Tag Archives: pattern-oriented modeling

Cross-site Comparison of Land-Use Decision-Making

The cumulative effects of local land-use and livelihood changes are a global force of environmental and socio-economic change. Land-use changes result from decisions of individual farmers, pastoralists,  and housing consumers and developers (to name a few). Their decisions are influenced by not only local environmental, social, and economic conditions, but also by far-reaching forces such as economic globalization. The choice of a farmer in Brazil to grow soybeans, for example, can be influenced by the consumption of people in China.

Not all land-uses are created equal. Some have minimum impact on the environment, and some offer sustainable livelihoods for local farmers – finding land uses that accomplish both is difficult. Crafting policies to achieve this two-part goal must contend with both local and global considerations.

Location of one of the study sites near Taoyuan, Hunan Province, China.

A study site near Taoyuan, Hunan Province, China.

On January 29th, my colleagues and I published a paper in PLoS ONE, titled “Cross-site comparison of land-use decision-making and its consequences across land systems with a generalized agent-based model” that describes the development and application of an agent-based virtual laboratory for comparing  land-use and livelihood decision-making processes of rural farmers across geographically distant locations and qualitatively different land-use systems. We use this modeling system across multiple study sites to understand the underlying motivations and rationale of land-use and livelihood decisions of our ‘farmer agents’ and the landscape and livelihood changes that result under various environmental, demographic, and economic scenarios.

Since the traditional mode of scientific experimentation is not feasible with real land-use systems – we are talking about people’s land and livelihoods here – we use simulation-based cross-site comparisons to teach us about what drives the choice of particular land uses and livelihood strategies under different conditions. We use the set of study sites as local examples to synthesis more broadly applicable knowledge of which factors are most important in what contexts.

To explore this question, our investigation had to happen at the decision-making level – a task to which agent-based models are well suited. We also needed a modeling framework that was sufficiently general that it could be applied across multiple locations, yet realistic enough that it could be grounded in real-world data. These needs gave rise to an innovative agent-based virtual laboratory approach that provides a powerful tool for model-based experimentation and synthesis.

Such a model synthesis system can generate the kind of high-level knowledge needed to inform regional policies designed to foster sustainable local land uses and livelihood strategies. Cross-site comparisons use each study site as an example of alternative conditions and/or potential future states, which can aid scenario analysis and the exploration of potential adaptive responses to changing conditions. Furthermore, insights gained from the application of the modeling system to one site can improve our understanding of other similar sites, and foster future research and policy efforts that are sensitive to both the global influence on and local realities of land-use and livelihood change.

Click here to see the web story about this article on SESYNC’s blog.

New Paper: Pattern-Oriented Modeling in Multi-Scale ABMs of Land Change

TGIS_screen_captureA particular challenge of investigating the causes of land-use change is the multi-scale nature of factors that influence land-use decisions. In an increasingly globalized world, land-use choices and livelihood strategies are linked to local AND regional to global forces. But attempts to incorporate such multi-scale causation in land change models often run into significant knowledge and data gaps – especially when trying to link incomplete and/or low quality global data to individual agents’ decision-making processes.

Figure4_mainOne way forward, which my co-author Dr. Erle Ellis and I present in this new open-access article in Transactions in GIS, is to use pattern-oriented modeling (Grimm et al., 2005) within an agent-based virtual laboratory to experimentally bound the possible values of uncertain parameters. By targeting characteristic patterns tied to important individual- and landscape-level processes – the selection of which are informed by theory, data, or both – ABMs can be designed and tested to be more realistic despite data limitations. We propose that this experimental method can help overcome significant data gaps, and help land change scientists begin to quantify some global trends in local land change processes.

Comments welcome!

Abstract

Local land-use and -cover changes (LUCCs) are the result of both the decisions and actions of individual land-users, and the larger global and regional economic, political, cultural, and environmental contexts in which land-use systems are embedded. However, the dearth of detailed empirical data and knowledge of the influences of global/regional forces on local land-use decisions is a substantial challenge to formulating multi-scale agent-based models (ABMs) of land change. Pattern-oriented modeling (POM) is a means to cope with such process and parameter uncertainty, and to design process-based land change models despite a lack of detailed process knowledge or empirical data. POM was applied to a simplified agent-based model of LUCC to design and test model relationships linking global market influence to agents’ land-use decisions within an example test site. Results demonstrated that evaluating alternative model parameterizations based on their ability to simultaneously reproduce target patterns led to more realistic land-use outcomes. This framework is promising as an agent-based virtual laboratory to test hypotheses of how and under what conditions driving forces of land change differ from a generalized model representation depending on the particular land-use system and location.