Coupling Simulations of Human Driven Land Use Change with Natural Vegetation Dynamics

摘要

Land cover change is the result of interactions and feedbacks between processes operating at different spatial and temporal scales. As human impact on the environment becomes more pronounced, there is growing interest in understanding the effects of environmental and scocio-economic changes on landscape dynamics. Computer simulation models provide a tool for studying the causes and consequences of landscape dynamics and projecting short- and long-term landscape changes. Currently, there is a need for a model that can simulate multiple drivers of land cover change, including natural disturbances vegetation succession along with anthropogenic effects such land use transitions and land management practices. The available land cover change models typically simulate only a subset of these disturbances, which is not sufficient for realistically simulating land cover change over large heterogeneous areas. To addressing this need, we developed a novel simulator that combines two existing modeling frameworks: human-driven land use change (derived from the FORE-SCE model) with natural disturbances and vegetation dynamics (derived from the LADS model) and will incorporate novel feedbacks between human land use and natural disturbance regimes. The simulator is a raster-based, spatially explicit, stochastic computer model that combines a demand-allocation land use change model, a state-and transition for natural vegetation dynamics, and spatially explicit fire initiation and spread. The simulator is being designed to incorporate the effects of climate change, land management, and human demand on resource on land use over and natural vegetation dynamics to provide realistic, high resolution, and scenario-based land cover products. The simulator is a stand-alone program written in Visual C++ environment for use in Microsoft Windows Operating System environment, and in continuous development. This poster highlights the conceptual and technical design of the model integration.