Structured Decision-making Framework Research Articles

Indigenous-led designation and management of culturally significant species.

Indigenous peoples globally are actively seeking better recognition of plants and animals that are of cultural significance, which encompass both species and ecological communities. Acknowledgement and collaborative management of culturally significant entities in biodiversity conservation improves environmental outcomes as well as the health and wellbeing of Indigenous people. The global diversity and complexity of Indigenous knowledge, values and obligations make achieving a universal approach to designating culturally significant entities highly unlikely. Instead, empowering local Indigenous-led governance structures with methods to identify place-based culturally significant entities will yield culturally supported results. Here we used a structured decision-making framework with objectives and biocultural measures developed by Indigenous experts, with the aim of prioritizing place-based culturally significant entities for collaborative management approaches on Bundjalung Country in coastal eastern Australia. We found some congruence and some important differences between culturally significant entities priorities and management compared with the colonial focus of threatened species management underpinned by current laws and policies. We provide reproduceable methods and a demonstration of successful local culturally significant entities designation and prioritization in an Australian context that highlights opportunities for Indigenous leadership, supported by governments in the designation and management of culturally significant entities.

10 years of decision‐making for biodiversity conservation actions: A systematic literature review

AbstractDecision science emphasizes necessary elements required for robust decision‐making. By incorporating decision science principles, frameworks, and tools, it has been demonstrated that decision‐makers can increase the chances of achieving conservation aims. Setting measurable objectives, clearly documenting assumptions about the impact of available actions on a specific threat or problem, explicitly considering constraints, exploring and characterizing uncertainty, and structured deliberation on trade‐offs have been identified as key elements of successful decision‐making. We quantify the extent to which these five elements were utilized in published examples of decision making in conservation in both academic and conservation practice between 2009 and 2018. We found that less than 50% of identified examples included all five elements, with differences in the degree of decision science applied across five commonly used decision support approaches: adaptive management (AM), systematic conservation planning (SCP), structured decision making (SDM), multi‐criteria decision analysis, and cost‐effectiveness analysis. Example applications that utilized the SDM framework were limited in numbers but used on average more than 50% of the five key elements we considered. Although SCP and AM constituted the majority of examples, they were more prevalent in academic studies rather than management applications. SCP and AM examples were widespread in protected area planning, threat abatement, and restoration. Strong geographic bias exists in documented conservation activities that deploy all five decision science elements.

A COMPREHENSIVE REVIEW OF ADVERSARIAL ATTACKS IN MACHINE LEARNING

Adversarial attacks pose a substantial risk to the security and dependability of machine learning (ML) models. These attacks entail creating harmful inputs, known as adversarial instances, which can lead models to provide inaccurate predictions. This article offers a thorough examination of adversarial assaults in machine learning, including their many forms, techniques of generation, current research, and potential future research areas. We analyze well-known attack techniques such as FGSM, DeepFool, Carlini & Wagner (C&W), and ZOO, emphasizing their advantages and constraints. The research limitations we have identified relate to the lack of comprehensive comparative analysis and the absence of a structured decision-making framework for offensive technique selection. In addition, we investigate the research obstacles related to adversarial variety, dynamic assault environments, the capacity to transfer knowledge across different domains, and the assessment of resilience in real-world scenarios. The paper highlights the need for investigating adversarial assaults to improve the resilience of models, enhance security measures, guide decision-making, stimulate innovation, and encourage responsible development of AI. In conclusion, we suggest potential areas for future study, such as the creation of improved defensive mechanisms, robust modeling tools, and the incorporation of multidisciplinary approaches. Key Words: adversarial Attacks, Machine Learning, Adversarial Examples, robustness, Fast Gradient Sign Method, DeepFool, Carlini & Wagner (C&W), Zoo-Adversarial Instance Optimization

A decision-making framework for the funding of shipping decarbonization initiatives in non-EU countries: insights from Türkiye

