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Little is known about productivity of smallholder maize–pigeonpea intercropping systems in sub-Saharan Africa. We conducted a survey of 277 farm households in Northern Tanzania to assess socio-economic factors, field management characteristics, and their association with productivity of maize–pigeonpea intercrops. On each farm, crop assessments were focused on a field that the farmer identified as most important for food supply. Variables associated with yields were evaluated using linear regression and regression classification. Biomass production ranged between 1.0 and 16.6 for maize, and between 0.2 and 11.9 t ha−1 for pigeonpea (at maize harvest). The corresponding grain yields ranged between 0.1 and 9.5 for maize, and between 0.1 and 2.1 t ha−1 for pigeonpea. Plant density at harvest, number of years the field had been cultivated, slope, weeding, soil fertility class, fertiliser and manure use were significantly associated with variation in maize grain yield, with interactions among the factors. Fields on flat and gentle slopes with plant density above 24,000 ha−1 had 28% extra yields when fertiliser was applied, while less than 24,000 plants ha−1 yielded 16% extra yield when manure was applied. Plant density at harvest was the key factor associated with pigeonpea yield; fields with densities above 24,000 plants ha−1 yielded an average of 1.4 t ha−1, while less than 24,000 plants ha−1 yielded 0.5 t ha−1. We conclude that performance of intercrops can be enhanced through application of organic and inorganic nutrient sources, and agronomic interventions including weeding, implementing soil conservation measures on steep slopes and optimising plant density.

Leguminous plants are known to require phosphorus fertilizers and inoculation with nitrogen fixing rhizobia for optimum yield but other nutrients may also be lacking. In this study, the most limiting nutrients for legume growth were determined in soils where the crops had not responded to P and rhizobial inoculation in field trials, using the double pot technique. Soils were collected from 17 farmers' fields in West Kenya, Northern Nigeria, Eastern and Southern Rwanda, South-west and North-west Sierra Leone. Plant growth and mean biomass were measured on soils to which a full nutrient solution, containing phosphorus (P), potassium (K), magnesium (Mg), sulfur (S) and micronutrients (MN) were added, and which were compared to a control (no nutrient added), and individual omissions of each nutrient. The relationship between soil properties and nutrient deficiencies was explored. Nutrient limitations were found to differ between soils, both within and across countries. Generally, each soil was potentially deficient in at least one nutrient, with K, P, Mg, MN and S emerging as most limiting in 88, 65, 59, 18, and 12% of tested soils, respectively. While K was the most limiting nutrient in soils from Kenya and Rwanda, P was most limiting in soils from Nigeria. P and K were equally limiting in soils from Sierra Leone. Mg was found limiting in two soils from Kenya and three soils from Rwanda and one soil each in Nigeria and Sierra Leone. Micronutrients were found to be limiting in one soil from Nigeria and one soil from Rwanda. Estimates of nutrient deficiency using growth and mean biomass were found to be correlated with each other although the latter proved to be a more sensitive measure of deficiency. With few exceptions, the relation between soil parameters and nutrient deficiencies was weak and there were no significant relations between deficiency of specific nutrients and the soil content of these elements. Although our results cannot be translated directly to the field, they confirm that individual and multiple nutrient deficiencies were common in these “non-responsive” soils and may have contributed to reported low yields. This highlights the need for balanced nutrition in legume production in SSA.

It is often claimed that cocoa producers are poor, but the extent of their poverty is rarely defined. We analyzed six data sets derived from household questionnaires of 385–88,896 cocoa producers in Côte d'Ivoire and Ghana. Across all data sets, many households (30–58%) earn a gross income below the World Bank extreme poverty line and the majority (73–90%) do not earn a Living Income. Households with less income per person per day generally achieve lower cocoa yields, consist of more household members, have a smaller land size available, and rely more on cocoa income than households with higher incomes. When comparing the effects of increasing prices and yields on gross income, yield increases lead to larger benefits especially for the poorest households. Doubling the cocoa price would leave 15–25% of households with a gross income below the extreme poverty line and 53–65% below the Living Income benchmark. At yields of 600 kg/ha, against current yields around 300 kg/ha, these percentages are reduced to 7–11 and 48–62%, respectively, while at yields of 1,500 kg/ha only 1–2% of households remain below the extreme poverty line and 13–20% below the Living Income benchmark. If we assume that the production costs of achieving a yield of 1,500 kg/ha are 30% of revenue, still only 2–4% of households earn a net income below the extreme poverty line and 25–32% below the Living Income benchmark. Whilst sustainable intensification of cocoa production is undoubtedly a strong approach to increase cocoa yields and farmer incomes, achieving this does not come without pitfalls. The poorer households face multiple barriers to invest in cocoa production. A better understanding of cocoa producing households and the resources available to them, as well as the opportunity for alternative income generation, is required to tailor options to increase their income. The utility and interpretability of future household surveys would be drastically improved if definitions and variables addressed were approached in a standardized way.

