia alone), while simultaneously exacerbating problems of flooding and soil salinization. These problems are creating a 'perfect storm' that makes agriculture increasingly challenging, at precisely the time when the pressure is increasing for these rich, fertile, landscapes to produce more food to support rapidly growing global populations. The world's third largest delta, the Mekong, is SE Asia's rice basket and home to almost 20 million people, but it is being exposed to severe environmental risks as a result of climate change and rapid economic development, most notably from the development of hydropower dams in the Mekong's catchment upstream which are cutting off the supply of sediment to the delta. The Mekong is therefore not only representative of many of the issues facing the world's deltas, but reliable data are urgently needed to help inform the sustainable management plans required to provide a safe operating space for the delta's inhabitants. In our prior work we have demonstrated that flows of water, sediment and associated nutrients within and through deltas are critical to the resilience of rice cultivation strategies. The sediments that are deposited in the delta help to offset sea level rise and they are very fertile because of the abundant nutrients (nitrogen and phosphorous) they contain. The key issue that is the focus of this proposal is that many of the Mekong delta's poor farmers (over 3.5 million farmers live below the poverty line) rely on the free fertilisation provided by river sediment deposition to reduce their 'input' costs (the portion of their income that is spent on purchasing and applying artificial fertiliser to maintain rice production). There is therefore a trade-off between the positive effects (delta building and free fertilisation) of natural sediment deposition versus the negative effects of the flooding process that causes it. As sediment and nutrient fluxes decline in the future (as a result of sediment trapping by dams upstream), new approaches are needed to inform adaptation strategies (such as managed flooding) to ensure that vulnerable communities can continue to farm sustainably in the future. In this proposal we will collaborate with Vietnamese partners to bring UK expertise in (i) the modelling of floods, sediment transport and nutrient fluxes; (ii) agricultural livelihoods; (iii) participatory stakeholder engagement processes and (iv) social-ecological systems dynamics to bear on this challenge. By bringing together this blend of expertise and working closely with our Vietnamese colleagues and stakeholders we will be able to define policy relevant scenarios of future change, quantify the links between flooding, sediment and nutrient deposition and agricultural livelihoods, and develop new modelling tools that will be able to evaluate the trade-offs between flooding and nutrient supply as the future environment changes. We will be able to concept-proof a new approach that can deliver an integrated assessment of the factors driving changes to livelihoods and explore the effects of adaptations that could enable more sustainable intensification of rice agriculture. This will be done within a globally significant, iconic, delta, providing a template for similar analyses in other vulnerable deltas in the Global South.

In good condition, peatlands are the most efficient carbon store of all soils. They regulate freshwater supply (peatlands are 95% water) and quality, mitigate climate change by storing greenhouse gases, and maintain biodiversity. Land use management interventions (e.g. use of peat for agriculture, drainage, forestry, burning for game management and recreation) can compromise the delivery of all these services by destabilising the vast carbon store that peat has locked away over thousands of years. The UK has 2 Mha of peatlands (10% land area), however, up to 80% of these peatlands are damaged to some degree. It is estimated that degraded UK peatlands emit 10 Mt C a-1, a similar magnitude to oil refineries or landfill sites, placing the UK among the top 20 countries for emissions of carbon from degrading peat. Restoring degraded peatlands to halt carbon losses is an essential part of a global strategy to fight climate change. However, to date, we do not have a tool to help us assess how land use affects peatland condition in a cost effective manner over large and often remote areas, making it difficult to identify which areas should be prioritised for management intervention. In the UK, several millions of pounds of public money have already been invested in large-scale peatland restoration projects yet we do not have a reliable and robust way to evaluate the effectiveness of restoration. These are important gaps in our knowledge that prevent us from being able to make cost-effective choices when it comes to peatland management With this project, we will develop new statistical methods to detect change in the condition of peatland landscapes from data collected by satellites. In a previous research project, we showed that peatland condition can be found from satellite data that measures surface motion of the peat. A wet peat in good condition displays very different characteristics to dry peat in poor condition. However, our satellite-based approach produces too much complex data that cannot be reliably and consistently analysed by eye. We aim to inform peatland management decisions by developing a new statistical method that can robustly and consistently quantify the changes in the peatland landscape from the satellite data. This requires methods capable of handling extremely large and complex structured datasets. In statistics, a new framework, known as Object-Oriented Data Analysis (OODA), is ideally suited to achieve this purpose by building models based on suitable choices of data objects. OODA can be used for developing parsimonious models for detecting change, and for quantifying uncertainty in predictions. OODA of the satellite data as functions of space and time will enable the modelling of trends and variability in the different regions, and the detection of reg change in the peatland. Our project will develop the OODA method further than its current capabilities and apply this method to the satellite datasets of peat surface motion. The result will be a series of maps that illustrate the change in peatland landscape over time that are designed to be used by land managers and policy makers to guide decision making. This will help reduce unnecessary spending and prioritise the most urgent and strategic areas for peat restoration. Our novel approach combining state-of-the-art statistical methods with satellite data will provide a reliable tool to evaluate investments in peat restoration and report to funding bodies. The ability to quantify changes in the peat landscape using statistics should provide confidence to peatland managers and to those who fund and invest in peatland restoration, enabling them to make better choices for peatlands.