The decarbonization of the shipping industry is a critical imperative in the global fight against climate change. Non-EU countries, being significant contributors to shipping emissions, play a crucial role in shaping the industry's sustainable future. However, securing funding for shipping decarbonization initiatives in these countries presents challenges, such as limited access to capital, lack of financial initiatives, political and regulatory uncertainties, technological risks, lack of local expertise, and the effects of global economic volatility. Addressing these challenges demands innovative strategies. The paper explores ways of effectively allocating funds for decarbonization projects in the shipping industry of non-EU countries, Türkiye in particular, using a structured decision-making framework tailored to their specific needs and challenges. We adopt the Moment Integrated Solution Method (THEMIS) to identify the “best” option from the range of alternative strategies identified in the framework. Our findings show that the use of incentive mechanisms is the most prioritized funding alternative, followed by the implementation of a sound Cap-and-Trade system and the promotion of strict local regulations to combat emissions. These imply that the prioritization of funding mechanisms, market-driven approaches, and more stringent regulation are key drivers in maritime decarbonization efforts. The Türkiye case study on strategies to achieve a greener maritime industry in developing countries also shows that securing funding for decarbonization requires a concerted effort by governments, private entities, and international organizations.

Distance sampling and spatial capture-recapture for estimating density of Northern Bobwhite

Obtaining accurate density estimates is critical for managers making decisions regarding wildlife populations. A variety of methods have been used to estimate population density, with two of the most common being distance sampling (DS) and spatial capture recapture (SCR). We evaluated precision and bias of density estimators through a simulation study of DS using data collected from either human observer point counts or automated recording units (ARUs), and SCR using trapping data or trapping data augmented with telemetry data. We then fit each of the four models to empirical data collected during autumn 2016–2018 for a population of northern bobwhite Colinus virginianus on Di-Lane Wildlife Management Area in Georgia. Density estimates in our simulation study were relatively unbiased using all four methods but were most accurate for the two SCR methods. Empirical density estimates were similar across methods and years, with annual averages of 0.41 birds per ha in 2016, 0.44 birds per ha in 2017 and 0.31 birds per ha in 2018. In general, both SCR methods were also the most precise using the empirical data, although ARU distance sampling did also produce comparable density estimates and precision values. Although SCR methods performed the best overall, cost and increased labor of these monitoring programs should be evaluated in relation to the relative ease of ARU deployment or point count surveys, which also provided adequate, and often similar, density estimates. Integrating these constraints into a structured decision-making framework will aid managers weighing decisions regarding how to monitor, and ultimately make management decisions.

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. 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].

Enhancing Sustainability in Belize’s Ecotourism Sector: A Fuzzy Delphi and Fuzzy DEMATEL Investigation of Key Indicators

Sustainable ecotourism has become a strategy to balance tourism growth with environmental and sociocultural considerations. This study aims to propose an integrated approach of the Delphi technique and the decision-making trial and evaluation laboratory (DEMATEL) based on fuzzy set theory to investigate sustainable ecotourism indicators in Belize. The study covers six dimensions: environmental, social, cultural, economic, political, and intrinsic. Firstly, the Fuzzy Delphi technique constructs a comprehensive set of indicators with expert consensus, resulting in 51 relevant and representative indicators out of the initial 63. Secondly, the Fuzzy DEMATEL approach is then applied to analyze the interdependencies among indicators and identify their causal relationships, providing insights into the complex dynamics of sustainable ecotourism in Belize. The results provide a structured decision-making framework to prioritize actions, allocate resources effectively, and promote sustainable practices in the ecotourism sector. Therefore, these findings enhance the understanding of indicator interconnections across dimensions, enabling informed decision making for policymakers, industry practitioners, and researchers. Policymakers can develop policies and regulations that foster sustainable practices, while industry practitioners can enhance visitor experiences, engage with local communities, and ensure the industry’s long-term viability. Researchers can further investigate specific dimensions and indicators to advance the knowledge and implementation of sustainable ecotourism. Finally, this investigation supports the goal of achieving a harmonious and sustainable balance between tourism development and environmental preservation in Belize. By safeguarding the natural and cultural heritage of the region, sustainable ecotourism can benefit present and future generations.

When are environmental DNA early detections of invasive species actionable?

