HR: 08:00h
AN: H41A-01 INVITED     [PDF]
TI: Process and Form in Holocene Landscapes: Modelling Human and Climatic Impacts
AU: * Wainwright, J
EM: john.wainwright@kcl.ac.uk
AF: Environmental Monitoring and Modelling Research Group, Department of Geography, King's College London, Strand, London, WC2R 2LS United Kingdom
AB: Observations suggest that Mediterranean environments are significantly more sensitive to human impacts that to climate change through the Holocene period. However, many explanations of landscape change rest on interpretations of climatic variability that are difficult to sustain. Erosion and sedimentation data support an interpretation relating to local- (and later regional-) scale human modifications of the landscape with major and often irreversible impacts on the soil resource. For example, on the Causse de Gramat, SW France, erosion rates have varied significantly over distances of several kilometres under very similar geological, soil and climate conditions over the last 6,000 years. Despite the realization that human activity significantly modifies the erosional landscape in such settings, most work aiming at understanding these impacts has been very simplistic. The difficulty of estimating time-varying human impacts has commonly led to the use of relatively basic scenario-based models, particularly over the longer term. Scenario-based approaches suffer from two major problems. They are typically static, so that there is no feedback between the impact and its consequences, even though the latter might often lead to major behavioural modifications. Secondly, there is an element of circularity in the arguments used to generate scenarios for understanding past landform change, in that changes are known to have happened, so that scenarios big enough to produce them are often generated without considering the range of possible alternatives. The approach presented here draws on agent-based models to investigate human interactions with the landscape. Agent-based models use a "bottom-up" approach to the development of these interactions by investing decision-making capacities at the level of individuals, whose behaviour is constrained by the nature of the landscape itself and by interaction with other individuals within it. The model presented consists of four elements. First, a cellular landscape-evolution model characterizes erosion processes, soil development and sedimentation. Secondly, a plant-growth model allows the evolution of vegetated landscapes according to major plant functional types. Thirdly, animal activity within the landscape is simulated using an agent-based approach. Animals are simulated as agents, using cellular automata rules governed by underlying energetics. Fourthly, there are the human agents, simulated either using cellular automata, or using neural networks. Landscape evolution is simulated as the interaction of all four of these levels. Results presented will illustrate a number of key factors. The stability of animal and human populations within these landscapes is not a foregone conclusion, leading to quite different outcomes for similar initial conditions. The model can illustrate the potential for self-organization and the development of quite different sets of behavioural patterns. This approach is useful in the investigation of how well past human-landscape interactions are understood, and allows a contrast with explanations simply based on climate.
DE: 1803 Anthropogenic effects
DE: 1809 Desertification
DE: 1815 Erosion and sedimentation
DE: 1824 Geomorphology (1625)
SC: Hydrology [H]
MN: 2003 Fall Meeting