Using an agent-based model to examine forest management outcomes in a fire-prone landscape in Oregon, USA

Abstract

. 2017. Using an agent-based model to examine forest management outcomes in a fire-prone landscape in Oregon, USA. Ecology and Society 22 (1) ABSTRACT. Fire-prone landscapes present many challenges for both managers and policy makers in developing adaptive behaviors and institutions. We used a coupled human and natural systems framework and an agent-based landscape model to examine how alternative management scenarios affect fire and ecosystem services metrics in a fire-prone multiownership landscape in the eastern Cascades of Oregon. Our model incorporated existing models of vegetation succession and fire spread and information from original empirical studies of landowner decision making. Our findings indicate that alternative management strategies can have variable effects on landscape outcomes over 50 years for fire, socioeconomic, and ecosystem services metrics. For example, scenarios with federal restoration treatments had slightly less high-severity fire than a scenario without treatment; exposure of homes in the wildland-urban interface to fire was also slightly less with restoration treatments compared to no management. Treatments appeared to be more effective at reducing high-severity fire in years with more fire than in years with less fire. Under the current management scenario, timber production could be maintained for at least 50 years on federal lands. Under an accelerated restoration scenario, timber production fell because of a shortage of areas meeting current stand structure treatment targets. Trade-offs between restoration outcomes (e.g., open forests with large fire-resistant trees) and habitat for species that require dense older forests were evident. For example, the proportional area of nesting habitat for northern spotted owl (Strix occidentalis) was somewhat less after 50 years under the restoration scenarios than under no management. However, the amount of resilient older forest structure and habitat for white-headed woodpecker (Leuconotopicus albolarvatus) was higher after 50 years under active management. More carbon was stored on this landscape without management than with management, despite the occurrence of high-severity wildfire. Our results and further applications of the model could be used in collaborative settings to facilitate discussion and development of policies and practices for fire-prone landscapes.

A Model-Based Framework to Evaluate Alternative Wildfire Suppression Strategies

“…Capturing the full set of temporal feedbacks resulting from alternative fire suppression strategies remains a challenge. For instance, models that update the landscape file to reflect burned area and vegetation succession would be a powerful way to examine temporal feedbacks in future work, but come with additional computational challenges and numerous inherent uncertainties [40,97].…”

Integrating social science into empirical models of coupled human and natural systems

“…We found that some of these factors operate as two-way feedbacks, which influence actors' forest management and wildfire risk mitigation activities, which in turn influence biophysical (e.g., vegetation, fuel) conditions. We were able to use qualitative and quantitative data and hypothesis testing, rather than relying on purely theoretical assumptions, to develop predictive models of actor behavior to aid in simulating CHANS dynamics over time in an ABM (e.g., Spies et al 2017). However, much of our social science research also involved developing a fundamental understanding of the social landscape of this fire-prone CHANS, including identifying key actors and the biophysical and socioeconomic factors that influence them.…”

“…Details about these decision rules can be found in Spies et al (2017). We developed decision rules for federal and state land managers, tribes, and corporate forest landowners as sets of heuristics that reflected manager interviews, existing management plans, planning documents, and expert opinion (Table 3).…”

“…Our social science team spanned anthropology, economics, environmental history, political science, and sociology. Details about the CHANS project, ABM, and landscape simulations can be found in Barros et al (2017), Spies et al (2017), and Shindler et al (2017). Details about individual social science contributions can be found in Charnley et al (2017), Olsen et al (2017), andSteen-Adams et al (2017).…”

Historical perspective on the influence of wildfire policy, law, and informal institutions on management and forest resilience in a multiownership, frequent-fire, coupled human and natural system in Oregon, USA

“…Wildfire-resilient structural attributes are based on historic forest conditions and fire regimes (Hagmann et al 2014; for details of forest metrics, see Spies et al 2017). Current forest structure was characterized using the gradient nearest neighbor method (Ohmann et al 2011) based on 2008 imagery and inventory plots ).…”