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This case study describes the application of a framework for developing stakeholder-driven scenarios of the future. The purpose of these scenarios is to inform land use planning toward the protection of ecosystems and derivable ecosystem services in Northwestern Virginia. We held two scenario development workshops with regional experts in conservation, agriculture, land use planning, policy, and economic development to create scenarios of land use in the northern Piedmont and northern Shenandoah Valley of Virginia. We structured the workshops around a framework that guided stakeholders through several steps eventually resulting in four unique scenarios describing the region in 50 years. Scenario narratives were defined by the intersection of highly influential and uncertain drivers of change relevant to land use planning and ecosystem services. Participants from the northern Shenandoah Valley region selected population growth and climate change adaptation as their scenario defining drivers, while participants from the northern Piedmont region selected planning strategy and climate change impact as their scenario defining drivers. Participants fleshed out scenarios into descriptive narratives that incorporated qualitative and quantitative measures of change. Details from the scenario narratives informed land use change models to further quantify tradeoffs between land use planning decisions and ecosystem services. Individuals interested in using scenario planning to guide research efforts, conservation, or land use planning, or even to broaden perspectives on how to view the future, will find value in this case study.

New England is a predominately forested landscape in which 80% of the forest is privately owned and patterns of land use are the result of diverse landowners acting individually in response to shifting social and economic conditions. In aggregate, perspectives of regional stakeholders can help to inform the challenges and opportunities related to achieving sustainable land-use at the landscape scale in regions like New England. We conducted structured interviews with stakeholders—largely resource management professionals—working in fields related to land-use management (n = 57) to elicit their perspectives on the future of New England’s landscape. The responses were analysed using qualitative content analysis and coded in terms of perceived challenges and opportunities for promoting sustainable land-use trajectories amidst conflicting priorities. The stakeholders overwhelmingly viewed ecological and social issues as interconnected rather than as distinct systems. They perceive the central challenges to sustainability to be: lack of funding and government support, increased development pressures, changing landowner demographics, and the difficulty of accounting for aggregate impacts in a dispersed planning context. The reduced ability of landowners to derive market values from their land was an overarching concern, with parcelization, fragmentation, and poorly planned development viewed as having a disproportionate impact on the character of the land and the potential to exacerbate the negative impacts of other drivers such as climate change. Perceived opportunities for promoting sustainable futures include improving the liveability of urban areas and quality of urban planning to encourage more compact forms of development, and realigning monetary incentives to recognize the collective benefits that forested landowners provide.

Structured protocols offer a transparent and systematic way to elicit and combine/aggregate, probabilistic predictions from multiple experts. These judgements can be aggregated behaviourally or mathematically to derive a final group prediction. Mathematical rules (e.g., weighted linear combinations of judgments) provide an objective approach to aggregation. The quality of this aggregation can be defined in terms of accuracy, calibration and informativeness. These measures can be used to compare different aggregation approaches and help decide on which aggregation produces the “best” final prediction. When experts’ performance can be scored on similar questions ahead of time, these scores can be translated into performance-based weights, and a performance-based weighted aggregation can then be used. When this is not possible though, several other aggregation methods, informed by measurable proxies for good performance, can be formulated and compared. Here, we develop a suite of aggregation methods, informed by previous experience and the available literature. We differentially weight our experts’ estimates by measures of reasoning, engagement, openness to changing their mind, informativeness, prior knowledge, and extremity, asymmetry or granularity of estimates. Next, we investigate the relative performance of these aggregation methods using three datasets. The main goal of this research is to explore how measures of knowledge and behaviour of individuals can be leveraged to produce a better performing combined group judgment. Although the accuracy, calibration, and informativeness of the majority of methods are very similar, a couple of the aggregation methods consistently distinguish themselves as among the best or worst. Moreover, the majority of methods outperform the usual benchmarks provided by the simple average or the median of estimates.

To help prepare for an uncertain future, planners and scientists often engage with stakeholders to co-design alternative scenarios of land-use change. Methods to translate the resulting qualitative scenarios into quantitative simulations that characterize the future landscape condition are needed to understand consequences of the scenarios while maintaining the legitimacy of the process. We use the New England Landscape Futures (NELF) project as a case study to demonstrate a transparent method for translating participatory scenarios to simulations of Land-Use and Land-Cover (LULC) change and for understanding the major drivers of land-use change and diversity of plausible scenarios and the consequences of alternative land-use pathways for conservation priorities. The NELF project co-designed four narrative scenarios that contrast with a Recent Trends scenario that projects a continuation of observed changes across the 18-million-hectare region during the past 20 years. Here, we (1) describe the process and utility of translating qualitative scenarios into spatial simulations using a dynamic cellular land change model; (2) evaluate the outcomes of the scenarios in terms of the differences in the LULC configuration relative to the Recent Trends scenario and to each other; (3) compare the fate of forests within key areas of concern to the stakeholders; and (4) describe how a user-inspired outreach tool was developed to make the simulations and analyses accessible to diverse users. The four alternative scenarios populate a quadrant of future conditions that crosses high to low natural resource planning and innovation with local to global socio-economic connectedness. The associated simulations are strongly divergent in terms of the amount of LULC change and the spatial pattern of change. Features of the simulations can be linked back to the original storylines. Among the scenarios there is a fivefold difference in the amount of high-density development, and a twofold difference in the amount of protected land. Overall, the rate of LULC change has a greater influence on forestlands of concern to the stakeholders than does the spatial configuration. The simulated scenarios have been integrated into an online mapping tool that was designed via a user-engagement process to meet the needs of diverse stakeholders who are interested the future of the land and in using future scenarios to guide land use planning and conservation priorities.

