On Valuing Information in Adaptive‐Management Models

Abstract: Active adaptive management looks at the benefit of using strategies that may be suboptimal in the near term but may provide additional information that will facilitate better management in the future. In many adaptive‐management problems that have been studied, the optimal active and passive policies (accounting for learning when designing policies and designing policy on the basis of current best information, respectively) are very similar. This seems paradoxical; when faced with uncertainty about the best course of action, managers should spend very little effort on actively designing programs to learn about the system they are managing. We considered two possible reasons why active and passive adaptive solutions are often similar. First, the benefits of learning are often confined to the particular case study in the modeled scenario, whereas in reality information gained from local studies is often applied more broadly. Second, management objectives that incorporate the variance of an estimate may place greater emphasis on learning than more commonly used objectives that aim to maximize an expected value. We explored these issues in a case study of Merri Creek, Melbourne, Australia, in which the aim was to choose between two options for revegetation. We explicitly incorporated monitoring costs in the model. The value of the terminal rewards and the choice of objective both influenced the difference between active and passive adaptive solutions. Explicitly considering the cost of monitoring provided a different perspective on how the terminal reward and management objective affected learning. The states for which it was optimal to monitor did not always coincide with the states in which active and passive adaptive management differed. Our results emphasize that spending resources on monitoring is only optimal when the expected benefits of the options being considered are similar and when the pay‐off for learning about their benefits is large.     

Decision Making in a Human Population Living Sustainably

Abstract: The Tiwi people of northern Australia have managed natural resources continuously for 6000–8000 years. Tiwi management objectives and outcomes may reflect how they gather information about the environment. We qualitatively analyzed Tiwi documents and management techniques to examine the relation between the social and physical environment of decision makers and their decision‐making strategies. We hypothesized that principles of bounded rationality, namely, the use of efficient rules to navigate complex decision problems, explain how Tiwi managers use simple decision strategies (i.e., heuristics) to make robust decisions. Tiwi natural resource managers reduced complexity in decision making through a process that gathers incomplete and uncertain information to quickly guide decisions toward effective outcomes. They used management feedback to validate decisions through an information loop that resulted in long‐term sustainability of environmental use. We examined the Tiwi decision‐making processes relative to management of barramundi (Lates calcarifer) fisheries and contrasted their management with the state government's management of barramundi. Decisions that enhanced the status of individual people and their attainment of aspiration levels resulted in reliable resource availability for Tiwi consumers. Different decision processes adopted by the state for management of barramundi may not secure similarly sustainable outcomes.     

Choosing and Using Climate‐Change Scenarios for Ecological‐Impact Assessments and Conservation Decisions

Increased concern over climate change is demonstrated by the many efforts to assess climate effects and develop adaptation strategies. Scientists, resource managers, and decision makers are increasingly expected to use climate information, but they struggle with its uncertainty. With the current proliferation of climate simulations and downscaling methods, scientifically credible strategies for selecting a subset for analysis and decision making are needed. Drawing on a rich literature in climate science and impact assessment and on experience working with natural resource scientists and decision makers, we devised guidelines for choosing climate‐change scenarios for ecological impact assessment that recognize irreducible uncertainty in climate projections and address common misconceptions about this uncertainty. This approach involves identifying primary local climate drivers by climate sensitivity of the biological system of interest; determining appropriate sources of information for future changes in those drivers; considering how well processes controlling local climate are spatially resolved; and selecting scenarios based on considering observed emission trends, relative importance of natural climate variability, and risk tolerance and time horizon of the associated decision. The most appropriate scenarios for a particular analysis will not necessarily be the most appropriate for another due to differences in local climate drivers, biophysical linkages to climate, decision characteristics, and how well a model simulates the climate parameters and processes of interest. Given these complexities, we recommend interaction among climate scientists, natural and physical scientists, and decision makers throughout the process of choosing and using climate‐change scenarios for ecological impact assessment. Selección y Uso de Escenarios de Cambio Climático para Estudios de Impacto Ecológico y Decisiones de Conservación     

An Adaptive‐Management Framework for Optimal Control of Hiking Near Golden Eagle Nests in Denali National Park

