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Exploring future changes in smallholder farming systems by linking socio-economic scenarios with regional and household models

TLDR
In this paper, the authors explore how smallholder agricultural systems in the Kenyan highlands might intensify and/or diversify in the future under a range of socioeconomic scenarios, and identify trajectories of intensification, diversification and stagnation for different farming systems.
Abstract
We explore how smallholder agricultural systems in the Kenyan highlands might intensify and/or diversify in the future under a range of socio-economic scenarios. Data from approximately 3000 households were analyzed and farming systems characterized. Plausible socio-economic scenarios of how Kenya might evolve, and their potential impacts on the agricultural sector, were developed with a range of stakeholders. We study how different types of farming systems might increase or diminish in importance under different scenarios using a land-use model sensitive to prices, opportunity cost of land and labour, and other variables. We then use a household model to determine the types of enterprises in which different types of households might engage under different socio-economic conditions. Trajectories of intensification, diversification, and stagnation for different farming systems are identified. Diversification with cash crops is found to be a key intensification strategy as farm size decreases and labour costs increase. Dairy expansion, while important for some trajectories, is mostly viable when land available is not a constraint, mainly due to the need for planting fodders at the expense of cropland areas. We discuss the results in relation to induced innovation theories of intensification. We outline how the methodology employed could be used for integrating global and regional change assessments with local-level studies on farming options, adaptation to global change, and upscaling of social, environmental and economic impacts of agricultural development investments and interventions.

