The farm-level economics of conservation agriculture for resource-poor farmers
Introduction
In response to concerns about food security, farm profitability, and land degradation in agriculture around the world, a range of practices have been developed and promoted to farmers. In developing countries, much attention has been given to a specific combination of measures packaged under the banner of “Conservation Agriculture” (CA) involving the key components of zero tillage (or at least minimum soil disturbance), retention of crop residues for soil cover (mulching), and rotation (or sometimes intercropping) of cereals with legumes (Kassam et al., 2009), or sometimes with other crops. In 2012 it was estimated that 9% of the world's cropland area was being farmed under CA (Friedrich et al., 2012) with the largest areas being in South America. There has been much more extensive adoption of some of the components but not necessarily within the CA ‘package’. For example, zero tillage (or no-tillage) has been a major success story in several agricultural systems of North America (Fulton, 2010, Horowitz et al., 2010) and Australia (Llewellyn et al., 2012) but not always in association with all other CA components.
The success of these land conservation and soil fertility measures in the countries mentioned above has largely evaded South Asia and Africa. There are certain local success stories, but overall, uptake of CA as a package in these regions has been disappointing (Friedrich et al., 2012, Giller et al., 2009). As noted by Erenstein et al. (2012, p. 181), there are “substantial challenges in terms of targeting, adapting and adopting CA—particularly for smallholders in the (sub)tropics”. The findings of a meta-analysis of field experiments from around the world (Rusinamhodzi et al., 2011) demonstrate the agronomic challenges for broad adoption. Their analysis shows an increase in maize yield over time with CA practices in low rainfall areas, but results are highly dependent on rainfall, soil type and nitrogen fertiliser inputs. For example, one of the key components of CA, mulching, led to reduced yield in most high rainfall situations but was important for success in dry areas. What is clear is that agro-ecological conditions play a major role in determining the benefits of CA and its components. An additional challenge, potentially even more difficult, is the need for socio-economic considerations that favour successful adaptation and adoption (Giller et al., 2011a, Pannell et al., 2006).
Economics may help us to understand and address these challenges. We define economic drivers broadly to include not only returns from production but consideration of the whole-farm management context, constraints on key resources such as labour and capital, risk and uncertainty, interactions between enterprises, and time-related factors, such as interest rates and the urgency of providing for the farm family. Economic drivers at the farm level have been one of the key factors influencing the adoption of CA practices in Australia (D’Emden et al., 2006, D’Emden et al., 2008) and the Americas (Gray et al., 1996) and are highly likely to be influential in determining potential adoption in Africa and South Asia. The statement that farmers often respond to the farm-level economics of CA does not imply that farmers respond in a strictly predictable or rational way. Rather, the economics provide insights into trends and tendencies that are likely to be observed across populations of farmers, and can help assess the potential of practices for wide adoption.
In Africa and South Asia, when the farm-level economics of CA are sufficiently favourable, adoption of specific practices can be rapid and extensive. One example is the adoption by smallholders of zero tillage for wheat in parts of the Indo-Gangetic Plains in northern India (Erenstein et al., 2012). On the other hand, there has been little sustained adoption of CA in Sub-Saharan Africa, with local exceptions in Ghana, Zambia and Tanzania (Giller et al., 2009). This can be viewed as a result of economic benefits not currently being large or obvious enough to overcome other existing barriers to adoption.
We note that our concept of the farm-level economics of CA is broader than commonly considered in many mentions of economics in the CA literature, or indeed in many of the published economic analyses we review below. Farm-level economics is not just about immediate financial gain, but should also include, at least: farming systems complexities (e.g. enterprise interactions); long-term comparisons (consistent with the length of the planning horizon of relevant farmers); and personal preferences (e.g. for or against risk). In the case of resource-poor agriculture, the potential trade-off between ensuring the basic immediate-term needs of smallholder farm households and the promise of future improved productivity needs particular recognition (Affholder et al., 2010). Conclusions on the economics of CA should not be reached without consideration of constraints (e.g. on labour or capital) and the potential for acquiring information and skills.
Economic outcomes of CA are likely to be specific to particular people, places and situations (FAO, 2001, Uri, 1999, Gowing and Palmer, 2008). This is due to heterogeneity between regions (e.g. Erenstein et al., 2012, p. 186) and between farms in a region (Tittonell et al., 2005), and heterogeneity in institutional factors (Stonehouse, 1996), farm sizes, risk attitudes, interest rates, access to markets (for inputs and outputs), farming systems, resource endowments, and farm management skills, driving differences in benefits and costs of CA.