Abstract: Unintended effects of recreational activities in protected areas are of growing concern. We used an adaptive‐management framework to develop guidelines for optimally managing hiking activities to maintain desired levels of territory occupancy and reproductive success of Golden Eagles (Aquila chrysaetos) in Denali National Park (Alaska, U.S.A.). The management decision was to restrict human access (hikers) to particular nesting territories to reduce disturbance. The management objective was to minimize restrictions on hikers while maintaining reproductive performance of eagles above some specified level. We based our decision analysis on predictive models of site occupancy of eagles developed using a combination of expert opinion and data collected from 93 eagle territories over 20 years. The best predictive model showed that restricting human access to eagle territories had little effect on occupancy dynamics. However, when considering important sources of uncertainty in the models, including environmental stochasticity, imperfect detection of hares on which eagles prey, and model uncertainty, restricting access of territories to hikers improved eagle reproduction substantially. An adaptive management framework such as ours may help reduce uncertainty of the effects of hiking activities on Golden Eagles.     

Active Adaptive Management for Conservation

Abstract:  Active adaptive management balances the requirements of management with the need to learn about the system being managed, which leads to better decisions. It is difficult to judge the benefit of management actions that accelerate information gain, relative to the benefit of making the best management decision given what is known at the time. We present a first step in developing methods to optimize management decisions that incorporate both uncertainty and learning via adaptive management. We assumed a manager can allocate effort to discrete units (e.g., areas for revegetation or animals for reintroduction), the outcome can be measured as success or failure (e.g., the revegetation in an area is successful or the animal survives and breeds), and the manager has two possible management options from which to choose. We further assumed that there is an annual budget that may be allocated to one or both of the two options and that the manager must decide on the allocation. We used Bayesian updating of the probability of success of the two options and stochastic dynamic programming to determine the optimal strategy over a specified number of years. The costs, level of certainty about the success of the two options, and the timeframe of management all influenced the optimal allocation of the annual budget. In addition, the choice of management objective had a large influence on the optimal decision. In a case study of Merri Creek, Melbourne, Australia, we applied the approach to determining revegetation strategies. Our approach can be used to determine how best to manage ecological systems in the face of uncertainty.     

Decision‐Making Triggers in Adaptive Management

We analyzed whether decision‐making triggers increase accountability of adaptive‐management plans. Triggers are prenegotiated commitments in an adaptive‐management plan that specify what actions are to be taken and when on the basis of information obtained from monitoring. Triggers improve certainty that particular actions will be taken by agencies in the future. We conducted an in‐depth, qualitative review of the political and legal contexts of adaptive management and its application by U.S. federal agencies. Agencies must satisfy the judiciary that adaptive‐management plans meet substantive legal standards and comply with the U.S. National Environmental Policy Act. We examined 3 cases in which triggers were used in adaptive‐management plans: salmon (Oncorhynchus spp.) in the Columbia River, oil and gas development by the Bureau of Land Management, and a habitat conservation plan under the U.S. Endangered Species Act. In all the cases, key aspects of adaptive management, including controls and preidentified feedback loops, were not incorporated in the plans. Monitoring and triggered mitigation actions were limited in their enforceability, which was contingent on several factors, including which laws applied in each case and the degree of specificity in how triggers were written into plans. Other controversial aspects of these plans revolved around who designed, conducted, interpreted, and funded monitoring programs. Additional contentious issues were the level of precaution associated with trigger mechanisms and the definition of ecological baselines used as points of comparison. Despite these challenges, triggers can be used to increase accountability, by predefining points at which an adaptive management plan will be revisited and reevaluated, and thus improve the application of adaptive management in its complicated political and legal context. Detonadores de la Toma de Decisiones en el Manejo Adaptativo     

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     

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.     

Bayesian Decision‐Network Modeling of Multiple Stakeholders for Reef Ecosystem Restoration in the Coral Triangle