In November 2014 I suffered a major stroke and was unable to work. I recently began to ‘wake up’ and have been able to re-engage with literature and discussions on agricultural development and climate change. I am surprised how familiar I am with much of the debate, but disappointed that major issues receive little attention – such as the impacts of climate change on smallholder agriculture, conservation of biodiversity and the need for reform of global financial institutions. In this short ‘perspective’, I comment on issues where there has been little academic attention over the past seven years and new issues that have arisen such as animal-free foods and artificial intelligence. I conclude by suggesting where attention needs to be focused. I expect this to be my final contribution to the literature.

The extreme poverty line is the most commonly used benchmark for poverty, set at US$ 1.90 by the World Bank. Another benchmark, based on the Anker living wage methodology, is the remuneration received for a standard work week necessary for a worker to meet his/her family’s basic needs in a particular place. The living wage concept has been used extensively to address incomes of plantation workers producing agricultural commodities for international markets. More recently intense discussion has emerged concerning the ‘living income’ of smallholder farmers who produce commodities for international supply chains on their own land. In this article we propose a simple method that can be used in all types of development projects to benchmark a rural ‘living income’. We launch the Living Income Methodology, as adapted from the Living Wage Methodology, to estimate the living income for rural households. In any given location this requires about one week of fieldwork. We express it per adult equivalent per day (AE/day) and data collection is focused on rural households and their immediate surroundings. Our three case studies showed that in 2017 in Lushoto District, rural Tanzania, the living income was US$ PPP 4.04/AE/day, in Isingiro District, rural Uganda, 3.82 and in Sidama Zone, rural Ethiopia, 3.60. In all cases, the extreme poverty line of US$ PPP 1.90 per capita per day is insufficient to meet the basic human rights for a decent living in low-income countries. The Living Income Methodology provides a transparent local benchmark that can be used to assess development opportunities of rural households, by employers in rural areas, including farmers hiring in labour, while respecting basic human rights on a decent living. It can be used to reflect on progress of rural households in low-income countries on their aspired path out of poverty. It further provides a meaningful benchmark to measure progress on Sustainable Development Goal 1, eliminating poverty, and 2, zero hunger and sustainable food systems, allowing for consideration of the local context.

Achieving SDG2 (zero hunger) in a situation of rapid global population growth requires a continued focus on food production. Farming not merely needs to sustainably produce nutritious diets, but should also provide livelihoods for farmers, while retaining natural ecosystems and services. Rather than focusing on production principles, this article explores the interrelations between farms and farming systems in the global food system. Evaluating farming systems around the world, we reveal a bewildering diversity. While family farms predominate, these range in size from less than 0.1 ha to more than 10,000 ha, and from hand hoe use to machine-based cultivation, enabling one person to plant more than 500 ha in a day. Yet, farming in different parts of the world is highly interdependent, not least because prices paid for farm produce are largely determined by global markets. Furthermore, the economic viability of farming is a problem, globally. We highlight trends in major regions of the world and explore possible trajectories for the future and ask: Who are the farmers of the future? Changing patterns of land ownership, rental and exchange mean that the concept of ‘what is a farm’ becomes increasingly fluid. Next to declining employment and rural depopulation, we also foresee more environmentally-friendly, less external input dependent, regionalised production systems. This may require the reversal of a global trend towards increasing specialisation to a recoupling of arable and livestock farming, not least for the resilience it provides. It might also require a slow-down or reversal of the widespread trend of scale enlargement in agriculture. Next to this trend of scale enlargement, small farms persist in Asia: consolidation of farms proceeds at a snail’s pace in South-east Asia and 70% of farms in India are ‘ultra-small’ – less than 0.05 ha. Also in Africa, where we find smallholder farms are much smaller than often assumed (< 1 ha), farming households are often food insecure. A raft of pro-poor policies and investments are needed to stimulate small-scale agriculture as part of a broader focus on rural development to address persistent poverty and hunger. Smallholder farms will remain an important source of food and income, and a social safety net in absence of alternative livelihood security. But with limited possibilities for smallholders to ‘step-up’, the agricultural engine of growth appears to be broken. Smallholder agriculture cannot deliver the rate of economic growth currently assumed by many policy initiatives in Africa.

