|Yadav, V -|
|Del Grosso, Stephen|
|Parton, William -|
|Malanson, G -|
Submitted to: Journal of Land Use Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: January 3, 2008
Publication Date: March 1, 2008
Citation: Yadav, V., Del Grosso, S.J., Parton, W.J., Malanson, G.P. 2008. Adding ecosystem function to agent-based land use models. Journal of Land Use Science. 3, 27-40. Interpretive Summary: Ecosystem function outcomes, such as carbon and nitrogen fluxes, are becoming more important in agricultural land use decisions due to interests in maintaining soil fertility, sequestering carbon, and reducing greenhouse gas emissions. The decision-makers will have some ability to judge such outcomes based on experience, guidance from others, policy, or computer simulations but these produce only partial knowledge. In some cases, such as for carbon markets, the demand for specificity in ecosystem function may be high and some representation of ecosystem function outcomes is needed in to model land use change in a spatially explicit agent-based framework. Detailed biogeochemical models, such as Century, are the most effective way to calculate the ecosystem function, but these models require knowledge of different parameters and are computationally intensive. Given the large number of options that a modeler is faced with, the combinatorial problem makes the computational requirements prohibitive. More work is needed on the human decision process so that the actual number of options is limited. Lastly, the computational limitations found here are mostly in the organizing and managing of data for eventual use, which are as much a problem of human organizing ability as of computer storage. Anticipated improvements in computing ability would indicate that the limits of processing speed encountered in the fully integrated coupling should be less of an issue in the future.
Technical Abstract: The objective of this paper is to examine issues in the inclusion of simulations of ecosystem functions in agent-based models of land use decision-making. The reasons for incorporating these simulations include local interests in land fertility and global interests in carbon sequestration. Biogeochemical models are needed in order to calculate such fluxes. The Century model is described with particular attention to the land use choices that it can encompass. When Century is applied to a land use problem the combinatorial choices lead to a potentially unmanageable number of simulation runs. Century is also parameter-intensive. Three ways of including Century output in agent-based models, ranging from separately calculated look-up tables to agents running Century within the simulation, are presented. The latter may be most efficient, but it moves the computing costs to where they are most problematic. Concern for computing costs should not be a roadblock.