This paper proposes an integrated, conceptual framework that forest managers can use to simulate the multiple objectives/indicators of sustainability for different spatial patterns of forest management practices under alternative futures, rank feasible (affordable) treatment patterns for forested areas, and determine if and when it is advantageous to adapt or change the spatial pattern over time for each alternative future. The latter is defined in terms of three drivers: economic growth; land use policy; and climate change. Four forest management objectives are used to demonstrate the framework, minimizing wildfire risk and water pollution and maximizing expected net return from timber sales and the extent of potential wildlife habitat. The fuzzy technique for preference by similarity to the ideal solution is used to rank the feasible spatial patterns for each subperiod in a planning horizon and alternative future. The resulting rankings for subperiods are used in a passive adaptive management procedure to determine if and when it is advantageous to adapt the spatial pattern over subperiods. One of the objectives proposed for the conceptual framework is simulated for the period 2010–2059, namely, wildfire risk, as measured by expected residential losses from wildfire in the wildland-urban interface for Flathead County, Montana. 1. Introduction Maintaining the long-term sustainability of forest ecosystems is challenging due to uncertainty about future changes in socioeconomic, biophysical, and other conditions that influence the achievement of forest management objectives. Several studies have proposed management strategies to enhance the capacity of forest ecosystems to respond or adapt to new or changing conditions or, equivalently, to increase the resilience of forest ecosystems to change [1–6]. Most studies of this sort focus on how changes in just one condition influence a particular management objective (e.g., how landscape fragmentation resulting from residential development degrades wildlife habitat or how increases in temperature resulting from climate change influence the distribution of tree species). Few studies have assessed how multiple socioeconomic, biophysical, and other conditions influence the multiple objectives for which many forests are managed. This deficiency may be due, in part, to the lack of an integrated conceptual framework that forest managers can use to evaluate the impacts of multiple conditions on multiple forest management objectives and how best to adapt forest management practices to uncertain future changes in those
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