Fire-prone landscapes as coupled human natural systems: An example from the eastern Cascades of Oregon

Background/Question/Methods The U.S. approach to dealing with wildfire is typically to fragment the fire-prone landscape (FPL) into a “wildland-urban interface (WUI)” under the influence of local fire management agencies and a fire-prone wildland under the influence of land managers.  These two fire worlds are often seen as socially, economically and ecologically separated, yet, they are clearly part of a single interconnected socio-ecological landscape.  Lack of understanding of these connections can lead to policies that are suboptimal or even maladaptive.  For example, emphasis on protecting property in the WUI can in some cases draw limited resources away from necessary ecological restoration work in wilder parts of the landscape.  Despite the importance of this coupled-human and natural system (CHANS), few studies of FPLs have been conducted by integrated teams of social and ecological scientists.  Our goal is to use systems models, integrated research, and collaborative learning to improve our understanding of adaptation to FPLs in central and south central Oregon.  We have developed conceptual models and identified potential positive and/or weak feedbacks that might lead to maladaptive policies.  We are using this conceptual model to guide empirical studies and design a simulation model to foster understanding of this CHANS.

Results/Conclusions The conceptual model we developed is based on existence of interconnections across ownerships as well as feedbacks between the natural and human subsystems. We are finding that feedbacks from the human system to the natural system are more easily modeled than are feedbacks from the natural system to the human system.  For example, we are able to model how homeowners and land managers manipulate vegetation to reduce risk of loss of values to high intensity fire.  However, it is less clear how to model the process of human learning about and response to changes in forest conditions, perceived fire risk, and actual fire events.  Our conceptual model suggests that slow or incorrect learning or poor dissemination of knowledge about the effects of vegetation treatments and/or wildfire suppression on forests or fire outcomes may limit the ability of humans to develop adaptive behaviors.  We hypothesize that the structure of social networks around forests and fire may act to amplify weak or intermittent signals from a FPL to humans and improve dissemination of scientific knowledge and thus improve the capacity for adaptation in these environments.  We demonstrate a prototype spatial agent-based landscape model that could facilitate understanding of socio-ecological processes in this CHANS.