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You are here: NRS Home / Research Programs /Forest Disturbance Processes / Science to support the National Fire and Fuels Strategy / Studying fire mitigation strategies in multi-ownership landscapes: Balancing management of fire-dependent ecosystems and fire risk.
Forest Disturbance Processes

Studying fire mitigation strategies in multi-ownership landscapes: Balancing management of fire-dependent ecosystems and fire risk

[photo:] Wild fire in an urban interface, Merrill, Wisconsin by Richard LavalleyResearch Issue

Fire risk mitigation within multi-owner landscapes containing flammable but fire-dependent ecosystems epitomizes the complexities of managing public lands.  The cumulative effects of fire and forest management over the last century have exacerbated fire risk in some regions and threatened fire-dependent systems in many others.  The issue is further complicated by the recent encroachment of human homes into fire prone ecosystems that simultaneously increase fire ignitions and increase demands on fire suppression agencies to protect lives and property.  Consequently, the balance between forest restoration, human rural development, and fire risk remains an issue of major concern to natural resource agencies.

Our Research

[photo:] Example fire probability map showing the spatial pattern of fire risk generated for the Lakewood study area, part of the Chequamegon-Nicolet National Forest. Wildland-Urban Interface is cross-hatched in black.

We worked with the Chequamegon-Nicolet National Forest (CNNF) to evaluate the relative effectiveness of four alternative fire mitigation strategies in an area of the CNNF where fire-dependent pine and oak systems overlap with a rapidly developing wildland urban interface (WUI) in northeastern Wisconsin.  Using the landscape disturbance and succession model, LANDIS, we integrated timber management of the current forest plan and empirical fire patterns to examine spatial interactions between human-caused ignitions, forest management, forest change, and fire risk.  Future work will integrate predicted rural development scenarios to investigate long-term interactions between human and forest processes as they affect fire risk and the persistence of fire-dependent communities.

Expected Outcomes

Simulation results suggested that reduction of ignitions caused by debris-burning had the strongest influence on fire risk, followed by the strategic redistribution of risky forest types away from the high ignition rates of the WUI.  Other treatments (fire breaks and reducing roadside ignitions) were less effective.  Simulations also showed that long-term maintenance of fire-dependent communities (i.e., pine and oak) representing the greatest forest fire risk requires active management.  Results will inform strategic planning efforts on the CNNF.

Research Results

Sturtevant, B.R., B.R. Miranda, J. Yang, H.S. He, E.J. Gustafson, R.M. Scheller.  2009.  Studying fire mitigation strategies in multi-ownership landscapes:  Balancing the management of fire-dependent ecosystems and fire risk.  Ecosystems 12: 445-461.

Miranda, B.R., Sturtevant, B.R., J.Yang, E.J. Gustafson.  2009. Contrasting fire spread algorithms using neutral landscape models. Landscape Ecology 24: 587-598.

Sturtevant, B.R. and D.T. Cleland.  2007. Human and biophysical factors influencing modern fire disturbance in Northern Wisconsin.  International Journal of Wildland Fire. 16: 398-413.

Gustafson, E.J., B.R. Sturtevant, and A. Fall. 2006.  A collaborative, iterative approach to transfer modeling technology to land managers.  In: A. Perera, L. Buse, and T. Crow (Eds.) Forest landscape ecology: Transferring knowledge to practice.  Springer Science+Business media, New York, NY, USA.

Research Participants

Principal Investigators

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Last Modified: 12/12/2016

Featured Product
Special Application

LANDIS - LANDIS is designed to model forest succession, disturbance (including fire, wind, harvesting, insects, global change), and seed dispersal across large (>1 million ha) landscapes. LANDIS represents landscapes as a grid of cells and tracks age cohorts of each species (presence/absence or biomass) rather than individual trees. LANDIS simulates distinct ecological processes, allowing complex interactions to play out as emergent properties of the simulation.

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