Yield improvement for smallholder farmers in developing countries via crop breeding has been slow, in part because breeders have focused primarily on higher yields rather than stability of yield across environments. We investigated the relationships between (i) grain yield and yield-component traits, (ii) grain yield and yield stability, and (iii) reproductive (R) and vegetative (V) biomass in a field experiment with 18 spring wheat genotypes varying from landraces to recently-released breeding lines in a semiarid region under three different levels of precipitation. Genotypic differences in grain yield varied with the environment. The relationship between grain yield and yield components was also dependent on the environment, making it difficult to identify early-screening parameters for use in breeding programs. A genotype main effects and genotype by environment interaction effect analysis (GGE) showed a negative relationship between mean grain yield and yield stability across environments. There were significant differences among genotypes in the allometric exponent of the R-V relationship (slope of the log R – log V relationship). For the three highest yielding but less stable genotypes, this slope value was > 1, while the five lowest yielding, but more stable genotypes, it was < 1. We hypothesize that the tradeoff between grain yield and yield stability reported here is biologically constrained and cannot be eliminated through breeding. Therefore, a balance between yield stability and high yield should be considered in future wheat breeding programs for smallholder farmers, rather than attempting to improve both.

Agricultural production in Ghana should more than double to fulfil the estimated food demand in 2050, but this is a challenge as the productivity of food crops has been low, extremely variable and prone to stagnation. Yield gap estimations and explanations can help to identify the potential for intensification on existing agricultural land. However, to date most yield gap analyses had a disciplinary focus. The objective of this paper is to assess the impact of crop management, soil and household factors on maize (Zea mays) yields in two major maize growing regions in Ghana through an integrated approach. We applied a variety of complementary methods to study sites in the Brong Ahafo and Northern region. Farm household surveys, yield measurements and soil sampling were undertaken in 2015 and 2016. Water-limited potential yield (Yw) was estimated with a crop growth simulation model, and two different on-farm demonstration experiments were carried out in 2016 and 2017. There is great potential to increase maize yields across the study sites. Estimated yield gaps ranged between 3.8 Mg ha−1 (67% of Yw) and 13.6 Mg ha−1 (84% of Yw). However, there was no consistency in factors affecting maize yield and yield gaps when using complementary methods. Demonstration experiments showed the potential of improved varieties, fertilizers and improved planting densities, with yields up to 9 Mg ha−1. This was not confirmed in the analysis of the household surveys, as the large yield variation across years on the same farms impeded the disclosure of effects of management, soil and household factors. The low-input nature of the farming system and the incidence of fall armyworm led to relatively uniform and low yields across the entire population. So, farmers’ yields were determined by interacting, and strongly varying, household, soil and management factors. We found that for highly variable and complex smallholder farming systems there is a danger in drawing oversimplified conclusions based on results from a single methodological approach. Integrating household surveys, crop growth simulation modelling and demonstration experiments can add value to yield gap analysis. However, the challenge remains to improve upon this type of integrated assessment to be able to satisfactorily disentangle the interacting factors that can be managed by farmers in order to increase crop yields.

