Planning for Restoration: A Decision Analysis Approach to Prioritization

Ecological restoration often relies on the use of expert opinion to make management decisions in the face of uncertainty. The quantification of expert opinion can be difficult, especially when more than one expert is consulted and experts are not in agreement. Decision analysis can provide a framework to systematically deconstruct a complex problem and provide greater objectivity to restoration decisions. We utilized decision analysis techniques to identify restoration objectives and to quantify expert opinions to prioritize restoration activities at 112 prairie openings in the Edge of Appalachia Preserve in southern Ohio, U.S.A. We first created an objectives hierarchy to model how decision‐makers decide which prairies to manage. We then determined how to measure each component of the hierarchy and sampled all prairies for percent woody cover, geology, indicator species index (an index of plant species richness), slope, aspect, and distance to nearest prairie. We modeled seven different experts’ preferences for managing prairies with varying values for each of these ecological measures. We then interviewed the same decision‐makers to determine relative weights for each component of the objectives hierarchy using trade‐off analysis. By combining the weights, preference relationships, and sampling data, we were able to rank each prairie and management unit based on its management priority. Experts had similar preferences except for the measure of distance to nearest prairie. We found that decision‐makers gave different weights to each of the different components of the hierarchy. Generally, experts weighted percent woody cover, indicator species index, and geology more highly than slope, aspect, and distance to nearest prairie. Despite these differences, priorities for management, once all factors were weighted and combined, were similar.     

The method matters: A guide for indicator aggregation in ecological assessments

Ecological assessment requires the integration of many physical, chemical, and/or biological quality elements. The choice of the aggregation method of such partial assessments into an overall assessment can considerably affect the assessment outcome – an issue that has been controversially discussed within the scientific community for the last decade. Current practice often considers only two different aggregation methods, the weighted arithmetic mean (additive aggregation) and the one-out, all-out method (minimum aggregation). However, both have important drawbacks. Additive aggregation compensates a bad status of one quality element by a number of elements featuring good status. Minimum aggregation can lead to overly pessimistic assessment results, since only the quality element in the worst status is considered. Here, we introduce a toolbox containing current and new aggregation methods, demonstrate and discuss their properties with simple, didactical examples, and suggest in which situations best to use them. Then, we illustrate the consequences of selected aggregation schemes for ecological river assessment with the case study of the Swiss Modular Concept of stream assessment (SMC), which we apply to ten river reaches in the Mönchaltdorfer Aa catchment in Switzerland. To be able to do so, we used multi-criteria decision analysis, i.e., multi-attribute value theory, to arrange the SMC quality elements into an objectives hierarchy, and to translate their individual assessments into value functions. Our case study revealed that choosing the most appropriate aggregation method particularly matters, if objectives with significantly different qualities are aggregated. We argue that redundant objectives (i.e., quality elements), often found at the lower levels of the objectives hierarchy, should best be aggregated additively allowing for compensation to increase the statistical significance of the results. Further, we suggest that complementary sub-objectives that often occur at higher levels may be optimally aggregated with a mixture of additive and minimum aggregation. Such a mixed method will allow some compensation, but nevertheless penalize for very bad states. Since here we compare commonly used aggregation methods with some which we believe have never been discussed in an assessment context before, our study concurrently informs ecological assessment in theory and in practice.     

Scientists versus Regulators: Precaution,Novelty & Regulatory Oversight as Predictors of Perceived Risks of Engineered Nanomaterials

Engineered nanoscale materials (ENMs) present a difficult challenge for risk assessors and regulators. Continuing uncertainty about the potential risks of ENMs means that expert opinion will play an important role in the design of policies to minimize harmful implications while supporting innovation. This research aims to shed light on the views of ‘nano experts’ to understand which nanomaterials or applications are regarded as more risky than others, to characterize the differences in risk perceptions between expert groups, and to evaluate the factors that drive these perceptions. Our analysis draws from a web-survey (N = 404) of three groups of US and Canadian experts: nano-scientists and engineers, nano-environmental health and safety scientists, and regulatory scientists and decision-makers. Significant differences in risk perceptions were found across expert groups; differences found to be driven by underlying attitudes and perceptions characteristic of each group. Nano-scientists and engineers at the upstream end of the nanomaterial life cycle perceived the lowest levels of risk, while those who are responsible for assessing and regulating risks at the downstream end perceived the greatest risk. Perceived novelty of nanomaterial risks, differing preferences for regulation (i.e. the use of precaution versus voluntary or market-based approaches), and perceptions of the risk of technologies in general predicted variation in experts'' judgments of nanotechnology risks. Our findings underscore the importance of involving a diverse selection of experts, particularly those with expertise at different stages along the nanomaterial lifecycle, during policy development.     