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Exploring future changes in smallholder farming systems by linking socio-economic
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scenarios with regional and household models
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Mario Herrero
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, Philip K. Thornton
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, Alberto Bernués
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, Isabelle Baltenweck
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, Joost
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Vervoort
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, Jeannette van de Steeg
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, Stella Makokha
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, Mark T. van Wijk
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, Stanley
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Karanja
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, Mariana C. Rufino
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and Steven J. Staal
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Commonwealth Scientific and Industrial Research Organisation, 306 Carmody Road, St
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Lucia, 4067 QLD, Australia
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CGIAR Research Programme on Climate Change, Agriculture and Food Security
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(CCAFS), PO Box 30709-00100, Nairobi, Kenya
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International Livestock Research Institute (ILRI), PO Box 30709-00100, Nairobi, Kenya
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AgriFood Research and Technology Centre of Aragon, Avda. Montaña 930, 50059
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Zaragoza, Spain
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Environmental Change Institute, University of Oxford, OX1 3QY, UK
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Kenyan Agricultural Research Institute (KARI), Nairobi, Kenya
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*Corresponding author: Dr Mario Herrero, CSIRO, 306 Carmody Road, St Lucia,
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4067, QLD, Australia, email: Mario.herrero@csiro.au; tel +61 7 3214 2538.
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Abstract
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We explore how smallholder agricultural systems in the Kenyan highlands might
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intensify and/or diversify in the future under a range of socio-economic scenarios. Data
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from approximately 3000 households were analysed and farming systems characterized.
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Plausible socio-economic scenarios of how Kenya might evolve, and their potential
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impacts on the agricultural sector, were developed with a range of stakeholders. We study
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how different types of farming systems might increase or diminish in importance under
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different scenarios using a land-use model sensitive to prices, opportunity cost of land
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and labour, and other variables. We then use a household model to determine the types of
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enterprises in which different types of households might engage under different socio-
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economic conditions. Trajectories of intensification, diversification, and stagnation for
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different farming systems are identified. Diversification with cash crops is found to be a
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key intensification strategy as farm size decreases and labour costs increase. Dairy
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expansion, while important for some trajectories, is mostly viable when land available is
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not a constraint, mainly due to the need for planting fodders at the expense of cropland
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areas. We discuss the results in relation to induced innovation theories of intensification.
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We outline how the methodology employed could be used for integrating global and
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regional change assessments with local-level studies on farming options, adaptation to
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global change, and upscaling of social, environmental and economic impacts of
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agricultural development investments and interventions.
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Keywords
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Scenarios, smallholders, household modeling, land use modeling, sustainable
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intensification, agriculture, dairy
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1. Introduction
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The role that smallholder agricultural producers are likely to play in global food
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production and food security in the coming decades is highly uncertain. In many parts of
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the tropics, particularly sub-Saharan Africa, smallholder production is critical to the food
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security of the poor. Industrialisation of agricultural production is occurring in many
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places, largely in response to burgeoning demand for food. Some smallholders may be
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able to seize the opportunities that exist and develop, and operate as sustainable and
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profitable smallholder agricultural production systems (Herrero et al., 2010; Thornton,
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2010). Whether large numbers of smallholders will be able to do this in a carbon-
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constrained global economy and in an environment characterised by a changing climate
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and by increased climatic variability, will depend on many things such as increasing
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regulation, building social protection and strengthening links to urban areas, and
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substantial investment in agriculture (Wiggins, 2009; World Bank, 2009). Understanding
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how smallholder systems may evolve in the future is critical if poverty alleviation and
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food security goals are to be achieved.
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In many parts of the tropics, particularly Africa and Asia, smallholders operate
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mixed crop-livestock systems, which integrate different enterprises on the farm; crops
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provide food for consumption and for cash sales, as well as residues to feed livestock, and
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livestock provide draft power to cultivate the land and manure to fertilise the soil. These
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systems are often highly diversified, and the synergies between cropping and livestock
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keeping offer real opportunities for raising productivity and increasing resource use
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efficiency (Herrero et al., 2010). Whether these systems can increase household incomes
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and enhance the availability of and access to food for rapidly increasing urban
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populations in the coming years, while at the same time maintaining environmental
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services, is a question of considerable importance.
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Studying this question requires some consideration of theories of change. A
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general model of agricultural intensification originated with Boserup (1965), who
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described it as an endogenous process responding to increased population pressure. As
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the ratio of land to population decreases, farmers are induced to adopt technologies that
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raise returns to land at the expense of a higher input of labour. The direct causal factor is
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relative factor price changes, in accordance with the theory of induced innovation. At
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low human population densities, production systems are extensive, with high availability
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of land and few direct crop-livestock interactions. Population increases lead to increases
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in demand for crop and livestock products, which in turn increases the value of manure
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and feed resources and other inputs, leading to increased crop and livestock productivity.
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As population increases yet further, systems intensify through specialisation or
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diversification in production as relative values of land, labour and capital continue to
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change: fertilizer replaces manure, tractors replace draft animals, concentrate feeds
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replace crop residues, and cash crops replace food crops (Baltenweck et al., 2003).
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Other factors can also play a significant role in determining the nature and
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evolution of crop-livestock systems (McIntire et al., 1992). In humid areas with a high
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disease challenge for large ruminants, crop-livestock interactions are likely to be limited
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owing to lower livestock densities. Other factors include economic opportunities, cultural
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preferences, climatic variability (e.g., droughts that lead to livestock losses), lack of
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capital to purchase animals, and labour bottlenecks at some periods of the year that may
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prevent farmers from adopting technologies such as draft power (Powell and Williams,
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1993). Nevertheless, common patterns of both the drivers and the outcomes of
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intensification of tropical crop-livestock systems can be identified. Choice of crops and
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livestock interventions have been shown to be at least partly dependent on relative labour
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and land costs and on market access, at a wide range of sites throughout the tropics
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(Baltenweck et al., 2003). Furthermore, in the same study education level, market access
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and human population densities were shown to be major drivers of crop-livestock
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systems intensification (Baltenweck et al., 2003).
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At the same time, alongside these larger scale drivers of farm development, the
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ability of smallholders to implement new practices is further determined by intrinsic
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system properties that may act as modifiers to their adoption. Farmers’ objectives and the
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rules governing labour allocation and gender differentiation in the household are
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examples (Thornton and Herrero, 2001; Waithaka et al., 2006). Such factors are not
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necessarily related to spatial or macro-economic drivers; they therefore need to be studied
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at the farm household level.
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To understand the evolution of smallholder crop-livestock systems, we propose that.
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these systems should be examined at multiple levels by analysing and linking macro-level
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socio-economic drivers, regional-level land-use patterns, and micro-level household
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dynamics and strategies. Complementary methods should be used that appropriately
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reflect the key dynamics of each of these levels (Cash et al., 2006). The significant
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complexity and uncertainty associated with the interacting biophysical and socio-
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economic dimensions of agricultural systems should be taken into account by using a
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multiple scenarios approach, informed by relevant stakeholder perspectives (Biggs et al.,
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2007). Interactions of smallholder systems with changing contexts should be simulated
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and discussed iteratively with key stakeholders to explore longer-term evolutionary
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pathways (Kinzig, 2006).
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In this paper we provide an example of this multi-level, multi-scenario, evolutionary
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framework for the analysis of smallholder systems, using complementary modeling
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approaches and harnessing relevant stakeholder perspectives. We build on the work of
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Baltenweck et al. (2003) and Herrero et al. (2007a) by studying the potential household-
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level impacts of crop-livestock intensification using crop-dairy systems data obtained
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from longitudinal monitoring of representative case studies and key informants
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(extension officers and policy makers) from Kenya. The objective of the study was to
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generate socio-economic development scenarios as to how crop-livestock systems in the
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highlands of Kenya might evolve in the next two decades and evaluate these plausible,
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alternative futures through a multi-level modeling framework that includes a) the
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development of scenarios providing different socio-economic conditions at the country
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level and above; b) a regional land-use change analysis projecting the spatial distribution
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of farming systems into the future; and c) the use of a household model to evaluate the
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results of the spatial analysis at the farm level, allowing for a deeper understanding of
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internal farm dynamics. We conclude with a discussion of the value of multi-scale,
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stakeholder-generated, iterative analyses in evaluating synergies and trade-offs in farming
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systems, particularly related to the dynamics of global change in tropical smallholder
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systems.
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Citations
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References
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The conditions of agricultural growth

