Adaptation policies to increase terrestrial ecosystem resilience: potential utility of a multicriteria approach

Climate change is rapidly undermining terrestrial ecosystem resilience and capacity to continue providing their services to the benefit of humanity and nature. Because of the importance of terrestrial ecosystems to human well-being and supporting services, decision makers throughout the world are busy creating policy responses that secure multiple development and conservation objectives— including that of supporting terrestrial ecosystem resilience in the context of climate change. This article aims to advance analyses on climate policy evaluation and planning in the area of terrestrial ecosystem resilience by discussing adaptation policy options within the ecology-economy-social nexus. The paper evaluates these decisions in the realm of terrestrial ecosystem resilience and evaluates the utility of a set of criteria, indicators, and assessment methods, proposed by a new conceptual multi-criteria framework for pro-development climate policy and planning developed by the United Nations Environment Programme. Potential applications of a multicriteria approach to climate policy vis-à-vis terrestrial ecosystems are then explored through two hypothetical case study examples. The paper closes with a brief discussion of the utility of the multi-criteria approach in the context of other climate policy evaluation approaches, considers lessons learned as a result efforts to evaluate climate policy in the realm of terrestrial ecosystems, and reiterates the role of ecosystem resilience in creating sound policies and actions that support the integration of climate change and development goals.     

A comparison of multiple criteria analysis and unaided approaches to environmental decision making

This study compares multiple criteria analysis (MCA) assisted decisions and unaided decisions in an environmental management context. It involved 55 decision makers in Queensland, Australia, who used MCA techniques to evaluate environmental projects alongside their own intuitive approaches under the Australian Natural Heritage Trust (NHT) program. The NHT is Australia's largest environmental program funded over A$ 2.5 billion over 10 years. The study assessed decision maker learning and perceptions of MCA's overall usefulness. It was found that MCA produced markedly different results to unaided evaluations. Feedback from decision makers typically showed that unaided decisions did not make explicit use of evaluation criteria. Even though most decision makers were unwilling to change their choices following the use of MCA, they found it a helpful input to their decision procedure. The majority of decision makers supported the adoption of MCA to make future investment decisions under the NHT program.     

The application of decision analysis in the remediation sector

Contaminated sites represent a serious environmental problem in Germany. The decision that remediation technology is optimal for a given site is complicated by the existence of multiple objectives to be optimized simultaneously, significant uncertainties about the remediation results, and the involvement of several decision-makers with conflicting interests. Decision analysis is a methodology to deal with problems of this kind. The application of decision analysis at a test site demonstrated that remediation decisions can greatly benefit from the structural guide, sound methodological approaches, and manifold results that can be deduced from decision analytic models. The careful preparation of the decision helps to prevent momentous wrong decisions, especially due to the sophisticated support, that decision analysis offers for risky decisions. Because remediation decisions can be regarded as prototypical for many decisions in the public sector, the results of this study may also impact other fields like waste management, water resource administration, traffic planning, or siting of hazardous industrial facilities.     

Collaborative use of geodesign tools to support decision-making on adaptation to climate change

Spatial planners around the world need to make climate change adaptation plans. Climate adaptation planning requires combining spatial information with stakeholder values. This study demonstrates the potential of geodesign tools as a mean to integrate spatial analysis with stakeholder participation in adaptation planning. The tools are interactive and provide dynamic feedback on stakeholder objectives in response to the application of spatial measures. Different rationalities formed by underlying internalized values influence the reasoning of decision-making. Four tools were developed, each tailored to different rationalities varying between a collective or individual viewpoint and analytical or political arguments. The tools were evaluated in an experiment with four groups of participants that were set around an interactive mapping device: the touch table. To study how local decision-making on adaptation can be supported, this study focuses on a specific case study in the Netherlands. In this case study, multiple different stakeholders need to make spatial decisions on land use and water management planning in response to climate change. The collaborative use of four geodesign tools was evaluated in an interactive experiment. The results show that the geodesign tools were able to integrate the engagement of stakeholders and assessment of measures. The experiment showed that decision-making on adaptation to climate change can benefit from the use of geodesign tools as long as the tool is carefully matched to the rationality that applies to the adaptation issue. Although the tools were tested to support the design of adaptation plans in a Dutch setting, the tools could be used for regional adaptation planning in other countries such as the development of regional adaptation strategies (RAS) as required by the European Union or on a national scale to support developing national adaptation plans of action (NAPAs) as initiated by the United Nations Framework Convention on Climate Change (UNFCCC) for least developed countries.     