Food security in Sub-Saharan Africa, particularly in semi-arid tropics (41% of the region; 6 months of dry season) is threatened by droughts, dry spells and infertile soils. In Zimbabwe, 74% of smallholder farming areas are located in semi-arid areas mostly in areas with soils of low fertility and water holding capacity. The dominant crop in these areas, maize (Zea mays L.), is susceptible to drought. Under smallholder farming in Zimbabwe, conventional tillage entails cutting and turning the soil with a mouldboard plough thereby burying weeds and crop residues. Seed is planted by hand into a furrow made by the plough, ensuring that crops germinate in relatively weed free seedbeds. Inter-row weed control is performed using the plough or ox-drawn cultivators and hand hoes. Conventional tillage has been criticised for failure to alleviate negative effects of long dry spells on crops and to combat soil loss caused by water erosion estimated at 50 to 80 t ha-1 yr-1. Therefore, conservation tillage has been explored for improving soil and water conservation and crop yields. Our objective was to determine the maize yield advantage of the introduced technology (conservation tillage) over conventional tillage (farmers’ practice) based on a review of experiments in semi-arid Zimbabwe. We use a broad definition of conservation tillage instead of the common definition of =30% cover after planting. Eight tillage experiments conducted between 1984 and 2008 were evaluated. Conventional tillage included ploughing using the mouldboard plough and digging using a hand hoe. Conservation tillage included tied ridging (furrow diking), mulch ripping, clean ripping and planting pits. Field-edge methods included bench terraces (fanya juus) and infiltration pits. Results showed small yield advantages of conservation tillage methods below 500 mm rainfall. For grain yields =2.5 t ha-1 and rainfall =500 mm, 1.0 m tied ridging produced 144 kg ha-1 and mulch ripping 344 kg ha-1 more than conventional tillage. Above 2.5 t ha-1 and for rainfall >500 mm, conventional tillage had =640 kg ha-1 yield advantage. Planting pits had similar performance to ripping and conventional tillage but faced digging labour constraints. Experiments and modelling are required to test conservation tillage seasonal rainfall thresholds. Constraints to adoption of conservation tillage by smallholder farmers necessitate best agronomic practices under conventional tillage while work on adoption of alternative tillage methods continues.

Global food production strongly depends on availability of nutrients. Assessment of future global phosphorus (P) fertilizer demand in interaction with nitrogen (N) and potassium (K) fertilizers under different levels of food demand requires a model-based approach. In this paper we tested use of the QUEFTS model (Quantitative Evaluation of Fertility of Tropical Soils) for assessing crop yields in response to N, P and K application in different environments. QUEFTS was initially developed to simulate interactions between N, P and K for tropical soils under maize crop. We performed an extensive model analysis of crop yields in relation to soil and fertilizer nutrients for six field data sets with maize, rice, and wheat crops grown in tropical and temperate regions. The model equations had to be adapted to broaden the model applicability beyond the original boundary conditions of pH, rain-fed cropping systems, optimum harvest index and temperature. Recalibration and modification resulted in a good agreement between model predicted and observed yields. Our results indicate that the adjustments increased the applicability of the model. However, for application in global studies QUEFTS is data demanding and, also, further testing (and probably improvement) is needed, since various processes (e.g. inputs of other nutrients than N, P and K, sub-soil properties and water supply) are ignored in the model, but may differ dramatically across the globe.

Crop-livestock farming systems that are predominant in Africa, are complex with various interrelated ecological and economic factors. They involve multiple products or benefits (intended and nonintended), with trade-offs and synergies occurring both on- and off-site and varying over time. Understanding both simplistic relationships and complex interactions between climate and agricultural production systems to determine overall system efficiency and impacts on human well-being is a major challenge. Computer-based tools coupled with participatory approaches for systems integrated assessments have the potential to resolve multiple dimensions of these complex systems. The products of these environmental, economic, and social analyses are important in the development of climate smart adaptation strategies. To reduce burdening the environment and contributing to resilience and sustained production capacity, highly efficient technologies are required. Although some advances have been made in technology generation, their assessment for delivery of crop-livestock systems has lagged behind. This chapter describes approaches that couple participatory methods with computer-based decision supporting tools to achieve an integrated assessment of crop-livestock systems in relation to climate change. Simulation results show that climate change will have an impact on crop-livestock production systems hence smallholder farmers' well-being will also affected. However, impacts will be varied, the three farm categories studied for Nkayi district will not be affected to the same degree due to agricultural management practices and wealth status. Tailoring adaptation packages to different farm categories can assist in developing context-specific technologies to buffer the impacts of climate change. Improved on-farm high-quality fodder production (inclusion of fodder and grain legume) and growing medium duration maize varieties would offset impacts of climate change by about 20%-30% for farmers with livestock. For those farmers without livestock (

