Production possibility frontiers and socioecological tradeoffs for restoration of fire adapted forests

Abstract

We used spatial optimization to analyze alternative restoration scenarios and quantify tradeoffs for a large, multifaceted restoration program to restore resiliency to forest landscapes in the western US. We specifically examined tradeoffs between provisional ecosystem services, fire protection, and the amelioration of key ecological stressors. The results revealed that attainment of multiple restoration objectives was constrained due to the joint spatial patterns of ecological conditions and socioeconomic values. We also found that current restoration projects are substantially suboptimal, perhaps the result of compromises in the collaborative planning process used by federal planners, or operational constraints on forest management activities. The juxtaposition of ecological settings with human values generated sharp tradeoffs, especially with respect to community wildfire protection versus generating revenue to support restoration and fire protection activities. The analysis and methods can be leveraged by ongoing restoration programs in many ways including: 1) integrated prioritization of restoration activities at multiple scales on public and adjoining private lands, 2) identification and mapping of conflicts between ecological restoration and socioeconomic objectives, 3) measuring the efficiency of ongoing restoration projects compared to the optimal production possibility frontier, 4) consideration of fire transmission among public and private land parcels as a prioritization metric, and 5) finding socially optimal regions along the production frontier as part of collaborative restoration planning.

Modeling Fuel Treatment Leverage: Encounter Rates, Risk Reduction, and Suppression Cost Impacts

“…The optimization model generates efficient frontiers and quantifies tradeoffs across risk reduction and thinning volume production objectives. While similar to other recent work evaluating tradeoffs across spatial treatment strategies [44][45][46], our interest here is less in evaluating these tradeoffs per se, and more in generating plausible, efficient treatment strategies for further investigation in terms of leverage.…”

Assessing Wildland Fire Risk Transmission to Communities in Northern Spain

“…Understanding major large fire movements would provide a wider perspective to identify the nodes or high priority areas in the landscape requiring investments in treatments. Identification of treatment polygons or stands in priority areas (or firesheds) can be facilitated with optimization models and trade-off analysis to maximize the reduction in risk to multiple values of interest, including structure loss, game species habitat improvement or conifer timber production [91]. The risk assessment in this study should be considered as a preliminary step for mitigation and it does not necessarily reveal the optimal treatment allocation, especially considering that treating fuels at locations far from the urban interface can substantially slow large fire arrival [35].…”

Economic Opportunities and Trade-Offs in Collaborative Forest Landscape Restoration

“…We expanded the scale and scope compared to earlier work (Vogler et al, 2015) to quantify variability in production possibilities and decision trade-offs at the ecoregion. Optimization modeling was simplified compared to Ager et al (2016) concerning the same study area, by predefining planning areas rather than using spatial optimization algorithms to build them. This latter modification simplifies field application of our methods by restoration planners to prioritize projects on national forests.…”

“…We used restoration objectives described in Ager et al (2016) and further outlined in Appendix A. Individual forest stands (n = 204,610) were defined using corporate USDA Forest Service spatial databases.…”