Short-term Forecasting of the Prevalence of Trachoma: Expert Opinion,Statistical Regression,versus Transmission Models

BackgroundTrachoma programs rely on guidelines made in large part using expert opinion of what will happen with and without intervention. Large community-randomized trials offer an opportunity to actually compare forecasting methods in a masked fashion.MethodsThe Program for the Rapid Elimination of Trachoma trials estimated longitudinal prevalence of ocular chlamydial infection from 24 communities treated annually with mass azithromycin. Given antibiotic coverage and biannual assessments from baseline through 30 months, forecasts of the prevalence of infection in each of the 24 communities at 36 months were made by three methods: the sum of 15 experts’ opinion, statistical regression of the square-root-transformed prevalence, and a stochastic hidden Markov model of infection transmission (Susceptible-Infectious-Susceptible, or SIS model). All forecasters were masked to the 36-month results and to the other forecasts. Forecasts of the 24 communities were scored by the likelihood of the observed results and compared using Wilcoxon’s signed-rank statistic.FindingsRegression and SIS hidden Markov models had significantly better likelihood than community expert opinion (p = 0.004 and p = 0.01, respectively). All forecasts scored better when perturbed to decrease Fisher’s information. Each individual expert’s forecast was poorer than the sum of experts.InterpretationRegression and SIS models performed significantly better than expert opinion, although all forecasts were overly confident. Further model refinements may score better, although would need to be tested and compared in new masked studies. Construction of guidelines that rely on forecasting future prevalence could consider use of mathematical and statistical models.     

Risk-Based Approaches to Managing Contaminants in Catchments

Risk-based methods promise improved decision-making for managing of contaminants, such as salinity, sediments, nutrients, and toxicants, that can adversely affect the ecological condition of aquatic ecosystems. Two aspects of ecological risk assessment (ERA) and management—stakeholder involvement and more quantitative approaches to risk analysis—are particularly challenging. Stakeholder involvement is crucial both in the risk assessment process and the development, acceptance, and implementation of a risk management plan. Additionally, a number of quantitative approaches (particularly Bayesian approaches and multi-criteria decision-making) have been identified as having the potential to include expert-based inputs into risk-based decision-making. These offer promise for better inclusion of stakeholder knowledge and preferences into the decision-making process, and for improving the links between stakeholder inputs and potential risks to the ecological condition of the system. A major challenge for ecologists and natural resource managers is to make the ERA process more quantitative. Most ERAs conducted to date have been qualitative assessments that suffer from a number of deficiencies, the most serious being the lack of transparency and a reliance on subjective judgments. This article argues that the most productive way forward may be to use Bayesian methods to couple existing process-based models, empirical relationships based on good data, and expert opinion, to make the analysis of ecological risks more robust, consistent, and repeatable.     

A structured analysis of risk to important wildlife elements in three Australian Wildlife Conservancy sanctuaries

Where data and information are lacking, structured expert risk assessments can provide a powerful tool to progress natural resource planning. In many situations, practitioners make informal assessments of risk within small groups that typically constitute employees. In this study, we report on three small (in terms of experts) structured expert‐based risk assessment case studies conducted by expert employees of a not‐for‐profit organisation (Australian Wildlife Conservancy) to demonstrate the utility of the approach. The case studies were carried out for three wildlife sanctuaries managed by AWC: Faure Island, Karakamia and Paruna. The likelihood that a set of direct risk factors would cause management failure for sets of important wildlife elements in the three sanctuaries was elicited from the small group of ecological experts. The analysis was couched in terms of a management aim to not lose species from each wildlife element over the management period of 25 years with current management. The experts believed, in particular, that increasing temperature and decreasing water availability associated with climate change were likely to impact significantly upon the vegetation elements and water‐reliant fauna associated with the sanctuaries. Some vegetation elements were also thought likely to be at risk of over‐grazing, unsuitable fire regimes and, in some cases, disease. In addition to predation by exotic predators at one sanctuary, the experts identified additional direct risk factors for various fauna elements associated with expected changes to the vegetation elements, including reduction in food availability, nesting habitat, and generally important life media. From the risk analyses, a preliminary conceptual model was developed to underpin monitoring and to indicate areas for possible management intervention and research. The case studies demonstrate that even in a small workplace team, structured risk assessments can be efficiently accomplished and can provide expedient and transparent information that effectively captures and aggregates the views of the experts.     

