Yield gaps estimations and explanations provide important information on the scope for production increases on existing agricultural land through better farming systems, farm management and enabling policies. The aim of this project is to develop and implement a framework that identifies the key bio-physical and management factors that influence the maize yield gap in SSA and how these are related to existing institutional, infrastructural, socio-economic and policy constraints. The research focuses on the major food crop in SSA, maize, mainly produced by small scale farmers. Maize is an important food crop in almost all Sub-Saharan African countries. Addressing yield performance in maize is therefore valuable from both a food security and poverty perspective. The project will focus on Ghana and Ethiopia as maize-growing case study countries where it builds on existing data and local partnerships. It is assumed that enhanced understanding for these two countries from West and East Africa will have wider meaning. The innovative part of this project is the use of a framework that integrates agronomic and economic approaches to assess the yield gap and analyse agricultural performance at the farm and plot level. The analysis consists of three stages. In the first stage crop growth and economic production models are used to calculate potential, technical efficient ('best practice') and economic ceiling yields at the national and regional level, which are subsequently combined with actual yield data from surveys to compute the various yield gaps. In the second stage, econometric techniques are used to analyse variations in the observed yield gaps in space and relate them to plot-level, farm-level and context determining factors. In the third stage, a small number of local case studies are organised at the village level to deepen the analyses and to thoroughly understand the determinants of yield gaps to allow identification of farm and management innovations and policy interventions. Information on yield potentials and actual yields will be taken from the Global Yield Gap Atlas (GYGA) that is currently being developed by University of Nebraska, Wageningen University and many partners from SSA. Farm/household level data and plot level information for Ethiopia and Ghana will be taken from the World Bank's Living Standards Measurement Study-Integrated Surveys on Agriculture (LSMS-ISA) and EGC-ISSER Ghana (expected to become available end of 2013). In addition, a survey in each of the case-study regions will be organised to collect additional and detailed information on plot-level crop production and management such as soil characteristics, cultivation history and agronomic management. The results will be used to derive targeted policy and farming recommendations that account for the complex environments in which male and female farmers in the SSA-region operate and incorporate the basic mechanisms that link farm performance to the broader enabling environment. This process will be supported by initiating participatory on-farm demonstration trials on the one hand and a policy dialogue with stakeholders on the other hand.

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 world's mountains host some of the most complex, dynamic, and diverse ecosystems. But these environments are under severe threats, ranging from local deforestation and soil degradation to global climate change. Global climate models project stronger warming at high elevations, with potentially disastrous consequences for its ecosystems services (ESS). For instance, melting glaciers alone will affect the water supply of millions people, while soil degradation and erosion put local agricultural practices in danger, but also cause water quality degradation and siltation of downstream reservoirs. At the same time, the complexity of mountains also makes predicting the direction of future changes in ecosystem services extremely difficult. For instance, global climate models do not capture the local weather patterns, and traditional models of the natural and physical processes may not represent the extreme and region specific behaviour. This leads to large uncertainties in future predictions about mountain ESS. Under such conditions, the value of day-to-day information about how local ecosystems behave increases sharply. Continuous monitoring of crucial ecosystem processes becomes paramount. It allows local decision-makers to flexibly change course in response to unexpected behaviour and large uncertainties. However, because of their remote location and difficult access, monitoring ESS in mountain regions tends the lag behind the rest of the world. The same remoteness and lack of access are also responsible for the propensity of mountain regions to host poor and underdeveloped communities compared to the surrounding lowlands. Lastly, mountain regions tend to be more prone to conflict, which further inhibits human development. This project will analyse how monitoring and knowledge generation of ESS in mountain regions can be improved, and used to support a process of adaptive, polycentric governance focused on poverty alleviation. For this, we will blend cutting-edge concepts of adaptive governance with technological breakthroughs. The availability of cheap and robust sensors and communication technologies provides great opportunities for citizen science: bottom-up, user oriented data collection focused on local concerns. We will take citizen science to a next level, by integrating it in a broader framework of participatory data processing, knowledge generation and sharing. We do this by adopting the concept of Environmental Virtual Observatories (EVOs) and leverage it for poverty alleviation. We see the potential of EVOs to be decentralised and open technology platforms for knowledge generation and exchange that enable participation of marginalised and vulnerable communities bypassed by the traditional mechanisms. Therefore, in this project we will analyse how EVOs can be used to generate knowledge and to alleviate poverty in 4 remote and poor mountain regions: the Ethiopian highlands around lake Tana, the Central Tien Shan Mountains of Kyrgyzstan, the Kaligandaki watershed in Northern Nepal, and the Andes of central Peru. In each location, we will collect evidence on the local decision-making processes on ESS and their local socio-economic context. At the same time, we will develop a technology toolset to enable EVO development for each case. Subsequently, the results of both processes will be brought together to implement tailored EVOs to support citizen science and local knowledge generation. We will create novel ways to interact with EVOs beyond the traditional Internet focussing on leaflets in the national language, community radios, and mobile phone applications. We will evaluate how the improved access to local observations fosters cross-scale linkages between the poor and external actors, as well as linkages between communities and marginal groups. Lastly, we will investigate how this can lead to better community awareness of environmental change and identification of pathways for poverty alleviation.