Environmental DNA (eDNA) sampling provides sensitive early detection capabilities for recently introduced taxa. However, natural resource managers struggle with how to integrate eDNA results into an early detection rapid response program because positive eDNA detections are not always indicative of an eventual infestation. We used a structured decision making (SDM) framework to evaluate appropriate response actions to hypothetical eDNA early detections of an introduced aquatic plant in Sebago Lake (Maine, USA). The results were juxtaposed to a recent study that used a similar SDM approach to evaluate response actions to hypothetical eDNA early detections of introduced mussels in Jordanelle Reservoir (Utah, USA). We found that eDNA early detections were not actionable in Sebago Lake because the plant's invasion potential was spatially constrained and the current management activities provided acceptable levels of mitigation. In Jordanelle Reservoir, eDNA detections were actionable due to high invasion potential and analyses supported management actions to contain the invasion. The divergent outcomes of the two case studies are related to the unique attributes of the habitats and species, highlighting the utility of the SDM approach when considering an eDNA monitoring program. We use these two case studies to present a general SDM framework and a set of heuristics that can be efficiently applied to eDNA early detection rapid response scenarios and other instances associated with indeterminant eDNA detections, especially when there is an imperative to make decisions as quickly as possible.

Qualitative value of information provides a transparent and repeatable method for identifying critical uncertainty.

Conservation decisions are often made in the face of uncertainty because the urgency to act can preclude delaying management while uncertainty is resolved. In this context, adaptive management is attractive, allowing simultaneous management and learning. An adaptive program design requires the identification of critical uncertainties that impede the choice of management action. Quantitative evaluation of critical uncertainty, using the expected value of information, may require more resources than are available in the early stages of conservation planning. Here, we demonstrate the use of a qualitative index to the value of information (QVoI) to prioritize which sources of uncertainty to reduce regarding the use of prescribed fire to benefit Eastern Black Rails (Laterallus jamaicensis jamaicensis), Yellow Rails (Coterminous noveboracensis), and Mottled Ducks (Anas fulvigula; hereafter, focal species) in high marshes of the U.S. Gulf of Mexico. Prescribed fire has been used as a management tool in Gulf of Mexico high marshes throughout the last 30+ years; however, effects of periodic burning on the focal species and the optimal conditions for burning marshes to improve habitat remain unknown. We followed a structured decision-making framework to develop conceptual models, which we then used to identify sources of uncertainty and articulate alternative hypotheses about prescribed fire in high marshes. We used QVoI to evaluate the sources of uncertainty based on their Magnitude, Relevance for decision-making, and Reducibility. We found that hypotheses related to the optimal fire return interval and season were the highest priorities for study, whereas hypotheses related to predation rates and interactions among management techniques were lowest. These results suggest that learning about the optimal fire frequency and season to benefit the focal species might produce the greatest management benefit. In this case study, we demonstrate that QVoI can help managers decide where to apply limited resources to learn which specific actions will result in a higher likelihood of achieving the desired management objectives. Further, we summarize the strengths and limitations of QVoI and outline recommendations for its future use for prioritizing research to reduce uncertainty about system dynamics and the effects of management actions.

Prioritizing species conservation programs based on IUCN Green Status and estimates of cost-sharing potential.

Over 1 million species around the world are at risk of extinction, and conservation organizations have to decide where to invest their limited resources. Cost-effectiveness can be increased by leveraging funding opportunities and increasing collaborative partnerships to achieve shared conservation goals. We devised a structured decision-making framework to prioritize species' conservation programs based on a cost-benefit analysis that takes collaborative opportunities into account in an examination of national and global conservation return on investment. Conservation benefit is determined by modifying the novel International Union for the Conservation of Nature Green Status for Species to provide an efficient, high-level measure that is comparable among species, even with limited information and time constraints. We applied this prioritization approach to the Wilder Institute/Calgary Zoo, Canada, a nonprofit organization seeking to increase the number of species it assists with conservation translocations. We sought to identify and prioritize additional species' programs for which conservation translocation expertise and actions could make the most impact. Estimating the likelihood of cost-sharing potential enabled total program cost to be distinguished from costs specific to the organization. Comparing a benefit-to-cost ratio on different geographic scales allowed decision makers to weigh alternative options for investing in new species' programs in a transparent and effective manner. Our innovative analysis aligns with general conservation planning frameworks and can be adapted for any organization.

Investigating the impact of brief training in decision-making on treatment escalation to intensive care using objective structured clinical examination-style scenarios.

