Coupled Natural and Human Systems

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View 2011 Seminar Series

Project Summary

Wildland fire policies in the U.S. are fragmented and broken and in need of integrated, socio-ecological understanding and solutions. Our current approaches to wildfire have been to separate the fire-prone landscape into a “wildland-urban interface” under the influence of fire management agencies, and a wild landscape under the influence of land managers. The two fire worlds are often seen as socially, economically, and institutionally separate, yet, they are clearly part of a single interconnected socio-ecological landscape. Lack of understanding of these connections has lead to policies that are suboptimal or even maladaptive. For example, fire suppression has increased the risk of high-severity fire and draws limited resources away from necessary ecological restoration work in wilder parts of the landscape. The problem of adaptation to fire-prone landscapes is even more challenging when climate change and carbon markets are considered. Developing more adaptive policies and actions is limited by lack of understanding of how social systems—networks and institutions—influence adaptive behavior in private and public landowners. This project would improve our understanding of how biophysical systems, management actions, and socio-economic influences interact to affect sustainability in fire-prone landscapes under climate change.

The goals of this research are to:

  1. Reveal complex system behaviors associated with fire-prone landscapes - an understudied type of coupled natural and human system (CNHS).
  2. Use collaborative learning and simulation models to improve the effectiveness of forest management policies in multi-ownership fire-prone landscapes.
  3. Understand the role of social networks (e.g. fire protection districts and environmental organizations) and economic forces in influencing how landowners and managers make decisions under risk and uncertainty.
  4. Understand how external forces of climate change and carbon markets could affect policy outcomes, biodiversity, and ecosystem services.

We integrate social and ecological sciences to study a fire-prone landscape in central Oregon that includes private, state, federal, and tribal lands. Our method will combine an established spatially explicit, policy-driven, multiagent model of land management decision-making, models of vegetative succession and fire ignition/spread that can represent climate change effects, and a suite of landscape evaluators of socio-economic and ecological system performance. We integrate existing studies of ecosystems with new and ongoing studies characterizing human preferences and values in these landscapes to parameterize the multiagent model with defensible representations of human decision-making. We extend the application of agent-based models to study how social networks influence landscape dynamics and adaptation. We explore landscape trajectories under alternative policy and climate change scenarios using Monte Carlo techniques to understand variant/invariant aspects of landscape change, land management policy strategies, human preferences, and ecosystem feedbacks. These analyses will help identify strategies that increase adaptive capacity.

Broader Impacts:

  1. Our novel collaborative learning effort produces valuable social information and also enables our findings to reach the landowners, managers, and institutions that have the greatest potential to change how humans adapt to fire-prone landscapes.
  2. Fire-prone landscapes are globally significant—our findings will be of interest to managers and scientists around the world.
  3. Inclusion of tribal lands will give broader recognition of the modern day role of Native Americans in natural systems.
  4. Software, spatial data bases, and web-based tools will enable stakeholders, managers, students, researchers, and secondary educators to better understand complex systems.
  5. An international workshop with scientists from Australia and other funded CNHS fire projects will broaden the scientific and social relevance of the work.
  6. Training and learning opportunities are created for undergraduates and graduate students.

 


Oregon State Univeristy
    
USDA Pacific Northwest
Research Station

 


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