Despite continuing economic growth, Uganda faces persistent challenges to achieve food security. The effectiveness of policy and development strategies to help rural households achieve food security must improve. We present a novel approach to relate spatial patterns of food security to livelihood strategies, including the contribution of on- and off-farm activities to household food availability. Data from 1927 households from the World Bank Living Standards Measurement Study were used to estimate the calorific contribution of livelihood activities to food availability. Consumption of crops produced on-farm contributed most to food availability for households with limited food availability, yet the majority of these households were not food self-sufficient. Off-farm and market-oriented on-farm activities were more important for households with greater food availability. Overall, off-farm income was important in the north, while market-oriented on-farm activities were important in western and central Uganda. Food availability patterns largely matched patterns of agroecological conditions and market access, with households doing worst in Uganda’s drier and remote northeast. Less food-secure households depended more on short-cycle food crops as compared with better-off households, who focused more on plantation (cash) crops, although this varied among regions. Targeting interventions to improve food security should consider such differences in enterprise choice and include options to improve household market access and off-farm income opportunities.

African 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’ technologies – technologies 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 best-fit technologies and the ways they can be best combined at farm level. The dynamic and integrated nature of the framework allows the impact of changes in external drivers such as climate change or development policy to be analysed. Fundamental questions for integrated analysis relate to the site-specific knowledge and the simplification of processes required to integrate and move from one level to the next. Keywords: Crop–livestock systems; Soil fertility; Smallholders; Farm types; Simulation modelling

Crop residues are important for livestock feed and nutrient cycling among many other functions on smallholder farming systems of sub-Saharan Africa. The objective of this study was to assess differences in resource endowment, crop productivity and crop residue management in selected sites in southern Africa. Three sites were selected along a gradient of intensification of crop production; Murehwa, Zimbabwe and Ruaca and Gorongosa, central Mozambique. Murehwa and Ruaca have mixed crop-livestock systems with more intensive crop production in Murehwa. Gorongosa is predominantly crop based with small livestock that do not impact on crop production. A combination of land size and cattle ownership was the major attribute that defined wealth status among farmers in mixed crop-livestock systems whereas land size and labor availability were important under crop-based extensification systems. Farm systems were more diverse where livestock was more important. The wealthiest farmers (resource group-RG1) in Murehwa produced an average of 2.2 t ha-1 maize crop residues, and productivity decreased with decrease in resource ownership with the poorest (RG4) achieving only 0.8 t ha-1. In Ruaca 1.3 and 0.5 t ha-1 was produced by RG1 and RG4 respectively, whereas in Gorongosa 0.4 and 0.2 t ha-1 was produced by RG1 and RG4. These crop residues are insufficient to achieve the minimum threshold of soil cover (30%) required for the practice of conservation agriculture. However, they can provide sufficient feed to sustain livestock of RG1 farmers in Murehwa for 63 days and 54 days for RG2 farmers. In Ruaca, they can feed cattle for 37 days for RG1 and 17 days for RG2 farmers. The product of livestock × population density determined the extent and manner in which crop residues are used. The population density limited the extent of the grazing area, increased grazing frequency and reduced the grazing quality leading to the need to supplement animal feed with crop residues. Farmers preferentially allocate crop residues to livestock where labor is available. The crop residues fed to animals allow farmers to increase manure quantity and quality which explains the major differences in crop productivity between the different resource groups. In the absence of cattle, crop residues are burned before the cropping season to facilitate land clearance. In conclusion, land size, cattle ownership and labor availability largely define the intensity of crop production and the fate of crop residues on smallholder farms in southern Africa.

Legume technologies are widely promoted among smallholders in southern Africa, providing an opportunity for sustainable intensification. Farms and farming strategies of smallholders differ greatly within any given locality and determine the opportunities for uptake of technologies. We provide an ex-ante assessment of the impact of grain legumes on different types of farms and identify niches for grain legumes in Malawi. After creation of a farm typology, detailed farm characterisations were used to describe the farming system. The characterisations provided the basis for the construction of simplified, virtual farms on which possible scenarios for expanding and intensifying grain legume production were explored using the farm-scale simulation model NUANCES-FARMSIM. Observed yields and labour inputs suggested that maize provides more edible yield per unit area with a higher calorific value and greater labour use efficiency than groundnut and soybean. Crop yields simulated by the model partly confirmed these yield trends, but at farm level maize-dominated systems often produced less food than systems with more grain legumes. Improved management practices such as addition of P-based fertiliser to grain legumes and inoculation of soybean were crucial to increase biological nitrogen fixation and grain yields of legumes and maize, and created systems with increased area of legumes that were more productive than the current farms. Improved legume management was especially a necessity for low resource endowed farmers who, due to little past use of P-based fertiliser and organic inputs, have soils with a poorer P status than wealthier farmers. Economic analyses suggested that legume cultivation was considerably more profitable than continuous maize cropping. Highest potential net benefits were achieved with tobacco, but the required financial investment made tobacco cultivation riskier. Grain legumes have excellent potential as food and cash crops particularly for medium and high resource endowed farmers, a role that could grow in importance as legume markets further develop. For low resource endowed farmers, legumes can improve food self-sufficiency of households, but only if legumes can be managed with P fertiliser and inoculation in the case of soybean. Given that low resource endowed farmers tend to be risk averse and have few resources to invest, the ability of poorer farmers to adopt legume technologies could be limited.

