Addressing multi-use issues in sustainable forest management with signal-transfer modeling
Management decisions concerning impacts of projected changes in environmental and social conditions on multi-use forest products and services, such as productivity, water supply or carbon sequestration, may be facilitated with signal-transfer modeling. This simulation method utilizes a hierarchy of simulators in which the integrated responses (signals) from smaller- scale process models are transferred and incorporated into the algorithms of larger spatial- and temporal-scale models of ecological and economic phenomena. Several innovative procedures germane to multi-issue sustainable forest management have been initiated in our signal-transfer modeling development for forests of the southeastern United States. These developments include response surface interpolation for multi-factor signal-transfer, use of loblolly pine modeling to infer the growth of other southern pines, determination of soil nutrient limitations to productivity, multivariate clustering as a spatial basis for defining land units relevant to forest management, and variance propagation through the modeling hierarchy. Algorithms for larger scale phenomena are shown to constrain the variance introduced from a smaller-scale in a simulation of ambient ozone exposure effects on loblolly pine timber yield. Outputs of forest variables are frequency distributions that may be statistically compared for alternative environmental or management scenarios.