Combining Structured Decision Making and Value‐of‐Information Analyses to Identify Robust Management Strategies

Abstract: Structured decision making and value‐of‐information analyses can be used to identify robust management strategies even when uncertainty about the response of the system to management is high. We used these methods in a case study of management of the non‐native invasive species gray sallow willow (Salix cinerea) in alpine Australia. Establishment of this species is facilitated by wildfire. Managers are charged with developing a management strategy despite extensive uncertainty regarding the frequency of fires, the willow's demography, and the effectiveness of management actions. We worked with managers in Victoria to conduct a formal decision analysis. We used a dynamic model to identify the best management strategy for a range of budgets. We evaluated the robustness of the strategies to uncertainty with value‐of‐information analyses. Results of the value‐of‐information analysis indicated that reducing uncertainty would not change which management strategy was identified as the best unless budgets increased substantially. This outcome suggests there would be little value in implementing adaptive management for the problem we analyzed. The value‐of‐information analyses also highlighted that the main driver of gray sallow willow invasion (i.e., fire frequency) is not necessarily the same factor that is most important for decision making (i.e., willow seed dispersal distance). Value of‐information analyses enables managers to better target monitoring and research efforts toward factors critical to making the decision and to assess the need for adaptive management.     

Integrated models to support multiobjective ecological restoration decisions

Many objectives motivate ecological restoration, including improving vegetation condition, increasing the range and abundance of threatened species, and improving species richness and diversity. Although models have been used to examine the outcomes of ecological restoration, few researchers have attempted to develop models to account for multiple, potentially competing objectives. We developed a combined state‐and‐transition, species‐distribution model to predict the effects of restoration actions on vegetation condition and extent, bird diversity, and the distribution of several bird species in southeastern Australian woodlands. The actions reflected several management objectives. We then validated the models against an independent data set and investigated how the best management decision might change when objectives were valued differently. We also used model results to identify effective restoration options for vegetation and bird species under a constrained budget. In the examples we evaluated, no one action (improving vegetation condition and extent, increasing bird diversity, or increasing the probability of occurrence for threatened species) provided the best outcome across all objectives. In agricultural lands, the optimal management actions for promoting the occurrence of the Brown Treecreeper (Climacteris picumnus), an iconic threatened species, resulted in little improvement in the extent of the vegetation and a high probability of decreased vegetation condition. This result highlights that the best management action in any situation depends on how much the different objectives are valued. In our example scenario, no management or weed control were most likely to be the best management options to satisfy multiple restoration objectives. Our approach to exploring trade‐offs in management outcomes through integrated modeling and structured decision‐support approaches has wide application for situations in which trade‐offs exist between competing conservation objectives.     

Planning for ex situ conservation in the face of uncertainty

Ex situ conservation strategies for threatened species often require long‐term commitment and financial investment to achieve management objectives. We present a framework that considers the decision to adopt ex situ management for a target species as the end point of several linked decisions. We used a decision tree to intuitively represent the logical sequence of decision making. The first decision is to identify the specific management actions most likely to achieve the fundamental objectives of the recovery plan, with or without the use of ex‐situ populations. Once this decision has been made, one decides whether to establish an ex situ population, accounting for the probability of success in the initial phase of the recovery plan, for example, the probability of successful breeding in captivity. Approaching these decisions in the reverse order (attempting to establish an ex situ population before its purpose is clearly defined) can lead to a poor allocation of resources, because it may restrict the range of available decisions in the second stage. We applied our decision framework to the recovery program for the threatened spotted tree frog (Litoria spenceri) of southeastern Australia. Across a range of possible management actions, only those including ex situ management were expected to provide >50% probability of the species’ persistence, but these actions cost more than use of in situ alternatives only. The expected benefits of ex situ actions were predicted to be offset by additional uncertainty and stochasticity associated with establishing and maintaining ex situ populations. Naïvely implementing ex situ conservation strategies can lead to inefficient management. Our framework may help managers explicitly evaluate objectives, management options, and the probability of success prior to establishing a captive colony of any given species.     