Aiming to translate resilience thinking theory into farming systems design practice, this paper examines fundamental properties of complex systems dynamics and their relation with the mechanisms that govern resilience and transformability in African smallholder agriculture. Agroecosystems dynamics emerge from the aggregation of diverse livelihood strategies in response to changes in the agroecosystem context, and are characterised by non-linearity, irreversibility, convergence/divergence and hysteresis. I examine a number of case studies from Africa to verify three guiding hypotheses in connection to the diversity of rural livelihood strategies: (1) diversity as alternative system regimes; (2) diversity as the result of transformability; (3) diversity determined by changing agricultural contexts. The hierarchy of constraints that determine the space for manoeuvring in agroecosystems is described through the analogy of the Matryoshka nesting dolls: each system level confines and is confined by their immediate sub- and supra-systems. Agricultural contexts, as defined by agro-ecological potential, demography and market connectivity are also dynamic and their trajectory can be described as shifts across stability domains. An example from Kenya shows that household diversity can be described as alternative system regimes, through hysteretic rather than continuous, reversible models. In some particular cases diversity emerges from divergent pathways that may have implied radical transformations in the past, as shown here for rural livelihoods in northern Cameroun. A comparative analysis of East African agroecosystems shows that thresholds in specific variables that may point to the existence of possible tipping points are rather elusive and largely site specific, requiring systematic categorisation of agricultural contexts. While agroecology needs to provide the knowledge base for the ecological intensification of smallholder landscapes, policy and market developments are needed to deal with the Matryoshka effect – or with interactions that are presumably panarchical in certain cases. Desirable shifts in farming systems can only be stimulated by working on both ends simultaneously.

This paper examines a number of agronomic field experiments in different regions of sub-Saharan Africa to assess the associated variability in the efficiencies with which applied and available nutrients are taken up by crops under a wide range of management and environmental conditions. We consider N and P capture efficiencies (NCE and PCE, kg uptake kg-1 nutrient availability), and N and P recovery efficiencies (NRE and PRE, kg uptake kg-1 nutrient added). The analyzed cropping systems employed different soil fertility management practices that included (1) N and P mineral fertilizers (as sole or their combinations) (2) cattle manure composted then applied or applied directly to fields through animal corralling, and legume based systems separated into (3) improved fallows/cover cropscereal sequences, and (4) grain legume-cereal rotations. Crop responses to added nutrients varied widely, which is a logical consequence of the wide diversity in the balance of production resources across regions from arid through wet tropics, coupled with an equally large array of management practices and inter-season variability. The NCE ranged from 0.05 to 0.98 kg kg-1 for the different systems (NP fertilizers, 0.16-0.98; fallow/cover crops, 0.05-0.75; animal manure, 0.10-0.74 kg kg-1), while PCE ranged from 0.09 to 0.71 kg kg-1, depending on soil conditions. The respective NREs averaged 0.38, 0.23 and 0.25 kg kg-1. Cases were found where NREs were[1 for mineral fertilizers or negative when poor quality manure immobilized soil N, while response to P was in many cases poor due to P fixation by soils. Other than good agronomy, it was apparent that flexible systems of fertilization that vary N input according to the current seasonal rainfall pattern offer opportunities for high resource capture and recovery efficiencies in semi-arid areas. We suggest the use of cropping systems modeling approaches to hasten the understanding of Africa's complex cropping systems. (Resume d'auteur)

Traditional farming systems in Sub-Saharan Africa depend primarily on mining soil nutrients. The African green revolution aims to intensify agriculture through the dissemination of integrated soil fertility management (ISFM). This paper develops a robust and operational definition of ISFM based on detailed knowledge of African farming systems and their inherent variability and of the optimal use of nutrients. The authors define ISFM as a set of soil fertility management practices that necessarily include the use of fertilizer, organic inputs and improved germplasm, combined with the knowledge on how to adapt these practices to local conditions, aimed at maximizing agronomic use efficiency of the applied nutrients and improving crop productivity. All inputs need to be managed in accordance with sound agronomic principles. The integration of ISFM practices into farming systems is illustrated with the dual-purpose grain legume–maize rotations in the savannas and fertilizer micro-dosing in the Sahel. Finally, the dissemination of ISFM practices is discussed.

