Pluralistic modelling approaches to simulating climate-land change interactions in East Africa

We summarize the use of several different modelling approaches we are employing to understand how climate change impacts changes in land use in East Africa. A role playing game model has been employed that helps to elucidate the behavioural drivers of land use change and how these factors are integrated with other biophysical (e.g. climate) and socioeconomic drivers. Outcomes from the game include a qualitative list and integrative understanding of these drivers over spatial and temporal scales and a series of decision maps produced by game participants. A second method includes the use of expert systems or knowledge acquisition approaches that attempt to synthesize expert opinion on how societies may adapt to changes in climate. Outcomes of these knowledge acquisition activities include expert maps and systems diagrams both of which are used to construct and validate models. These two qualitative approaches were used to construct three different sets of models: those that use multi-criteria evaluation techniques integrating a variety of spatial data layers using a geographic information system; a machine learning based model employing artificial neural networks that learn from patterns in data, and a behavioural model using Bayesian Belief Networks that simulates individual behaviour in the context of social interactions. We show how these diverse methods are used together to aid in our understanding of the drivers and impacts of climate change on land use systems in East Africa. In particular, we are interested in the impacts climate change might have on pastoralist, cropping, and urban systems over the next 10-50 years. These methods are being used along with process based models of regional climate change and crop production models to understand the coupling of climate and land systems in this geographically diverse area of the world. In our discussion we compare and contrast these very different, but complementary, modelling approaches to understand climate change at local to regional scales.

openalex: W2512253078 mag: 2512253078