The decision to admit patients to the intensive care unit (ICU) is complex. Structuring the decision-making process may be beneficial to patients and decision-makers alike. The aim of this study was to investigate the feasibility and impact of a brief training intervention on ICU treatment escalation decisions using the Warwick model- a structured decision-making framework for treatment escalation decisions. Treatment escalation decisions were assessed using Objective Structured Clinical Examination-style scenarios. Participants were ICU and anaesthetic registrars with experience of making ICU admission decisions. Participants completed one scenario, followed by training with the decision-making framework and subsequently a second scenario. Decision-making data was collected using checklists, note entries and post-scenario questionnaires. Twelve participants were enrolled. Brief decision-making training was successfully delivered during the normal ICU working day. Following training participants demonstrated greater evidence of balancing the burdens and benefits of treatment escalation. On visual analogue scales of 0-10, participants felt better trained to make treatment escalation decisions (4.9 vs 6.8, p = 0.017) and felt their decision-making was more structured (4.7 vs 8.1, p = 0.017).Overall, participants provided positive feedback and reported feeling more prepared for the task of making treatment escalation decisions. Our findings suggest that a brief training intervention is a feasible way to improve the decision-making process by improving decision-making structure, reasoning and documentation. Training was implemented successfully, acceptable to participants and participants were able to apply their learning. Further studies of regional and national cohorts are needed to determine if training benefit is sustained and generalisable.

Implementation of a structured decision-making framework to evaluate and advance understanding of airborne microplastics

Microplastic pollution is increasingly recognised as a global environmental challenge which stems from the rapid growth of the use of petrochemical-derived plastic. As researchers and practitioners face a myriad of environmental challenges, oceanic microplastic pollution has so far dominated interest. However, airborne microplastics present an increasing environmental and public health concern. There is currently a need for research addressing this emerging challenge, and at the same time, the lack of knowledge and consensus regarding airborne microplastics presents an obstacle to action. The purpose of this study is to utilise a participatory Structured Decision-Making (SDM) approach to understand the perspectives of a range of stakeholders involved in the microplastics landscape, and subsequently refine common research priorities and knowledge gaps to advance the field. Through two participatory workshops, we first defined shared objectives of stakeholders and then negotiated best courses of action to achieve these objectives based on discussion between stakeholders and facilitators. The qualitative approach taken has enabled the full, complex and multidisciplinary aspects of the research into airborne microplastic pollution to be considered. Our findings highlight some important potential consequences of airborne microplastic pollution, including impacts on human health, and the need for more interdisciplinary research, and collaborative, integrated approaches in this area. As a result of the first workshop, five fundamental objectives on the theme of airborne microplastics were identified. As a direct consequence of this, participants identified 84 actions split across eight themes, which are outlined later in this paper.

Tender Evaluation Improvement at PT. X Using Analytical Hierarchy Process

A project is part of the activity done by the company in order to achieve its business goal. One of the activities inside a project is tendering to ensure the availability of the resources needed for the project is fulfilled. PT. X is one of the companies that implement the tendering process to achieve its business goal. One of the operations that require the tendering process is the security operation. The tender announcement is made for the public for any vendors able to fulfilled the requirement can apply for the tender and follow the selection process. The selection process is conducted by the procurement committee and the contract engineer. They determined the tender evaluation criteria and give scores to each of the criteria. In the current condition, the determination of the weight is prone to subjectivity due to the non-existence of any quantitative method in the decision-making process. This study proposes the use of the Analytical Hierarchy Process (AHP) as a tool to help the company to determine the criteria, sub-criteria, and each of the weights as the quantitative method. This method reduces the subjectivity factor and ensures a structured decision-making framework. The winner of the tender from this study and the current condition are the same. However, the final score is different, and the vendor with the lowest score is also different. This difference is due to the different weights in the current condition and this study.

Risk Analysis Frameworks Used in Biological Control and Introduction of a Novel Bayesian Network Tool.

