Which options fit best? Operationalizing the socio-ecological niche concept

Article Purchased; Published: 1st August 2016The large diversity of farms and farming systems in sub-Saharan Africa calls for agricultural improvement options that are adapted to the context in which smallholder farmers operate. The socio-ecological niche concept incorporates the agro-ecological, socio-cultural, economic and institutional dimensions and the multiple levels of this context in order to identify which options fit best. In this paper, we illustrate how farming systems analysis, following the DEED cycle of Describe, Explain, Explore and Design, and embedding co-learning amongst researchers, farmers and other stakeholders, helps to operationalize the socio-ecological niche concept. Examples illustrate how farm typologies, detailed farm characterization and on-farm experimental work, in combination with modelling and participatory approaches inform the matching of options to the context at regional, village, farm and field level. Recommendation domains at these gradually finer levels form the basis for gradually more detailed baskets of options from which farmers and other stakeholders may choose, test and adjust to their specific needs. Tailored options identified through the DEED cycle proof to be more relevant, feasible and performant as compared to blanket recommendations in terms of both researcher and farmer-identified criteria. As part of DEED, on-farm experiments are particularly useful in revealing constraints and risks faced by farmers. We show that targeting options to the niches in which they perform best, helps to reduce this risk. Whereas the conclusions of our work about the potential for improving smallholders’ livelihoods are often sobering, farming systems analysis allows substantiating the limitations of technological options, thus highlighting the need for enabling policies and institutions that may improve the larger-scale context and increase the uptake potential of options

The input reduction principle of agroecology is wrong when it comes to mineral fertilizer use in sub-Saharan Africa

Can farmers in sub-Saharan Africa (SSA) boost crop yields and improve food availability without using more mineral fertilizer? This question has been at the center of lively debates among the civil society, policy-makers, and in academic editorials. Proponents of the “yes” answer have put forward the “input reduction” principle of agroecology, i.e. by relying on agrobiodiversity, recycling and better efficiency, agroecological practices such as the use of legumes and manure can increase crop productivity without the need for more mineral fertilizer. We reviewed decades of scientific literature on nutrient balances in SSA, biological nitrogen fixation of tropical legumes, manure production and use in smallholder farming systems, and the environmental impact of mineral fertilizer. Our analyses show that more mineral fertilizer is needed in SSA for five reasons: (i) the starting point in SSA is that agricultural production is “agroecological” by default, that is, very low mineral fertilizer use, widespread mixed crop-livestock systems and large crop diversity including legumes, but leading to poor soil fertility as a result of widespread soil nutrient mining, (ii) the nitrogen needs of crops cannot be adequately met solely through biological nitrogen fixation by legumes and recycling of animal manure, (iii) other nutrients like phosphorus and potassium need to be replaced continuously, (iv) mineral fertilizers, if used appropriately, cause little harm to the environment, and (v) reducing the use of mineral fertilizers would hamper productivity gains and contribute indirectly to agricultural expansion and to deforestation. Yet, the agroecological principles directly related to soil fertility—recycling, efficiency, diversity—remain key in improving soil health and nutrient-use efficiency, and are critical to sustaining crop productivity in the long run. We argue for a nuanced position that acknowledges the critical need for more mineral fertilizers in SSA, in combination with the use of agroecological practices and adequate policy support