In risky situations characterized by imminent decisions, scarce resources, and insufficient data, policymakers rely on experts to estimate model parameters and their associated uncertainties. Different elicitation and aggregation methods can vary substantially in their efficacy and robustness. While it is generally agreed that biases in expert judgments can be mitigated using structured elicitations involving groups rather than individuals, there is still some disagreement about how to best elicit and aggregate judgments. This mostly concerns the merits of using performance-based weighting schemes to combine judgments of different individuals (rather than assigning equal weights to individual experts), and the way that interaction between experts should be handled. This article aims to contribute to, and complement, the ongoing discussion on these topics.

To help prepare for an uncertain future, planners and scientists often engage with stakeholders to co-design alternative scenarios of land-use change. Methods to translate the resulting qualitative scenarios into quantitative simulations that characterize the future landscape condition are needed to understand consequences of the scenarios while maintaining the legitimacy of the process. We use the New England Landscape Futures (NELF) project as a case study to demonstrate a transparent method for translating participatory scenarios to simulations of Land-Use and Land-Cover (LULC) change and for understanding the major drivers of land-use change and diversity of plausible scenarios and the consequences of alternative land-use pathways for conservation priorities. The NELF project co-designed four narrative scenarios that contrast with a Recent Trends scenario that projects a continuation of observed changes across the 18-million-hectare region during the past 20 years. Here, we (1) describe the process and utility of translating qualitative scenarios into spatial simulations using a dynamic cellular land change model; (2) evaluate the outcomes of the scenarios in terms of the differences in the LULC configuration relative to the Recent Trends scenario and to each other; (3) compare the fate of forests within key areas of concern to the stakeholders; and (4) describe how a user-inspired outreach tool was developed to make the simulations and analyses accessible to diverse users. The four alternative scenarios populate a quadrant of future conditions that crosses high to low natural resource planning and innovation with local to global socio-economic connectedness. The associated simulations are strongly divergent in terms of the amount of LULC change and the spatial pattern of change. Features of the simulations can be linked back to the original storylines. Among the scenarios there is a fivefold difference in the amount of high-density development, and a twofold difference in the amount of protected land. Overall, the rate of LULC change has a greater influence on forestlands of concern to the stakeholders than does the spatial configuration. The simulated scenarios have been integrated into an online mapping tool that was designed via a user-engagement process to meet the needs of diverse stakeholders who are interested the future of the land and in using future scenarios to guide land use planning and conservation priorities.

In dynamic landscapes, effective species conservation requires an understanding of the spatial and temporal dynamics of species’ habitats. In this study, vegetation data across differently aged sites, site management history data and expert elicitation are used to estimate (i) expected habitat patch lifetimes and (ii) the impacts of habitat management history on how habitat quality changes through time for an early-successional habitat specialist, the endangered false heath fritillary butterfly (Melitaea diamina). Results demonstrate the accelerated temporal dynamics experienced by false heath fritillary habitats, with the quality of false heath fritillary habitats peaking 2–3 years after management, and a median-sized habitat patch initially without tree cover predicted to become unsuitable 15 years after management due to overgrowth. As a co-product of habitat management patterns, habitat succession and land use changes, non-conserved false heath fritillary habitats had an expected lifetime of 13.1 years. This study demonstrates a method that can be used to estimate habitat network dynamics for an early-successional habitat specialist economically in situations where the urgency of conservation challenges favours fast decision-making.

In risky situations characterized by imminent decisions, scarce resources, and insufficient data, policymakers rely on experts to estimate model parameters and their associated uncertainties. Different elicitation and aggregation methods can vary substantially in their efficacy and robustness. While it is generally agreed that biases in expert judgments can be mitigated using structured elicitations involving groups rather than individuals, there is still some disagreement about how to best elicit and aggregate judgments. This mostly concerns the merits of using performance-based weighting schemes to combine judgments of different individuals (rather than assigning equal weights to individual experts), and the way that interaction between experts should be handled. This article aims to contribute to, and complement, the ongoing discussion on these topics.

