Ecosystem services can and should be related to carbon management, in combination with sustainable water and land management. The global nature of climate change mitigation provides opportunities for developing countries to alleviate poverty by capitalizing on their natural resources and trading on the international carbon markets. Such opportunities may arise from biotic carbon sequestration through reforestation or biofuel production. However, the changes in land-use that result from any such initiatives may be detrimental to ecosystem services, such as biodiversity, water quality and water availability. In the long term, changes in climate and population may worsen these impacts, rendering such land management initiatives unsustainable from both biophysical and socio-economic standpoints. Land use change initiatives should therefore be assessed in a framework that incorporates climate and socio-economic change, in order to identify those that have the potential to alleviate poverty in the long term, and discount those that are likely to worsen the problem. The extensive existing work on land management has yielded much valuable data on energy crop physiology, the economic implications of different land management strategies, the observed effects of land management on ecosystem services, and best practice for implementing land management projects. Parallel to this, there has been much work on land surface feedbacks, the water cycle, regional climate variability and change, which has involved the development of state-of-the-art climate, land surface, hydrological and crop models. This project proposes to bring these strands of research together to investigate the sustainability of land management initiatives in a changing climate. Existing tools, informed by published data, would be combined into a modeling framework that would be applied to a series of scenarios involving intensive cultivation of sugar cane. Specifically, the following three issues would be addressed: (1) The feasibility and sustainability (economic and physical) of sugarcane cultivation for biofuel production in a changing climate, and the capacity of such activities to alleviate poverty in the long term. (2) The long term impact of land management on ecosystem services, with particular focus on the effect on water availability (3) Land surface - climate feedbacks, and their impact on the sustainability of land management initiatives and existing land use. The modeling would be applied to sugarcane cultivation in Brazil and Ghana. Brazil has a well-established sugarcane industry that already provides substantial employment and income. The dependence of large parts of the country on biofuel production makes the industry's long-term economic viability a pressing issue. Although production is not currently limited by water availability, this may change in the future due to changing environmental conditions. Ghana was chosen for the other case study because it is on the verge of becoming a major player in the bio-ethanol market, as the result of an agreement signed with Brazilian partners in 2006 to grow bio-energy crops. The prospect of exporting biofuel technology from Brazil to Africa raises urgent questions about environmental sustainability and the capacity of energy crop cultivation initiatives to alleviate poverty. In particular, there is a pressing need for rigorous assessment of the delicate balance between yield (and hence profitability), irrigation, water resources and the livelihoods of local people. The proposed study is primarily a proof of concept, with the main focus on developing a modeling framework and engaging with researchers in Ghana and Brazil, in order to apply it in a useful and informative way. It should be emphasized, however, that the framework would be equally applicable to other energy and food crops, such as Jatropha Curcas and could be applied to any region of the world.

Invasive species pose a serious threat to native ecosystems, food security and income generation. The Old World cotton bollworm, Helicoverpa armigera, is a global crop pest, causing >US$2 billion of damage annually. Recently, it was found that this voracious pest had finally arrived in Brazil and is now established across the country. The aims of this partnership are: - To convene a workshop of stakeholders to undertake a risk assessment of the potential impact of bollworm spread in Brazil. - To collect field samples of bollworms for analysis of genetic diversity, beneficial microbes and natural enemies. - To assess the potential for microbial symbionts to modulate biopesticide efficacy. - To determine the role of phenotypic plasticity in modulating susceptibility to biopesticides. The longer-term goal is to establish a consortium of stakeholders equipped to identify, monitor and control the spread of this invasive species and to minimize its environmental impact.

Transitioning towards FAIR data has been notoriously challenging in the long tail of science. This is mainly because the long tail consists of many independently assembled datasets different in structure and management, yet collected with a similar purpose. This proposal builds on the recently established SPI-Birds Network and Database on long-term population studies of birds, hosting and standardising individual-level data. Our aim is to develop this network as a model for other (ecological) research domains, with particular emphasis on the currently under-addressed stages of data processing, data analysis, and data preservation. First, we will develop a repository with citable datasets that can be linked to publications, analytical codes, and other output, thereby closing the research lifecycle in the long tail of science. Second, we will expand the user base with respect to both data producers (expanding geographic and ecological coverage of the datasets), researchers within and outside the SPI-Birds community, and users outside research such as educators, journalists, environmental professionals or artists and designers. Central to these first two objectives is the continued development and refinement of an existing standard data format with rich metadata (and accessible metadata guides) according to common standards such as the Darwin Core. Third, we will establish a peer-reviewed archive (including tests by selected users) for data processing and analytical codes (that can be applied to the datasets hosted in the database, but also beyond), promoting efficiency and replicability of large-scale data analyses. Our final goal is a fully transparent FAIR research landscape of datasets, analytical tools and publications that are connected by digital identifiers and rich metadata.