A decision inventory approach for improving decision support for climate change impact assessment and adaptation

Assessing and adapting to the impacts of climate change requires balancing social, economic, and environmental factors in the context of an ever-expanding range of objectives, uncertainties, and management options. The term decision support describes a diverse class of resources designed to help manage this complexity and assist decision makers in understanding impacts and evaluating management options. Most climate-related decision support resources implicitly assume that decision making is primarily limited by the quantity and quality of available information. However, a wide variety of evidence suggests that institutional, political, and communication processes are also integral to organizational decision making. Decision support resources designed to address these processes are underrepresented in existing tools. These persistent biases in the design and delivery of decision support may undermine efforts to move decision support from research to practice. The development of new approaches to decision support that consider a wider range of relevant issues is limited by the lack of information about the characteristics, context, and alternatives associated with climate-related decisions. We propose a new approach called a decision assessment and decision inventory that will provide systematic information describing the relevant attributes of climate-related decisions. This information can be used to improve the design of decision support resources, as well as to prioritize research and development investments. Application of this approach will help provide more effective decision support based on a balanced foundation of analytical tools, environmental data, and relevant information about decisions and decision makers.     

厦门湾沙滩沉积物微塑料污染特征

微塑料（MPs）广泛存在于各种环境介质中,目前已经成为全球性环境问题.为了解海湾沙滩沉积物中微塑料的污染特征,揭示微塑料沉积规律及其影响因素,在厦门湾选择了5个典型沙滩,根据潮汐变化,同时在高潮线、中潮线和低潮线分层采集了0~10、10~20和20~30 cm的沉积物柱状样品,研究了沙滩沉积物中微塑料水平与垂直分布特征.结果表明,厦门湾沙滩45个沉积物样品中均检出微塑料,微塑料丰度范围为39~260 n ·kg^-1,平均丰度为（114±26） n ·kg^-1;微塑料形状主要为纤维状、碎片状、颗粒状和泡沫状,其中纤维状占比最大;主要成分为聚对苯二甲酸乙二醇酯（PET）、赛璐芬（cellophane）和聚乙烯（PE）;微塑料的颜色包括透明、蓝色、黄色、黑色和白色等.从统计结果可以看出,微塑料的平均丰度因沙滩位置、潮间带位置和采样深度的不同呈一定的规律,并且波浪、潮汐、岸线形状、风、游客数量和海漂垃圾清洁等自然和人为多种因素均影响沙滩微塑料的丰度和分布.研究成果有助于了解沙滩沉积物中微塑料的污染特征及来源,为微塑料的陆海传输提供依据,对海漂垃圾及岸滩垃圾收集提供数据支撑.     

Spatial and temporal variability of greenhouse gas emissions from rural development land use operations

Climate change objectives of mitigation and adaptation are being mainstreamed into many policies and strategies around the world. In Europe, this has included the Rural Development Programme, which aims to tackle multiple social, economic and environmental objectives in rural areas, and the integration of climate change objectives adds another strand of complexity to the decision making process. When formulating policies determining the likely effectiveness of any particular measure can be challenging, especially with respect to the spatial and temporal variability of greenhouse gas emissions. This is a challenge faced by all countries and regions around the world. This study uses Europe as an example to explore this issue. It highlights the variability in emissions from land use operations that may be encountered under different conditions and time horizons and considers this in the context of policy formulation. The Optimal Strategies for Climate change Action in Rural Areas software has been adapted to derive net greenhouse gas emissions for rural development operations for all regions in Europe. Operations have been classified into five categories based on their benefit/burden over different time horizons. The analysis shows that it is important to understand the time period over which benefits or burdens are realised and determine how this fits with policy instruments, such as land management agreements and the permanency of actions. It also shows that in some regions an operation can have benefits, but in other regions it has burdens; thus, location can be critical. Finally, in the context of developing operations to meet multiple social, economic and environmental objectives, it is important to acknowledge that seeking options that only reduce emissions may not always be practical or possible. In some instances, we may have to accept an increase in emissions in order to meet other objectives. It is important that we evaluate the net greenhouse gas emissions of all operations, not just those aimed at climate change mitigation. We can then select those with the least burden in the process of developing optimal solutions to meet multiple objectives.     