Measures, perceptions and scaling patterns of aggregated species distributions

Non-random (aggregated) species distributions arise from habitat heterogeneity and nonlinear biotic processes. A comprehensive understanding of the concept of aggregation, as well as its measurement, is pivotal to our understanding of species distributions and macroecological patterns. Here, using an individual-based model, we analyzed opinions on the concept of aggregation from the public and experts (trained ecologists), in addition to those calculated from a variety of aggregation indices. Three forms of scaling patterns (logarithmic, power-law and lognormal) and four groups of scaling trajectories emerged. The experts showed no significant difference from the public, although with a much lower deviation. The public opinion was partially influenced by the abundance of individuals in the spatial map, which was not found in the experts. With the increase of resolution (decrease of grain), aggregation indices showed a general trend from significantly different to significantly similar to the expert opinion. The over-dispersion index (i.e. the clumping parameter k in the negative binomial distribution) performed, at certain scales, as the closest index to the expert opinion. Examining performance of aggregation measures from different groups of scaling patterns was proposed as a practical way of analyzing spatial structures. The categorization of the scaling patterns of aggregation measures, as well as their over- and in-sensitivity towards spatial structures, thus not only provides a potential solution to the modifiable areal unit problem, but also unveils the interrelationship among the concept, measures and perceptions of aggregated species distributions.     

Indicators of environmentally sound land use in the humid tropics: The potential roles of expert opinion,knowledge engineering and knowledge discovery

Despite abundant literature on indicators for sustainable resource management, practical tools to help local users to apply its general concepts at a local to regional level are scarce. This means that decisions over land evaluation and land use at a local level are often not based on the formal application of indicators or decision support systems for environmentally sound management but instead on the opinion of local expertise, for instance forest managers, cattle breeders, farmers and/or academics. This is particularly seen to be the case in the tropics where access to modern communication and information technologies is restricted.As the opinions of experts are often based on and influenced by personal experience, intuition, heuristics and bias, their evaluations and decision are often unclear to the non-expert working at a local level. In order to make their reasoning more comprehensible to the non-expert, the ecological condition of 176 plots in the tropical Southeast of Mexico were evaluated by experts on soil fertility, forest management, cattle breeding and agriculture. With the assistance of a knowledge engineer (one who converts expert knowledge and reasoning into a model), these expert opinions and reasoning were then translated into a formal computer model.As an alternative approach we applied a knowledge discovery technique, namely the induction of regression trees and automatically developed models using the expert evaluations as training data. Where knowledge engineering was tedious and time consuming, regression models could be rapidly generated. Moreover, the correspondence between regression trees and expert opinions was considerably higher than the correspondence between expert opinion and their own models. The regression trees used less explicative variables than the models generated by the experts. The minimisation of sampling effort due to variable space reduction means that the application of regression tree induction has a high potential for a rapid development of indicators for narrowly defined ecological assessments, needed for decision making on a local or regional scale.     

Dung Beetle Community and Functions along a Habitat-Disturbance Gradient in the Amazon: A Rapid Assessment of Ecological Functions Associated to Biodiversity

