We recently discovered the world's largest tropical peatland complex, spanning an area larger than England, in the heart of Africa. This proposal brings together an interdisciplinary team of scientists to study this newly discovered ecosystem. Our goal is to understand how the peatland became established, how it functions today, and how it will respond to human-induced climate change and differing future development pathways. We will use the results to inform critical policy decisions about the region. Peat is partially decomposed plant matter. Peatlands are some of the most carbon-dense ecosystems on Earth. Covering 3% of Earth's land surface, they store one-third of soil carbon. A recent NERC-funded PhD, led by CongoPeat PI Professor Lewis, showed for the first time that the largest wetland in Africa, in the central Congo Basin, contains extensive peat deposits. This research, published in 2017 in Nature, estimates that the peatland stores 30 billion tonnes of carbon (C). By comparison, in 2016, UK emissions were 0.1 billion tonnes of C. Our discovery increases global tropical peatland C stocks by 36%. We know very little about this new globally important ecosystem. Our data show peat accumulation began about 10,600 years ago, when central Africa's climate became wetter. Accumulation has been slow - on average just 2 m has accumulated over this period - but it is unknown whether this is due to a constant slow build-up of peat and C, or fast rates interspersed with losses in drier periods. Our evidence suggests that the peatlands are fed by rainfall, but such peatlands usually form domes ('raised bogs'), yet satellite data do not show this feature. Thus, we do not know how this peatland system developed, how it functions today, or how vulnerable it is to future climate and land use changes. Tropical peatlands in SE Asia have been extensively damaged by drainage for industrial agriculture, particularly oil palm, with serious biodiversity, climate and human health implications. Oil palm is now rapidly expanding across Africa. Congolese peatlands could become a globally significant source of atmospheric CO2 if they are drained, leading to their decay. A prerequisite of following a different development pathway is a scientific understanding of the region. The CongoPeat proposal therefore brings together leading experts from six UK universities, a science-policy communication specialist, and five Congolese partner organisations, to gain: 1. An integrated understanding of the origin and development of the central Congo peatland complex over the last 10,000 years. We will analyse peat deposit sequences from across the region, extracting preserved pollen grains, charcoal, and chemical markers, to reconstruct the changing environment through time. We will use an unmanned aerial vehicle to map peatland surface topography, and develop a mathematical model of peatland development. 2. A better estimate of the amount of C stored in the peat, its distribution, and the amounts of important greenhouse gases, CO2, methane, and nitrous oxide, being exchanged with the atmosphere. This will be achieved via extensive fieldwork to map peat distribution, and by installing intensive measurement stations to determine the flows of C into and out of the ecosystem. 3. An understanding of the possible future scenarios for the Congo peatlands. A range of models will be used to simulate the possible impacts of future climate and land-use change on the peatland, at local to global scales. Finally, we will effectively communicate these results to policy-makers in Africa and internationally via briefings and active media engagement. The CongoPeat team will produce the first comprehensive assessment of the genesis, development, and future of the world's largest tropical peatland, enabling the UK to retain world-leading expertise in understanding how the Earth functions as an integrated system and how humans are changing it.

Rural people across the global south are caught between competing land demands for large-scale cultivation, global conservation, and local needs. These can in theory be integrated locally through community-based natural resource management (CBNRM) and payments for ecosystem services (PES): where communities can decide on and benefit directly from natural resources, they may invest in and manage those resources in ways that are more socially and environmentally sustainable. CBNRM/PES initiatives are being rolled out across the global south, but there are conflicting views as to how well they work, for whom and under what circumstances. This is partly due to the complexity and multidimensionality of the ecosystem services (ES) and poverty alleviation (PA) outcomes involved, and the inevitable tradeoffs, but also to the hitherto limited use of either qualitatively or quantitatively rigorous impact evaluation approaches that are independent, control for confounding factors and ensure the voices of the most marginalized are heard. As well as being limited by generally weak research design, studies to date have often failed to account for the ways political sensitivities around changing access to and use of ecosystem services may compromise data quality and mask differentiated impacts. PIMA seizes a unique policy moment, with Tanzania's poverty reduction strategy Mkukuta driving nationwide implementation of CBNRM/PES-based Wildlife Management Areas (WMAs), and other countries in the region considering comparable initiatives. The WMAs comprise different ecosystems (rangeland, miombo), socio-political structures (long-established/ethnically uniform vs recent, heterogeneous constituent villages), and a broad range of ecosystem services (water-regulating and -supplying, provision of forest products, grazing, livestock, crop and wildlife production, cultural services both local and global (from locally significant social and ritual spaces, to heritage and tourism). Before/after, inside/outside comparison of social and ecological outcomes for established WMAs with matched non-WMA areas (within the same ecosystems) offers an ideal opportunity for rigorous impact evaluation. PIMA combines analysis of remotely-sensed, public-domain MODIS and NDVI data, with cutting edge study of governance, and new data from qualitatively and quantitatively rigorous, differentiated survey of livelihoods and resource use histories, structured within a before/after, control/impact (BACI) research design. PIMA brings together a powerful international research team to work with strongly-rooted civil society organizations to ensure research excellence and development impact. Building on ongoing stakeholder engagement, with input sought from users, practitioners and policymakers at all stages pre- to post-project, PIMA ensures findings will be of direct use locally, nationally and internationally. PIMA 's framework and approach create channels for grassroots users to make experienced change in ecosystem services quality and quantity, and in poverty and wellbeing, more clearly heard by policymakers and practitioners, as well as highlighting tradeoffs and best practice lessons. Establishing what works, why and for whom will be of use not only to the one million rural people directly affected by WMAs, but will deliver insights and best practice lessons generalizable to the many millions more whose livelihoods and wellbeing are to be shaped by comparable CBNRM/PES initiatives. The findings delivered, and the mechanisms piloted, will give local users and national and international policymakers and practitioners the insights and tools to improve interventions through creating better upward and downward accountability. PIMA findings will be of use locally to rural people making collective and individual resource use decisions, through national levels, to international donors deciding how to invest scarce resources for ecosystem services and poverty alleviation.

