Simulation models in farming systems research : potential and challenges

Integrated simulation models can be useful tools in farming system research. This chapter reviews three commonly used approaches, i.e. linear programming, system dynamics and agent-based models. Applications of each approach are presented and strengths and drawbacks discussed. We argue that, despite some challenges, mainly related to the integration of different approaches, model validation and the representation of human agents, integrated simulation models contribute important insights to the analysis of farming systems. They help unravelling the complex and dynamic interactions and feedbacks among bio-physical, socio-economic, and institutional components across scales and levels in farming systems. In addition, they can provide a platform for integrative research, and can support transdisciplinary research by functioning as learning platforms in participatory processes.

Comparing rice production systems: A challenge for agronomic research and for the dissemination of knowledge-intensive farming practices

This article is a commentary on several research studies conducted on the prospects for aerobic rice production systems that aim at reducing the demand for irrigation water which in certain major rice producing areas of the world is becoming increasingly scarce. The research studies considered, as reported in published articles mainly under the aegis of the International Rice Research Institute (IRRI), have a narrow scope in that they test only 3 or 4 rice varieties under different soil moisture treatments obtained with controlled irrigation, but with other agronomic factors of production held as constant. Consequently, these studies do not permit an assessment of the interactions among agronomic factors that will be of critical significance to the performance of any production system. Varying the production factor of "water" will seriously affect also the levels of the other factors required to optimise the performance of a production system. The major weakness in the studies analysed in this article originates from not taking account of the interactions between experimental and non-experimental factors involved in the comparisons between different production systems. This applies to the experimental field design used for the research studies as well as to the subsequent statistical analyses of the results. The existence of such interactions is a serious complicating element that makes meaningful comparisons between different crop production systems difficult. Consequently, the data and conclusions drawn from such research readily become biased towards proposing standardised solutions for possible introduction to farmers through a linear technology transfer process. Yet, the variability and diversity encountered in the real-world farming environment demand more flexible solutions and approaches in the dissemination of knowledge-intensive production practices through "experiential learning" types of processes, such as those employed by farmer field schools. This article illustrates, based on expertise of the 'system of rice intensification' (SRI), that several cost-effective and environment-friendly agronomic solutions to reduce the demand for irrigation water, other than the asserted need for the introduction of new cultivars, are feasible. Further, these agronomic Solutions can offer immediate benefits of reduced water requirements and increased net returns that Would be readily accessible to a wide range of rice producers, particularly the resource poor smallholders. (C) 2009 Elsevier B.V. All rights reserved.

Agricultural adaptation to climate change: insights from a farming community in Sri Lanka

The vulnerability of smallholder farmers to climate change and variability is increasingly rising. As agriculture is the only source of income for most of them, agricultural adaptation with respect to climate change is vital for their sustenance and to ensure food security. In order to develop appropriate strategies and institutional responses, it is necessary to have a clear understanding of the farmers’ perception of climate change, actual adaptations at farm-level and what factors drive and constrain their decision to adapt. Thus, this study investigates the farm-level adaptation to climate change based on the case of a farming community in Sri Lanka. The findings revealed that farmers’ perceived the ongoing climate change based on their experiences. Majority of them adopted measures to address climate change and variability. These adaptation measures can be categorised into five groups, such as crop management, land management, irrigation management, income diversification, and rituals. The results showed that management of non-climatic factors was an important strategy to enhance farmers’ adaptation, particularly in a resource-constrained smallholder farming context. The results of regression analysis indicated that human cognition was an important determinant of climate change adaptation. Social networks were also found to significantly influence adaptation. The study also revealed that social barriers, such as cognitive and normative factors, are equally important as other economic barriers to adaptation. While formulating and implementing the adaptation strategies, this study underscored the importance of understanding socio-economic, cognitive and normative aspects of the local communities.