Although there is increasing interest in the effects of habitat disturbance on community attributes and the potential consequences for ecosystem functioning, objective approaches linking biodiversity loss to functional loss are uncommon. The objectives of this study were to implement simultaneous assessment of community attributes (richness, abundance and biomass, each calculated for total-beetle assemblages as well as small- and large-beetle assemblages) and three ecological functions of dung beetles (dung removal, soil perturbation and secondary seed dispersal), to compare the effects of habitat disturbance on both sets of response variables, and their relations. We studied dung beetle community attributes and functions in five land-use systems representing a disturbance gradient in the Brazilian Amazon: primary forest, secondary forest, agroforestry, agriculture and pasture. All response variables were affected negatively by the intensification of habitat disturbance regimes, but community attributes and ecological functions did not follow the same pattern of decline. A hierarchical partitioning analysis showed that, although all community attributes had a significant effect on the three ecological functions (except the abundance of small beetles on all three ecological functions and the biomass of small beetles on secondary dispersal of large seed mimics), species richness and abundance of large beetles were the community attributes with the highest explanatory value. Our results show the importance of measuring ecological function empirically instead of deducing it from community metrics.     

How to make river assessments comparable: A demonstration for hydromorphology

River monitoring and assessment programs are important tools to quantify the condition of river ecosystems, identify deficits, and provide preliminary indication of how to improve them. But, they are limited in delivering comparable assessment results across national or transnational borders, aggregating site-specific assessments into broader scale assessments, and supporting river management decisions. We present a multi-criteria decision analysis approach for improving the comparability of ecological assessment methods of different origin and for combining these assessments into a joint procedure. The approach consists of seven consecutive steps. The most central ones concern the hierarchical allocation of ecological assessment endpoints, and the harmonization of the scoring procedure of attributes (ecological indicators or assets) to a common scale from 0 to 1. We demonstrate the approach integrating three programs developed to assess the hydromorphological river condition in Switzerland, Germany, and the USA. In our example, the integrated assessment produces comparable results for the whole range from natural to impacted rivers, while data continuity with original assessments was maintained. Our approach provides a common assessment standard due to the definition of the minimum amount of information required, is flexible regarding measurement and assessment endpoints, and bridges the gap between river quality assessment and management.     

A simple way to unify multicriteria decision analysis (MCDA) and stochastic multicriteria acceptability analysis (SMAA) using a Dirichlet distribution in benefit–risk assessment

Quantitative methodologies have been proposed to support decision making in drug development and monitoring. In particular, multicriteria decision analysis (MCDA) and stochastic multicriteria acceptability analysis (SMAA) are useful tools to assess the benefit–risk ratio of medicines according to the performances of the treatments on several criteria, accounting for the preferences of the decision makers regarding the relative importance of these criteria. However, even in its probabilistic form, MCDA requires the exact elicitations of the weights of the criteria by the decision makers, which may be difficult to achieve in practice. SMAA allows for more flexibility and can be used with unknown or partially known preferences, but it is less popular due to its increased complexity and the high degree of uncertainty in its results. In this paper, we propose a simple model as a generalization of MCDA and SMAA, by applying a Dirichlet distribution to the weights of the criteria and by making its parameters vary. This unique model permits to fit both MCDA and SMAA, and allows for a more extended exploration of the benefit–risk assessment of treatments. The precision of its results depends on the precision parameter of the Dirichlet distribution, which could be naturally interpreted as the strength of confidence of the decision makers in their elicitation of preferences.     

Applications of Background Data in Ecological Risk Assessment: Various Shades of Gray

This paper discusses general approaches for evaluating the utility and manner of conducting background analyses in soil for ecological risk assessments. The types and sources of background data are discussed, and advantages and disadvantages of using literature-based versus site-specific background data are presented. The value of background evaluations is discussed with regard to the goals and objectives for a project. A comparison of literature-based ecological soil screening levels with generic metal background concentrations is presented to illustrate a typical problem in incorporating background data in ecological risk assessments, which is that many generic background concentrations are higher than ecological screening levels. This brings into question both the relevance of ecological screening levels and generic background levels. These issues are discussed along with cost-benefit considerations in an attempt to provide recommendations for determining the most appropriate type of background evaluation to conduct at a given site.     