Aim: The koala is a widely distributed Australian marsupial with regional populations that are in rapid decline, are stable or have increased in size. This study examined whether it is possible to use expert elicitation to estimate abundance and trends of populations of this species. Diverse opinions exist about estimates of abundance and, consequently, the status of populations. Location: Eastern and south-eastern Australia Methods: Using a structured, four-step question format, a panel of 15 experts estimated population sizes of koalas and changes in those sizes for bioregions within four states. They provided their lowest plausible estimate, highest plausible estimate, best estimate and their degree of confidence that the true values were contained within these upper and lower estimates. We derived estimates of the mean population size of koalas and associated uncertainties for each bioregion and state. Results: On the basis of estimates of mean population sizes for each bioregion and state, we estimated that the total number of koalas for Australia is 329,000 (range 144,000-605,000) with an estimated average decline of 24% over the past three generations and the next three generations. Estimated percentage of loss in Queensland, New South Wales, Victoria and South Australia was 53%, 26%, 14% and 3%, respectively. Main conclusions: It was not necessary to achieve high levels of certainty or consensus among experts before making informed estimates. A quantitative, scientific method for deriving estimates of koala populations and trends was possible, in the absence of empirical data on abundances.

Developing scenarios to explore possible environmental futures is a widely used tool in social-ecological research. Scenario planners working in environmental systems increasingly enlist stakeholders to help develop scenarios, but effectively integrating stakeholder participation with scenario analyses and modeling remains a challenge. Using the New England Landscape Futures project as a case study, we explore how a method for codesigning a scenario elicitation process can be used to help balance the needs of both stakeholders and scientists. To illustrate the design process, we document eight influential decisions made with stakeholder input, describe the competing demands that we negotiated, and outline the rationale for the selected approach. We find that three priorities drove most of our decisions: maximizing stakeholder involvement in the scenario development process, efficient use of stakeholder time, and research needs. The outcome was a robust, intense, and highly structured one-day scenario development protocol that engaged stakeholders in the full scenario development process from initial orientation and identification of driving forces through to fleshed-out scenarios narratives and quantitative inputs able to inform land-use simulations. Its deployment in six state-specific workshops was successful in eliciting divergent scenarios that stakeholders perceived as being plausible and relevant. Stakeholder responses to the process were positive, though also reflected the compromises made during the codesign process. Research needs were largely met, though initial expectations likely exceeded what could reasonably be elicited from a stakeholder group in one day. Our experiences highlight the importance of process design and how selection of scenario development techniques should follow from the project objectives, problem context, and stakeholder preferences for engagement activities. The use of a codesign framework that recognizes the challenges involved and engages stakeholders in the design process can act as a shared learning experience and contribute to greater effectiveness and impact for participatory social-ecological scenario processes.

Summary Expert judgment informs a variety of important applications in conservation and natural resource management, including threatened species management, environmental impact assessment, and structured decision-making. However, expert judgments can be prone to contextual biases. Structured elicitation protocols mitigate these biases and improve the accuracy and transparency of the resulting judgments. Despite this, the elicitation of expert judgment within conservation and natural resource management remains largely informal. We suggest this may be attributed to financial and practical constraints which are not addressed by many existing structured elicitation protocols. In this paper, we advocate that structured elicitation protocols must be adopted when expert judgments are used to inform science. In order to motivate a wider adoption of structured elicitation protocols, we outline the IDEA protocol. The protocol improves the accuracy of expert judgments and includes several key steps which may be familiar to many conservation researchers, such as the four-step elicitation, and a modified Delphi procedure (“Investigate”, “Discuss”, “Estimate” and “Aggregate”). It can also incorporate remote elicitation, making structured expert judgment accessible on a modest budget. The IDEA protocol has recently been outlined in the scientific literature, however, a detailed description has been missing. This paper fills that important gap by clearly outlining each of the steps required to prepare for and undertake an elicitation. Whilst this paper focuses on the need for the IDEA protocol within conservation and natural resource management, the protocol (and the advice contained in this paper), is applicable to a broad range of scientific domains, as evidenced by its application to biosecurity, engineering, and political forecasting. By clearly outlining the IDEA protocol, we hope that structured protocols will be more widely understood and adopted, resulting in improved judgments and increased transparency when expert judgment is required. This article is protected by copyright. All rights reserved.

Aim Decision-making for conservation management often involves evaluating risks in the face of environmental uncertainty. Models support decision-making by (1) synthesizing available knowledge in a systematic, rational and transparent way and (2) providing a platform for exploring and resolving uncertainty about the consequences of management decisions. Despite their benefits, models are still not used in many conservation decision-making contexts. In this article, we provide evidence of common objections to the use of models in environmental decision-making. In response, we present a series of practical solutions for modellers to help improve the effectiveness and relevance of their work in conservation decision-making. Location Global review. Methods We reviewed scientific and grey literature for evidence of common objections to the use of models in conservation decision-making. We present a set of practical solutions based on theory, empirical evidence and best-practice examples to help modellers substantively address these objections. Results We recommend using a structured decision-making framework to guide good modelling practice in decision-making and highlight a variety of modelling techniques that can be used to support the process. We emphasize the importance of participatory decision-making to improve the knowledgebase and social acceptance of decisions and to facilitate better conservation outcomes. Improving communication and building trust are key to successfully engaging participants, and we suggest some practical solutions to help modellers develop these skills.