Vulnerability and adaptation to climate risks in Ontario agriculture

A vulnerability approach to climate change adaptation research is employed to explore prospects of agricultural adaptation to climatic variability and change. The methodological approach focuses on the system of concern, in this case, farms in Perth County, Ontario. Twenty-five interviews and four focus groups with farmers were used to identify climate risks on farms, and to document farmers’ responses to conditions and risks associated with climate and weather. The information collected describes a complex decision-making environment, with many forces both external and internal to the farm operation influencing management decisions. Within this environment, climate and weather are consistently referred to as a significant force influencing both farm operations and management decisions. Farmers have, however, developed a wide-range of anticipatory and reactive management strategies to manage climate risks. While these have potential to address future climate-related risks and opportunities, there are limits to adaptation, and an increase in the frequency of extreme events may exceed their adaptive capacities. Farmers are also generally unaware and/or unconcerned about future climate change, which could constrain opportunities to adopt long-term climate change adaptations.     

Assessment of risks for adaptation to climate change: the case of land-slides

This paper describes how relatively detailed knowledge about probabilities of natural hazards can be used to make decisions to develop areas and control the risk within hazard zones. The assessment serves two purposes. First, it shows how information can support decisions. Second, decision criteria put leads on what information is required. This is helpful to identify unavailable information. We show by an example from a land-slide prone area in Norway how a relatively reliable estimate of the probability of slides ends up in a rather uncertain estimate of the risk. Uncertainty about the risk represented by natural hazards imply great challenges to the development of adaptation policies to meet climate change, but they are required. We develop a simplified criterion for optimal adaptation, and estimate the added social value required to defend development in hazard prone areas instead of developing a risk-free alternative. The value is estimated between 0 and 0.40 Euros per Euro invested in the case area, depending on type of slide, category of asset and other costs that occur in the wake of slides.     

An evaluation of adaptation options for climate change impacts on agriculture in Kazakhstan

Agriculture in Kazakhstan is sensitive to climate, and wheat yields could be reduced up to 70% under climate change. With the transition from a socialist economy to a free market economy, decisions are being made now that will affect Kazakhstan's ability to cope with climate change. A team of Kazakh and American researchers examined the cost-effectiveness and barriers to implementations of adaptation options for climate change. Twelve adaptation options that increase flexibility to respond to climate change were identified using a screening matrix. Four options, forecasting pest outbreaks, developing regional centers for preserving genetic diversity of seeds, supporting a transition to a free market, and reducing soil erosion through the use of changed farming practices, were examined. The Adaptation Decision Matrix (ADM) was then applied to estimate benefits using expert judgment (using an arbitrary numerical scale, not monetary values) and benefits estimates were compared to costs to determine cost-effectiveness. The ADM uses subjective measures of how well adaptation options meet policy objectives. Controlling soil erosion was estimated to have the highest benefits, but the high costs of implementation appears to make it relatively cost-ineffective. Supporting a transition to a free market was ranked as the most cost-effective measure, with regional centers second. However, use of different scales to quantify benefits or different weights can result in regional centers being more cost-effective than the transition to a free market. Regional centers was also judged to have fewer barriers to implementation than a transition to a free market. These results will be incorporated in Kazakhstan's National Action Plan. The ADM and other tools are relatively easy to apply, but are quite subjective and difficult to evaluate. The tools can be quite useful by decision makers to analyze advantages and disadvantages between different adaptation options, but should be supplemented with additional, particularly quantitative analysis.     

