Search USGS⌕ Search
Home/Archive/USGS

USGS · 70242702

A simplified method for value of information using constructed scales

Michael C. Runge·Clark S. Rushing·James E. Lyons·Madeleine A. Rubenstein
View original source ↗Export metadata ↓

Abstract

The value of information is a central concept in decision analysis, used to quantify how much the expected outcome of a decision would be improved if epistemic uncertainty could be resolved prior to committing to a course of action. One of the challenges, however, in quantitative analysis of the value of information is that the calculations are demanding, especially in requiring predictions of outcomes as a function of alternative actions and sources of uncertainty. However, the concept of value of information is important in early framing of some decisions, before such predictions are available. We propose a novel measure of the value of information based on constructed scales (CVOI), grounded in the algebra of the expected value of perfect information (EVPI), but requiring less of experts and analysts. The CVOI calculation decomposes EVPI into a contribution representing the relevance of the uncertainty to the decision and a contribution representing the magnitude of uncertainty; constructed ratio scales are then proposed for each contribution. We demonstrate the use of CVOI to identify research priorities related to migratory bird management in the face of climate change.

Explore related subjects

Decision AnalysisArticle

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Michael C. Runge, Clark S. Rushing, James E. Lyons, Madeleine A. Rubenstein. 2023. A simplified method for value of information using constructed scales. https://doi.org/10.1287/deca.2023.0474

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related USGS reports

USGS2023

Lessons learned in applying decision analysis to natural resource management for high stakes issues surrounded by uncertainty

Management agencies are tasked with difficult decisions for conservation and management of natural resources. These decisions are difficult because of ecological and social uncertainties, the potential for multiple decision makers from multiple jurisdictions, and the need to account for the diverse values of stakeholders. Decision analysis provides a framework for accounting for these difficulties when making conservation and management decisions. We discuss the benefits of the application of decision analysis for these types of issues and provide insights from three case studies from the Laurentian Great Lakes. These case studies describe applications of decision analysis for decisions within an agency (management of double-crested cormorant), among agencies (response to invasive grass carp), and among agencies and stakeholders (sustainable fisheries harvest management). These case studies provide insight into the ways that decision analysis can be useful for conservation and management of natural resources, but we also highlight future needs for decision making for these resources. In particular, applications of decision analysis for conservation and management would benefit from enhanced integration of both ecological and social science, inclusion of a broader base of stakeholders and rightsholders, and better educational opportunities surrounding decision analysis for undergraduates and graduate students of natural resources management programs. Specific lessons from our experiences include the importance of establishing trust and transparency early through the formation of a working group, collaboratively defining objectives and evaluating uncertainties, risks, and tradeoffs, and implementing participatory modeling processes with an independent facilitator with appropriate quantitative skills.

Decision Analysis↗
USGS2023

Prioritization of species status assessments for decision support

Species status assessments are used to inform U.S. Fish and Wildlife Service (USFWS) decision making for Endangered Species Act (ESA) classification decisions, recovery planning, and more. The large number of species that require assessment and uncertainty in the data available impede the process of assigning and completing the assessments, which makes creating a multiyear work plan extremely difficult. An optimized triaging system that maximizes the use of the best available information while managing the complex ESA workload and meeting deadlines is necessary. We used a structured decision-making framework to approach the problem with the goal of creating a prioritization tool that would be effective at scheduling assessments, given the best information available and priorities of the USFWS. We collected data on the species awaiting assessment and developed a value function that incorporates existing deadlines, taxonomic uncertainty, controversy of the species, and population and habitat data availability and quality. We used a constrained linear optimization algorithm to maximize the value function and ensure that workload capacity was not exceeded. A comparison of model scenarios indicates that imposed deadlines impact the model more than capacity constraints. Additionally, differential weighting of the metrics significantly affected the outcome of the model. In the future, elicitation of metric weights should be done routinely before the model is run for use in official planning to ensure alignment with current USFWS priorities. Output from this optimization can be used to inform a five-year work plan, allocate resources, and discuss workforce decisions.

Decision Analysis↗
USGS2023

Using decision analysis to determine the feasibility of a conservation translocation

Conservation translocations, intentional movements of species to protect against extinction, have become widespread in recent decades and are projected to increase further as biodiversity loss continues worldwide. The literature abounds with analyses to inform translocations and assess whether they are successful, but the fundamental question of whether they should be initiated at all is rarely addressed formally. We used decision analysis to assess northern leopard frog reintroduction in northern Idaho, with success defined as a population that persists for at least 50 years. The Idaho Department of Fish and Game was the decision maker (i.e., the agency that will use this assessment to inform their decisions). Stakeholders from government, indigenous groups, academia, land management agencies, and conservation organizations also participated. We built an age-structured population model to predict how management alternatives would affect probability of success. In the model, we explicitly represented epistemic uncertainty around a success criterion (probability of persistence) characterized by aleatory uncertainty. For the leading alternative, the mean probability of persistence was 40%. The distribution of the modelling results was bimodal, with most parameter combinations resulting in either very low (<5%) or relatively high (>95%) probabilities of success. Along with other considerations, including cost, the Idaho Department of Fish and Game will use this assessment to inform a decision regarding reintroduction of northern leopard frogs. Conservation translocations may benefit greatly from more widespread use of decision analysis to counter the complexity and uncertainty inherent in these decisions.

Decision Analysis↗