Heterogeneity may also operate within a farm where soil types may result in farmers choosing to adopt CA on some parts of their farm but not others (e.g. Baudron et al., 2012) and different cropping systems suiting some crops and not others (e.g. Erkossa et al., 2006). There may also be heterogeneity in how adoption proceeds. In some cases it may involve step-wise adoption, starting with the component of a ‘package’ that provides the best returns to the farmer's limiting resources (Byerlee and Hesse De Polanco, 1986) rather than adoption of the full CA package. As a result, the component that is adopted first can vary depending on the situation (Mazvimavi and Twomlow (2009). Chiputwa et al. (2011) found that in a study of CA use by Zimbabwean farmers only 20% had adopted all components of CA and that adoption of each component was affected by a distinct set of factors. CA systems can also diverge through local adaptation to suit farmers’ own personal circumstances or preferences (Giller et al., 2011b, Erenstein, 2002).
Reviewing a large number of studies of CA adoption, Knowler and Bradshaw (2007) concluded that the adoption process for CA is highly heterogeneous, and that “there are few if any universal variables that regularly explain the adoption of conservation agriculture across past analyses”. In reference to the plethora of individual specific variables that have been related to adoption (e.g. proportion of land devoted to row crops, expenditure on fertilizer, length of growing season), this is not surprising. However, the great majority of factors that have been found to be statistically significant explanators of extensive CA adoption relate one way or another to the farm-level economics of CA; they generally relate to the benefits, costs or risks of CA, the farm's human, financial or land resources, or the farmers’ risk and time preferences. The study also highlights social capital as being widely relevant in CA adoption. All this means that it is necessary to consider site-specific conditions in determining the financial attractiveness of CA (FAO, 2001) and efforts to promote CA should be targeted to those regions and situations where there is confidence that it generates sufficient benefits to outweigh the costs and the risks. Thus, not just CA itself, but CA extension efforts need to be tailored to reflect the particular conditions of individual locales (Knowler and Bradshaw, 2007).
The aim of this paper is to help understand the farm-level economics of CA in smallholder agriculture, typified by those of Africa and South Asia. There are important differences between agriculture in these two regions, with South Asia having more examples of larger and better-resourced farming systems. As will become clear below, some of the advantages and disadvantages of CA are related to farm scale and intensity, so the economic performance of CA should not be presumed to be the same in both regions. Nevertheless, compared with most commercial farmers in developed countries, farmers in these two regions have smaller properties and may face tighter constraints on key resources of labour and capital, have higher levels of aversion to risk and uncertainty, have poorer access to markets for farm inputs and outputs, and may face different time-related pressures through a pressing need to provide for the farm family and/or through high costs of borrowed finance. These factors influence the economics of CA. Relevant questions include, under what circumstances are the farm-level economics of CA likely to be favourable, which factors influence the economic attractiveness of CA (and its components) to farmers, and is adoption of the whole CA package more beneficial than adoption of a subset of the CA components?
In the next section we present a conceptual framework for thinking about the role of the farm-economics of CA. In subsequent sections we use the framework in two ways. First we use it as a prism to review existing literature on the farm-level economics of CA in Africa and South Asia. Secondly, we use it as the basis for development of a quantitative model of the economics of CA adoption, and use that model to explore how the economic performance of CA and its components vary in different circumstances.
Section snippets
Conceptual framework
This section provides a conceptual framework for analysis of the farm-level economics of CA. Literature on the adoption of innovations in agriculture is introduced and related to the framework. Put simply, a sound model of the farm-level economics of CA needs to account for: the costs and benefits (broadly defined) of CA relative to the best alternative approach, adjusted for time lags and risk, subject to the need to satisfy resource and other constraints. Our model is essentially a household
Literature on farm-level economics
Here we review existing published research on the economics of CA at farm or field levels, discussing its implications and limitations. The first limitation is that the number of published studies of CA in Africa and South Asia is not large, so it is not possible to develop a comprehensive understanding of how the economics vary between regions, farming systems and farmers. Secondly, many of the existing studies examine individual components of CA rather than the full package. Those that do
Economic model
There are several reasons for developing a new model of the farm-level economics of CA. Models used in most of the existing studies appear to be simple. Most existing models appear to omit one or more of the potentially important factors we identified in our conceptual framework. Many studies confound the economics of the components of CA; they don’t allow the individual and interacting effects to be teased out. Few of the authors provide explicit enough information about the model for a reader
Conclusion
In the right circumstances, conservation agriculture has potential to contribute to the welfare of farmers in developing countries. However, not all circumstances are the right circumstances. It is also possible for CA to be economically unattractive to farmers because its benefits (broadly defined) are not sufficient to outweigh its costs (broadly defined), considering the specific farming context, risk and uncertainty, learning costs, constraints on key resources such as labour and capital,
Acknowledgements
David Pannell and Marc Corbeels are grateful to James Stevenson and Ken Cassman for inviting us to participate in a workshop in Lincoln, Nebraska in October 2012, providing the impetus for preparation of this paper. The authors thank Derek Byerlee for his support and advice and Olive Mungai for her technical assistance in preparing the literature review. We thank Sabine Homann-Kee Tui for access to unpublished research results to help us parameterize the model. We are grateful for feedback from
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