Aim: Effective decisions for managing invasive species depend on feedback about the progress of eradication efforts. Panetta & Lawes. developed the eradograph, an intuitive graphical tool that summarizes the temporal trajectories of delimitation and extirpation to support decision-making. We correct and extend the tool, which was affected by incompatibilities in the units used to measure these features that made the axes impossible to interpret biologically. Location: Victoria, New South Wales and Queensland, Australia. Methods: Panetta and Lawes' approach represented delimitation with estimates of the changes in the area known to be infested and extirpation with changes in the mean time since the last detection. We retain the original structure but propose different metrics that improve biological interpretability. We illustrate the methods with a hypothetical example and real examples of invasion and treatment of branched broomrape (Orobanche ramosa L.) and the guava rust complex (Puccinia psidii (Winter 1884)) in Australia. Results: These examples illustrate the potential of the tool to guide decisions about the effectiveness of search and control activities. Main conclusions: The eradograph is a graphical data summary tool that provides insight into the progress of eradication. Our correction and extension of the tool make it easier to interpret and provide managers with better decision support. © 2013 John Wiley & Sons Ltd.

This study presents the results of an approach to the prediction of the outcomes of geopolitical events, which we term the IDEA protocol. The participants investigate the background and causal factors behind a question, predict the outcome, and discuss their thinking with others. They then make a second, private and anonymous judgement of the probability of the event, which is subsequently aggregated mathematically. The method performed well relative to both an equally weighted linear pool and a prediction market, and is relatively simple to implement. The results indicate the value of discussion for removing arbitrary linguistic uncertainty and for sharing and debating knowledge, thereby improving the judgements. Weighting individual judgements based on prior performance using Cooke's method improved group judgements. Even though some of the results are not statistically significant, the study may not have had sufficient power to detect some important effects. Nevertheless, the results help us to formulate conjectures, which can then be investigated further.

Expert judgement is pervasive in all forms of risk analysis, yet the development of tools to deal with such judgements in a repeatable and transparent fashion is relatively recent. This work outlines new findings related to an approach to expert elicitation termed the IDEA protocol. IDEA combines psychologically robust interactions among experts with mathematical aggregation of individual estimates. In particular, this research explores whether communication among experts adversely effects the reliability of group estimates. Using data from estimates of the outcomes of geopolitical events, we find that loss of independence is relatively modest and it is compensated by improvements in group accuracy.

Summary 1. Expert knowledge is used routinely to inform listing decisions under the IUCN Red List criteria. Differences in opinion arise between experts in the presence of epistemic uncertainty, as a result of different interpretations of incomplete information and differences in individual beliefs, values and experiences. Structured expert elicitation aims to anticipate and account for such differences to increase the accuracy of final estimates. 2. A diverse panel of 16 experts independently evaluated up to 125 parameters per taxon to assess the IUCN Red List category of extinction risk for nine Australian bird taxa. Each panellist was provided with the same baseline data. Additional judgments and advice were sought from taxon specialists outside the panel. One question set elicited lowest and highest plausible estimates, best estimates and probabilities that the true values were contained within the upper and lower bounds. A second question set elicited yes ⁄ no answers and a degree of credibility in the answer provided. 3. Once initial estimates were obtained, all panellists were shown each others’ values. They discussed differences and reassessed their original values. Most communication was carried out by email. 4. The process took nearly 6 months overall to complete, and required an average of 1 h and up to 13 h per taxon for a panellist to complete the initial assessment. 5. Panellists were mostly in agreement with one another about IUCN categorisations for each taxon. Where they differed, there was some evidence of convergence in the second round of assessments, although there was persistent non-overlap for about 2% of estimates. The method exposed evidence of common subjective biases including overconfidence, anchoring to available data, definitional ambiguity and the conceptual difficulty of estimating percentages rather than natural numbers. 6. This study demonstrates the value of structured elicitation techniques to identify and to reduce potential sources of bias and error among experts. The formal nature of the process meant that the consensus position reached carried greater weight in subsequent deliberations on status. The structured process is worthwhile for high profile or contentious taxa, but may be too time intensive for less divisive cases.