Trajectories of agricultural change in southern Mali

Key words: longitudinal study, farm typology, food self-sufficiency, income, legumes, ex-ante analysis, participatory research, scenario. Smallholder agriculture in sub-Saharan Africa provides basis of rural livelihoods and food security, yet farmers have to cope with land constraints, variable rainfall and unstable institutional support. This study integrates a diversity of approaches (household typology and understanding of farm trajectories, on-farm trials, participatory ex-ante trade-off analysis) to design innovative farming systems to confront these challenges. We explored farm trajectories during two decades (1994 to 2010) in the Koutiala district in southern Mali, an area experiencing the land constraints that exert pressure in many other parts of sub-Saharan Africa. We classified farms into four types differing in land and labour productivity and food self-sufficiency status. During the past two decades, 17% of the farms stepped up to a farm type with greater productivity, while 70% of the farms remained in the same type, and only 13% of the farms experienced deteriorating farming conditions. Crop yields did not change significantly over time for any farm type and labour productivity decreased. Together with 132 farmers in the Koutiala district, we tested a range of options for sustainable intensification, including intensification of cereal (maize and sorghum) and legume (groundnut, soyabean and cowpea) sole crops and cereal-legume intercropping over three years and cropping seasons (2012-2014) through on-farm trials. Experiments were located across three soil types that farmers identified – namely black, sandy and gravelly soils. Enhanced agronomic performance was achieved when targeting legumes to a given soil type and/or place in the rotation: the biomass production of the cowpea fodder variety was doubled on black soils compared with gravelly soils and the additive maize/cowpea intercropping option after cotton or maize resulted in no maize grain penalty, and 1.38 t ha−1 more cowpea fodder production compared with sole maize. Farm systems were re-designed together with the farmers involved in the trials. A cyclical learning model combining the on-farm testing and participatory ex-ante analysis was used during four years (2012-2015). In the first cycle of 2012-2014, farmers were disappointed by the results of the ex-ante trade-off analysis, i.e marginal improvement in gross margin when replacing sorghum with soybean and food self-sufficiency trade-offs when intercropping maize with cowpea. In a second cycle in 2014-2015 the farm systems were re-designed using the niche-specific (soil type/previous crop combinations) information on yield and gross margin, which solved the concerns voiced by farmers during the first cycle. Farmers highlighted the saliency of the niches and the re-designed farm systems that increased farm gross margin by 9 to 29% (depending on farm type and options considered) without compromising food self-sufficiency. The involvement of farmers in the co-learning cycles allowed establishment of legitimate, credible and salient farm reconfiguration guidelines that could be scaled-out to other communities within the “old cotton basin”. Five medium-term contrasting socio-economic scenarios were built towards the year 2027, including hypothetical trends in policy interventions and change towards agricultural intensification. A simulation framework was built to account for household demographic dynamics and crop/livestock production variability. In the current situation, 45% of the 99 households of the study village were food self-sufficient and above the 1.25 US$ day-1 poverty line. Without change in farmer practices and additional policy intervention, only 16% of the farms would be both food self-sufficient and above the poverty line in 2027. In the case of diversification with legumes combined with intensification of livestock production and support to the milk sector, 27% of farms would be food self-sufficient and above the poverty line. Additional broader policy interventions to favour out-migration would be needed to lift 69% of the farms out of poverty. Other additional subsidies to favour yield gap narrowing of the main crops would lift 92% of the farm population out of poverty. Whilst sustainable intensification of farming clearly has a key role to play in ensuring food self-sufficiency, and is of great interest to local farmers, in the face of increasing population pressure other approaches are required to address rural poverty. These require strategic and multi-sectoral approaches that address employment within and beyond agriculture, in both rural and urban areas. </p

Unravelling the causes of variability in crop yields and treatment responses for better tailoring of options for sustainable intensification in southern Mali