Resolving future fire management conflicts using multicriteria decision making

Management strategies to reduce the risks to human life and property from wildfire commonly involve burning native vegetation. However, planned burning can conflict with other societal objectives such as human health and biodiversity conservation. These conflicts are likely to intensify as fire regimes change under future climates and as growing human populations encroach farther into fire‐prone ecosystems. Decisions about managing fire risks are therefore complex and warrant more sophisticated approaches than are typically used. We applied a multicriteria decision making approach (MCDA) with the potential to improve fire management outcomes to the case of a highly populated, biodiverse, and flammable wildland–urban interface. We considered the effects of 22 planned burning options on 8 objectives: house protection, maximizing water quality, minimizing carbon emissions and impacts on human health, and minimizing declines of 5 distinct species types. The MCDA identified a small number of management options (burning forest adjacent to houses) that performed well for most objectives, but not for one species type (arboreal mammal) or for water quality. Although MCDA made the conflict between objectives explicit, resolution of the problem depended on the weighting assigned to each objective. Additive weighting of criteria traded off the arboreal mammal and water quality objectives for other objectives. Multiplicative weighting identified scenarios that avoided poor outcomes for any objective, which is important for avoiding potentially irreversible biodiversity losses. To distinguish reliably among management options, future work should focus on reducing uncertainty in outcomes across a range of objectives. Considering management actions that have more predictable outcomes than landscape fuel management will be important. We found that, where data were adequate, an MCDA can support decision making in the complex and often conflicted area of fire management.     

Setting conservation management thresholds using a novel participatory modeling approach

We devised a participatory modeling approach for setting management thresholds that show when management intervention is required to address undesirable ecosystem changes. This approach was designed to be used when management thresholds: must be set for environmental indicators in the face of multiple competing objectives; need to incorporate scientific understanding and value judgments; and will be set by participants with limited modeling experience. We applied our approach to a case study where management thresholds were set for a mat‐forming brown alga, Hormosira banksii, in a protected area management context. Participants, including management staff and scientists, were involved in a workshop to test the approach, and set management thresholds to address the threat of trampling by visitors to an intertidal rocky reef. The approach involved trading off the environmental objective, to maintain the condition of intertidal reef communities, with social and economic objectives to ensure management intervention was cost‐effective. Ecological scenarios, developed using scenario planning, were a key feature that provided the foundation for where to set management thresholds. The scenarios developed represented declines in percent cover of H. banksii that may occur under increased threatening processes. Participants defined 4 discrete management alternatives to address the threat of trampling and estimated the effect of these alternatives on the objectives under each ecological scenario. A weighted additive model was used to aggregate participants’ consequence estimates. Model outputs (decision scores) clearly expressed uncertainty, which can be considered by decision makers and used to inform where to set management thresholds. This approach encourages a proactive form of conservation, where management thresholds and associated actions are defined a priori for ecological indicators, rather than reacting to unexpected ecosystem changes in the future.     

Improving supplementary feeding in species conservation

Supplementary feeding is often a knee‐jerk reaction to population declines, and its application is not critically evaluated, leading to polarized views among managers on its usefulness. Here, we advocate a more strategic approach to supplementary feeding so that the choice to use it is clearly justified over, or in combination with, other management actions and the predicted consequences are then critically assessed following implementation. We propose combining methods from a set of specialist disciplines that will allow critical evaluation of the need, benefit, and risks of food supplementation. Through the use of nutritional ecology, population ecology, and structured decision making, conservation managers can make better choices about what and how to feed by estimating consequences on population recovery across a range of possible actions. This structured approach also informs targeted monitoring and more clearly allows supplementary feeding to be integrated in recovery plans and reduces the risk of inefficient decisions. In New Zealand, managers of the endangered Hihi (Notiomystis cincta) often rely on supplementary feeding to support reintroduced populations. On Kapiti island the reintroduced Hihi population has responded well to food supplementation, but the logistics of providing an increasing demand recently outstretched management capacity. To decide whether and how the feeding regime should be revised, managers used a structured decision making approach informed by population responses to alternative feeding regimes. The decision was made to reduce the spatial distribution of feeders and invest saved time in increasing volume of food delivered into a smaller core area. The approach used allowed a transparent and defendable management decision in regard to supplementary feeding, reflecting the multiple objectives of managers and their priorities.     