Aim Expert knowledge routinely informs ecological research and decision-making. Its reliability is often questioned, but is rarely subject to empirical testing and validation. We investigate the ability of experts to make quantitative predictions of variables for which the answers are known. Location Global. Methods Experts in four ecological subfields were asked to make predictions about the outcomes of scientific studies, in the form of unpublished (in press) journal articles, based on information in the article introduction and methods sections. Estimates from students were elicited for one case study for comparison. For each variable, participants assessed a lower and upper bound, best guess and level of confidence that the observed value will lie within their ascribed interval. Responses were assessed for (1) accuracy: the degree to which predictions corresponded with observed experimental results, (2) informativeness: precision of the uncertainty bounds, and (3) calibration: degree to which the uncertainty bounds contained the truth as often as specified. Results Expert responses were found to be overconfident, specifying 80% confidence intervals that captured the truth only 49-65% of the time. In contrast, student 80% intervals captured the truth 76% of the time, displaying close to perfect calibration. Best estimates from experts were on average more accurate than those from students. The best students outperformed the worst experts. No consistent relationships were observed between performance and years of experience, publication record or self-assessment of expertise. Main conclusions Experts possess valuable knowledge but may require training to communicate this knowledge accurately. Expert status is a poor guide to good performance. In the absence of training and information on past performance, simple averages of expert responses provide a robust counter to individual variation in performance. © 2012 Blackwell Publishing Ltd.

Expert knowledge is used widely in the science and practice of conservation because of the complexity of problems, relative lack of data, and the imminent nature of many conservation decisions. Expert knowledge is substantive information on a particular topic that is not widely known by others. An expert is someone who holds this knowledge and who is often deferred to in its interpretation. We refer to predictions by experts of what may happen in a particular context as expert judgments. In general, an expert-elicitation approach consists of five steps: deciding how information will be used, determining what to elicit, designing the elicitation process, performing the elicitation, and translating the elicited information into quantitative statements that can be used in a model or directly to make decisions. This last step is known as encoding. Some of the considerations in eliciting expert knowledge include determining how to work with multiple experts and how to combine multiple judgments, minimizing bias in the elicited information, and verifying the accuracy of expert information. We highlight structured elicitation techniques that, if adopted, will improve the accuracy and information content of expert judgment and ensure uncertainty is captured accurately. We suggest four aspects of an expert elicitation exercise be examined to determine its comprehensiveness and effectiveness: study design and context, elicitation design, elicitation method, and elicitation output. Just as the reliability of empirical data depends on the rigor with which it was acquired so too does that of expert knowledge.

Free to read on publisher website In general, conservation seeks to prevent further habitat loss but in many cases there is a need to reverse habitat degradation. Restoration of habitat is necessary to achieve biodiversity conservation goals but often it is a costly and time-intensive process. Prioritization of where and when habitat is restored can help to ensure the cost-effective delivery of desired outcomes. 2. We develop a restoration prioritization decision support tool to identify the combination of restoration sites and the schedule for their implementation most likely to deliver the greatest utility for a fixed budget and operational constraints. We use a case study to apply our prioritization approach in order to illustrate the data that can be employed to parameterise the analysis and the outputs that are able to inform restoration planning. We compare restoration schedules under alternative utility functions to demonstrate trade-offs associated with different objectives, assumptions and preferences for particular outcomes. 3. Our prioritization approach is spatially and temporally explicit and accounts for the costs and benefits of restoration, the likelihood of restoration success, the probability of stochastic events, feedbacks, time lags and spatial connectivity. 4. Through collaboration with restoration practitioners we derive quantitative and spatially explicit data on each site requiring restoration. We determine the relative priority for restoring each site and develop a restoration schedule over 20years. 5. Our results showed that after 20years a little over a half of the sites requiring restoration are likely be successfully restored, while the total expenditure at our site will be c. US13·7million - almost the entire budget of 14million. 6. Synthesis and applications. Our restoration prioritization approach provides a schedule for where and when restoration should occur, and also provides operational guidance and support for cost-effective restoration planning such as informing the likely total cost of restoration. © 2011 The Authors. Journal of Applied Ecology © 2011 British Ecological Society.

Expert judgments are a necessary part of environmental management. Typically, experts are defined by their qualifications, track record, professional standing, and experience. We outline the limitations of conventional definitions of expertise and describe how these requirements can sometimes exclude people with useful knowledge. The frailties and biases in expert judgments can interact with the social status afforded to experts to produce judgments that are both unassailable and wrong. Several approaches may improve the rigor of expert judgments; they include widening the set of experiences and skills involved in deliberations, employing structured elicitation, and making experts more accountable through testing and training. We outline the most serious impediments to the routine deployment of these tools, and suggest protocols that would overcome these hurdles.

