The People and Landscape Model (PALM): Towards full integration of human decision-making and biophysical simulation models

Abstract A model for simulating resource flows in a rural subsistence community is described. The People and Landscape Model (PALM) consists of a number of agents representing households, the landscape, and livestock. The landscape is made up of a number of homogeneous land units, or ‘fields’, each represented by an object containing data, methods and properties relevant to the field. Each field object consists of a number of soil layer objects, each of which contains routines to calculate its water balance and carbon and nitrogen dynamics. Organic matter decomposition is simulated by a version of the CENTURY model, while water and nitrogen dynamics are simulated by versions of the routines in the DSSAT crop models. The soil processes are simulated continuously, and vegetation types (crops, weeds, trees) can come and go in a field depending on its management. Crop growth and development are simulated by a generic model based on the DSSAT crop models, and which can be parameterised for different crops. Similarly, livestock growth and resource use is simulated by a generic model which can be parameterised for buffalo, cows, goats, sheep, chickens and pigs. Each household agent has stores of food, cash, fertiliser, fodder, seed, labour, manure, milk and meat, and also maintains dynamic lists of the patches and livestock units it has access to. Various types of household can be accommodated, ranging from resource-poor to resource-rich. Household agents can also communicate and exchange messages with one another and with the agents representing the landscape and livestock. Decision-making occurs on the basis of the internal state of each household agent and on its perception of the outside world gained from the information received during communication with other agents and the environment. Decisions result in activities being carried out by the household, which in turn influence the flows of water, carbon, nitrogen, labour, and finance—activities can be transactions, involving money, such as purchase of food, or actions, which do not include money, such as application of fertiliser to a field. The model uses object-oriented concepts with multiple instances of various sub-models being possible, so that, for example, different crop models (or even the same one) can be run simultaneously in different fields with different parameters (e.g. planting dates, etc.) for each instance. The advantages of using an agent-based approach as a way of integrating the biophysical and socio-economic characteristics of a system is discussed. The model was used to simulate a community of households each of which were allocated one of seven strategies of crop nutrient management, with these strategies competing with one another over the period of the simulation, during which soil fertility slowly declined. Unsuccessful strategies, determined by the returns generated in relation to an ‘aspiration level’, were replaced by more successful strategies. The impacts of agents requiring farm-yard manure being allowed to purchase from agents with a surplus of manure was also investigated.