a b s t r a c tAfrican farming systems are highly heterogeneous: between agroecological and socioeconomic environments, in the wide variability in farmers' resource endowments and in farm management. This means that single solutions (or 'silver bullets') for improving farm productivity do not exist. Yet to date few approaches to understand constraints and explore options for change have tackled the bewildering complexity of African farming systems. In this paper we describe the Nutrient Use in Animal and Cropping systems -Efficiencies and Scales (NUANCES) framework. NUANCES offers a structured approach to unravel and understand the complexity of African farming to identify what we term 'best-fit' technologiestechnologies targeted to specific types of farmers and to specific niches within their farms. The NUANCES framework is not 'just another computer model'! We combine the tools of systems analysis and experimentation, detailed field observations and surveys, incorporate expert knowledge (local knowledge and results of research), generate databases, and apply simulation models to analyse performance of farms, and the impacts of introducing new technologies. We have analysed and described complexity of farming systems, their external drivers and some of the mechanisms that result in (in)efficient use of scarce resources. Studying sites across sub-Saharan Africa has provided insights in the trajectories of change in farming systems in response to population growth, economic conditions and climate variability (cycles of drier and wetter years) and climate change. In regions where human population is dense and land scarce, farm typologies have proven useful to target technologies between farmers of different production objectives and resource endowment (notably in terms of land, labour and capacity for investment). In such regions we could categorise types of fields on the basis of their responsiveness to soil improving technologies along soil fertility gradients, relying on local indicators to differentiate those that may be managed through 'maintenance fertilization' from fields that are highly-responsive to fertilizers and fields that require rehabilitation before yields can improved. Where human population pressure on the land is less intense, farm and field types are harder to discern, without clear patterns. Nutrient cycling through livestock is in principle not efficient for increasing food production due to increased nutrient losses, but is attractive for farmers due to the multiple functions of livestock. We identified trade-offs between income generation, soil conservation and community agreements through optimising concurrent objectives at farm and village levels. These examples show that future analyses must focus at farm and farming system level and not at the level of individual fields to achieve appropriate targeting of technologies -both between locations and between farms at any given location. The approach for integrated assessment described here can be used ex ante to explore the potential of bes...

Long-term ecosystem-level experiments, in which the environment is manipulated in a controlled manner, are important tools to predict the responses of ecosystem functioning and composition to future global change. We present the results of a meta-analysis performed on the results of long-term ecosystem-level experiments near Toolik Lake, Alaska, and Abisko, Sweden. We quantified aboveground biomass responses of different arctic and subarctic ecosystems to experimental fertilization, warming and shading. We not only analysed the general patterns but also the differences in responsiveness between sites and regions. Aboveground plant biomass showed a broad similarity of responses in both locations, and also showed some important differences. In both locations, aboveground plant biomass, particularly the biomass of deciduous and graminoid plants, responded most strongly to nutrient addition. The biomass of mosses and lichens decreased in both locations as the biomass of vascular plants increased. An important difference between the two regions was the smaller positive aboveground biomass response of deciduous shrubs in Abisko as compared with Toolik Lake. Whereas in Toolik Lake Betula nana increased its dominance and replaced many of the other plant types, in Abisko all vascular plant types increased in abundance without major shifts in relative abundance. The differences between the responses of the dominant vegetation types of the Toolik Lake region, i.e. tussock tundra systems, and that of the Abisko region, i.e. heath systems, may have important implications for ecosystem development under expected patterns of global change. However, there were also large site-specific differences within each region. Several potential mechanistic explanations for the differences between sites and regions are discussed. The response patterns show the need for analyses of joint data sets from many regions and sites, in order to uncover common responses to changes in climate across large arctic regions from regional or local responses.

We calculated a simple indicator of food availability using data from 93 sites in 17 countries across contrasted agroecologies in subSaharan Africa (>13,000 farm households) and analyzed the drivers of variations in food availability. Crop production was the major source of energy, contributing 60% of food availability. The off-farm income contribution to food availability ranged from 12% for households without enough food available (18% of the total sample) to 27% for the 58% of households with sufficient food available. Using only three explanatory variables (household size, number of livestock, and land area), we were able to predict correctly the agricultural determined status of food availability for 72% of the households, but the relationships were strongly influenced by the degree of market access. Our analyses suggest that targeting poverty through improving market access and off-farm opportunities is a better strategy to increase food security than focusing on agricultural production and closing yield gaps. This calls for multisectoral policy harmonization, incentives, and diversification of employment sources rather than a singular focus on agricultural development. Recognizing and understanding diversity among smallholder farm households in sub-Saharan Africa is key for the design of policies that aim to improve food security.food security | smallholder farmers | yield gap | resource scarcity | farm size A chieving sustainable food security (i.e., the basic right of people to produce and/or purchase the food they need, without harming the social and biophysical environment) is a major challenge in a world of rapid human population growth and large-scale changes in economic development (1). In sub-Saharan Africa (SSA), production on smallholder farms is critical to the food security of the rural poor (2) and contributes the majority of food production at the national level. National policies and local interventions have profound impacts on the opportunities and constraints that affect smallholders (3). However, policy frameworks that aim to improve food security and rural livelihoods in the developing world face many uncertainties and often fail (4).The formulation of effective policies needs adequate information on how different options affect the complex issues surrounding food security and sustainable development. A complication in generating such information is the large diversity within and among smallholder farming systems. Agroecological conditions, markets, and local cultures determine land use patterns and agricultural management across regions, whereas within a given region, farm households differ in many ways, including resource endowment, production orientation and objectives, ethnicity, education, past experience, management skills, and in the farm households' attitude toward risk. Policies by their nature have to be widely applicable, but recognizing this diversity in farm households is key to designing more effective policies to help poor farmers (5). Understanding the main drivers of ho...

1 Arctic landscapes are characterized by extreme vegetation patchiness, often with sharply defined borders between very different vegetation types. This patchiness makes it difficult to predict landscape-level C balance and its change in response to environment. 2 Here we develop a model of net CO 2 flux by arctic landscapes that is independent of vegetation composition, using instead a measure of leaf area derived from NDVI (normalized-difference vegetation index). 3 Using the light response of CO 2 flux (net ecosystem exchange, NEE) measured in a wide range of vegetation in arctic Alaska and Sweden, we exercise the model using various data subsets for parameter estimation and tests of predictions. 4 Overall, the model consistently explains ~80% of the variance in NEE knowing only the estimated leaf area index (LAI), photosynthetically active photon flux density (PPFD) and air temperature. 5 Model parameters derived from measurements made in one site or vegetation type can be used to predict NEE in other sites or vegetation types with acceptable accuracy and precision. Further improvements in model prediction may come from incorporating an estimate of moss area in addition to LAI, and from using vegetation-specific estimates of LAI. 6 The success of this model at predicting NEE independent of any information on species composition indicates a high level of convergence in canopy structure and function in the arctic landscape.