Options that contribute to sustainable intensification offer an avenue to improve crop yields and farmers' livelihoods. However, insufficient knowledge on the performance of various options in the context of smallholder farm systems impedes local adaptation and adoption. Therefore, together with farmers in southern Mali we tested a range of options for sustainable intensification including intensification of cereal (maize and sorghum) and legume (groundnut, soyabean and cowpea) sole crops and cereal-legume intercropping during three years on on-farm trials. There was huge variability among fields in crop yields of unamended control plots: maize yielded from 0.20 to 5.24tha-1, sorghum from 0 to 3.53tha-1, groundnut from 0.10 to 1.16tha-1, soyabean from 0 to 2.48tha-1 and cowpea from 0 to 1.02tha-1. This variability was partly explained by (i) soil type and water holding capacity, (ii) previous crop, its management and the nutrient carry-over and (iii) inter-annual weather variability. Farmers recognized three soil types: gravelly soils, sandy soils and black soils. Yields were very poor on gravelly soils and two to three times greater (depending on the crop) on black soils. Yields were also poor at the end of the typical crop rotation, i.e., after sorghum and millet, and 1.3-1.7 times greater (depending on the crop) after the fertilized crops maize and cotton. We diagnosed a number of cases of technology failure where no improvement in yield was observed with hybrid varieties of maize and sorghum and rhizobial inoculation of soyabean. Regardless of soil type and previous crop, mineral fertilizer improved yields by 34-126% depending on the crop. Targeting options to a given soil type and/or place in the rotation enhanced their agronomic performance: (i) the biomass production of the cowpea fodder variety was doubled on black soils compared with gravelly soils, (ii) the additive maize/cowpea intercropping option after cotton or maize resulted in an average overall LER of 1.47, no maize grain penalty, and 1.38tha-1 more cowpea fodder production compared with sole maize. Soil type and position in the rotation, two indicators easy to assess by farmers and extension workers, allowed the identification of specific niches for enhanced agronomic performance of legume sole cropping and/or intercropping

Understanding farm trajectories and development pathways: Two decades of change in southern Mali

Institutional support for smallholders has been the motor for the expanding cotton production sector in southern Mali since the 1970s. Smallholder farms exhibit diverse resource endowments and little is known on how they benefit from and cope with changes in this institutional support. In this paper we explore farm trajectories during two decades (1994 to 2010) and their link with farm resource endowment and government support. We distinguished a favourable period for cotton production and an unfavourable period during which institutional support collapsed. A panel survey that monitored 30 farms in the Koutiala district in southern Mali over this period was analysed. Based on indicators of resource endowment and using Ascending Hierarchical Classification (AHC), farms were grouped into four types: High Resource Endowed farms with Large Herds (HRE-LH), High Resource Endowed (HRE) farms, Medium Resource Endowed (MRE) farms and Low Resource Endowed (LRE) farms. Average yield, labour productivity and food self-sufficiency status of each type were calculated. Farms remaining in the same type were classified as ‘hanging in’, while farms moving to a type of higher yields, labour productivity and food self-sufficiency status were classified as ‘stepping up’, and farms following the opposite trajectory of deteriorating farming conditions were classified as ‘falling down’. The LRE farms differed from all other farm types due to lower yields, while both LRE and HRE farms differed from the MRE and HRE-LH farm types due to a combination of less labour productivity and less food self-sufficiency. During those two decades, 17% of the farms ‘stepped up’, while 70% of the farms remained ‘hanging in’, and only 13% of the farms ‘fell down’. We found no obvious negative impact of the collapse of government support on farm trajectories. For MRE, HRE and HRE-LH farms, average N and P use intensity increased from 1994 to 2004 and then decreased during the following cotton crisis. On the other hand, organic fertilizer use intensity increased continuously over the entire monitoring period for HRE-LH and MRE farms. Crop yields did not change significantly over time for any farm type and labour productivity decreased. We discuss how technical options specific for different farm types (increase in farm equipment, sale of cereals, incorporation of legumes and intensification of milk production) and broader institutional change (improvement in finance system and infrastructure, tariffs) can enhance ‘step up’ trajectories for farming households and avoid stagnation (‘hanging in’) of the whole agricultural sector

Using remote sensing to assess the effect of trees on millet yield in complex parklands of Central Senegal

