Bioenergy crops have gained international prominence as fossil fuel prices increase and concerns about climate change grow. Increasing demand for bioenergy crops on international markets might lead to conflict with smallholder food production in the tropics and/or act as a driver of deforestation if large scale forest land conversions are initiated. Alternatively, smallholders might not jeopardise their own food security, and would grow bioenergy crops alongside food crops, incorporating their production into their current land use systems, increasing cash flow and thus permitting them to purchase inputs to intensify food production. The profitability, energy balance, social and ecological impacts will depend on the bioenergy crop used, how it is grown, with which inputs, on what type of land, what, if any, are the alternative uses of that land, and who reaps the benefit. So whether biofuel production is a threat or an opportunity will depend on the specific context. Jatropha curcas is a shrub, native to central America but is cultivated across the tropics. It is being promoted as a bioenergy crop as its seeds contain 20-30% oil, which can be easily extracted and converted to biodiesel. In Mexico, jatropha is traditionally used as a hedge. Large scale plantings were initiated in early 2006. By 2008, 20,000 ha were planted in Chiapas state and it is expected that 150,000 ha will be planted Veracruz state in the next two years. In India, large-scale land conversions to jatropha have been initiated, for example, more than 400,000 hectares of land in Uttar Pradesh state and the Indian government has proposed that biofuels account for 20% of its transportation fuel consumption by 2017, from the present 5%. Yet, despite these ambitious projects, little is known about its yield, pest and disease problems and environmental impact and so in which context it would be advisable to grow jatropha, rather than another bioenergy crop, such as Elaeis guineensis (oil palm). To some extent, ecological ranges of jatropha and oil palm overlap. In India, state governments of Orissa and Tamil Nadu are encouraging farmers to plant oil palm, given that India consumes an estimated 4.2 megatonnes per year. Similarly in Mexico, there are some large scale oil palm initiatives. This project aims to assess profitability, economic, social and environmental impacts of the production of two bioenergy crops, jatropha and oil palm. With data obtained it aims to identify the most suitable areas and conditions for sustainable and profitable yields and the extent of economic, social and environmental production risks. It aims to identify current shortfalls in land tenure systems or law and develop legislation to ensure social sustainability and equity of bioenergy projects.

The project aims to bring together and produce cutting edge research to provide pest and disease monitoring and forecast information, integrating multi-source (Earth Observation (EO), meteorological and vertical looking radar) to support decision making in the sustainable management of insect pests and diseases. The project will explore the integration and fusion of new data sources from recently launched satellites with existing data products. This will overcome spatial and temporal differences to produce new data solutions and algorithms which are suitable for pest and disease monitoring and prediction, intervention efficacy forecasting and estimation of yield losses. The new data products and algorithms will be tested using two candidate systems: a fungal disease of wheat (stripe rust) and a serious insect pest (migratory locust). The corresponding efficacy of a biopesticide used to control the locust will also be explored, with the aim to investigate whether the same data inputs produced during this project can be utilised under a wide range of systems, leading to a greater impact of data assimilation in the future. Models will be validated in the laboratory and in the field to give a measure of certainty of predictions. Additionally, risk and loss estimation will be investigated using cutting edge EO techniques, and monitoring of locusts will be explored using Vertical Looking Radar, a technology which is capable of identifying the size and species of insect flying through a radar beam. In addition to building monitoring and forecasting systems with data assimilated during this project, routes to extend this information to appropriate end users will be explored to ensure maximum impact of technologies developed during the project. The project consortium will work closely with NATESC in China to ensure the system is built in a way that is compatible with existing methods of information dissemination. The project consortium is a strong multidisciplinary team with expertise in EO, vertical-looking radar technology and agricultural research and extension.

Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.