Assessment of vulnerability to climate change using a multi-criteria outranking approach with application to heat stress in Sydney

Climate change vulnerability assessment is a complex form of risk assessment which accounts for both geophysical and socio-economic components of risk. In indicator-based vulnerability assessment (IBVA), indicators are used to rank the vulnerabilities of socio-ecological systems (SESs). The predominant aggregation approach in the literature, sometimes based on multi-attribute utility theory (MAUT), typically builds a global-scale, utility function based on weighted summation, to generate rankings. However, the corresponding requirement for additive independence and complete knowledge of system interactions by analyst are rarely if ever satisfied in IBVA.We build an analogy between the structures of Multi-Criteria Decision Analysis (MCDA) and IBVA problems and show that a set of techniques called Outranking Methods, developed in MCDA to deal with criteria incommensurability, data uncertainty and preference imprecision, offer IBVA a sound alternative to additive or multiplicative aggregation. We reformulate IBVA problems within an outranking framework, define thresholds of difference and use an outranking method, ELECTRE III, to assess the relative vulnerability to heat stress of 15 local government areas in metropolitan Sydney. We find that the ranking outcomes are robust and argue that an outranking approach is better suited for assessments characterized by a mix of qualitative, semi-quantitative and quantitative indicators, threshold effects and uncertainties about the exact relationships between indicators and vulnerability.     

城市生态风险管理关键问题与研究进展

我国目前正处于社会经济转型和城市化进程加快时期,随着城市化发展和城市人居环境的变化,城市生态风险受到越来越多关注。在综述国内外城市生态风险管理研究进展,总结风险源与受体特点和风险评价方法的基础上,结合城市生态风险管理的需求,明确了城市生态风险的管理目标,将管理目标系统归纳划分为控制目标、调控目标和规划目标3个层次;在解析城市生态风险管理特点的基础上,结合风险管理目标从弹性力、动态管理性和空间异质性3个方面对生态风险管理措施与方案进行了总结分析,并进一步探讨了风险管理保障机制。从生态风险管理目标制定、构建城市生态系统特点的风险管理体系及其管理机制等方面提出了建议与展望,以期推动我国城市生态风险管理的发展。     

Predictive Assessment of Fish Health and Fish Kills in the Neuse River Estuary Using Elicited Expert Judgment

Declining fish health and the occurrence of large fish kills are some of the more publicly meaningful indicators of water quality in the impaired Neuse River Estuary, North Carolina. It is generally believed that such problems are caused by the widespread depletion of dissolved oxygen—an indirect result of anthropogenic nutrient pollution. However, the development of scientific simulation models to predict how improvements in oxygen conditions will improve the health of fish and reduce the frequency of fish kills has proven elusive. As a pragmatic solution to this problem, the expert opinion of estuarine fisheries scientists in possession of relevant data and experience was elicited. The relations between joint and conditional probabilities were exploited to translate quantities that are normally hard to assess into quantities that can be drawn more directly from the experiential knowledge of the experts. A combined model of expert opinion was constructed as an influence diagram, and Monte Carlo simulation was used to generate predictions of fish health and fish kills in the Neuse River Estuary under current and improved oxygen conditions. Full model results are expressed as probability distributions, capturing the effects of natural variability and knowledge uncertainty—both contributors to total ecological risk.     

Assessment of a large number of empirical plant species niche models by elicitation of knowledge from two national experts

Quantitative models play an increasing role in exploring the impact of global change on biodiversity. To win credibility and trust, they need validating. We show how expert knowledge can be used to assess a large number of empirical species niche models constructed for the British vascular plant and bryophyte flora. Key outcomes were (a) scored assessments of each modeled species and niche axis combination, (b) guidance on models needing further development, (c) exploration of the trade‐off between presenting more complex model summaries, which could lead to more thorough validation, versus the longer time these take to evaluate, (d) quantification of the internal consistency of expert opinion based on comparison of assessment scores made on a random subset of models evaluated by both experts. Overall, the experts assessed 39% of species and niche axis combinations to be “poor” and 61% to show a degree of reliability split between “moderate” (30%), “good” (25%), and “excellent” (6%). The two experts agreed in only 43% of cases, reaching greater consensus about poorer models and disagreeing most about models rated as better by either expert. This low agreement rate suggests that a greater number of experts is required to produce reliable assessments and to more fully understand the reasons underlying lack of consensus. While area under curve (AUC) statistics showed generally very good ability of the models to predict random hold‐out samples of the data, there was no correspondence between these and the scores given by the experts and no apparent correlation between AUC and species prevalence. Crowd‐sourcing further assessments by allowing web‐based access to model fits is an obvious next step. To this end, we developed an online application for inspecting and evaluating the fit of each niche surface to its training data.     