Agroforestry is pointed out by the Intergovernmental Panel on Climate Change report as a key option to respond to climate change and land degradation while simultaneously improving global food security (IPCC, 2019). Faidherbia albida parklands are widespread in Sub-Saharan Africa and provide several ecosystem services to populations, notably an increase in crop productivity. While remote sensing has been proven useful for crop yield assessment in smallholder farming system, it has so far ignored the woody component. We propose an original approach combining remote sensing, landscape ecology and statistical modelling to i) improve the accuracy of millet yield prediction in parklands and ii) identify the main drivers of millet yield spatial variation. The parkland of Central Senegal was chosen as a case study. Firstly, we calibrated a remote sensing-based linear model that accounted for vegetation productivity and tree density to predict millet yield. Integrating parkland structure improved the accuracy of yield estimation. The best model based on a combination of Green Difference Vegetation Index and number of trees in the field explained 70% of observed yield variability (relative Root Mean Squared Error (RRMSE) of 28%). The best model based solely on vegetation productivity (no information on parkland structure) explained only 46% of the observed variability (RRMSE = 34%). Secondly we investigated the drivers of the spatial variability in estimated yield using Gradient Boosting Machine algorithm (GBM) and biophysical and management factors derived from geospatial data. The GBM model explained 81% of yield spatial variability. Predominant drivers were soil nutrient availability (i.e. soil total nitrogen and total phosphorous) and woody cover in the surrounding landscape of fields. Our results show that millet yield increases with woody cover in the surrounding landscape of fields up to a woody cover of 35%. These findings have to be strengthened by testing the approach in more diversified and/or denser parklands. Our study illustrates that recent advances in earth observations open up new avenues to improve the monitoring of parkland systems in smallholder context

Exploring the agricultural landscape diversity-food security nexus: an analysis in two contrasted parklands of Central Senegal

International audienceCONTEXT: Fostering diversity within agricultural systems can substantially contribute to improved food security among smallholder farmers. Agroforestry parklands are diverse agricultural landscapes where trees can provide an array of ecosystem services. Previous studies analyzing the agricultural landscape diversity-food security nexus in agroforestry parklands have only considered tree cover. OBJECTIVE: We propose an original empirical approach that combines the analysis of spatial data on agricultural landscape diversity with agricultural field monitoring and household surveys. These three sources of data were used to scrutinize the direct and indirect contributions of agricultural landscape diversity to food availability and food access. METHODS: Millet yield was used as a proxy for food availability, and household food access was approximated using the Household Food Insecurity Access Scale (HFIAS) indicator. Two contrasted agroforestry parklands of Central Senegal were chosen as case studies. Firstly, we used a Gradient Boosting Machine (GBM) algorithm to disentangle the relative contribution of landscape diversity, biophysical and crop management variables in explaining millet yield variability. Secondly, we investigated the pathways linking agricultural landscape di-versity to HFIAS using a Correlation Network Analysis (CNA). RESULTS AND CONCLUSIONS: The GBM model explained 77% and 84% of millet yield variability for the two parklands, respectively, with landscape diversity variables accounting for 53% and 47% of relative influence. Among the landscape diversity variables, tree species richness and tree density were the most important ones. Millet yield was positively associated with tree density in the Nioro site until a threshold of 5 trees/ha, and with tree species richness in the two sites. The CNA showed that greater tree cover and larger tree patches were moderately correlated with HFIAS. This suggests that tree species with large crown, as it the case for most fruit bearing tree species in the region, are the main species contributing directly to food access. Agricultural land-scape diversity contributed mainly indirectly to household food access through an "agroecological pathway", i.e. by the provision of ecosystem services regulating and supporting crop production. SIGNIFICANCE: Using an integrated landscape approach relying on up-to-date remote sensing data and recent advances in data analysis methods, our study shows that tree species diversity matters as much as the amount of tree cover for the production of food, and it can contribute to improve food security. We bring a more nuanced picture of the contribution of agricultural landscape diversity to food security suggesting that land management policies supporting food security should consider both tree density and tree species diversity to optimize the co -benefits of trees for the different food security dimensions