A typology of time‐scale mismatches and behavioral interventions to diagnose and solve conservation problems

Ecological systems often operate on time scales significantly longer or shorter than the time scales typical of human decision making, which causes substantial difficulty for conservation and management in socioecological systems. For example, invasive species may move faster than humans can diagnose problems and initiate solutions, and climate systems may exhibit long‐term inertia and short‐term fluctuations that obscure learning about the efficacy of management efforts in many ecological systems. We adopted a management‐decision framework that distinguishes decision makers within public institutions from individual actors within the social system, calls attention to the ways socioecological systems respond to decision makers’ actions, and notes institutional learning that accrues from observing these responses. We used this framework, along with insights from bedeviling conservation problems, to create a typology that identifies problematic time‐scale mismatches occurring between individual decision makers in public institutions and between individual actors in the social or ecological system. We also considered solutions that involve modifying human perception and behavior at the individual level as a means of resolving these problematic mismatches. The potential solutions are derived from the behavioral economics and psychology literature on temporal challenges in decision making, such as the human tendency to discount future outcomes at irrationally high rates. These solutions range from framing environmental decisions to enhance the salience of long‐term consequences, to using structured decision processes that make time scales of actions and consequences more explicit, to structural solutions aimed at altering the consequences of short‐sighted behavior to make it less appealing. Additional application of these tools and long‐term evaluation measures that assess not just behavioral changes but also associated changes in ecological systems are needed.     

Adaptive Comanagement of a Marine Protected Area Network in Fiji

Adaptive management of natural resources is an iterative process of decision making whereby management strategies are progressively changed or adjusted in response to new information. Despite an increasing focus on the need for adaptive conservation strategies, there remain few applied examples. We describe the 9‐year process of adaptive comanagement of a marine protected area network in Kubulau District, Fiji. In 2011, a review of protected area boundaries and management rules was motivated by the need to enhance management effectiveness and the desire to improve resilience to climate change. Through a series of consultations, with the Wildlife Conservation Society providing scientific input to community decision making, the network of marine protected areas was reconfigured so as to maximize resilience and compliance. Factors identified as contributing to this outcome include well‐defined resource‐access rights; community respect for a flexible system of customary governance; long‐term commitment and presence of comanagement partners; supportive policy environment for comanagement; synthesis of traditional management approaches with systematic monitoring; and district‐wide coordination, which provided a broader spatial context for adaptive‐management decision making. Co‐Manejo Adaptativo de una Red de Áreas Marinas Protegidas en Fiyi     

Structuring Decisions for Managing Threatened and Endangered Species in a Changing Climate

The management of endangered species under climate change is a challenging and often controversial task that incorporates input from a variety of different environmental, economic, social, and political interests. Yet many listing and recovery decisions for endangered species unfold on an ad hoc basis without reference to decision‐aiding approaches that can improve the quality of management choices. Unlike many treatments of this issue, which consider endangered species management a science‐based problem, we suggest that a clear decision‐making process is equally necessary. In the face of new threats due to climate change, managers’ choices about endangered species require closely linked analyses and deliberations that identify key objectives and develop measurable attributes, generate and compare management alternatives, estimate expected consequences and key sources of uncertainty, and clarify trade‐offs across different dimensions of value. Several recent cases of endangered species conservation decisions illustrate our proposed decision‐focused approach, including Gulf of Maine Atlantic salmon (Salmo salar) recovery framework development, Cultus Lake sockeye salmon (Oncorhynchus nerka) management, and Upper Columbia River white sturgeon (Acipenser transmontanus) recovery planning. Estructuración de Decisiones para Manejar Especies Amenazadas y en Peligro en un Clima Cambiante     

