CNH: Coupled Natural and Human Systems in Fire-Prone Landscapes: Interactions, Dynamics, and Adaptation

这个项目的重点是提高我们对生物物理系统、管理行动和社会经济影响如何相互作用以影响气候变化下易发火灾景观的可持续性的理解。这项工作将社会科学和生态科学结合起来，研究俄勒冈州中部的火灾易发景观，包括私人、州、联邦和部落土地。我们的方法将结合一个已建立的空间明确的、政策驱动的、多主体的土地管理决策模型、可以代表气候变化影响的植被演替和火灾着火/蔓延模型，以及一套社会经济和生态系统绩效的景观评估工具。该项目将把现有的生态系统研究与新的和正在进行的研究结合起来，这些研究描述了人类在这些景观中的偏好和价值观，以参数化人类决策的可辩护表示的多智能体模型。我们将扩展基于主体的模型的应用，以研究社会网络如何影响景观动态和适应，并利用蒙特卡罗技术探索不同政策和气候变化情景下的景观轨迹，以了解景观变化、土地管理政策策略、人类偏好和生态系统反馈的变/不变方面。这些分析将有助于确定管理策略，提高这些景观的适应能力，以应对不确定的未来。我们预计该项目将：1)揭示与易火景观相关的复杂系统行为，2)提高多所有权易火景观中森林管理政策的有效性，3)提高对社会网络（例如消防区域和环境组织）和经济力量在影响土地所有者和管理者如何在风险和不确定性下做出决策方面的作用的理解。4)提高对气候变化和碳市场外部力量如何影响政策结果、生物多样性和生态系统服务的理解。美国的野火政策支离破碎，很大程度上是因为土地和野火管理政策没有充分考虑到人类和生态的影响。通常，易发生火灾的景观被分为受消防管理机构影响的“荒地-城市界面”和受土地管理者影响的野生景观。这两个世界通常被认为在社会、经济和组织上是分开的，但它们显然是一个相互联系的景观的一部分。缺乏对这些联系的理解会导致政策无效，甚至适得其反。例如，灭火会增加火灾的严重程度，并将资源从荒野地区必要的生态恢复工作中抽离。当考虑到气候变化和碳市场时，适应容易发生火灾的景观的问题更具挑战性。为了制定更有效的政策，我们需要更好地了解社会系统——网络和机构——如何影响私人和公共土地所有者的行为。本研究将开发方法来描述这些社会系统及其与环境的相互作用，并利用这些信息来探索和测试改善景观的替代策略，同时最大限度地减少与野火相关的社会和经济成本。

This project focuses on improving our understanding of how biophysical systems, management actions, and socio-economic influences interact to affect sustainability in fire-prone landscapes under climate change. This work integrates 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. The project will 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 will extend the application of agent-based models to study how social networks influence landscape dynamics and adaptation, and 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 management strategies that increase adaptive capacity of these landscapes to respond to uncertain futures. We anticipate this project will: 1) reveal complex system behaviors associated with fire-prone landscapes, 2) improve effectiveness of forest management policies in multiownership fire-prone landscapes, 3) improve understanding of 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, and 4) improve understanding of how external forces of climate change and carbon markets could affect policy outcomes, biodiversity, and ecosystem services. Wildland fire policies in the U.S. are fragmented and broken, largely because land and wildfire management policies do not fully consider human and ecological effects. Typically, the fire-prone landscape is divided into a "wildland-urban interface" under the influence of fire management agencies, and a wild landscape under the influence of land managers. These two fire worlds are often seen as socially, economically, and organizationally separate, yet they are clearly part of a single interconnected landscape. Lack of understanding of these connections has lead to policies that are ineffective or even counterproductive. For example, fire suppression can increase the severity of fires and draws 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. In order to develop more effective policies, we need to improve our understanding of how social systems - networks and institutions - influence behavior in private and public landowners. This study will develop methods to characterize these social systems and their interactions with the environment, and use this information to explore and test alternative strategies that improve the landscape while minimizing the social and economic costs associated with wildfire.