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Policy makers need research based decision analysis models that include carbon sequestration and forest products in order to make policies that are both economically viable and effective. Forests and wood products have been identified as important mechanisms for carbon sequestration and storage. Policies often cover carbon sequestration but not product storage and substitution. Furthermore, many researchers have developed and published models on carbon management. However, a gap exists in operational level models that include product substitution. We developed a model to investigate optimal stand level management with competing objectives of maximizing soil expectation value, carbon storage in the forest, and carbon dioxide emission savings from product storage and substitution. Our purpose was to produce an accurate and usable analytical product for Southeastern U.S. foresters growing loblolly pine ( Pinus taeda) in the presence of carbon policies. The decision variables were traditional stand level management variables: planting density, thinning timing and density, and rotation length. Over time these variables influence the proportion of wood going into pulp, chip-n-saw, and sawtimber where each of these classes has an expected use (carbon storage) life. Compromise programming was employed to solve the multiple-objective problem and to demonstrate the tradeoffs between the competing objectives. This type of model demonstrates a practical method for comparing tradeoffs associated with adjusting forest management for a carbon market. The difference in costs among objectives is important for decision makers considering climate change policies, as it represents the minimum value a rational landowner would accept to sequester a unit of carbon. [ABSTRACT FROM AUTHOR]