Scale,context, and decision making in agricultural adaptation to climate variability and change

This work presents a framework for viewing agricultural adaptation, emphasizing the multiple spatial and temporal scales on which individuals and institutions process information on changes in their environment. The framework is offered as a means to gain perspective on the role of climate variability and change in agricultural adaptation, and developed for a case study of Australian agriculture. To study adaptation issues at the scale of individual farms we developed a simple modelling framework. The model highlights the decision making element of adaptation in light of uncertainty, and underscores the importance of decision information related to climate variability. Model results show that the assumption of perfect information for farmers systematically overpredicts adaptive performance. The results also suggest that farmers who make tactical planting decisions on the basis of historical climate information are outperformed by those who use even moderately successful seasonal forecast information. Analysis at continental scales highlights the prominent role of the decline in economic operating conditions on Australian agriculture. Examples from segments of the agricultural industry in Australia are given to illustrate the importance of appropriate scale attribution in adapting to environmental changes. In particular, adaptations oriented toward short time scale changes in the farming environment (droughts, market fluctuations) can be limited in their efficacy by constraints imposed by broad changes in the soil/water base and economic environment occuring over longer time scales. The case study also makes the point that adaptation must be defined in reference to some goal, which is ultimately a social and political exercise. Overall, this study highlights the importance of allowing more complexity (limited information, risk aversion, cross-scale interactions, mis-attribution of cause and effect, background context, identification of goals) in representing adaptation processes in climate change studies.     

沿岸熏烟扩散的中尺度模拟系统

建立了一个沿岸熏扩散的中尺度模拟系统，它由一个二维二阶矩闭合的ＰＢＬ模式和一个随机流动扩散模式组成。初步的模拟和一些数值试验结果表明，随机游动扩散模式与现行的基于高斯扩散公式的熏烟扩散模式比较，其物理模型更为合理；采用二阶矩湍流闭合方案的ＰＢＬ模式能模拟得到合理的热力内边界层（ＴＩＢＬ）结构特征，将二阶矩湍流闭合ＰＢＬ模式模拟所得气象场作为随机游动扩散模式的气象输入，可以较好地预测沿岸地区日间持续     

Interdisciplinary production of knowledge with participation of stakeholders: A case study of a collaborative project on climate variability,human decisions and agricultural ecosystems in the Argentine Pampas

There is a growing perception that science is not responding adequately to the global challenges of the 21st century. Addressing complicated, “wicked” current and future environmental issues requires insights and methods from many disciplines. Furthermore, to reach social robustness in a context of uncertainty and multiple values and objectives, participation of relevant social actors is required. As a consequence, interdisciplinary research teams with stakeholder or practitioner involvement are becoming an emerging pattern for the organization of integrative scientific research or integrated assessments. Nevertheless, still there is need to learn from actual experiences that bring together decision makers and scholars from different disciplines. This paper draws lessons from a self-reflective study of the collaborative process in two interdisciplinary, multi-institutional, multinational research teams addressing linkages between climate variability, human decisions and agricultural ecosystems in the Argentine Pampas. During project design, attention must be placed on team composition, ensuring not only that the needed talents are included, but also recruiting investigators with an open attitude toward interdisciplinary interaction. As the project begins, considerable effort must be dedicated to shared problem definition and development of a common language. Simple conceptual models and considerable redundancy in communication are helpful. As a project evolves, diverging institutional incentives, tensions between academic publication and outreach or policy-relevant outputs, disciplinary biases, and personality issues play increasingly important roles. Finally, toward a project's end the challenge arises of assessing interdisciplinary, integrative work. The lack of consensus on criteria for assessment of results is often ranked as a major practical difficulty of this kind of research. Despite many efforts to describe and characterize collaborative research on complex problems, conditions for success (including the very definition of “success”) remain to be rigorously grounded on actual cases. Toward this goal, we argue that a self-reflective process to identify and intervene on factors that foster or impede cooperative production of knowledge should be an essential component of integrated assessments involving scientists, practitioners and stakeholders.     

