Incorporating the Effects of Socioeconomic Uncertainty into Priority Setting for Conservation Investment

Abstract:  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.     

基于非本地物种毒性数据推导出的水质基准可为本地物种提供适当保护吗？

基于非本地物种的毒性数据推导出的水质基准一直存在争议,质疑者提出应有针对不同生物区系的水质基准。而这个问题在中国尤为突出。本文作者搜集了38种污染物对本地物种和非本地物种的毒性数据,比较了这些生物的HC₅和物种敏感度分布,结果显示,基于非本地物种推导的水质基准有74%的确定性可以有效保护中国的水生态系统。如果采用评价因子(AF=5)来校正基准,那么可以获得90%的确定性。
精选自Xiaowei Jin, Zijian Wang, Yeyao Wang, Yibing Lv, Kaifeng Rao, Wei Jin, John P. Giesy and Kenneth M. Y. Leung. Do water quality criteria based on nonnative species provide appropriate protection for native species? Environmental Toxicology and Chemistry: Volume 34, Issue 8, pages 1744–1750, August 2015. DOI: 10.1002/etc.2985
详情请见http://onlinelibrary.wiley.com/doi/10.1002/etc.2985/full     

基于非本地物种毒性数据推导出的水质基准可为本地物种提供适当保护吗？

基于非本地物种的毒性数据推导出的水质基准一直存在争议,质疑者提出应有针对不同生物区系的水质基准。而这个问题在中国尤为突出。本文作者搜集了38种污染物对本地物种和非本地物种的毒性数据,比较了这些生物的HC₅和物种敏感度分布,结果显示,基于非本地物种推导的水质基准有74%的确定性可以有效保护中国的水生态系统。如果采用评价因子(AF=5)来校正基准,那么可以获得90%的确定性。
精选自Xiaowei Jin, Zijian Wang, Yeyao Wang, Yibing Lv, Kaifeng Rao, Wei Jin, John P. Giesy and Kenneth M. Y. Leung. Do water quality criteria based on nonnative species provide appropriate protection for native species? Environmental Toxicology and Chemistry: Volume 34, Issue 8, pages 1744–1750, August 2015. DOI: 10.1002/etc.2985
详情请见http://onlinelibrary.wiley.com/doi/10.1002/etc.2985/full     

基于非本地物种毒性数据推导出的水质基准可为本地物种提供适当保护吗？

基于非本地物种的毒性数据推导出的水质基准一直存在争议,质疑者提出应有针对不同生物区系的水质基准。而这个问题在中国尤为突出。本文作者搜集了38种污染物对本地物种和非本地物种的毒性数据,比较了这些生物的HC₅和物种敏感度分布,结果显示,基于非本地物种推导的水质基准有74%的确定性可以有效保护中国的水生态系统。如果采用评价因子(AF=5)来校正基准,那么可以获得90%的确定性。
精选自Xiaowei Jin, Zijian Wang, Yeyao Wang, Yibing Lv, Kaifeng Rao, Wei Jin, John P. Giesy and Kenneth M. Y. Leung. Do water quality criteria based on nonnative species provide appropriate protection for native species? Environmental Toxicology and Chemistry: Volume 34, Issue 8, pages 1744–1750, August 2015. DOI: 10.1002/etc.2985
详情请见http://onlinelibrary.wiley.com/doi/10.1002/etc.2985/full     

The Reliability of Using Population Viability Analysis for Risk Classification of Species

I examine whether or not it is appropriate to use extinction probabilities generated by population viability analyses, based on best estimates for model parameters, as criteria for listing species in Red Data Book categories as recently proposed by the World Conservation Union. Such extinction probabilities are influenced by how accurately model parameters are estimated and by how accurately the models depict actual population dynamics. I evaluate the effect of uncertainty in parameter estimation through simulations. Simulations based on Steller sea lions were used to evaluate bias and precision in estimates of probability of extinction and to consider the performance of two proposed classification schemes. Extinction time estimates were biased (because of violation of the assumption of stable age distribution) and underestimated the variability of probability of extinction for a given time (primarily because of uncertainty in parameter estimation). Bias and precision in extinction probabilities are important when these probabilities are used to compare the risk of extinction between species. Suggestions are given for population viability analysis techniques that incorporate parameter uncertainty. I conclude that testing classification schemes with simulations using quantitative performance objectives should precede adoption of quantitative listing criteria.     