NB! https://doi.org/10.1111/csp2.6 (right) Wrong doi reported in PDF Considerable effort has gone into assessing the effectiveness of protected areas (PAs) in preventing biodiversity loss, and PA impacts on local communities. However, little is known about how pressures are being perceived and dealt with by local PA managers and what perceptions managers have of biodiversity trends and human‐induced pressures in the PAs they manage. We surveyed and convened a workshop with PA managers in Madagascar asking about the impacts of PA establishment. The managers reported that PAs have been successful in reducing threats. However, managers lacked specific knowledge of trends in species abundance, reporting the need for more species monitoring and knowledge transfer from scientific researchers. We argue that greater collaboration and exchange of knowledge between researchers, managers, and local communities is necessary to ensure that PA effectiveness research is of practical value and contributes to improved PA outcomes. Considerable effort has gone into assessing the effectiveness of protected areas (PAs) in preventing biodiversity loss, and PA impacts on local communities. However, little is known about how pressures are being perceived and dealt with by local PA managers and what perceptions managers have of biodiversity trends and human‐induced pressures in the PAs they manage. We surveyed and convened a workshop with PA managers in Madagascar asking about the impacts of PA establishment. The managers reported that PAs have been successful in reducing threats. However, managers lacked specific knowledge of trends in species abundance, reporting the need for more species monitoring and knowledge transfer from scientific researchers. We argue that greater collaboration and exchange of knowledge between researchers, managers, and local communities is necessary to ensure that PA effectiveness research is of practical value and contributes to improved PA outcomes. Considerable effort has gone into assessing the effectiveness of protected areas (PAs) in preventing biodiversity loss, and PA impacts on local communities. However, little is known about how pressures are being perceived and dealt with by local PA managers and what perceptions managers have of biodiversity trends and human‐induced pressures in the PAs they manage. We surveyed and convened a workshop with PA managers in Madagascar asking about the impacts of PA establishment. The managers reported that PAs have been successful in reducing threats. However, managers lacked specific knowledge of trends in species abundance, reporting the need for more species monitoring and knowledge transfer from scientific researchers. We argue that greater collaboration and exchange of knowledge between researchers, managers, and local communities is necessary to ensure that PA effectiveness research is of practical value and contributes to improved PA outcomes.

Ecological restoration is an increasingly important tool for managing and improving highly degraded or altered environments. Faced with a large number of sites or ecosystems to restore, and a diverse array of restoration approaches, investments in ecological restoration must be prioritized. Nevertheless, there are relatively few examples of the systematic prioritization of restoration actions. The development of a general theory for ecological restoration that is sufficiently sophisticated and robust to account for the inherent complexity of restoration planning, and yet is flexible and adaptable to ensure applicability to a diverse array of restoration problems is needed. In this paper we draw on principles from systematic conservation planning to explicitly formulate the ‘restoration prioritization problem’. We develop a generalized theory for static and dynamic restoration planning problems, and illustrate how the basic problem formulation can be expanded to allow for many factors characteristic of restoration problems, including spatial dependencies, the possibility of restoration failure, and the choice of multiple restoration techniques. We illustrate the applicability of our generic problem definition by applying it to a case study – restoration prioritization on The Irvine Ranch Natural Landmark in Southern California. Through this case study we illustrate how the definition of the general restoration problem can be extended to account for the specific constraints and considerations of an on-the-ground restoration problem. Copyright © 2010 Elsevier B.V. All rights reserved.

The optimal allocation of conservation resources between biodiverse conservation regions has generally been calculated using stochastic dynamic programming, or using myopic heuristics. These solutions are hard to interpret and may not be optimal. To overcome these two limitations, this paper approaches the optimal conservation resource allocation problem using optimal control theory. A solution using Pontryagin's maximum principle provides novel insight into the general properties of efficient conservation resource allocation strategies, and allows more extensive testing of the performance of myopic heuristics. We confirmed that a proposed heuristic (minimize short-term loss) yields near-optimal results in complex allocation situations, and found that a qualitative allocation feature observed in previous analyses (bang-bang allocation) is a general property of the optimal allocation strategy.

Uncertainty in the implementation and outcomes of conservation actions that is not accounted for leaves conservation plans vulnerable to potential changes in future conditions. We used a decision-theoretic approach to investigate the effects of two types of investment uncertainty on the optimal allocation of global conservation resources for land acquisition in the Mediterranean Basin. We considered uncertainty about (1) whether investment will continue and (2) whether the acquired biodiversity assets are secure, which we termed transaction uncertainty and performance uncertainty, respectively. We also developed and tested the robustness of different rules of thumb for guiding the allocation of conservation resources when these sources of uncertainty exist. In the presence of uncertainty in future investment ability (transaction uncertainty), the optimal strategy was opportunistic, meaning the investment priority should be to act where uncertainty is highest while investment remains possible. When there was a probability that investments would fail (performance uncertainty), the optimal solution became a complex trade-off between the immediate biodiversity benefits of acting in a region and the perceived longevity of the investment. In general, regions were prioritized for investment when they had the greatest performance certainty, even if an alternative region was highly threatened or had higher biodiversity value. The improved performance of rules of thumb when accounting for uncertainty highlights the importance of explicitly incorporating sources of investment uncertainty and evaluating potential conservation investments in the context of their likely long-term success.

Indigenous societies hold a great deal of ethnoclimatological knowledge that could potentially be of key importance for both climate change science and local adaptation; yet, we lack studies examining how such knowledge might be shaped by media communication. This study systematically investigates the interplay between local observations of climate change and the reception of media information amongst the Tsimane’, an indigenous society of Bolivian Amazonia where the scientific discourse of anthropogenic climate change has barely reached. Specifically, we conducted a Randomized Evaluation with a sample of 424 household heads in 12 villages to test to what degree local accounts of climate change are influenced by externally influenced awareness. We randomly assigned villages to a treatment and control group, conducted workshops on climate change with villages in the treatment group, and evaluated the effects of information dissemination on individual climate change perceptions. Results of this work suggest that providing climate change information through participatory workshops does not noticeably influence individual perceptions of climate change. Such findings stress the challenges involved in translating between local and scientific framings of climate change, and gives cause for concern about how to integrate indigenous peoples and local knowledge with global climate change policy debates.

