Pepijn Schreinemachers

Comparison of empirical methods for building agent-based models in land use science

The use of agent-based models (ABMs) for investigating land-use science questions has been increasing dramatically over the last decade. Modelers have moved from ‘proofs of existence’ toy models to case-specific, multi-scaled, multi-actor, and data-intensive models of land-use and land-cover change. An international workshop, titled ‘Multi-Agent Modeling and Collaborative Planning—Method2Method Workshop’, was held in Bonn in 2005 in order to bring together researchers using different data collection approaches to informing agent-based models. Participants identified a typology of five approaches to empirically inform ABMs for land use science: sample surveys, participant observation, field and laboratory experiments, companion modeling, and GIS and remotely sensed data. This paper reviews these five approaches to informing ABMs, provides a corresponding case study describing the model usage of these approaches, the types of data each approach produces, the types of questions those data can answer, and an evaluation of the strengths and weaknesses of those data for use in an ABM.

An agent-based simulation model of human-environment interactions in agricultural systems

This paper describes an agent-based software package, called Mathematical Programming-based Multi Agent Systems (MP-MAS), which builds on a tradition of using constrained optimization to simulate farm decision-making in agricultural systems. The purpose of MP-MAS is to understand how agricultural technology, market dynamics, environmental change, and policy intervention affect a heterogeneous population of farm households and the agro-ecological resources these households command. The software is presented using the Overview, Design concepts, and Details (ODD) protocol. Modeling features are demonstrated with empirical applications to study sites in Chile, Germany, Ghana, Thailand, Uganda, and Vietnam. We compare MP-MAS with eight other simulators of human-environment interactions (ABSTRACT, CATCHSCAPE, ECECMOD, IMT, LUDAS, PALM, SAM, and SIM). The comparison shows that the uniqueness of MP-MAS lies in its combination of a microeconomic modeling approach and a choice of alternative biophysical modules that are either coded as part of the software or coupled with it using the Typed Data Transfer (TDT) library.

Creating agents and landscapes for multiagent systems from random samples

An important goal of modeling human-environment interactions is to provide scientific information to policymakers and stakeholders in order to better support their planning and decision-making processes. Modern technologies in the fields of GIS and data processing, together with an increasing amount of accessible information, have the potential to meet the varying information needs of policymakers and stakeholders. Multiagent modeling holds the promise of providing an enhanced collaborative framework in which planners, modelers, and stakeholders may learn and interact. The fulfillment of this promise, however, depends on the empirical parameterization of multiagent models. Although multiagent models have been widely applied in experimental and hypothetical settings, only few studies have strong linkages to empirical data and the literature on methods of empirical parameterization is still limited. This paper presents a straightforward approach to parameterize multiagent models in applied development research. The parameterization uses a common sampling frame to randomly select observation units for both biophysical measurements and socioeconomic surveys. The biophysical measurements, i.e., soil properties in this study, are then extrapolated over the landscape using multiple regressions and a digital elevation model. The socioeconomic surveys are used to estimate probability functions for key characteristics of human actors, which are then assigned to the model agents with Monte Carlo techniques. This approach generates a landscape and agent populations that are robust and statistically consistent with empirical observations.

Land use decisions in developing countries and their representation in multi-agent systems

Recent research on land use and land cover change (LUCC) has put more emphasis on the importance of understanding the decision-making of human actors, especially in developing countries. The quest is now for a new generation of LUCC models with a decision-making component. This paper deals with the question of how to realistically represent decision-making in land use models. Two main agent decision architectures are compared. Heuristic agents take sequential decisions following a pre-defined decision tree, while optimizing agents take simultaneous decisions by solving a mathematical programming model. Optimizing behaviour is often discarded as being unrealistic. Yet the paper shows that optimizing agents do have important advantages for empirical land use modelling and that multi-agent systems (MAS) offer an ideal framework for using the strengths of both agent decision architectures. The use of optimization models is advanced with a novel three-stage decision model of investment, production, and consumption to represent uncertainty in models of land use decision-making.

A software coupling approach to assess low-cost soil conservation strategies for highland agriculture in Vietnam

Soil degradation is an environmental process mainly caused by land use decision-makers that has substantial feedback effects on livelihoods and the environment. To capture these feedback effects and the resulting human-environment interactions, we used an agent-based modeling approach to couple two software packages that simulate soil, water and plant dynamics (LUCIA), and farm decision-making (MP-MAS). We show that such a software coupling approach has advantages over hard-coded model integration as applied by most other comparable studies, as it facilitates combining of increasingly sophisticated individual models and can achieve a well-balanced representation of agricultural systems. Using a numerical application for a small mountainous watershed in northwest Vietnam we show the challenges in model coupling, calibration and partial validation, and explore the properties of the coupled model system. Scenario analysis covering the introduction of low-cost soil conservation techniques indicates that some of these techniques would have an impact on soil erosion, maize productivity and household income levels in the study catchment area under current conditions. However, maize yields and the adoption of soil conservation appear to be sensitive to the price of mineral fertilizers, with lower fertilizer prices impeding the adoption of soil conservation measures. The software coupling approach was able to capture interactions between decision-makers and natural resources, as well as the level of spatial variability, in more detail than the individual models. Still, the greater number of endogenous variables and thus degrees of freedom increased the importance of validation and testing parameter sensitivity of the results.

