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Scenario Investment Planning Platform

This research concerns the development and application of spatial scenario planning models to analyze a wide range of forest and restoration management issues on fire frequent landscapes.

US public land management agencies are faced with multiple and often conflicting objectives to meet management targets and produce a wide range of ecosystem services expected from public lands. To understand how these conflicts play out on large fire frequent landscapes we built a spatial scenario planning model (FORSYS) and used to in several case studies to examine how different management priorities translate into landscape change. The model was designed to explore landscape management scenarios and optimize decisions in terms of where and how to achieve different outcomes and outputs at different scales. We are studying these management tradeoffs by simulating a wide range of management scenarios where activities are prioritized according to multiple agency land assessments on wildfire risk, economic opportunity, and ecological conditions.

The Forest Service invests in vegetation management programs with the long-term goal of restoring fire resiliency to fire frequent forests, protecting communities from wildfire, improving forest health, and providing economic opportunities for rural communities. The multiple and conflicting objectives of restoration and forest management programs coupled with finite budgets and a large backlog of areas needing treatments have created a challenge for managers to prioritize management efforts and allocate funding to high priority areas. The need for prioritization models continues to grow as the agency is increasingly challenged to meet management targets and produce a wide range of ecosystem services from national forest lands. Explicit identification of tradeoffs among program areas for fuels, timber, watersheds, and forest health at the scale of national forests and regions can potentially have manifold benefits to the agency in terms of articulating current and alternative investment strategies. Prioritization models are also needed to address shared stewardship goals for co-prioritization of projects as specified in MOUs with State partners. While the Forest Service has used many forms of scenario planning approaches in the past, (e.g. forest plans), the science is underutilized in current agency planning activities, both within the agency and in co-prioritization activities with stakeholders. Currently, there does not exist a comprehensive scenario planning framework that can be readily applied across forests and regions with existing data to quickly analyze priorities and tradeoffs. Existing ad hoc GIS overlay tools that are widely used do not predict outcomes from management activities, nor do they provide a way to measure tradeoffs and explore optimal solutions. These gaps are being addressed in the current research through the Scenario Investment Planning Project (SIPP), a project jointly sponsored by Forest Service Research and Development, the National Forest System, and State & Private Forestry. The project is an interdisciplinary project that brings together scientists from landscape planning, fire ecology, operations research, and economics to create a work bench to explore a wide range of investment strategies.

A new spatial scenario modelling platform (“ForSys”) was developed that can analyze prioritization problems at multiple scales ranging from planning areas to districts, forests and regions. The system simulates the implementation of specific priorities and examines the rate of achieving specific outcomes. In this way, planners and managers can examine how shifting investments strategies affect outputs and outcomes on the ground. The model can integrate national and local assessments (e.g. terrestrial condition, wildfire hazard, insect and disease, harvest volume) to explore how alternative short-range (1-5 year) prioritizations among forest and regions affect the rate of achieving specific outcomes (e.g., reduced wildfire risk). While ForSys is a standalone model, it was designed as a modelling workbench to integrate other models to predict how action leads to outcomes. It is best viewed as an integration framework with the ultimate goal of creating an enterprise system that can be used both within and outside the agency.

  • The system has been used in several scientific assessments to demonstrate the utility of scenario planning as a tool to simulate the implementation of Forest Service program direction and examine outcomes from a range of management scenarios.
  • Prioritizing treatments to reduce fire transmission to the wildland urban interface substantially reduces timber revenue and the harvest volume per unit area.
  • Production frontiers are scale dependent and are highly variable among planning areas and national forests, and point to specific spatial priorities and opportunities to achieve restoration goals
  • Locally optimal production, as determined by collaborative groups or by optimal joint production on a PPF, may not lead to optimal outcomes at larger (e.g., agency wide) scales. The former maximizes the utility of stakeholder preferences, but may lead to inefficient outcomes at larger scales.
  • The economic viability of restoration projects is tenuous under current practices, and optimizing revenue to help finance restoration projects leads to a sharp reduction in the attainment of other socioecological objectives, especially reducing forest departure from historical conditions
  • Outputs from the model were used to prioritize a portion of the FY18 and FY20 hazardous fuels budget.
  • The development team is currently working with selected regions to refine inputs and tailor the system to meet regional needs. Pilot projects are underway on several national forests as well.
  • Modeling facsimile projects within planning areas using stand-scale data captured local spatial variation in economic parameters that are potentially not represented in assessment using gridded forest inventory data.
  • The modelling system has been applied in several international settings to analyze similar management issues on fire prone landscapes.

The longer goal of this work is to build a scenario planning system that integrates numerous assessments of land conditions with foundational databases on economics, NEPA capacity, operational constraints, and land management planning. The system will support a wide range of prioritization activities and predict outcomes of forest management activities.

Image: Comparison of production possibility frontiers between optimal simulated and actual restoration projects

Comparison of production possibility frontiers between optimal simulated and actual restoration projects in the Blue Mountain National Forests. Red symbols show the production from actual projects. Production frontiers are noted for the highest and lowest priority out of 20 simulated projects optimized for producing eityher harvest volume, ttreating ecological departure, or both. Comparisons between optimal and restration management projects are rare to nonexistant.