One of the most pressing issues facing the global conservation community is how to distribute limited resources between regions identified as priorities for biodiversity conservation. Approaches such as biodiversity hotspots, endemic bird areas and ecoregions are used by international organizations to prioritize conservation efforts globally. Although identifying priority regions is an important first step in solving this problem, it does not indicate how limited resources should be allocated between regions. Here we formulate how to allocate optimally conservation resources between regions identified as priorities for conservation--the 'conservation resource allocation problem'. Stochastic dynamic programming is used to find the optimal schedule of resource allocation for small problems but is intractable for large problems owing to the "curse of dimensionality". We identify two easy-to-use and easy-to-interpret heuristics that closely approximate the optimal solution. We also show the importance of both correctly formulating the problem and using information on how investment returns change through time. Our conservation resource allocation approach can be applied at any spatial scale. We demonstrate the approach with an example of optimal resource allocation among five priority regions in Wallacea and Sundaland, the transition zone between Asia and Australasia.

Macro-economic decisions determine the resources allocated at an international and a country-level to natural resource management. Micro-economic theory and tools are then used to ensure that this allocation will materialize into desired economic, environmental and societal outcomes. Restoration projects differ in their costs and benefits. The costs may entail operational costs, and those associated with alternative foregone opportunities. The benefits of restoration may reflect biodiversity outcomes or the provision of ecosystem goods and services, such as the supply of water and carbon sequestration. Restoration also has the potential to ensure supply of timber and non-timber forest products such as food and medicines, with potential significance for subsistence livelihoods. We synthesise approaches to valuing the costs and benefits of restoration projects in order to explore the economic consequences of restoration decisions and to prioritise investments. We finish the chapter by outlining economic incentives and policies that might support the implementation of restoration activities.

Expert knowledge plays an integral role in applied ecology and conservation (Burgman 2005). Environmental systems are characterized by complex dynamics, multiple drivers, and a paucity of data (Carpenter 2002). Action is often required before uncertainties can be resolved. Where empirical data are scarce or unavailable, expert knowledge is often regarded as the best or only source of information (Sutherland 2006; Kuhnert et al. 2010). Experts may be called upon to provide input for all stages of the modeling and management process, and specifically to inform the definition and structuring of the problem (Cowling and Pressey 2003; Sutherland et al. 2008), to inform the selection of data or variables, model structures, and assumptions about functional relationships between variables (Pearce et al. 2001; Czembor and Vesk 2009), and to inform the analysis of data, estimation of parameters, interpretation of results, and the characterization of uncertainty (Alho and Kangas 1997; Martin et al. 2005).

Elicitation of expert opinion is important for risk analysis when only limited data are available. Expert opinion is often elicited in the form of subjective confidence intervals; however, these are prone to substantial overconfidence. We investigated the influence of elicitation question format, in particular the number of steps in the elicitation procedure. In a 3-point elicitation procedure, an expert is asked for a lower limit, upper limit, and best guess, the two limits creating an interval of some assigned confidence level (e.g., 80%). In our 4-step interval elicitation procedure, experts were also asked for a realistic lower limit, upper limit, and best guess, but no confidence level was assigned; the fourth step was to rate their anticipated confidence in the interval produced. In our three studies, experts made interval predictions of rates of infectious diseases (Study 1, n = 21 and Study 2, n = 24: epidemiologists and public health experts), or marine invertebrate populations (Study 3, n = 34: ecologists and biologists). We combined the results from our studies using meta-analysis, which found average overconfidence of 11.9%, 95% CI [3.5, 20.3] (a hit rate of 68.1% for 80% intervals)-a substantial decrease in overconfidence compared with previous studies. Studies 2 and 3 suggest that the 4-step procedure is more likely to reduce overconfidence than the 3-point procedure (Cohen's d = 0.61, [0.04, 1.18]).

Priorities for conservation investment at a global scale that are based on a single taxon have been criticized because geographic richness patterns vary taxonomically. However, these concerns focused only on biodiversity patterns and did not consider the importance of socioeconomic factors, which must also be included if conservation funding is to be allocated efficiently. In this article, we create efficient global funding schedules that use information about conservation costs, predicted habitat loss rates, and the endemicity of seven different taxonomic groups. We discover that these funding allocation schedules are less sensitive to variation in taxon assessed than to variation in cost and threat. Two-thirds of funding is allocated to the same regions regardless of the taxon, compared with only one-fifth if threat and cost are not included in allocation decisions. Hence, if socioeconomic factors are considered, we can be more confident about global-scale decisions guided by single taxonomic groups.