Resettling Farm Households in Northwestern Vietnam: Livelihood Change and Adaptation

This paper examines how a resettlement programme in northwestern Vietnam has affected the livelihood assets, strategies and outcomes of the resettled and host households. Data were collected using informal interviews, followed by a structured survey of 56 resettled and 52 host households. Results show a significant decline in natural capital for the resettled households and a lesser decline for the host households; however, both groups have partially compensated for this through land use intensification. The net income of the host households did not change significantly after resettlement, whereas the farm revenues of the resettled households fell dramatically, but, due to the compensation payments made to them, their net household income actually increased. Most compensation money has been consumed rather than invested in livelihood assets; livelihood outcomes might therefore deteriorate when the compensation payments end.

Impact and cost-effectiveness of women's training in home gardening and nutrition in Bangladesh

ABSTRACT This study quantifies the impact and cost-effectiveness of training poor rural women in Bangladesh in home gardening and nutrition. We use baseline and follow-up data for 646 intervention and control households and apply a difference-in-difference estimator. We find that the intervention significantly (p < 0.01) increased vegetable production (+16.5 g/person/day), vegetable consumption and the micronutrient supply from the garden. Using the disability-adjusted life years (DALYs) approach, we show that the intervention can be considered cost-effective in abating iron, vitamin A and zinc deficiencies. Home garden interventions can therefore make an effective contribution to addressing micronutrient undernutrition.

Sowing seeds of empowerment: effect of women’s home garden training in Bangladesh

BackgroundThere is a lack of scientific evidence that home gardens contribute to women empowerment, which eventually leads to greater gender equality, although it is generally assumed that they do. Using data from poor rural households in Bangladesh, this paper analyzes if and how women’s training in home gardening and nutrition empowers women. The study used a mixed methods approach, combining statistical analysis of quantitative data for 456 women with content analysis of qualitative data from in-depth interviews.ResultsThe results show that home garden training is popular and widely accepted by both men and women largely because it does not contest existing socially constructed gender roles. Nevertheless, we find clear signs of increased control by women over food supplies and income, and gains in women’s self-confidence and role in the community—as husbands and outsiders begin to recognize their agricultural skills. However, such improvements have been gradual rather than radical. Many men and women appreciated the new opportunity to work together on something of common interest that advanced their quality of life.ConclusionThe evidence presented shows gradual but clear signs of women empowerment as a result of training in home gardens and nutrition.

Agricultural Pesticide Use in Mountainous Areas of Thailand and Vietnam: Towards Reducing Exposure and Rationalizing Use

A change in land use from the growing of upland rice to the cultivation of cash crops has increased the level of use of synthetic pesticides in the mountainous areas of Thailand and Vietnam. Although this increase has occurred generally across both countries, it has been especially prevalent in mountainous areas. The objective of this chapter is to describe the challenges faced when wishing to reduce the risks caused by the use of agricultural pesticides in mountainous areas, both from an economic and a biophysical point of view. Building on case studies from Thailand and Vietnam, we show how the potential risk of pesticide use is related to the limited experience farmers have in handling pesticides, and the hydrological relationships between highland and lowland areas.

From Challenges to Sustainable Solutions for Upland Agriculture in Southeast Asia

Agriculture carried out in the mountainous areas of Southeast Asia is intensifying rapidly, driven as it is by economic growth, policy changes, the introduction of new technologies and population growth. Rice, the dominant crop, is giving way to a greater variety of cash crops such as maize, vegetables, fruits, flowers and rubber. Building on a long-term interdisciplinary research project run by the University of Hohenheim over the period 2000–2014, in collaboration with various universities and research institutes in Thailand and Vietnam, we discuss three interrelated problems that tend to accompany land use intensification in mountainous areas, these being rapid land degradation, increasing levels of pesticide use and pollution, and persistent poverty. We set the framework for this book by introducing these problems and discussing how research into the development, testing and adaptation of innovations, as well as the development of knowledge on mountainous land use systems, has contributed to more sustainable land use and rural development among the mountainous areas of Southeast Asia.