Evaluation of potential responses to invasive non-native species with structured decision making

In managing invasions and colonizations of non-native species, eradication or control efforts must proceed quickly. There are 2 challenges in taking such quick action. First, managers frequently have to choose among complex and often competing environmental, social, and economic objectives. Second, the effects are highly uncertain. We applied participatory structured decision making (SDM) to develop a response plan for the recent invasion of non-native myrtle rust (Uredo rangelii) in Australia. Structured decision making breaks a complex decision process into 5 steps: identify problems (i.e., decisions to be made), formulate objectives, develop management alternatives, estimate consequences of implementing those alternatives, and select preferred alternatives by evaluating trade-offs among alternatives. To determine the preferred mid- to long-term alternatives to managing the rust, we conducted 2 participatory workshops and 18 interviews with individuals to elicit stakeholders' key concerns and convert them into 5 objectives (minimize management cost, minimize economic cost to industry, minimize effects on natural ecosystems and landscape amenities, and minimize environmental effects associated with use of fungicide) and to identify the 5 management alternatives (full eradication, partial eradication, slow spread, live with it [i.e., major effort invested in mitigation of effects], and do nothing). We also developed decision trees to graphically represent the essence of the decision by displaying the relations between uncertainties and decision points. In the short term or before local expansion of myrtle rust, the do-nothing alternative was not preferred, but an eradication alternative was only recommended if the probability of eradication exceeded about 40%. After the expansion of myrtle rust, the slow-the-spread alternative was preferred regardless of which of the short-term management alternatives was selected at an earlier stage. The participatory SDM approach effectively resulted in informed and transparent response plans that incorporated multiple objectives in decision-making processes under high uncertainty.     

Bayesian Decision Analysis for Evaluating Management Options to Promote Recovery of a Depleted Salmon Population

Abstract:  The endangered population of sockeye salmon (Oncorhynchus nerka) in Cultus Lake, British Columbia, Canada, migrates through commercial fishing areas along with other, much more abundant sockeye salmon populations, but it is not feasible to selectively harvest only the latter, abundant populations. This situation creates controversial trade-offs between recovery actions and economic revenue. We conducted a Bayesian decision analysis to evaluate options for recovery of Cultus Lake sockeye salmon. We used a stochastic population model that included 2 sources of uncertainty that are often omitted from such analyses: structural uncertainty in the magnitude of a potential Allee effect and implementation uncertainty (the deviation between targets and actual outcomes of management actions). Numerous state-dependent, time-independent management actions meet recovery objectives. These actions prescribe limitations on commercial harvest rates as a function of abundance of Cultus Lake sockeye salmon. We also quantified how much reduction in economic value of commercial harvests of the more abundant sockeye salmon populations would be expected for a given increase in the probability of recovery of the Cultus population. Such results illustrate how Bayesian decision analysis can rank options for dealing with conservation risks and can help inform trade-off discussions among decision makers and among groups that have competing objectives.     

Adaptive resource management and the value of information

The value of information is a general and broadly applicable concept that has been used for several decades to aid in making decisions in the face of uncertainty. Yet there are relatively few examples of its use in ecology and natural resources management, and almost none that are framed in terms of the future impacts of management decisions. In this paper we discuss the value of information in a context of adaptive management, in which actions are taken sequentially over a timeframe and both future resource conditions and residual uncertainties about resource responses are taken into account. Our objective is to derive the value of reducing or eliminating uncertainty in adaptive decision making. We describe several measures of the value of information, with each based on management objectives that are appropriate for adaptive management. We highlight some mathematical properties of these measures, discuss their geometries, and illustrate them with an example in natural resources management. Accounting for the value of information can help to inform decisions about whether and how much to monitor resource conditions through time.     