Ester Boserup
TL;DR: In this paper, Boserup argues that changes and improvements occur from within agricultural communities, and that improvements are governed not simply by external interference, but by those communities themselves using extensive analyses of the costs and productivity of the main systems of traditional agriculture.
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The DSSAT cropping system model

TL;DR: The benefits of the new, re-designed DSSAT-CSM will provide considerable opportunities to its developers and others in the scientific community for greater cooperation in interdisciplinary research and in the application of knowledge to solve problems at field, farm, and higher levels.
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Livestock production: recent trends, future prospects

TL;DR: Demand for livestock products in the future could be heavily moderated by socio-economic factors such as human health concerns and changing socio-cultural values, and Livestock production is likely to be increasingly affected by carbon constraints and environmental and animal welfare legislation.
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Scale and Cross-Scale Dynamics: Governance and Information in a Multilevel World

TL;DR: It is suggested that the advent of co-management structures and conscious boundary management that includes knowledge co-production, mediation, translation, and negotiation across scale-related boundaries may facilitate solutions to complex problems that decision makers have historically been unable to solve.
Related Papers (5)
Frequently Asked Questions (17)
Q1. What are the contributions in this paper?

In this paper, the authors studied how agricultural systems in the Kenyan highlands might evolve as a result of drivers of change that could create opportunities for intensification and diversification for different types of farming systems. 

The authors set out to study how agricultural systems in the Kenyan highlands might evolve as a 29 result of drivers of change that could create opportunities for intensification and 30 diversification for different types of farming systems. As change occurs, it 11 is essential to have the ability to study what may happen to different types of households, 12 how they might react and adapt or not, what the costs associated with these adaptations 13 could be, who will be the winners and the losers, what kinds of robust interventions may 14 be suitable for different types of farming systems, and what could be the socio-economic 15 and environmental trade-offs if these were to be implemented. Rather 10 than providing a two-dimensional “ low-medium-high investment ” set of scenarios, the 11 scenario set included equitable versus inequitable growth as another dimension, one that 12 can be expressed as spatial differentiation. The scenarios have furthermore provided a long-term 14 future context beyond present-day conditions in which evolution of smallholder systems 15 can be simulated over multiple iterations. 

Some off-farm income is obtained through wages received from work on other farms by 4 the household head and his wife, accounting for 18.8% of total household income. 

The involvement of regional experts in the development of socio-economic 1 scenarios has enabled us to explore change in smallholder systems under different policy-2 relevant conditions that incorporate both desired futures as expressed by government 3 strategies as well as less optimistic, more challenging futures. 

The map with farming systems distribution at the base year, the set of static and 17 dynamic spatial data layers, and the logit models that relate the probability of occurrence 18 of farming systems to location characteristics were used as input to a spatial and temporal 19 model of farming systems dynamics. 

5 Livestock keeping costs are more important than those due to agriculture, because of little 6 hiring of labour for cropping activities. 

Income elasticity 8 demands were derived from USDA (2013); the authors used 0.58, 0.81, 0.9 and 1.6 for maize, 9beans, milk and tea respectively. 

in their iterative simulations the authors have 16 not considered feedbacks from the models to the scenarios which might result in cross-17 level system shifts (Kinzig, 2006), such as regional land-use change patterns prompting 18 changes in national government policies. 

This move towards more specialized dairy activities near cities is consistent 24 with previous studies that showed that dairy is profitable near cities despite high farming 25 costs, because of high demand for milk translating into a higher milk price. 

Farm size is the biggest of all the case studies with 4.8 ha 16 (all owned), from which 3.7 ha is dedicated to crops and the rest to cut-and-carry 17 pastures. 

6 7Description of Case Study Households 8 9From the final 18 household groups (six classes and three sub-groups in each), a 10 representative case study farm was selected. 

As spatial variables are changing over time, the optimal occurrence 29 of a certain farming system for a given location will change (Table 7). 

It is important to notice that the farmer only starts growing 16 passion fruit if cash is available to start this activity, which has high initial costs. 

The “optimal base scenario” slightly 31increases the amount of land used for food and cash crops (maize and beans) at the 1 expense of the grassland area, but maintains the dairy activity. 

It is important to notice that, due to the peri-urban location of the farm, close to 4 the capital city Nairobi where population densities are higher and where there is a higher 5 demand for land for non-agricultural activities, the evolution of land size is opposite to 6 that observed for the other case studies. 

27 28 Inequitable growth scenario 29 About 15% of the surface area of the study area was projected to change for this scenario, 30 the lowest value of the range predicted in Figure 5. 

Through this procedure it is possible that the local suitability based on the 3 location factors is overruled by the iteration variable due to the differences in regional 4 demand.