Variability of soil fertility within, and across farms, poses a major challenge for increasing crop productivity in smallholder systems of sub- Saharan Africa. This study assessed the effect of farmers' resource endowment and nutrient manage- ment strategies on variability in soil fertility and plant nutrient uptake between different fields in Gokwe South (ave. rainfall *650 mm year -1 ; 16.3 per- sons km -2 ) and Murewa (ave. rainfall *850 mm year -1 ; 44.1 persons km -2 ) districts, Zimbabwe. In Murewa, resource-endowed farmers applied manure ((3.5 t ha -1 year -1 ) on fields closest to their home- steads (homefields) and none to fields further away (outfields). In Gokwe the manure was not targeted to any particular field, and farmers quickly abandoned outfields and opened up new fields further way from the homestead once fertility had declined, but homefields were continually cultivated. Soil available P was higher in homefields (8-13 mg kg -1 ) of resource-endowed farmers than on outfields and all fields on resource constrained farms (2-6 mg kg -1 ) in Murewa. Soil fertility decreased with increasing distance from the homestead in Murewa while the reverse trend occurred in Gokwe South, indicating the impact of different soil fertility management strategies on spatial soil fertility gradients. In both districts, maize showed deficiency of N and P, implying that these were the most limiting nutrients. It was concluded that besides farmers' access to resources, the direction of soil fertility gradients also depends on agro-ecological conditions which influence resource management strategies.

SAD CT1 ridaura@supagro.inra.fr Nutrient Cycling in Agroecosystems: formerly Fertilizer Research ; FI 2008 1.282; International audience; Smallholder farming systems in sub-Saharan Africa are often nutrient-limited, and therefore imports must be increased to compensate exports and losses. To explore whether the properties of nutrient cycling networks relate to the systems'capability to sustain rural families, we investigated N flows within contrasting crop-livestock systems in Ethiopia, Kenya and Zimbabwe applying concepts from ecological network analysis. Farm households were conceptualised as networks, the compartments were the household and their farming activities which were connected by the N flows. Indicators assessing network size, activity and cycling, and the organisation and diversity of the N flows were compared with system productivity and food self-sufficiency. Results showed that organisation and diversity of N flows to, from and within the farm households differed more between farms of different resource endowments than across sites. The amount of N cycled per household was small and comparable across sites: less than 25 kg N year-1, and for the poor households less than 5 kg N year-1. Poor households with soil N stocks that were 50-60% smaller than wealthier households depended more on external inputs (e.g. a dependence of 65% vs. 45% in Zimbabwe). Productivity was positively related to network size, its organisation and N cycling, but utilisation efficiencies were different across sites in relation to soil N stock and the importance of livestock for N flows. Greater size of the N flow network and its organisation led to increased productivity and food self-sufficiency, reducing dependence, which may increase the adaptability and reliability of smallholder crop-livestock systems.