Making Consistent IUCN Classifications under Uncertainty

Abstract: The World Conservation Union (IUCN) defined a set of categories for conservation status supported by decision rules based on thresholds of parameters such as distributional range, population size, population history, and risk of extinction. These rules have received international acceptance and have become one of the most important decision tools in conservation biology because of their wide applicability, objectivity, and simplicity of use. The input data for these rules are often estimated with considerable uncertainty due to measurement error, natural variation, and vagueness in definitions of parameters used in the rules. Currently, no specific guidelines exist for dealing with uncertainty. Interpretation of uncertain data by different assessors may lead to inconsistent classifications because attitudes toward uncertainty and risk may have an important influence on the classification of threatened species. We propose a method of dealing with uncertainty that can be applied to the current IUCN criteria without altering the rules, thresholds, or intent of these criteria. Our method propagates the uncertainty in the input parameters and assigns the evaluated species either to a single category (as the current criteria do) or to a range of plausible categories, depending on the nature and extent of uncertainties.     

The understanding and role of uncertainty and risk in climate change adaptation: local and central authorities in Norway

A common claim is that emerging and future climate change is rendering traditional conceptions of uncertainty and risk obsolete. This is because a changing climate makes it quite a challenge to calculate uncertainties, establishing the measurable uncertainty as the basis for quantifying risk. Approaches that are capable of accommodating and possibly countering the wickedness caused by increasing uncertainty are necessary, the argument holds. Following up on previous studies of learning–knowledge and adapting to a changing climate, this article provides an analysis of how differences in the understanding of uncertainty and risk inform and determine governmental adaptation policies and actions of the local and central government in Norway, also discussing governance implications. The study finds that the understanding of uncertainty and risk generally is poor at the local level, but better at the state level, especially among highly educated staff with a background in, for example, natural sciences and engineering. On the other hand, a traditional understanding of uncertainty and risk is dominating: seeking to establish measurable uncertainty as a basis for quantifying risk. The article discusses combining different approaches of uncertainty and risk, thereby introducing a broader basis for governance, also implying multi-level network governance. On the one hand, this may help the local–central government in handling wicked problems of adapting to a changing climate but on other hand, it also possibly nurture struggles between different knowledge bases and stakeholder interest, thereby fuelling the wickedness of adaptation policies.     

Enforcement and price controls in emissions trading

This paper examines how enforcement affects the structure and performance of emissions trading programs with price controls under uncertainty about firms' abatement costs. The analysis highlights how an enforcement strategy can cause abatement-cost risk to be transmitted to enforcement costs via the price of permits. When this occurs, accommodating the effect of abatement-cost risk with an optimal policy results in higher expected emissions and lower expected permit price than their second-best optimal values. However, it is possible to design an enforcement strategy that shields enforcement costs from abatement-cost risk by tying sanctions directly to permit prices. This enforcement strategy stabilizes enforcement effort, the optimal permit supply and price controls are independent of enforcement costs, and the policy produces the second-best optimal outcome.     

Risk aversion and CO2 regulatory uncertainty in power generation investment: Policy and modeling implications

We consider a simulation of risk-averse producers when making investment decisions in a competitive energy market, who face uncertainty about future regulation of carbon dioxide emissions. Investments are made under regulatory uncertainty; then the regulatory state is revealed and producers realize returns. We consider anticipated taxes, grandfathered permits and auctioned permits and show that some anticipated policies increase investment in the relatively dirty technology. Beliefs about the policy instrument that will be used to price carbon may be as important as certainty that carbon will be priced. More generally, a failure to consider risk aversion may bias policy analysis for the power sector.     

Meeting report

SUMMARY

In many developing countries, the determination of a ranking of investments designed to improve and extend the road system is a commonplace prerequisite of planning for the transport sector as a whole and the road sub-sector within it. A major objective of determining investment priorities is to secure the greatest efficiency in the use of resources allocated to the sector and, for this reason, any system of assigning priorities must rely upon conventional investment appraisal techniques producing quantifiable measures of worth. Exercises of this kind, in which road investments are identified and ranked, are usually undertaken to produce a road sector investment plan. The implementation of such plans is, however, often compromised because of perceived deficiencies with a methodology which places undue reliance on investment appraisal and fails to properly address the issue of public interest and sustainability. This paper attempts to produce a pragmatic set of ground rules which, while mindful of the need to promote economic efficiency, allow for other factors to be embraced in a more holistic methodology.     