It is widely acknowledged that poor rural communities are frequently highly dependent on ecosystem services (ES) for their livelihoods, especially as a safety net in times of hardship or crisis. However, a major challenge to the understanding and management of these benefit flows to the poor is a lack of data on the supply, demand and use of ecosystem services by the poor, particularly in the developing world where dependence on ES is often highest. Recent work suggests that errors associated with the commonly used global proxies (eg. benefits transfer) are likely to be substantial and therefore confuse or worse, misdirect, policy formulation or management interventions (e.g. perverse subsidies). Given these issues, recent improvements in integrated modelling platforms - in some cases founded on desktop process-based models - which aim to provide improved and dynamic maps of current and future distributions of ES have much to offer ES-based poverty alleviation interventions and policy. While these next generation process-based models appear to have a role to play in ES-based poverty alleviation efforts, the level of sophistication and data needs that is required to deliver policy relevant information is poorly understood. It is, for example, unclear whether even the most sophisticated process-based biophysical model is able to provide sufficiently accurate information for regional- or local-scale policy decision making when based on globally available datasets. Similarly, there has been no attempt to quantify the degree to which disaggregation of beneficiaries is necessary within integrated modelling platforms to provide information on managing natural assets that is relevant to the poorest people. Such analyses are vital to ensure that next generation models produce useful and credible results as efficiently as possible - that is, with a minimum investment in data collection and bespoke model development. We will evaluate the effectiveness of a range of current modelling approaches of varying degrees of complexity for mapping at least six ecosystem services - crop production, stored carbon, water availability, non-timber forest products (NTFPs), grazing resources, and pollination - at multiple spatial scales across sub-Saharan Africa. We will assess model performance based on two broad metrics: model data requirements and the usefulness to decision-making. Firstly, we will evaluate the data requirements of each modelling tier, using data availability, spatial resolution and uncertainty to score in the intensity of the required inputs. Those models with intensive data requirements will be scored poorly. Secondly, we will evaluate the usefulness of the model in a decision-making process using statistical binary discriminator tests. We will use the same approach to evaluate the impact of consideration of beneficiaries on decision making by comparing the biophysical model outputs with both socioeconomic measures and models also using binary discriminator tests. Our goal in this project is to ascertain the degree of complexity of modelling that needs to be applied to map ES at resolutions that are useful for poverty alleviation. The findings of this project will enable decision makers to: 1) best use existing ES models to inform national and regional land use/cover change policies supporting ES management and promoting equality and justice amongst the beneficiaries of these services; and 2) set priorities determining where scarce resources should be invested to improve effective management of ES. Thus, WISER may help improve the lives of the approximately 400 million people living in poverty in sub-Saharan Africa by evaluating the tools available to policy makers in this region.