Proposals for marine conservation measures have proliferated in the last 2 decades due to increased reports of fishery declines and interest in conservation. Fishers and fisheries managers have often disagreed strongly when discussing controls on fisheries. In such situations, ecosystem‐based models and fisheries‐stock assessment models can help resolve disagreements by highlighting the trade‐offs that would be made under alternative management scenarios. We extended the analytical framework for modeling such trade‐offs by including additional stakeholders whose livelihoods and the value they place on conservation depend on the condition of the marine ecosystem. To do so, we used Bayesian decision‐network models (BDNs) in a case study of an Indonesian coral reef fishery. Our model included interests of the fishers and fishery managers; individuals in the tourism industry; conservation interests of the state, nongovernmental organizations, and the local public; and uncertainties in ecosystem status, projections of fisheries revenues, tourism growth, and levels of interest in conservation. We calculated the total utility (i.e., value) of a range of restoration scenarios. Restricting net fisheries and live‐fish fisheries appeared to be the best compromise solutions under several combinations of settings of modeled variables. Results of our case study highlight the implications of alternate formulations for coral reef stakeholder utility functions and discount rates for the calculation of the net benefits of alternative fisheries management options. This case study may also serve as a useful example for other decision analyses with multiple stakeholders. Modelo de Red de Decisión Bayesiana de Múltiples Actores Interesados en la Restauración de Ecosistemas de Arrecife en el Triángulo de Coral     

Incentivizing Monitoring and Compliance in Trophy Hunting

Conservation scientists are increasingly focusing on the drivers of human behavior and on the implications of various sources of uncertainty for management decision making. Trophy hunting has been suggested as a conservation tool because it gives economic value to wildlife, but recent examples show that overharvesting is a substantial problem and that data limitations are rife. We use a case study of trophy hunting of an endangered antelope, the mountain nyala (Tragelaphus buxtoni), to explore how uncertainties generated by population monitoring and poaching interact with decision making by 2 key stakeholders: the safari companies and the government. We built a management strategy evaluation model that encompasses the population dynamics of mountain nyala, a monitoring model, and a company decision making model. We investigated scenarios of investment into antipoaching and monitoring by governments and safari companies. Harvest strategy was robust to the uncertainty in the population estimates obtained from monitoring, but poaching had a much stronger effect on quota and sustainability. Hence, reducing poaching is in the interests of companies wishing to increase the profitability of their enterprises, for example by engaging community members as game scouts. There is a threshold level of uncertainty in the population estimates beyond which the year‐to‐year variation in the trophy quota prevented planning by the safari companies. This suggests a role for government in ensuring that a baseline level of population monitoring is carried out such that this level is not exceeded. Our results illustrate the importance of considering the incentives of multiple stakeholders when designing frameworks for resource use and when designing management frameworks to address the particular sources of uncertainty that affect system sustainability most heavily. Incentivando el Monitoreo y el Cumplimiento en la Caza de Trofeos     

A Strategy for Monitoring and Managing Declines in an Amphibian Community

Although many taxa have declined globally, conservation actions are inherently local. Ecosystems degrade even in protected areas, and maintaining natural systems in a desired condition may require active management. Implementing management decisions under uncertainty requires a logical and transparent process to identify objectives, develop management actions, formulate system models to link actions with objectives, monitor to reduce uncertainty and identify system state (i.e., resource condition), and determine an optimal management strategy. We applied one such structured decision‐making approach that incorporates these critical elements to inform management of amphibian populations in a protected area managed by the U.S. National Park Service. Climate change is expected to affect amphibian occupancy of wetlands and to increase uncertainty in management decision making. We used the tools of structured decision making to identify short‐term management solutions that incorporate our current understanding of the effect of climate change on amphibians, emphasizing how management can be undertaken even with incomplete information. Estrategia para Monitorear y Manejar Disminuciones en una Comunidad de Anfibios     

Evaluating Areas of High Conservation Value in Western Oregon with a Decision‐Support Model

Abstract: The Northwest Forest Plan was implemented in 1994 to protect habitat for species associated with old‐growth forests, including Northern Spotted Owls (Strix occidentailis caurina) in Washington, Oregon, and northern California (U.S.A.). Nevertheless, 10‐year monitoring data indicate mixed success in meeting the ecological goals of the plan. We used the ecosystem management decision‐support model to evaluate terrestrial and aquatic habitats across the landscape on the basis of ecological objectives of the Northwest Forest Plan, which included maintenance of late‐successional and old‐growth forest, recovery, and maintenance of Pacific salmon (Oncorhynchus spp.), and viability of Northern Spotted Owls. Areas of the landscape that contained habitat characteristics that supported these objectives were considered of high conservation value. We used the model to evaluate ecological condition of each of the 36, 180 township and range sections of the study area. Eighteen percent of the study area was identified as habitat of high conservation value. These areas were mostly on public lands. Many of the sections that contained habitat of exceptional conservation value were on Bureau of Land Management land that has been considered for management‐plan revisions to increase timber harvests. The results of our model can be used to guide future land management in the Northwest Forest Plan area, and illustrate how decision‐support models can help land managers develop strategies to better meet their goals.     

