Scenario-Based Framework For Resource Management Under Uncertain Climatic Futures

October 2, 2023 Kristen Fontana

Sunset, DeKalb County, Georgia. Image by Alan Cressler (USGS).

A SE CASC supported publication, Scenario-Based Decision Analysis: Integrated Scenario Planning and Structured Decision Making for Resource Management under Climate Change was recently published to Biological Conservation. SE CASC Research Ecologist Mitch Eaton is co-author with Brian Miller from the North Central CASC and others from CU-Boulder, the National Park Service, and USGS.

Recent SE CASC supported research develops a new generalized framework, Scenario-Based Decision Analysis (SBDA), to assist resource management under a changing climate and enhance decision support for climate-focused problems.

Planning for and adapting to climate change is all but simple. With the uncertainty of future climate projections compounding the complexity of competing management objectives, it becomes difficult for resource managers to identify effective climate adaptation responses. “We have a number of useful decision frameworks and tools available to researchers and managers for aiding complex decisions,” says co-author Mitch Eaton.

Climate uncertainties are intensified by the range of potential biophysical responses to a changing environment, necessitating flexible decision tools to address “wicked problems” in climate change adaptation. Eaton adds, “Climate change presents new challenges in the form of uncertainty, risk, and implementing actions whose success or failure may be difficult to assess for years or decades.” Existing decision frameworks include scenario planning (SP) and structured decision making (SDM), but each has its limitations when it comes to confronting climate change.

“The authors of this paper have a good deal of experience applying a number of these tools, primarily scenario planning and decision analytic methods, such as adaptive management and structured decision making (SDM),” says Eaton. This paper explores the strengths and weaknesses of these approaches and proposes a new generalized framework that draws on both of their strengths to develop a Scenario-Based Decision Analysis (SBDA).

Scenario planning is a well-established method for assessing system responses and supporting decision making under a range of uncertain and uncontrollable conditions. A key limitation of this approach is the absence of a defined structure for establishing objectives, quantifying tradeoffs, and evaluating the performance of decisions pursued to meet those objectives. Structured decision making is rooted in decision theory and generally relies on a quantitative assessment of expected outcomes. This approach, however, has been criticized for its inability to account for surprises, simplification of system components, and for its overly narrow framing of problems.

On their own, structured decision making and scenario planning are insufficient for decision making under situations with high uncertainty and low objective clarity (Figure 2). Therefore, researchers proposed a new approach: Scenario-Based Decision Analysis (SBDA). This method is a generalized and analytical framework that incorporates the strengths of both SP and SDM to better inform resource management decision making under climate change. SBDA identifies resource management problems and solutions while also considering potential uncertainties and surprises. See Figure 1 for a depiction of the Scenario-Based Decision Analysis (SBDA) framework integrating SDM and SP.

Figure 1. The Scenario-Based Decision Analysis (SBDA) framework for integrating SDM (black) and SP (white). Grey circles and arrows indicate hybrid steps in the process.

***Figure 2.*** *SBDA, SP, and SDM performance under different levels of objective clarity and uncertainty.*

Resource management with highly uncertain climatic futures requires novel thinking and a breadth of analytical tools. While scenario planning and structured decision making are useful frameworks for identifying and preparing for such unknown futures, they do come with their limitations. Scenario-Based Decision Analysis was developed to integrate the strengths of both of these approaches to help guide scientists, managers, and stakeholders as they identify and pursue adaptation efforts under an uncertain future.

The study, “Scenario-Based Decision Analysis: Integrated Scenario Planning and Structured Decision Making for Resource Management under Climate Change,” was published online September 29, 2023, in Biological Conservation. Authors are Brian W. Miller, Mitchell J. Eaton, Amy J. Symstad, Gregor W. Schuurman, Imtiaz Rangwala, William R. Travis.

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Note to Editors: The study abstract follows.

“Scenario-Based Decision Analysis: Integrated Scenario Planning and Structured Decision Making for Resource Management under Climate Change“

Authors: Brian W. Miller, Mitchell J. Eaton, Amy J. Symstad, Gregor W. Schuurman, Imtiaz Rangwala, William R. Travis

DOI: https://doi.org/10.1016/j.biocon.2023.110275

Abstract: Managing resources under climate change is a high-stakes and daunting task, especially because climate change and associated complex biophysical responses engender sustained directional changes as well as abrupt transformations. This environmental non-stationarity challenges assumptions and expectations among scientists, managers, rights holders, and stakeholders. These challenges are anything but straightforward – a high degree of uncertainty impedes our ability to predict the environmental trajectory with confidence, and affected resources often span multiple governance jurisdictions or are subject to competing management objectives. Fortunately, tools exist to help grapple with such challenges. Two commonly used tools are scenario planning (SP) and structured decision making (SDM). SP is a well-established approach for assessing system response and facilitating decision making under a wide range of conditions that are uncertain and uncontrollable, such as those associated with adapting to climate change. However, SP lacks a defined structure for establishing objectives, quantifying tradeoffs, and evaluating the performance of candidate decisions to meet those objectives. SDM, on the other hand, is rooted in decision theory and focuses on explicit (often quantitative) assessment of the expected outcomes of choosing among a set of decision alternatives. SDM has been criticized for an inability to account for surprises and for imposing an overly narrow framing of problems to increase tractability. We discuss the strengths and limitations of SDM and SP as experienced through their application in various resource-management contexts, and then propose a new generalized framework – Scenario-Based Decision Analysis (SBDA) – that integrates these complementary approaches. SBDA structures resource management problems and solutions while considering uncertainties and surprises to inform resource management decision making.