Classical biological control, the introduction of natural enemies to new environments to control unwanted pests or weeds, is, despite numerous successful examples, associated with rising concerns about unwanted environmental impacts such as population decline of nontarget species. Recognition of these biosafety risks is globally increasing, and prerelease assessments of biological control agents (BCAs) have become more rigorous in many countries. We review the current approaches to risk assessment for BCAs as used in Australasia, Europe, and North America. Traditionally, these assessments focus on providing assurance about the specificity of a proposed BCA, generally via a list of suitable versus nonsuitable hosts determined through laboratory specificity tests (i.e., by determining the BCA's physiological host range). The outcome of interactions of proposed agents in the natural environment can differ from laboratory-based predictions. Potential nontarget host testing may be incomplete, additional ecological barriers under field conditions may limit encounters between BCA and nontargets or reduce attack levels, and BCAs could disperse to habitats beyond those used by the target species and adversely affect nontarget species. We advocate for the adoption of more comprehensive, ecologically-based, probabilistic risk assessment approaches to BCA introductions. An example is provided using a Bayesian network that can integrate information on probabilities and uncertainties of a BCA to spread and establish in new habitats, interact with nontarget species in these habitats, and eventually negatively impact the populations of these nontarget species. Our new model, Biocontrol Adverse Impact Probability Assessment, aims to be incorporated into a structured decision-making framework to support national regulatory authorities.

Warming temperatures and ectoparasitic sea lice impair internal organs in juvenile Atlantic salmon

Without insights into the threats affecting species across their distributions and throughout their annual cycles, effective conservation management cannot be applied. The Whenua Hou diving petrel Pelecanoides whenuahouensis (WHDP) is a Critically Endangered small seabird whose offshore habits and threats are poorly understood. We tracked WHDPs year-round in 2015/16, 2017/18, and 2018/19 using global location-sensing immersion loggers to identify offshore distribution, movements, behaviour, and overlap with commercial fishing effort. During the breeding period, WHDPs ranged from southern Aotearoa (New Zealand) to Maukahuka (Auckland Islands). After breeding, WHDPs migrated southwest towards the Polar Front south of Australia, exhibited clockwise movements, and returned to their breeding grounds via the Subantarctic Front. During the non-breeding period, WHDPs exhibited extreme aquatic behaviour and spent >95% of their time on, or under, water. The core areas used consistently during breeding and non-breeding periods warrant listing as Important Bird and Biodiversity Areas. Spatiotemporal overlap of commercial fishing effort with breeding distributions was considerable, in contrast with non-breeding distributions. Spatiotemporal management of anthropogenic activity around the breeding colony during the breeding period could help protect WHDPs, but such measures should be subjected to a structured decision-making framework. Our results illustrate the importance of year-round studies to inform conservation of marine species.

Year-round offshore distribution, behaviour, and overlap with commercial fisheries of a Critically Endangered small petrel

Without insights into the threats affecting species across their distributions and throughout their annual cycles, effective conservation management cannot be applied. The Whenua Hou diving petrel Pelecanoides whenuahouensis (WHDP) is a Critically Endangered small seabird whose offshore habits and threats are poorly understood. We tracked WHDPs year-round in 2015/16, 2017/18, and 2018/19 using global location-sensing immersion loggers to identify offshore distribution, movements, behaviour, and overlap with commercial fishing effort. During the breeding period, WHDPs ranged from southern Aotearoa (New Zealand) to Maukahuka (Auckland Islands). After breeding, WHDPs migrated southwest towards the Polar Front south of Australia, exhibited clockwise movements, and returned to their breeding grounds via the Subantarctic Front. During the non-breeding period, WHDPs exhibited extreme aquatic behaviour and spent >95% of their time on, or under, water. The core areas used consistently during breeding and non-breeding periods warrant listing as Important Bird and Biodiversity Areas. Spatiotemporal overlap of commercial fishing effort with breeding distributions was considerable (35%), in contrast with non-breeding distributions (0%). Spatial restrictions of anthropogenic activity around the breeding colony during the breeding period could help protect WHDPs, but such measures should be subjected to a structured decision-making framework. Our results illustrate the importance of year-round studies to inform conservation of marine species.