基于“评价-模拟-优化”的流域环境经济决策模型研究

流域管理是一个具有经济、社会与水环境等多维发展目标的复杂系统,不同目标之间存在复杂的非线性响应关系,如何模拟、协调、优化各种目标,是长期制约流域环境经济优化决策的关键技术瓶颈之一.当前在构建流域模型时往往缺乏全局性和系统性的考虑,采用线性单向建模思路,忽略了流域环境经济问题的复杂性、综合性和整体性,难以实现最优决策.针对这一不足,结合现有流域模型的建模经验与流域量化管理的需求,从系统优化发展的角度出发,基于环境经济协调度模型、系统动力学模拟模型和Powell优化模型提出了流域环境经济优化决策模型(简称ASO模型).该模型弥补了现有流域模型仅能在概念上描述因果反馈关系的不足,在数值模型上实现流域经济-社会-水环境各子系统中反馈回路的闭合,提供了一种对流域系统复杂反馈关系的模拟方法.最后,基于该模型对抚仙湖流域进行了案例研究.     

Mountain communities and climate change adaptation: barriers to planning and hurdles to implementation in the Southern Rocky Mountain Region of North America

Geographic factors make mountain communities around the world vulnerable to the direct effects of climate change, and reliance on recreation and tourism can increase vulnerability to the secondary economic impacts.The goal of this research was to investigate the current state of community adaptation planning in the Southern Rocky Mountain region of North America. Using original survey data this paper discusses the challenges that community and county officials currently face, the perceived effects of future climate change in this region, and the perceived barriers to adaptation planning and hurdles to adaptation implementation. Results show lack of resources, information and political will are the most commonly reported barriers to adaptation. This paper also examines the connectivity between mountain communities and the surrounding federal public lands. Fifty one percent of respondents report that decisions made on nearby public lands frequently or always affect planning and decision making in their community. Collaborative efforts between these entities are proposed as a way to reduce the resource burden of adaptation planning for both entities. Finally, this paper discusses how attitudes and beliefs about climate change affect responses to questions about adaptation planning. On average, respondents who report higher levels of concern about and belief in climate change and those who are better informed about climate change report higher levels of adaptation planning. Elected officials in this sample have, on average, lower concern about and belief in climate change than bureaucratic respondents. Thus changes in elected official composition or improved leadership on climate change planning by incumbent officials could facilitate progress on adaptation     

基于不确定性的矿区污染治理投入决策研究

基于现实的基础上,考虑矿区污染治理所面临的不确定性,对污染治理最优投入的政策决策机制进行研究.根据污染治理投入成本的不可逆性及不确定性建立污染治理最优投入决策机制模型,求出了污染治理投入的临界点.结果表明,该模型能够真实、客观、全面地评价矿区污染治理投入决策机制,并可动态指导治理政策实施的最优时机.同时,分析了模型中各参数对污染治理决策的影响,结合案例验证了此模型在污染治理决策问题上的分析结果.结果发现,考虑了不确定性的模型有效避免了传统决策模型的局限性,可以帮助政府和煤矿企业做出科学有效的污染治理投入决策和制度设计,能更有效地推动煤矿企业安全生产的实施.本研究对环境政策的制定和实施具有理论和实践指导意义.     

污染场地调查中离散采样的局限性分析

采样误差是污染场地调查不确定性的主要来源.对污染场地调查采样方法进行研究,是提升调查数据精度和风险管控决策水平的重要手段.该研究结合污染场地的调查目标、污染物在土壤中分布的空间异质性特征,重点对离散采样方法和增量采样方法的应用现状及局限性进行了分析阐述.结果表明:①采样目标的设定取决于决策尺度.基于地块尺度决策的采样目标是表征污染物的空间分布,基于网格尺度决策的采样目标是获取更小尺度决策单元内污染物的平均浓度水平;②利用离散点表征污染物空间分布时,由于本身空间自相关性不强,表征结果不确定性大;③通过采用大样本量、高覆盖率的增量采样方法,能增强样本的代表性,更加精确地表征污染物在决策单元内的平均浓度,弥补离散采样的不足.但增量采样在挥发性有机物场地、深层土壤调查等情景下存在局限性.因此,污染场地调查应充分考虑污染物分布的空间异质性特征、采样方法应用条件、决策尺度等因素,选择合适的采样方法才能有效提升污染场地风险管控决策的科学性.      