Image: Comparison of net revenue and restoration attainment among planning areas under alternative prioritization scenarios

Comparison of net revenue and restoration attainment among planning areas under alternative prioritization scenarios. A) Cumulative attainment of the five objectives when each of them are individually prioritized; B) same as A when revenue is prioritized; C) the revenue associated with levels of attainment when each of the objectives are prioritized; and D) cumulative revenue as a function of total area treated. Attainment is measured as the total inventoried quantity of each of the restoration goals on the landscape.

Image: Production possibility frontiers (PPF) for each of the 102 planning areas in the Blue Mountains

Production possibility frontiers (PPF) for each of the 102 planning areas in the Blue Mountains for revenue from treatment versus each of the other restoration objectives: A) forest departure, B) insect risk, C) structure exposure in the wildland urban interface from national forest (NF) ignited wildfires, and D) wildfire hazard. PPFs are generated by optimizing the selection of stands to address one or the other or both of the restoration objectives in each panel. Convex and symmetrical curves indicate opportunity for restoration to accomplish multiple objectives. Asymmetrical curves show that optimal joint production favors one objective over the other.

Modified: May 19, 2020

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SIPP Website: https://usfs-gis-dev.esriemcs.com/portal/apps/MapSeries/index.html?appid...

Ager, A. A., M. A. Day, and K. Vogler. 2016. Production possibility frontiers and socioecological tradeoffs for restoration of fire adapted forests. Journal of Environmental Management 176:157-168. https://www.fs.usda.gov/treesearch/pubs/52994

Ager, A. A., M. A. Day, A. E. M. Waltz, M. Nigrelli, and M. Lata. In review. Optimizing ecological and economic objectives in restoration of fire frequent forests. Gen. Tech. Rep. RMRS-GTR-XXX, USDA Forest Service, Rocky Mountain Research Station, Fort Collins, CO. https://www.fs.usda.gov/treesearch/pubs/39604

Ager, A. A., R. Houtman, M. A. Day, C. Ringo, and P. Palaiologou. 2019. Tradeoffs between US national forest harvest targets and fuel management to reduce wildfire transmission to the wildland urban interface. Forest Ecology and Management 434:99-109. https://www.fs.usda.gov/treesearch/pubs/57897

Ager, A. A., N. M. Vaillant, and M. A. Finney. 2010. A comparison of landscape fuel treatment strategies to mitigate wildland fire risk in the urban interface and preserve old forest structure. Forest Ecology and Management 259:1556-1570. https://www.fs.usda.gov/treesearch/pubs/39604

Ager, A. A., N. M. Vaillant, and A. McMahan. 2013. Restoration of fire in managed forests: a model to prioritize landscapes and analyze tradeoffs. Ecosphere 4: 29. https://www.fs.usda.gov/treesearch/pubs/48615.

Ager, A. A., K. C. Vogler, M. A. Day, and J. D. Bailey. 2017. Economic opportunities and trade-offs in collaborative forest landscape restoration. Ecological Economics 136:226-239. https://www.fs.usda.gov/treesearch/pubs/54922

Vogler, K. C., A. A. Ager, M. A. Day, M. Jennings, and J. D. Bailey. 2015. Prioritization of forest restoration projects: tradeoffs between wildfire protection, ecological restoration and economic objectives. Forests 6:4403–4420. https://www.fs.usda.gov/treesearch/pubs/52992

Salis, M., M. Laconi, A. A. Ager, F. J. Alcasena, B. Arca, O. Lozano, A. Fernandes de Oliveira, and D. Spano. 2016. Evaluating alternative fuel treatment strategies to reduce wildfire losses in a Mediterranean area. Forest Ecology and Management 368:207-221.

Salis, M., L. Del Guiudice, B. Arca, A. A. Ager, F. Alcasena, O. Lozano, V. Bacciu, D. Spano, and P. Duce. 2018. Modeling the effects of different fuel treatment mosaics on wildfire spread and behavior in a Mediterranean agro-pastoral area. Journal of Environmental Management 212:490-505.

Alcasena, F. J., A. A. Ager, M. Salis, M. A. Day, and C. Vega-Garcia. 2018. Optimizing prescribed fire allocation for managing fire risk in central Catalonia. Science of the Total Environment 4:872-885.

Alcasena, F. J., A. A. Ager, J. D. Bailey, N. Pineda, and C. Vega-Garcia. 2019. Towards a comprehensive wildfire management strategy for Mediterranean areas: Framework development and implementation in Catalonia, Spain. Journal of Environmental Management 231:303-320.

Martín, A., B. R. Botequim, T. M. Oliveira, A. A. Ager, and F. Pirotti. 2016. Temporal optimization of fuel treatment design in blue gum (Eucalyptus globulus) plantations. Forest Systems 25(2): eRC09-eRC09. doi: 10.5424/fs/2016252-09293