‘WildLift’: An Open-Source Tool to Guide Decisions for Wildlife Conservation

A recurring challenge for resource managers and decision makers is quantifying the trade-offs associated with alternative recovery actions for threatened species. Structured decision-making approaches can help evaluate such complex problems by formalizing objectives and constraints into functions that quantify the benefits and costs associated with each action. Yet many of the scientific tools necessary to implement structured decision making require extensive literature review and often involve complex algorithms that make them inaccessible to managers. To address these issues, we integrated available information and developed a decision-support tool that managers can readily use to compare costs and benefits associated with alternative recovery actions for threatened species. Our software can be used to quantitatively estimate and compare the costs and demographic benefits of recovery actions for an iconic threatened species, woodland caribou (Rangifer tarandus caribou). While we use caribou as a case study, our approach to developing this management tool is transferable to other threatened taxa. The tool consists of a generalized matrix population model that is parametrized based on information from the published literature or ongoing experiments. Users can input population parameters (e.g., population size and survival rates) or choose from pre-set caribou subpopulations to estimate changes to populations from implementing recovery actions. The tool estimates the trade-offs associated with seven alternative recovery actions: Linear Feature Restoration, Linear Feature Deactivation, Maternal Penning, Conservation Breeding, Predator Exclosure, Wolf Reduction, and Moose Reduction. We demonstrate our software by comparing recovery actions for the East Side Athabasca River caribou subpopulation and discuss how this tool can be used under a structured decision-making framework. This case study suggests that our open-source tool can be useful to guide wildlife conservation decisions by explicitly estimating costs and benefits associated with recovery actions, which ultimately helps to bridge the gap between management and science via increased accessible application of current knowledge.

Harnessing multiple models for outbreak management.

Expert elicitation methods and a structured decision-making framework will help account for risk and uncertainty

An Application of Structured Decision Making Process in Approaching Deforestation and Promoting Sustainable Forest Management of Sylhet, Bangladesh

Deforestation is a global phenomenon with a critical recognition. It is very visible mostly in developing countries in Asia and Southern America. In many regions where forest loss is significant, so much effort has been garnered towards protecting the natural forest and promoting sustainable forest management (SFM). Evidence of such efforts includes the various policies, principles, and frameworks put in place both at the international and domestic levels. Despite these efforts, forest depletion continues to thrive at alarming rates particularly in developing countries like Bangladesh. This paper brings out a plethora of complex causes and consequences of deforestation in Sylhet, Bangladesh, with the principal objective of using a structured decision-making (SDM) approach to address deforestation in Sylhet through a pluralistic stakeholder engagement that represents all the objectives of the various groups in a very understandable manner. Mainly deploying FGD to consult with different stakeholder groups, representing different interests working through the steps of SDM, the consultations developed a SDM framework with suggested alternative approaches towards addressing deforestation in Sylhet, Bangladesh. Based on the judgments of the consultations, suitable policy options for addressing deforestation in Sylhet, Bangladesh should focus on maximizing forest management, minimizing dependence on forest resources, and Alternative ‘A’ (Safe guarding forest by improving forest management). This case study provides insights on how SDM can be implemented for SFM in Sylhet, as well as some challenges and opportunities encountered during the process.

A cost-effective framework to prioritise stakeholder participation options

Stakeholder participation is increasingly being embedded into decision-making processes from the local to the global scale. With limited resources to engage stakeholders, frameworks that allow decision-makers to make cost-effective choices are greatly needed. In this paper, we present a structured decision-making (SDM) framework that enables environmental decision-makers to prioritise different engagement options by assessing their relative cost-effectiveness. We demonstrate the application of this framework using a case study in biosecurity management. Drawing on a scenario of Panama Disease Tropical Race 4 (TR4) invasion in the Australian banana industry, we conducted 25 semi-structured interviews and held a workshop with key stakeholders to elicit their key concerns and convert them into four objectives-making more informed decisions, maximising buy-in, empowering people, and minimising the stress of biosecurity incidents. We also identified ten engagement alternatives at local, State/Territory, and National scales. Our results showed that options to engage local stakeholders and enable capacity to undertake adaptive approaches to biosecurity management are more cost-effective than engagement efforts that seek to build capacities at higher decision-making levels. More interestingly, using the weights provided by different stakeholder groups does not significantly affect the cost-effectiveness ranking of the ten options considered. Even though the results are contingent on the context of this biosecurity study, the SDM framework developed for maximising cost-effectiveness is transferable to other areas of environmental management. The efficient frontier generated by this framework allows decision-makers to examine the trade-offs between the costs and benefits and select the best portfolio for their investment. This approach provides a practical and transparent estimate of the return on investment for stakeholder engagement in highly complex or uncertain situations, as is usually the case for environmental issues.