Combining Strategies to Select Reserves in Fragmented Landscapes

Abstract:  In the identification of reserve networks in fragmented landscapes with limited species-specific data at hand, one approach is to use selection criteria, such as patch size, to rank the habitat patches' conservation value and evaluate reserve-network alternatives. These criteria are assumed to be reasonable surrogates for the true network objectives. Caution is warranted, however, because the relationships between the selection criteria and the reserve-network objectives may be inconsistent. Conflicts are also likely to arise because no single reserve network will be optimal with respect to multiple objectives (or selection criteria) simultaneously. Instead, reserve planners must compromise between conflicting demands. We field tested the relationships between a variety of selection criteria and the objectives of a reserve network for the sandplain natural communities on Martha's Vineyard Island, Massachusetts (U.S.A.). Selection criteria that correlated with the reserve-network objectives were used in a multi-objective integer program to identify the 10-patch reserve networks that were optimal with each objective independently and those that offered optimal tradeoffs between the reserve-network objectives. From these 10-patch networks, one can select a final reserve network that provides the preferred compromise between the objectives.     

Incorporating Uncertainty into Management Models for Marine Mammals

Abstract: Good management models and good models for understanding biology differ in basic philosophy. Management models must facilitate management decisions despite large amounts of uncertainty about the managed populations. Such models must be based on parameters that can be estimated readily, must explicitly account for uncertainty, and should be simple to understand and implement. In contrast, biological models are designed to elucidate the workings of biology and should not be constrained by management concerns. We illustrate the need to incorporate uncertainty in management models by reviewing the inadequacy of using standard biological models to manage marine mammals in the United States. Past management was based on a simple model that, although it may have represented population dynamics adequately, failed as a management tool because the parameter that triggered management action was extremely difficult to estimate for the majority of populations. Uncertainty in parameter estimation resulted in few conservation actions. We describe a recently adopted management scheme that incorporates uncertainty and its resulting implementation. The approach used in this simple management scheme, which was tested by using simulation models, incorporates uncertainty and mandates monitoring abundance and human-caused mortality. Although the entire scheme may be suitable for application to some terrestrial and marine problems, two features are broadly applicable: the incorporation of uncertainty through simulations of management and the use of quantitative management criteria to translate verbal objectives into levels of acceptable risk.     

Effect of risk aversion on prioritizing conservation projects

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

Data quality assessment for studies investigating microplastics and nanoplastics in food products: Are current data reliable?

● Data quality assessment criteria for MP/NPs in food products were developed. ● Data quality of 71 data records (69 of them only focused on MPs) was assessed. ● About 96% of the data records were considered unreliable in at least one criterion. ● Improvements need to be made regarding positive controls and polymer identification. ● A mismatch between MP/NPs used in toxicity studies and those in foods was recorded. Data on the occurrence of microplastics and nanoplastics (MP/NPs) in foods have been used to assess the human health risk caused by the consumption of MP/NPs. The reliability of the data, however, remains unclear because of the lack of international standards for the analysis of MP/NPs in foods. Therefore, the data quality needs to be assessed for accurate health risk assessment. This study developed 10 criteria applicable to the quality assessment of data on MP/NPs in foods. Accordingly, the reliability of 71 data records (69 of them only focused on MPs) was assessed by assigning a score of 2 (reliable without restrictions), 1 (reliable but with restrictions), or 0 (unreliable) on each criterion. The results showed that only three data records scored 2 or 1 on all criteria, and six data records scored 0 on as many as six criteria. A total of 58 data records did not include information on positive controls, and 12 data records did not conduct the polymer identification, which could result in the overestimation or underestimation of MP/NPs. Our results also indicated that the data quality of unprocessed foods was more reliable than that of processed foods. Furthermore, we proposed a quality assurance and quality control protocol to investigate MP/NPs in foods. Notably, the characteristics of MP/NPs used in toxicological studies and those existing in foods showed a remarkable discrepancy, causing the uncertainty of health risk assessment. Therefore, both the estimated exposure of MP/NPs and the claimed potential health risks should be treated with caution.     