Cost‐effective conservation of an endangered frog under uncertainty

How should managers choose among conservation options when resources are scarce and there is uncertainty regarding the effectiveness of actions? Well‐developed tools exist for prioritizing areas for one‐time and binary actions (e.g., protect vs. not protect), but methods for prioritizing incremental or ongoing actions (such as habitat creation and maintenance) remain uncommon. We devised an approach that combines metapopulation viability and cost‐effectiveness analyses to select among alternative conservation actions while accounting for uncertainty. In our study, cost‐effectiveness is the ratio between the benefit of an action and its economic cost, where benefit is the change in metapopulation viability. We applied the approach to the case of the endangered growling grass frog (Litoria raniformis), which is threatened by urban development. We extended a Bayesian model to predict metapopulation viability under 9 urbanization and management scenarios and incorporated the full probability distribution of possible outcomes for each scenario into the cost‐effectiveness analysis. This allowed us to discern between cost‐effective alternatives that were robust to uncertainty and those with a relatively high risk of failure. We found a relatively high risk of extinction following urbanization if the only action was reservation of core habitat; habitat creation actions performed better than enhancement actions; and cost‐effectiveness ranking changed depending on the consideration of uncertainty. Our results suggest that creation and maintenance of wetlands dedicated to L. raniformis is the only cost‐effective action likely to result in a sufficiently low risk of extinction. To our knowledge we are the first study to use Bayesian metapopulation viability analysis to explicitly incorporate parametric and demographic uncertainty into a cost‐effective evaluation of conservation actions. The approach offers guidance to decision makers aiming to achieve cost‐effective conservation under uncertainty.     

Incorporating Uncertainty of Management Costs in Sensitivity Analyses of Matrix Population Models

The importance of accounting for economic costs when making environmental‐management decisions subject to resource constraints has been increasingly recognized in recent years. In contrast, uncertainty associated with such costs has often been ignored. We developed a method, on the basis of economic theory, that accounts for the uncertainty in population‐management decisions. We considered the case where, rather than taking fixed values, model parameters are random variables that represent the situation when parameters are not precisely known. Hence, the outcome is not precisely known either. Instead of maximizing the expected outcome, we maximized the probability of obtaining an outcome above a threshold of acceptability. We derived explicit analytical expressions for the optimal allocation and its associated probability, as a function of the threshold of acceptability, where the model parameters were distributed according to normal and uniform distributions. To illustrate our approach we revisited a previous study that incorporated cost‐efficiency analyses in management decisions that were based on perturbation analyses of matrix population models. Incorporating derivations from this study into our framework, we extended the model to address potential uncertainties. We then applied these results to 2 case studies: management of a Koala (Phascolarctos cinereus) population and conservation of an olive ridley sea turtle (Lepidochelys olivacea) population. For low aspirations, that is, when the threshold of acceptability is relatively low, the optimal strategy was obtained by diversifying the allocation of funds. Conversely, for high aspirations, the budget was directed toward management actions with the highest potential effect on the population. The exact optimal allocation was sensitive to the choice of uncertainty model. Our results highlight the importance of accounting for uncertainty when making decisions and suggest that more effort should be placed on understanding the distributional characteristics of such uncertainty. Our approach provides a tool to improve decision making.     

Accounting for Complementarity to Maximize Monitoring Power for Species Management

