Robinson, Kelly F.; Baker, Erin; Ewing, Elizabeth; Hemming, Victoria; Kenney, Melissa A.; Runge, Michael C.
doi: 10.1287/deca.2023.intro.v20.n4pmid: N/A
Decision analysis provides a robust framework for complex decisions related to environmental sustainability and conservation, including for energy and water, fisheries and wildlife management, agriculture, and climate change response. The complexities of these problems stem from their large scope and scale, which leads to multiple decision makers, stakeholders, rightsholders, and other entities with potentially competing objectives. These problems often are time limited (e.g., urgent action is required to prevent species’ extinction), involve management interventions over long time scales and delayed responses to management (deep uncertainty), and are impeded by limited resources (funding, capacity, etc.). In this Special Issue on “Decision Analysis to Advance Environmental Sustainability,” we present five case studies of applications of decision analysis to complex problems in environmental sustainability and conservation. These case studies incorporate multiple objectives related to ecological and environmental sustainability, economic and social concerns, and logistics of implementation. They showcase a wide range of tools and applications to these problems. We also provide suggestions for new avenues of research and application of decision analysis to problems of environmental sustainability and conservation, including how to incorporate other decision-making tools into decision analysis processes, how to broaden the reach of decision analysis to other sustainability problems, how to incorporate more stakeholders and rightsholders into the decision process, the potential to incorporate new technology into these processes, identifying more creative alternatives, how to secure more funding, ways to move from decision to action, and how to move beyond status quo to make big transitions necessary to achieve sustainability.
Contasti, Adrienne L.; Firth, Alexandra G.; Baker, Beth H.; Brooks, John P.; Locke, Martin A.; Morin, Dana J.
doi: 10.1287/deca.2023.0478pmid: N/A
There is a need to achieve sustainable agricultural production to secure food, fiber, and fuel for a growing global population. Climate-smart (CS) actions (no-till and cover crops) can reduce carbon emissions and promote soil organic carbon (SOC) storage. Contemporary voluntary carbon markets provide producers with a monetary incentive to adopt CS actions. However, SOC–yield dynamics under CS actions are not well known, making it difficult for producers to judge whether additional income from carbon credits will offset potential losses to yield income. We designed a SOC–yield framework that captures SOC–yield–income dynamics under traditional (reduced tillage, no cover crops) and CS actions. Using a modified structured decision-making approach, we applied the framework to a case study in which producers aim to increase income by selling carbon credits after adopting CS actions. Specifically, we demonstrated how to balance tradeoffs between yield and carbon credit income that arise from tillage and winter cover crop actions (cereal rye, Secale cereale L. and crimson clover, Trifolium incarnatum L.) in a soybean (Glycine max L.) production system in Mississippi. Results indicated that a producer could minimize losses to net yield income by adopting no-till if already using cover crops. There was also evidence that carbon credit income could offset losses to yield income when adopting CS in place of traditional actions. Identifying risks to yield income and SOC storage can help design carbon neutrality policies that have minimum impact on a producer’s income.History: This paper has been accepted for the Decision Analysis Special Issue on Decision Analysis to Advance Environmental Sustainability.Funding: This work was supported by the USDA-ARS [Grants 58-0200-0-002 (Advancing Agricultural Research) and 58-6001-8-003] and the USDA National Institute of Food and Agriculture [McIntire Stennis Project 1020959].Supplemental Material: The online appendix is available at https://doi.org/10.1287/deca.2023.0478.
Belval, Erin J.; Thompson, Matthew P.
doi: 10.1287/deca.2022.0047pmid: N/A
In recent years, the state of Colorado has experienced extreme wildfire events that have degraded forest and watershed health and devastated human communities. With expanding human development and a changing climate, wildfire activity is likely to increase, and wildfire management agencies will be challenged to sustain landscapes and the ecosystem services they provide. A critical element of the United States’ federal-, state-, and local-level multiagency wildfire response is the interagency dispatching system, which facilitates the ordering, mobilization, and tracking of firefighting resources to and from wildfire incidents—a role that is likely to increase in both importance and workload in the future. Given increasing demands, it is worth considering ways to improve efficiencies, capacity, and capability within the current Colorado dispatching system. With this, the Rocky Mountain Coordinating Group (RMCG) and the Rocky Mountain Area Fire Executive Council (RMA-FEC) sought to reorganize the dispatching system, beginning with exploration of changes to dispatching zone boundaries and the number and location of dispatching centers throughout the state. Here we describe a multiyear research–management partnership with the RMCG and RMA-FEC to apply a structured decision-making process to guide this reorganization effort. We highlight the steps used in a participatory process that involved local decision makers and included iteratively revising and clarifying the problem statement, developing objectives and translating them into measurable attributes, building a multiobjective optimization model to generate and compare alternatives, and communicating a recommended alternative that was ultimately adopted. To conclude, we discuss insights from our experience and highlight opportunities for similar work to support efficient wildfire management elsewhere in the United States.History: This paper has been accepted for the Decision Analysis Special Issue on Decision Analysis to Advance Environmental Sustainability.Funding: This research was supported by the U.S. Department of Agriculture Forest Service.
Keating, Laura M.; Randall, Lea; Stanton, Rebecca; McCormack, Casey; Lucid, Michael; Seaborn, Travis; Converse, Sarah J.; Canessa, Stefano; Moehrenschlager, Axel
doi: 10.1287/deca.2023.0472pmid: N/A
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.History: This paper has been accepted for the Decision Analysis Special Issue on Decision Analysis to Advance Environmental Sustainability.Funding: This work was supported by the Wilder Institute/Calgary Zoo, the U.S. Fish and Wildlife Service [Grant F18AS00095], the NSF Idaho EPSCoR Program and the National Science Foundation [Grant OIA-1757324], and the Hunt Family Foundation.Supplemental Material: The online appendix is available at https://doi.org/10.1287/deca.2023.0472.
Goode, Ashley B. C.; Rivenbark, Erin; Gilbert, Jessica A.; McGowan, Conor P.
doi: 10.1287/deca.2023.0026pmid: N/A
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.History: This paper has been accepted for the Decision Analysis Special Issue on Decision Analysis to Advance Environmental Sustainability.Funding: This work was funded via an inter-agency agreement between the USFWS and the USGS and subsequently by a Research Work Order contract between the USGS and the University of Florida [Grant G21AC00016].
Robinson, Kelly F.; DuFour, Mark R.; Fischer, Jason L.; Herbst, Seth J.; Jones, Michael L.; Nathan, Lucas R.; Newcomb, Tammy J.
doi: 10.1287/deca.2023.0015pmid: N/A
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.History: This paper has been accepted for the Decision Analysis Special Issue on Decision Analysis to Advance Environmental Sustainability.Funding: This study was supported by Great Lakes Restoration Initiative funding provided to the Michigan Department of Natural Resources [Grant F16AP01094] from the U.S. Fish and Wildlife Service and sub-awarded to Michigan State University.
doi: 10.1287/deca.2023.reviewthx.v20.n4pmid: N/A
Vicki Bier, the Editor-in-Chief of Decision Analysis, thanks the referees who generously provide expert counsel and guidance on a voluntary basis. Without them, the journal could not function. The following list acknowledges those individuals who acted as referees for papers considered during calendar year 2023.
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