Multi-agent modelling of climate outlooks and food security on a community garden scheme in Limpopo, South Africa

Abstract

Seasonal climate outlooks provide one tool to help decision-makers allocate resources in anticipation of poor, fair or good seasons. The aim of the 'Climate Outlooks and Agent-Based Simulation of Adaptation in South Africa' project has been to investigate whether individuals, who adapt gradually to annual climate variability, are better equipped to respond to longer-term climate variability and change in a sustainable manner. Seasonal climate outlooks provide information on expected annual rainfall and thus can be used to adjust seasonal agricultural strategies to respond to expected climate conditions. A case study of smallholder farmers in a village in Vhembe district, Limpopo Province, South Africa has been used to examine how such climate outlooks might influence agricultural strategies and how this climate information can be improved to be more useful to farmers. Empirical field data has been collected using surveys, participatory approaches and computer-based knowledge elicitation tools to investigate the drivers of decision-making with a focus on the role of climate, market and livelihood needs. This data is used in an agent-based social simulation which incorporates household agents with varying adaptation options which result in differing impacts on crop yields and thus food security, as a result of using or ignoring the seasonal outlook. Key variables are the skill of the forecast, the social communication of the forecast and the range of available household and community-based risk coping strategies. This research provides a novel approach for exploring adaptation within the context of climate change.

Issues in the interpretation of climate model ensembles to inform decisions

“…Nevertheless, if we are to go beyond minimization of vulnerability to today's climate, we desire information on how climate will change in the coming decades on regional or smaller scales (Bharwani et al 2005)-preferably in the form of a seamless prediction across time-scales (Washington et al 2006). To the extent that model-based information is relevant to our decision, it can be used in a climate risk management framework, i.e.…”

Introduction: food crops in a changing climate

“…Escaping the poverty trap is a major challenge for development and cannot be achieved without coherent national and international policies and without proper recognition of the roles science, technology and innovation play in development. Currently, natural climate variability is one of many factors already pushing people below the poverty trap threshold (Bharwani et al 2005). Farmers on the brink of poverty will not want to take a risk based on advice (such as to grow an alternative crop) and may make a decision that pushes them below the poverty level.…”

“…Rapidly changing socioeconomic factors can lead to increased sensitivity to climate shocks; for example, the high incidence of HIV and increasing levels of poverty in Africa increase the exposure of the population and its inability to cope with climatic stress. Simulation methods that integrate climate and human behaviour provide a novel approach to understanding adaptation options for climate variability and change (Bharwani et al 2005).…”

Integrating Modelling Approaches for Understanding Telecoupling: Global Food Trade and Local Land Use

“…As a result of its flexibility, agent-based modelling has been used widely to investigate human-environment interactions and for understanding land use and landscape change, e.g., [22,30,31]. In the context of land use and global food trade, ABMs have been used to examine smallholder adaptation to climate change by examining agent forecasting and communication [32], decision-making about adoption of organic farming practices [33], and the importance of social networks for farmer decision-making [34].…”