Legumes are a group of important plant species that, together with bacteria that live in nodules on the root, can convert nitrogen in the atmosphere to a form that can be used by plants. They include peas and beans as well as crop plants that are used for animal feed. Some legume species have been developed as 'models' that allow us to investigate genome structure, DNA sequence and the control of gene expression in a way that would be more difficult in crops. Model species typically have a small genome size, short generation times and an inbreeding system of reproduction. The barrel medic (Medicago truncatula ) has been developed as a model legume and, for example, is expected to have all its genes sequenced by the end of 2007. Information and resources from model species can be used to understand more about the genetics and genomics of crop plants in a way that will facilitate improved ways of breeding new varieties for the changing needs of agriculture. In this work we will use knowledge of Medicago truncatula to gain understanding of a closely related species, red clover. Red clover (Trifolium pratense L.) is an important crop for feeding animals (sheep, beef and dairy cattle) in the UK and many temperate parts of the world. In this work we will compare the genomes of the model and crop to lay the foundation for new approaches to breeding in the crop. We will do this in several different ways: (i) The sequences of long stretches of DNA will be compared. To do this we will use DNA that has been inserted into bacterial artificial chromosomes (BACs) in a way that allows it to be held together and suitable for sequencing. The extent of similarity in sequence between red clover and M. truncatula will tell us how closely related the two species are and the extent to which we can use information from the model e.g. to clone genes in the crop. (ii) The position of differences in DNA sequence (polymorphisms) will be mapped in the genome of red clover in such as way as to relate these differences to the physical genome as represented by the BACs (iii) A number of bio-informatic approaches will be used to extract information from DNA sequencing, physical and genetic mapping and to place the information found in the wider context of legume genetics. The bioinformatic component of the work will also facilitate the application of the knowledge gained and resources generated to the development of new varieties of red clover and other important crop species.

We will examine the genetic basis of sex ratio behaviour in the parasitoid wasp Nasonia vitripennis. Female N. vitripennis facultatively change their offspring sex ratios in line with Hamilton's theory of Local Mate Competition (LMC). LMC arises from competition between related males (e.g. brothers) for mates, and can occur when mating occurs in localised groups, for instance amongst groups of kin. When LMC is intense (e.g. if all males are brothers), the optimal sex ratio is a female-biased one. This bias reduces competition amongst sons and increases the number of mates for those sons. As LMC declines, so does the predicted sex ratio bias. The degree of LMC depends on how many females lay eggs on a patch of hosts (and how many eggs they lay). Over the last decade, we have explored the cues female Nasonia use when allocating sex under LMC. With a robust theoretical framework, we now have a remarkably good understanding of facultative sex allocation under LMC at the phenotypic level in Nasonia. However, our understanding of the genetics of sex ratio is more rudimentary, especially in terms of the mechanism of sex allocation. Thus far, we have some picture of the quantitative genetics of sex ratio in Nasonia (estimates of heritability, input of new mutations, and the identification of four Quantitative Trait Loci, or QTL). We have also begun to explore what genes are expressed during oviposition. In this proposal, we will build on this work to explore the genetic basis of sex ratio variation and control in Nasonia, using three complementary approaches. First, we will first follow-up our recent QTL study using a Restriction Site Associated DNA sequencing ("RAD-seq") approach and a repeat of the cross between High and Low sex ratio lines drawn from the same natural population. RAD-seq can generate thousands of markers across a genome enabling finer-scale QTL mapping projects. We will also use the data we generate to test for clutch size variation QTL, testing for loci pleiotropically influencing both sex ratio and clutch size. Second, we will follow-up our recent gene expression work to explore changes in gene expression associated with exposure to different LMC environments and different combinations of LMC cues. Back in 2004, Shuker & West experimentally showed that female Nasonia vitripennis responded differentially to "host" versus "social" LMC cues. We will follow a similar protocol, assaying the transcriptomes of the focal females using RNA-seq on the Illumina platform. Our aim is to see whether we can link patterns of gene expression to subtle environmental differences which we know have a big effect on the sex ratio phenotype. Third, we will test whether or not epigenetic modifications of DNA (specifically DNA methylation) are associated with the regulation of sex ratio behaviour. The extent to which epigenetic control of gene expression influences behaviour is currently the focus of much interest, both in humans and other vertebrates, but also increasingly in insects. First, we will look for patterns of differential methylation associated with either mating (as females switch from mate-searching to host-searching) and/or interactions with LMC cues whilst ovipositing. Second, we will disrupt DNA methylation and look for changes in sex allocation. If DNA methylation helps regulate gene networks associated with sex ratio behaviour, then we will see patterns of differential methylation across the treatments in the first experiment and changes in sex allocation across the treatments in the second. Taken together, these approaches will address both the genetic architecture of sex ratio variation and also the genes and gene pathways associated with sex allocation, and whether or not the regulation of those pathways involves DNA methylation. They will provide complementary sets of candidate genes, enabling the functional genomic/molecular evolution studies required to fully realise the genotype-phenotype link.