The productivity and residual benefits of four grain legumes to sorghum (Sorghum bicolor) grown in rotation were measured under semi-arid conditions over three cropping seasons. Two varieties of each of the grain legumes; cowpea (Vigna unguiculata); groundnut (Arachis hypogaea); pigeon pea (Cajanus cajan); Bambara groundnut (Vigna subterranea), and sorghum were grown during the first season. The same experiment was implemented three times in different, but adjacent fields that had similar soil types. At the end of the season the original plots were split in two and residues were either removed or incorporated into the subplots. The following season sorghum was planted in all subplots. In 2002/03 (314 mm rainfall) cowpeas produced the largest dry grain yield (0.98 and 1.36 t ha¿1) among the legumes. During the wettest year (2003/04, 650 mm rainfall) groundnut had the highest yields (0.76 to 1.02 t ha¿1). In 2004/05 (301 mm rainfall) most legume yields were less than 0.5 t ha¿1, except for pigeon pea. Estimates of % N from N2-fixation from the legumes were 15¿50% (2002/03), 16¿61% (2003/04) and 29¿83% (2004/05). Soil water changes during the legume growth cycle were proportional to varietal differences in total legume biomass. Sorghum grain yield after legumes reached up to 1.62 t ha¿1 in 2003/04 compared with 0.42 t ha¿1 when following sorghum. In 2004/05, sorghum yields after legumes were also higher (up to 1.26 t ha¿1) than sorghum after sorghum. Incorporation of crop residues had no significant effect on sorghum yield. Beneficial effect of legumes on yields of the subsequent sorghum crop were more readily explained by improvements in soil nitrogen supply than by the small observed changes in soil water relations. Our results demonstrate clear potential benefits for increasing grain legume cultivation in semi-arid environments through the use of improved germplasm, which also gave substantial increases in subsequent sorghum productivity (up 200% in a wet season and 30¿100% in a dry season), compared with an unfertilized sorghum crop following sorghum.

Corresponding author at: Tropical Soil Biology and Fertility Institute of the International Centre for Tropical Agriculture (TSBF-CIAT), P.O. Box 30677, Nairobi, Kenya.; fax: +254 20 524763; International audience; The spatial variability in crop yields commonly observed in smallholder farms of sub-Saharan Africa is often caused by gradients of declining soil fertility with increasing distance from the homestead. This heterogeneity means that recommendations based on regional soil surveys are of limited value. The variability in soil qualities within farms must be considered when designing management strategies, and their feasibility analysed by integrating results at the farm livelihood scale. For this purpose, we have developed the model FARMSIM, a dynamic bio-economic model for analysis and exploration of trade-offs in resource and labour allocation in heterogeneous smallholder farms. Focusing on farm-scale strategies, the approach to simulation of soil and crop processes in EARMSIM (the sub-model FIELD) is designed to be simple, but to keep the necessary degree of complexity to capture heterogeneity in resource use efficiencies. To test our approach, the sub-model FIELD was calibrated against chronosequences of woodland clearance in three agroccological zones of Zimbabwe (with soil textures of 3, 10, 35% clay), and used to simulate: (i) the creation of soil fertility gradients, and (ii) different strategies of N, P and manure applications to maize and soyabean rotations in homefields and outfields of smallholder farms on clayey and sandy soils. The results of the simulation of managernent strategies were tested against on-farm experimental data from Murewa, Zimbabwe. The model produced satisfactory predictions (r(2) : 0.6-0.9) of long-term changes in soil organic C, of crop responses to N and P and of nutrient use efficiencies across a wide range of yields and different field types. This demonstrated the broad applicability of the model despite the sparse data required for initialisation. However, the model results were less accurate in predicting crop responses to N and P applications in the outfields on sandy soils. Experimental evidence indicated yield limitation by Ca and Zn deficiencies in highly depleted outfields on sandy soils, which were not included mechanistically in the current version of FIELD. Repeated applications of 16 t ha(-1) year(-1) of manure allowed larger responses to applied N and P after 3 years of experimentation; such a corrective effect of manure was simulated to be due to improved N and P recovery efficiencies in the model. In combination with the experimental data, the simulation results suggested that soil fertility gradients affect nutrient use efficiencies, operating mostly on the efficiencies of nutrient capture rather than conversion. A typology of fields according to the type of management interventions needed is introduced, based on a generic application of FIELD with this parameterisation

Information on fertilizer response in cassava in Africa is scarce. We conducted a series of on-farm and on-station trials in two consecutive years to quantify yield responses of cassava to mineral fertilizer in Kenya and Uganda and to evaluate factors governing the responses. Average unfertilized yields ranged from 4.2 to 25.7 t ha-1 between sites and years. Mineral fertilizer use increased yields significantly, but response to fertilizer was highly variable (- 0.2 to 15.3 t ha-1). Average yield response per kg applied nutrient was 37, 168 and 45 and 106, 482 and 128 kg fresh yield per kg of applied N, P and K, respectively in 2004 and 2005. Fertilizer response was governed by soil fertility, rainfall and weed management, but was not influenced by variety, pest and disease pressure and harvest age. Relative N and K yields were positively correlated to SOC and exchangeable K, while response to fertilizer decreased on more fertile soils. Still, fertilizer response varied widely on low fertility soils (e.g. on soils with