Dynamic aspects of effluent taxation under uncertainty

The optimal adjustment process for an effluent charge is derived when the firm's response to the charge is uncertain. The optimal process is shown to exhibit the dual effects of caution and probing. Because of uncertainty, society should be risk averse or cautious when setting the charge. However, because of the possibility of generating information for improved future control, this caution is balanced by the incentive to probe for additional information. Finally, if the uncertain parameters of the firm's response function are nonautonomous, their change over time must be explicitly considered to avoid bias in estimation.     

Adjusting to Climate Change: Implications of Increased Variability and Asymmetric Adjustment Costs for Investment in Water Reserves

In this paper we study the determination of optimal water storage capacity in a region, taking into account that the supply of the resource, the flow into the reserve, is uncertain, that a measure of the uncertainty, the variance, is likely to increase with climate change, that building capacity is costly, and that the development of water resources may entail alsoenvironmental costs. We find that water storage capacity in the long run ispositivelyrelated to increases in uncertainty if the marginal benefit of water withdrawal isconvexand that, for the case of costly reversibility of investment, a range of inaction for investment appears, and the stability of water storage capacity with respect to changes in variance increases.     

Uncertainty, learning, and the optimal management of wildlife

Wildlife management is limited by uncontrolled and often unrecognized environmental variation, by limited capabilities to observe and control animal populations, and by a lack of understanding about the biological processes driving population dynamics. In this paper I describe a comprehensive framework for management that includes multiple models and likelihood values to account for structural uncertainty, along with stochastic factors to account for environmental variation, random sampling, and partial controllability. Adaptive optimization is developed in terms of the optimal control of incompletely understood populations, with the expected value of perfect information measuring the potential for improving control through learning. The framework for optimal adaptive control is generalized by including partial observability and non-adaptive, sample-based updating of model likelihoods. Passive adaptive management is derived as a special case of constrained adaptive optimization, representing a potentially efficient suboptimal alternative that nonetheless accounts for structural uncertainty.     

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.     

Uncertainty in the assessment of hazard,exposure and risk

The terminology, concepts and current approaches to uncertainty in the assessment of hazard, exposure and risk are reviewed. Five generic questions are discussed on uncertainty, including sources, levels, when and how it should be dealt with or reduced, what are our gaps in understanding and how they can be addressed. A case study of lead exposure of children in Lavrion, Greece, is used to exemplify these questions and possible answers. Estimation of uncertainty may be improved by the use of interorganisational studies to capture sources of uncertainty that are often overlooked. Gaps identified in our understanding of uncertainty include: a limitation in the availability of basic measurements, a lack of knowledge of the environmental processes, an inability to predict the effects of mixtures, the aetiology of disease and devising procedures for optimal resource allocation in impact assessment.     

Developing Classification Criteria under the U.S. Endangered Species Act: Bowhead Whales as a Case Study

Abstract: Under the U.S. Endangered Species Act, a species is classified as endangered, threatened, or recovered based on the extent to which its survival is affected by one or more of five subjective factors. A key criticism of the act is that it makes no reference to quantitative or even qualitative parameters of what constitutes "danger of extinction." Without objective standards to guide decisionmakers, classification decisions fall prey to political and social influences. We recommend the development of species-specific, status-determining criteria as a means to rationalize and expedite the listing process and reclassification decisions, independent of the requirement for delisting criteria in recovery plans. Such criteria should (1) clearly define levels of vulnerability, (2) identify gaps in information on life-history parameters, and (3) address uncertainty in existing data. As a case study, we developed preliminary criteria for bowhead whales (    Balaena mysticetus ). Thresholds for endangered and threatened status were based on World Conservation Union ( IUCN) Red List criteria and population viability analyses. Our analysis indicates that particular attention must be focused on population structure within the species to appropriately classify the degree to which one or more components of a species are vulnerable to extinction. A similar approach could be used in the classification of other species. According to our application of the IUCN criteria and those developed for similar species by Gerber and DeMaster (1999) , the Bering Sea population of bowhead whales should be delisted, whereas the other four populations of bowheads should continue to be considered endangered.