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.     

Management Decentralization and Montane Forest Conditions in Tanzania

Abstract: We examined how differences in local forest‐management institutions relate to disparate anthropogenic forest disturbance and forest conditions among three neighboring montane forests in Tanzania under centralized, comanaged, or communal management. Institutional differences have been shaped by decentralization reforms. We conducted semistructured interviews with members of forest management committees, local government, and village households and measured anthropogenic disturbance, tree structure, and species composition in forest plots. We assessed differences in governance system components of local institutions, including land tenure, decision‐making autonomy by forest users, and official and de facto processes of rule formation, monitoring, and enforcement among the three management strategies. We also assessed differences in frequencies of prohibited logging and subsistence pole cutting, and measures of forest condition. An adjacent research forest served as an ecological reference for comparison of forest conditions. Governance was similar for comanaged and centralized management, whereas communal managers had greater tenure security and decision‐making autonomy over the use and management of their forest. There was significantly less illegal logging in the communal forest, but subsistence pole cutting was common across all management strategies. The comanaged forest was most disturbed by recent logging and pole cutting, as were peripheral areas of the larger centralized forest. This manifested in more degraded indicators of forest conditions (lower mean tree size, basal area, density of trees ≥ 90 cm dbh, and aboveground biomass and higher overall stem density). Greater tenure security and institutional autonomy of the communal strategy contributed to more effective management, less illegal logging, and maintenance of good forest conditions, but generating livelihood benefits was a challenge for both decentralized strategies. Our results underscore the importance of well‐designed institutional arrangements in forest management and illustrate mechanisms for improved forest governance and conservation in the context of Tanzanian decentralization reforms.     

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     

Positives and pathologies of natural resource management on private land‐conservation areas

In managed natural resource systems, such as fisheries and rangelands, there is a recognized trade‐off between managing for short‐term benefits and managing for longer term resilience. Management actions that stabilize ecological attributes or processes can improve productivity in the supply of ecosystem goods and services in the short term but erode system resilience at longer time scales. For example, fire suppression in rangelands can increase grass biomass initially but ultimately result in an undesirable, shrub‐dominated system. Analyses of this phenomenon have focused largely on how management actions influence slow‐changing biophysical system attributes (such as vegetation composition). Data on the frequency of management actions that reduce natural ecological variation on 66 private land‐conservation areas (PLCAs) in South Africa were used to investigate how management actions are influenced by manager decision‐making approaches, a largely ignored part of the problem. The pathology of natural resource management was evident on some PLCAs: increased focus on revenue‐generation in decision making resulted in an increased frequency of actions to stabilize short‐term variation in large mammal populations, which led to increased revenues from ecotourism or hunting. On many PLCAs, these management actions corresponded with a reduced focus on ecological monitoring and an increase in overstocking of game (i.e., ungulate species) and stocking of extralimitals (i.e., game species outside their historical range). Positives in natural resource management also existed. Some managers monitored slower changing ecological attributes, which resulted in less‐intensive management, fewer extralimital species, and lower stocking rates. Our unique, empirical investigation of monitoring‐management relationships illustrates that management decisions informed by revenue monitoring versus ecological monitoring can have opposing consequences for natural resource productivity and sustainability. Promoting management actions that maintain resilience in natural resource systems therefore requires cognizance of why managers act the way they do and how these actions can gradually shift managers toward unsustainable strategies.     

Deconstructing adaptive management: criteria for applications to environmental management.

The concept of adaptive management has, for many ecologists, become a foundation of effective environmental management for initiatives characterized by high levels of ecological uncertainty. Yet problems associated with its application are legendary, and many of the initiatives promoted as examples of adaptive management appear to lack essential characteristics of the approach. In this paper we propose explicit criteria for helping managers and decision makers to determine the appropriateness of either passive or active adaptive-management strategies as a response to ecological uncertainty in environmental management. Four categories of criteria--dealing with spatial and temporal scale, dimensions of uncertainty, the evaluation of costs and benefits, and institutional and stakeholder support--are defined and applied using hypothetical yet realistic case-study scenarios that illustrate a range of environmental management problems. We conclude that many of the issues facing adaptive management may have less to do with the approach itself than with the indiscriminate choice of contexts within which it is now applied.     