Expert Opinions on Improving Femicide Data Collection across Europe: A Concept Mapping Study

Femicide, defined as the killings of females by males because they are females, is becoming recognized worldwide as an important ongoing manifestation of gender inequality. Despite its high prevalence or widespread prevalence, only a few countries have specific registries about this issue. This study aims to assemble expert opinion regarding the strategies which might feasibly be employed to promote, develop and implement an integrated and differentiated femicide data collection system in Europe at both the national and international levels. Concept mapping methodology was followed, involving 28 experts from 16 countries in generating strategies, sorting and rating them with respect to relevance and feasibility. The experts involved were all members of the EU-Cost-Action on femicide, which is a scientific network of experts on femicide and violence against women across Europe. As a result, a conceptual map emerged, consisting of 69 strategies organized in 10 clusters, which fit into two domains: “Political action” and “Technical steps”. There was consensus among participants regarding the high relevance of strategies to institutionalize national databases and raise public awareness through different stakeholders, while strategies to promote media involvement were identified as the most feasible. Differences in perceived priorities according to the level of human development index of the experts’ countries were also observed.     

Qualichem In Vivo: A Tool for Assessing the Quality of In Vivo Studies and Its Application for Bisphenol A

In regulatory toxicology, quality assessment of in vivo studies is a critical step for assessing chemical risks. It is crucial for preserving public health studies that are considered suitable for regulating chemicals are robust. Current procedures for conducting quality assessments in safety agencies are not structured, clear or consistent. This leaves room for criticism about lack of transparency, subjective influence and the potential for insufficient protection provided by resulting safety standards. We propose a tool called “Qualichem in vivo” that is designed to systematically and transparently assess the quality of in vivo studies used in chemical health risk assessment. We demonstrate its use here with 12 experts, using two controversial studies on Bisphenol A (BPA) that played an important role in BPA regulation in Europe. The results obtained with Qualichem contradict the quality assessments conducted by expert committees in safety agencies for both of these studies. Furthermore, they show that reliance on standardized guidelines to ensure scientific quality is only partially justified. Qualichem allows experts with different disciplinary backgrounds and professional experiences to express their individual and sometimes divergent views—an improvement over the current way of dealing with minority opinions. It provides a transparent framework for expressing an aggregated, multi-expert level of confidence in a study, and allows a simple graphical representation of how well the study integrates the best available scientific knowledge. Qualichem can be used to compare assessments of the same study by different health agencies, increasing transparency and trust in the work of expert committees. In addition, it may be used in systematic evaluation of in vivo studies submitted by industry in the dossiers that are required for compliance with the REACH Regulation. Qualichem provides a balanced, common framework for assessing the quality of studies that may or may not be following standardized guidelines.     

Ecological risk assessment of urban stormwater ponds: Literature review and proposal of a new conceptual approach providing ecological quality goals and the associated bioassessment tools

Stormwater ponds are a common feature of the urban landscape in many countries with advanced stormwater management. Built to control the impacts of urbanization in the form of increased runoff flows, volumes and pollution loads, stormwater ponds are exposed to strong anthropogenic pressures. Meanwhile, as open water systems, they represent new aquatic habitats potentially enhancing the biodiversity of urban areas and balancing the transformation of original ecosystems existing prior to urbanization. In the current context of sustainable development, assessing the ecological risks of stormwater ponds serving as aquatic habitats is therefore crucial for ensuring both the preservation and rehabilitation of biodiversity in urban areas. During the last decade, ecological risk assessments applied to stormwater ponds lacked adoption of integrated interdisciplinary approaches. This prevented advances in developing adaptive methodologies for assessing the ecological quality of stormwater ponds and for providing quality objectives for the management of these facilities. Also, the application of established integrated assessment methodologies, such as the Sediment Quality Triad widely used in North America, based on comparisons with reference sites, is challenged by the man-made features of urban stormwater ponds. The search for a more specific and effective methodology led to the proposal of supplementing the Sediment Quality Triad with the Oligochaete methodology, which was developed and standardized in France for determining the biological status of sediments in stagnant water ecosystems. The benefits of this approach are discussed in a conceptual framework providing ecological quality goals for urban stormwater ponds.