Application of real option analysis for planning under climate change uncertainty: a case study for evaluation of flood mitigation plans in Korea

With concerns regarding global climate change increasing, recent studies on adapting to nonstationary climate change recommended a different planning strategy that could spread risks. Uncertainty in global climate change should be considered in any decision-making processes for flood mitigation strategies, especially in areas within a monsoon climate regime. This study applied a novel planning method called real option analysis (ROA) to an important water resources planning practice in Korea. The proposed method can easily be applied to other watersheds that are threatened by flood risk under climate change. ROA offers flexibility for decision-makers to reflect uncertainty at every stage during the project planning period. We successfully implemented ROA using a binomial tree model, including two real options—delay and abandon—to evaluate flood mitigation alternatives for the Yeongsan River Basin in Korea. The priority ranking of the four alternatives between the traditional discount cash flow (DCF) and ROA remained the same; however, two alternatives that were assessed as economically infeasible using DCF, were economically feasible using ROA. The binomial decision trees generated in this study are expected to be informative for decision-makers to conceptualize their adaptive planning procedure.     

A methodological framework to operationalize climate risk management: managing sovereign climate-related extreme event risk in Austria

Despite considerable uncertainties regarding the exact contribution of anthropogenic climate change to disaster risk, rising losses from extreme events have highlighted the need to comprehensively address climate-related risk. This requires linking climate adaptation to disaster risk management (DRM), leading to what has been broadly referred to as climate risk management (CRM). While this concept has received attention in debate, important gaps remain in terms of operationalizing it with applicable methods and tools for specific risks and decision-contexts. By developing and applying a methodological approach to CRM in the decision context of sovereign risk (flooding) in Austria we test the usefulness of CRM, and based on these insights, inform applications in other decision contexts. Our methodological approach builds on multiple lines of evidence and methods. These comprise of a broad stakeholder engagement process, empirical analysis of public budgets, and risk-focused economic modelling. We find that a CRM framework is able to inform instrumental as well as reflexive and participatory debate in practice. Due to the complex interaction of social–ecological systems with climate risks, and taking into account the likelihood of future contingent climate-related fiscal liabilities increasing substantially as a result of socioeconomic developments and climate change, we identify the need for advanced learning processes and iterative updates of CRM management plans. We suggest that strategies comprising a portfolio of policy measures to reduce and manage climate-related risks are particularly effective if they tailor individual instruments to the specific requirements of different risk layers.     

Multiattribute utility analysis for addressing Section 316(b) of the Clean Water Act

We believe that the fundamental issues associated with implementing Section 316(b) of the Clean Water Act are whether or not it requires a balancing of objectives and if it does, how that balancing should be done. If balancing is required, we recommend the use of multiattribute utility analysis (MUA). MUA is a formal, analytic approach for evaluating and comparing options for decisions with multiple objectives. It differentiates the two types of judgments needed for public policy decisions: (1) value judgments, which indicate what people want to happen as the result of a decision and their willingness to make tradeoffs, and (2) scientific judgments, which indicate what scientists or other technical specialists think is likely to happen based on the option that is chosen. MUA provides an approach for deciding what is an ‘adverse environmental impact’ and what is ‘best technology available’ based on site-specific considerations that can be consistently applied to all cooling water intakes. To illustrate the first step of a collaborative MUA process, we present a preliminary hierarchy of objectives constructed during a 1-day meeting held with regulators, electric utilities, and environmental groups to address the renewal of SPDES permits for four power plants operating on the Hudson River.