To choose among conservation actions that may benefit many species, managers need to monitor the consequences of those actions. Decisions about which species to monitor from a suite of different species being managed are hindered by natural variability in populations and uncertainty in several factors: the ability of the monitoring to detect a change, the likelihood of the management action being successful for a species, and how representative species are of one another. However, the literature provides little guidance about how to account for these uncertainties when deciding which species to monitor to determine whether the management actions are delivering outcomes. We devised an approach that applies decision science and selects the best complementary suite of species to monitor to meet specific conservation objectives. We created an index for indicator selection that accounts for the likelihood of successfully detecting a real trend due to a management action and whether that signal provides information about other species. We illustrated the benefit of our approach by analyzing a monitoring program for invasive predator management aimed at recovering 14 native Australian mammals of conservation concern. Our method selected the species that provided more monitoring power at lower cost relative to the current strategy and traditional approaches that consider only a subset of the important considerations. Our benefit function accounted for natural variability in species growth rates, uncertainty in the responses of species to the prescribed action, and how well species represent others. Monitoring programs that ignore uncertainty, likelihood of detecting change, and complementarity between species will be more costly and less efficient and may waste funding that could otherwise be used for management. Contabilización de la Complementariedad para Maximizar el Poder de Monitoreo para el Manejo de Especies     

The Why,What, and How of Global Biodiversity Indicators Beyond the 2010 Target

Abstract: The 2010 biodiversity target agreed by signatories to the Convention on Biological Diversity directed the attention of conservation professionals toward the development of indicators with which to measure changes in biological diversity at the global scale. We considered why global biodiversity indicators are needed, what characteristics successful global indicators have, and how existing indicators perform. Because monitoring could absorb a large proportion of funds available for conservation, we believe indicators should be linked explicitly to monitoring objectives and decisions about which monitoring schemes deserve funding should be informed by predictions of the value of such schemes to decision making. We suggest that raising awareness among the public and policy makers, auditing management actions, and informing policy choices are the most important global monitoring objectives. Using four well‐developed indicators of biological diversity (extent of forests, coverage of protected areas, Living Planet Index, Red List Index) as examples, we analyzed the characteristics needed for indicators to meet these objectives. We recommend that conservation professionals improve on existing indicators by eliminating spatial biases in data availability, fill gaps in information about ecosystems other than forests, and improve understanding of the way indicators respond to policy changes. Monitoring is not an end in itself, and we believe it is vital that the ultimate objectives of global monitoring of biological diversity inform development of new indicators.     

The dilemma of pest suppression in the conservation of endangered species

In the conservation of endangered species, suppression of a population of one native species to benefit another poses challenges. Examples include predator control and nest parasite reduction. Less obvious is the control of blood-feeding arthropods. We conducted a case study of the effect of native black flies (Simulium spp.) on reintroduced Whooping Cranes (Grus americana). Our intent was to provide a science-driven approach for determining the effects of blood-feeding arthropods on endangered vertebrates and identifying optimal management actions for managers faced with competing objectives. A multiyear experiment demonstrated that black flies reduce nest success in cranes by driving incubating birds off their nests. We used a decision-analytic approach to develop creative management alternatives and evaluate trade-offs among competing objectives. We identified 4 management objectives: establish a self-sustaining crane population, improve crane well-being, maintain native black flies as functional components of the ecosystem, and minimize costs. We next identified potential management alternatives: do nothing, suppress black flies, force crane renesting to occur after the activity period of black flies, relocate releases of cranes, suppress black flies and relocate releases, or force crane renesting and relocate releases. We then developed predictions on constructed scales of 0 (worst-performing alternative) to 1 (best-performing alternative) to indicate how alternative actions performed in terms of management objectives. The optimal action depended on the relative importance of each objective to a decision maker. Only relocating releases was a dominated alternative, indicating that it was not optimal regardless of the relative importance of objectives. A rational decision maker could choose any other management alternative we considered. Recognizing that decisions involve trade-offs that must be weighed by decision makers is crucial to identifying alternatives that best balance multiple management objectives. Given uncertainty about the population dynamics of blood-feeding arthropods, an adaptive management approach could offer substantial benefits.     

