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While qualitative data can be highly empirical, ABM also offers a means of identi-
fying general patterns and processes that can have relevance in a general range of
settings whilst operating within the parameters of the particular case study. Using
sequential descriptive and analytical coding to develop theory and abstract rules for
the ABM has proven a useful way of interrogating the narratives that are grounded in
the qualitative data. Model-building acts as a further layer of analysis helping to in-
terpret the data in different ways.
This analysis has identified worldview as an important factor in pastoralist deci-
sion-making processes. Agent architecture has been developed which reflects this
finding, building agents with three overarching goals executed through sets of inten-
tions which are modified by their belief sets (i.e. BDI agents).
Further versions of this ABM will be developed to explore scenarios of interest
that have been identified by participants. Furthermore, the ABM will be fully coupled
with a dynamic vegetation model for savannah ecosystems [33] which will represent
the agents' shared environment and the potential impacts on and dynamics between
socio-cultural changes and vegetation structure and function. The integrated social-
ecological model will be tested and implemented at a range of spatial and temporal
scales as appropriate to the system to investigate system resilience to climate and
land-use changes.
Acknowledgments.
This work was supported by the Economic and Social Research
Council and the Natural Environment Research Council (grant number
ES/I025758/1).
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