Continental shelf seas are typically less than 200m deep and can be described by the shallow ocean surrounding continental land masses. Due to their accessibility, shelf seas are commercially and economically important, with oil and gas extraction alone in UK shelf seas valued at £37B pa. Despite occupying only 7% of the surface ocean, shelf seas also play a major role in the global carbon cycle and marine ecosystem. Shelf seas are 3-4 times more productive than open-ocean, are estimated to support more than 40% of carbon sequestration and support 90% of global fish catches providing a critical food source for growing coastal populations. However, shelf seas are also exposed to climate driven and anthropogenic stress that could have a profound impact on their biological productivity, oxygen dynamics and ecosystem function. Many processes contributing to this threat are related to regions that undergo vertical stratification. This process occurs when the bottom layer of shelf seas becomes detached from the atmospherically ventilated near surface layer. In temperate shelf seas stratification predominantly occurs as solar heating outcompetes the tide and wind-driven mixing to produce a warm surface layer, resulting in seasonal stratification over large areas of the NW European shelf seas. A combination of physical detachment from the surface and increased biological oxygen consumption in the bottom layer, accentuated by the enhanced productivity that stratification also supports in the upper ocean, can result in a drastically reduced bottom layer oxygen concentration. When oxygen levels get so low, they are classified as being oxygen deficient and this can be problematic for benthic and pelagic marine organisms and have a detrimental effect on ecosystem function. Evidence of increasing seasonal oxygen deficiency in the regions of North Sea by members of the AlterEco team and a recognised global increase in the extent of shelf sea and coastal oxygen deficiency calls for an urgent need to increase the spatial and temporal measurement of oxygen and a better understanding of the processes that lead to oxygen deficiency in shelf sea bottom waters. This need is severely impeded by the natural complexity of ecosystem functioning, the impact of a changing climate, connectivity between different regions of our shelf seas and large-scale external forcing from ocean and atmosphere. Current methods are severely restricted in resolving this complexity, due to the poor resolution in observational coverage, which calls for a new strategy for observing and monitoring marine ecosystem and environmental status. AlterEco seeks to address this challenge within the framework of the given call by the development of a novel monitoring framework to deliver improved understanding of key shelf sea ecosystem drivers. We will capitalise on recent UK investments in marine autonomous vehicles and planning capability to investigate an area of the North Sea known to undergo variable physical, chemical and biological conditions throughout an entire seasonal cycle, including areas identified to experience low bottom layer oxygen levels during summer months. Ocean gliders will be used to undertake repeat transects over a distance of ~150km, sufficient to capture important shelf sea features; such as fronts and eddies. The AlterEco strategy will employ small fleets of vehicles to capture these meso-scale features (typically ~100km in scale) but will also resolve sub-mesoscale variability (~100m). We will benefit from successes and lessons learnt from recent, pioneering deployments of underwater gliders and use a suite of sensors that permit high-resolution coincident measurements of key ecosystem indicators. Combining the expertise within the AlterEco team we will not only provide a new framework for marine observations that has global transferability, but also the diagnostic capability to improve understanding of shelf sea ecosystem health and function.

Continental shelf seas are typically less than 200m deep and can be described by the shallow ocean surrounding continental land masses. Due to their accessibility, shelf seas are commercially and economically important, with oil and gas extraction alone in UK shelf seas valued at £37B pa. Despite occupying only 7% of the surface ocean, shelf seas also play a major role in the global carbon cycle and marine ecosystem. Shelf seas are 3-4 times more productive than open-ocean, are estimated to support more than 40% of carbon sequestration and support 90% of global fish catches providing a critical food source for growing coastal populations. However, shelf seas are also exposed to climate driven and anthropogenic stress that could have a profound impact on their biological productivity, oxygen dynamics and ecosystem function. Many processes contributing to this threat are related to regions that undergo vertical stratification. This process occurs when the bottom layer of shelf seas becomes detached from the atmospherically ventilated near surface layer. In temperate shelf seas stratification predominantly occurs as solar heating outcompetes the tide and wind-driven mixing to produce a warm surface layer, resulting in seasonal stratification over large areas of the NW European shelf seas. A combination of physical detachment from the surface and increased biological oxygen consumption in the bottom layer, accentuated by the enhanced productivity that stratification also supports in the upper ocean, can result in a drastically reduced bottom layer oxygen concentration. When oxygen levels get so low, they are classified as being oxygen deficient and this can be problematic for benthic and pelagic marine organisms and have a detrimental effect on ecosystem function. Evidence of increasing seasonal oxygen deficiency in the regions of North Sea by members of the AlterEco team and a recognised global increase in the extent of shelf sea and coastal oxygen deficiency calls for an urgent need to increase the spatial and temporal measurement of oxygen and a better understanding of the processes that lead to oxygen deficiency in shelf sea bottom waters. This need is severely impeded by the natural complexity of ecosystem functioning, the impact of a changing climate, connectivity between different regions of our shelf seas and large-scale external forcing from ocean and atmosphere. Current methods are severely restricted in resolving this complexity, due to the poor resolution in observational coverage, which calls for a new strategy for observing and monitoring marine ecosystem and environmental status. AlterEco seeks to address this challenge within the framework of the given call by the development of a novel monitoring framework to deliver improved understanding of key shelf sea ecosystem drivers. We will capitalise on recent UK investments in marine autonomous vehicles and planning capability to investigate an area of the North Sea known to undergo variable physical, chemical and biological conditions throughout an entire seasonal cycle, including areas identified to experience low bottom layer oxygen levels during summer months. Ocean gliders will be used to undertake repeat transects over a distance of ~150km, sufficient to capture important shelf sea features; such as fronts and eddies. The AlterEco strategy will employ small fleets of vehicles to capture these meso-scale features (typically ~100km in scale) but will also resolve sub-mesoscale variability (~100m). We will benefit from successes and lessons learnt from recent, pioneering deployments of underwater gliders and use a suite of sensors that permit high-resolution coincident measurements of key ecosystem indicators. Combining the expertise within the AlterEco team we will not only provide a new framework for marine observations that has global transferability, but also the diagnostic capability to improve understanding of shelf sea ecosystem health and function.