Investment and the Policy Process in Conservation Monitoring

Despite decades of discussion and implementation, conservation monitoring remains a challenge. Many current solutions in the literature focus on improving the science or making more structured decisions. These insights are important but incomplete in accounting for the politics and economics of the conservation decisions informed by monitoring. Our novel depiction of the monitoring enterprise unifies insights from multiple disciplines (conservation, operations research, economics, and policy) and highlights many underappreciated factors that affect the expected benefits of monitoring. For example, there must be a strong link between the specific needs of decision makers and information gathering. Furthermore, the involvement of stakeholders other than scientists and research managers means that new information may not be interpreted and acted upon as expected. While answering calls for sharply delineated objectives will clearly add focus to monitoring efforts, for practical reasons, high‐level goals may purposefully be left vague, to facilitate other necessary steps in the policy process. We use the expanded depiction of the monitoring process to highlight problems of cooperation and conflict. We critique calls to invest in monitoring for the greater good by arguing that incentives are typically lacking. Although the benefits of learning accrued within a project (e.g., improving management) provide incentives for investing in some monitoring, it is unrealistic, in general, to expect managers to add potentially costly measures to generate shared benefits. In the traditional linear model of the role of science in policy decisions, monitoring reduces uncertainty and decision makers are rational, unbiased consumers of the science. However, conservation actions increasingly involve social conflict. Drawing insights from political science, we argue that in high‐conflict situations, it is necessary to address the conflict prior to monitoring. Las Inversiones y el Proceso de Políticas en el Monitoreo de la Conservación Sanchirico et al.     

Use of Multicriteria Decision Analysis to Address Conservation Conflicts

Conservation conflicts are increasing on a global scale and instruments for reconciling competing interests are urgently needed. Multicriteria decision analysis (MCDA) is a structured, decision‐support process that can facilitate dialogue between groups with differing interests and incorporate human and environmental dimensions of conflict. MCDA is a structured and transparent method of breaking down complex problems and incorporating multiple objectives. The value of this process for addressing major challenges in conservation conflict management is that MCDA helps in setting realistic goals; entails a transparent decision‐making process; and addresses mistrust, differing world views, cross‐scale issues, patchy or contested information, and inflexible legislative tools. Overall we believe MCDA provides a valuable decision‐support tool, particularly for increasing awareness of the effects of particular values and choices for working toward negotiated compromise, although an awareness of the effect of methodological choices and the limitations of the method is vital before applying it in conflict situations. Uso de Análisis de Decisiones Multicriterio para Abordar Conflictos de Conservación     

Effect of risk aversion on prioritizing conservation projects

Conservation outcomes are uncertain. Agencies making decisions about what threat mitigation actions to take to save which species frequently face the dilemma of whether to invest in actions with high probability of success and guaranteed benefits or to choose projects with a greater risk of failure that might provide higher benefits if they succeed. The answer to this dilemma lies in the decision maker's aversion to risk—their unwillingness to accept uncertain outcomes. Little guidance exists on how risk preferences affect conservation investment priorities. Using a prioritization approach based on cost effectiveness, we compared 2 approaches: a conservative probability threshold approach that excludes investment in projects with a risk of management failure greater than a fixed level, and a variance‐discounting heuristic used in economics that explicitly accounts for risk tolerance and the probabilities of management success and failure. We applied both approaches to prioritizing projects for 700 of New Zealand's threatened species across 8303 management actions. Both decision makers’ risk tolerance and our choice of approach to dealing with risk preferences drove the prioritization solution (i.e., the species selected for management). Use of a probability threshold minimized uncertainty, but more expensive projects were selected than with variance discounting, which maximized expected benefits by selecting the management of species with higher extinction risk and higher conservation value. Explicitly incorporating risk preferences within the decision making process reduced the number of species expected to be safe from extinction because lower risk tolerance resulted in more species being excluded from management, but the approach allowed decision makers to choose a level of acceptable risk that fit with their ability to accommodate failure. We argue for transparency in risk tolerance and recommend that decision makers accept risk in an adaptive management framework to maximize benefits and avoid potential extinctions due to inefficient allocation of limited resources. El Efecto de la Aversión de Riesgo sobre la Priorización de Proyectos de Conservación