The human microbiome is a term used to describe the bacteria and other microorganisms that live on, and in, the human body. These microorganisms coexist with us. They are with us from birth and they play an important role in shaping the development of our immune system. Much of the interaction between the microbiome and the immune system occurs at specialised barrier surfaces, such as those found in the gut and lung. These surfaces are adapted to protect the body from invasion. They also enable human immune cells to interact with both good and potentially harmful microbes and the substances (metabolites) they produce. Genetic diseases (diseases caused by errors in human DNA sequence) may sometimes result in disruption of normal function at barrier surfaces. This is true of diseases such as cystic fibrosis (CF) and inflammatory bowel disease (IBD), as well as a number of rare genetic conditions. Under these circumstances, the breakdown of normal interactions between the body (in particular the immune system) and its microbiome may contribute significantly to disease development. Understanding the contribution of the human microbiome to genetic diseases involving disruption to barrier surfaces is therefore important. It may lead to a better understanding of how these diseases develop and opportunities for new drug development. It may also lead to opportunities to manipulate the microbiome itself as a novel form of treatment. A major challenge that limits our ability to understand the role of the microbiome in disease development is its complexity. Trillions of microbes inhabit a single human body and microbiomes can vary greatly between individuals. Mouse models are therefore an essential tool in microbiome research because they allow for the microbiome to be tightly controlled or even removed entirely (so called germ-free mice) so that its impact on disease can be studied and understood. As part of the MRC Mouse Genetics Network, we will bring together a range of clinical, immunological, and microbiome expertise from across the UK to form a cluster that addresses the role of the microbiome in genetic diseases involving barrier surface malfunction. Our 'Microbiome and Barrier Function' cluster will achieve two complementary goals: First, it will develop an experimental pipeline for creating and studying mouse models of human genetic diseases involving barrier surfaces, with a focus on understanding the impact of the microbiome in these diseases. Second, it will establish a national infrastructure for cutting-edge mouse microbiome research that will be accessible to all UK researchers. Key deliverables for Aim 1 include studying three different mouse models of human genetic diseases involving barrier surface disruption in the gut and lung. We will apply state-of-the-art microbiome research techniques (such as generating germ-free mice and generating synthetic microbiome communities) to each model along with in-depth immunological analysis. In combination, these approaches will help us to identify precisely how the microbiome contributes to disease development and identify new treatment opportunities. To better understand the relevance of these results to human disease, we will simultaneously apply computational approaches to better characterize the mouse microbiome and compare its functional potential to human microbiomes in relevant disease groups. Key deliverables for Aim 2 include working with the Mary Lyon Centre to establish new standards and best practices in mouse microbiome research. In addition, we will provide training to other UK researchers in the computational and experimental techniques developed by our cluster. Finally, we will expand our experimental pipeline to other related genetic disease models involving barrier surface malfunction, as well as other models of diseases where the microbiome is thought to play a key role (e.g. colorectal cancer).

Pests and diseases cause significant losses of crops around the world and is a significant threat to food security. In China the migratory locust affects over 2 million hectares of agricultural land, while in Laos the yellow spined bamboo locust which is widespread across the 9 districts of Norther Laos and damaged over 5,000 hectares of crops in 2019. A new invasive pest, the Fall Army Worm is becoming prevalent in Southeast Asia and China. It has been found in 22 provinces in China and affected 35,000 hectares of maize in Laos. Experience from Africa shows it can cause almost total crop losses. Managing the damage from pests can be difficult due to lack of detailed information on where risks to crops are greatest, use of inappropriate or ineffective control measures, and build of resistance in pest populations to chemical pesticides. In addition overuse of chemical pesticides causes environmental damage in the form of loss of biodiversity and through chemical residues left in the environment, particularly in waterways. In this project we will use Earth observation and meteorological data to provide information that will help farmers and agricultural authorities manage pest risk more sustainably. Using Earth observation imagery we will prepare risk maps that identify habitats where locusts and fall armyworm are most likely to establish populations. Using satellite data on surface temperature we will develop and run models that predict i) the growth of insect populations and ii) the effectiveness of biological control methods. The models will provide information to help preparedness and to guide the timing of application of biopesticides. The project will build upon work already undertaken in North-East China and apply it in the Southern Chinese province of Hainan, and in Laos. We will provide risk base maps and information products that help chose the method and timing of interventions. We will work with agricultural management authorities in China and Laos, providing training in the use of the information.