Uncertainty in the implementation and outcomes of conservation actions that is not accounted for leaves conservation plans vulnerable to potential changes in future conditions. We used a decision-theoretic approach to investigate the effects of two types of investment uncertainty on the optimal allocation of global conservation resources for land acquisition in the Mediterranean Basin. We considered uncertainty about (1) whether investment will continue and (2) whether the acquired biodiversity assets are secure, which we termed transaction uncertainty and performance uncertainty, respectively. We also developed and tested the robustness of different rules of thumb for guiding the allocation of conservation resources when these sources of uncertainty exist. In the presence of uncertainty in future investment ability (transaction uncertainty), the optimal strategy was opportunistic, meaning the investment priority should be to act where uncertainty is highest while investment remains possible. When there was a probability that investments would fail (performance uncertainty), the optimal solution became a complex trade-off between the immediate biodiversity benefits of acting in a region and the perceived longevity of the investment. In general, regions were prioritized for investment when they had the greatest performance certainty, even if an alternative region was highly threatened or had higher biodiversity value. The improved performance of rules of thumb when accounting for uncertainty highlights the importance of explicitly incorporating sources of investment uncertainty and evaluating potential conservation investments in the context of their likely long-term success.

BackgroundConventional wisdom identifies biodiversity hotspots as priorities for conservation investment because they capture dense concentrations of species. However, density of species does not necessarily imply conservation 'efficiency'. Here we explicitly consider conservation efficiency in terms of species protected per dollar invested.Methodology/principal findingsWe apply a dynamic return on investment approach to a global biome and compare it with three alternate priority setting approaches and a random allocation of funding. After twenty years of acquiring habitat, the return on investment approach protects between 32% and 69% more species compared to the other priority setting approaches. To correct for potential inefficiencies of protecting the same species multiple times we account for the complementarity of species, protecting up to three times more distinct vertebrate species than alternate approaches.Conclusions/significanceIncorporating costs in a return on investment framework expands priorities to include areas not traditionally highlighted as priorities based on conventional irreplaceability and vulnerability approaches.

Conservation priority-setting schemes have not yet combined geographic priorities with a framework that can guide the allocation of funds among alternate conservation actions that address specific threats. We develop such a framework, and apply it to 17 of the world's 39 Mediterranean ecoregions. This framework offers an improvement over approaches that only focus on land purchase or species richness and do not account for threats. We discover that one could protect many more plant and vertebrate species by investing in a sequence of conservation actions targeted towards specific threats, such as invasive species control, land acquisition, and off-reserve management, than by relying solely on acquiring land for protected areas. Applying this new framework will ensure investment in actions that provide the most cost-effective outcomes for biodiversity conservation. This will help to minimise the misallocation of scarce conservation resources., Author Summary Given limited funds for biodiversity conservation, we need to carefully prioritise where funds are spent. Various schemes have been developed to set priorities for conservation spending among different countries and regions. However, there is no framework for guiding the allocation of funds among alternative conservation actions that address specific threats. Here, we develop such a framework, and apply it to 17 of the world's 39 Mediterranean-climate ecoregions. We discover that one could protect many more plant and vertebrate species by investing in a sequence of conservation actions targeted towards specific threats, such as invasive species control and fire management, rather than by relying solely on acquiring land for protected areas. Applying this new framework will ensure investment in actions that provide the most cost-effective outcomes for biodiversity conservation., A new framework applied to 17 of the world's Mediterranean ecoregions reveals that investing in a sequence of conservation actions targeted towards specific threats will protect more species than just acquiring land for protected areas.

Expert judgment is essential for most practical, science-based risk analyses and forecasts. Typically, experts are asked to provide judgments in precise quantitative language. This requirement is a significant impediment to accurate and well-calibrated judgments because many scientists routinely misinterpret formal statistical language and concepts. Cognitive biases compound these conceptual and linguistic misunderstandings, compromising potentially vital information. We designed a protocol to remedy this problem, using a trained facilitator who deployed a range of techniques to elicit knowledge for a case study of recycled water contamination. The elicitation generated a range of imprecise information about the parameter, which we translated into constraints for probability bounds analysis. This approach allows experts to use forms of reasoning and communication best suited to them. We show how to represent and combine expert knowledge, and discuss the use of probability bounds analysis to supplement expert elicitation by framing risk problems in heuristic and mathematical terms.

Expert judgements are essential when time and resources are stretched or we face novel dilemmas requiring fast solutions. Good advice can save lives and large sums of money. Typically, experts are defined by their qualifications, track record and experience [1], [2]. The social expectation hypothesis argues that more highly regarded and more experienced experts will give better advice. We asked experts to predict how they will perform, and how their peers will perform, on sets of questions. The results indicate that the way experts regard each other is consistent, but unfortunately, ranks are a poor guide to actual performance. Expert advice will be more accurate if technical decisions routinely use broadly-defined expert groups, structured question protocols and feedback.