A density projection approach for non-trivial information dynamics: Adaptive management of stochastic natural resources

We demonstrate a density projection approximation method for solving resource management problems with imperfect state information. The method expands the set of partially-observed Markov decision process (POMDP) problems that can be solved with standard dynamic programming tools by addressing dimensionality problems in the decision maker's belief state. Density projection is suitable for uncertainty over both physical states (e.g. resource stock) and process structure (e.g. biophysical parameters). We apply the method to an adaptive management problem under structural uncertainty in which a fishery manager's harvest policy affects both the stock of fish and the belief state about the process governing reproduction. We solve for the optimal endogenous learning policy—the active adaptive management approach—and compare it to passive learning and non-learning strategies. We demonstrate how learning improves efficiency but typically follows a period of costly short-run investment.     

Cost‐Effectiveness of Alternative Conservation Strategies with Application to the Pacific Leatherback Turtle

Although holistic conservation addressing all sources of mortality for endangered species or stocks is the preferred conservation strategy, limited budgets require a criterion to prioritize conservation investments. We compared the cost‐effectiveness of nesting site and at‐sea conservation strategies for Pacific leatherback turtles (Dermochelys coriacea). We sought to determine which conservation strategy or mix of strategies would produce the largest increase in population growth rate per dollar. Alternative strategies included protection of nesters and their eggs at nesting beaches in Indonesia, gear changes, effort restrictions, and caps on turtle takes in the Hawaiian (U.S.A.) longline swordfish fishery, and temporal and area closures in the California (U.S.A.) drift gill net fishery. We used a population model with a biological metric to measure the effects of conservation alternatives. We normalized all effects by cost to prioritize those strategies with the greatest biological effect relative to its economic cost. We used Monte Carlo simulation to address uncertainty in the main variables and to calculate probability distributions for cost‐effectiveness measures. Nesting beach protection was the most cost‐effective means of achieving increases in leatherback populations. This result creates the possibility of noncompensatory bycatch mitigation, where high‐bycatch fisheries invest in protecting nesting beaches. An example of this practice is U.S. processors of longline tuna and California drift gill net fishers that tax themselves to finance low‐cost nesting site protection. Under certain conditions, fisheries interventions, such as technologies that reduce leatherback bycatch without substantially decreasing target species catch, can be cost‐effective. Reducing bycatch in coastal areas where bycatch is high, particularly adjacent to nesting beaches, may be cost‐effective, particularly, if fisheries in the area are small and of little commercial value. Rentabilidad de Estrategias de Conservación Alternativas Aplicadas a Tortugas Laúd del Pacífico     

Confronting Uncertainty and Missing Values in Environmental Value Transfer as Applied to Species Conservation

Abstract: The nonuse (or passive) value of nature is important but time‐consuming and costly to quantify with direct surveys. In the absence of estimates of these values, there will likely be less investment in conservation actions that generate substantial nonuse benefits, such as conservation of native species. To help overcome decisions about the allocation of conservation dollars that reflect the lack of estimates of nonuse values, these values can be estimated indirectly by environmental value transfer (EVT). EVT uses existing data or information from a study site such that the estimated monetary value of an environmental good is transferred to another location or policy site. A major challenge in the use of EVT is the uncertainty about the sign and size of the error (i.e., the percentage by which transferred value exceeds the actual value) that results from transferring direct estimates of nonuse values from a study to a policy site, the site where the value is transferred. An EVT is most useful if the decision‐making framework does not require highly accurate information and when the conservation decision is constrained by time and financial resources. To account for uncertainty in the decision‐making process, a decision heuristic that guides the decision process and illustrates the possible decision branches, can be followed. To account for the uncertainty associated with the transfer of values from one site to another, we developed a risk and simulation approach that uses Monte Carlo simulations to evaluate the net benefits of conservation investments and takes into account different possible distributions of transfer error. This method does not reduce transfer error, but it provides a way to account for the effect of transfer error in conservation decision making. Our risk and simulation approach and decision‐based framework on when to use EVT offer better‐informed decision making in conservation.