生态风险评价研究进展

20多年来,生态风险评价研究经历了从环境风险到生态风险到区域生态风险评价的发展历程,风险源由单一风险源扩展到多风险源,风险受体由单一受体发展到多受体,评价范围由局地扩展到区域景观水平.区域生态风险评价就是大尺度上研究复杂环境背景下包含多风险源、多风险受体的综合风险研究.目前,区域生态风险评价的理论框架已经搭建起来,统计方法多采用相对评价法.区域生态风险评价未来的发展方向为继续加强实验和野外调查,进一步减小不确定性,逐步解决尺度推移问题.区域生态风险评价必须与经济、社会、文化相结合,才能充分发挥它在管理决策中的作用.     

Operationalizing resilience for adaptive coral reef management under global environmental change

Cumulative pressures from global climate and ocean change combined with multiple regional and local‐scale stressors pose fundamental challenges to coral reef managers worldwide. Understanding how cumulative stressors affect coral reef vulnerability is critical for successful reef conservation now and in the future. In this review, we present the case that strategically managing for increased ecological resilience (capacity for stress resistance and recovery) can reduce coral reef vulnerability (risk of net decline) up to a point. Specifically, we propose an operational framework for identifying effective management levers to enhance resilience and support management decisions that reduce reef vulnerability. Building on a system understanding of biological and ecological processes that drive resilience of coral reefs in different environmental and socio‐economic settings, we present an Adaptive Resilience‐Based management (ARBM) framework and suggest a set of guidelines for how and where resilience can be enhanced via management interventions. We argue that press‐type stressors (pollution, sedimentation, overfishing, ocean warming and acidification) are key threats to coral reef resilience by affecting processes underpinning resistance and recovery, while pulse‐type (acute) stressors (e.g. storms, bleaching events, crown‐of‐thorns starfish outbreaks) increase the demand for resilience. We apply the framework to a set of example problems for Caribbean and Indo‐Pacific reefs. A combined strategy of active risk reduction and resilience support is needed, informed by key management objectives, knowledge of reef ecosystem processes and consideration of environmental and social drivers. As climate change and ocean acidification erode the resilience and increase the vulnerability of coral reefs globally, successful adaptive management of coral reefs will become increasingly difficult. Given limited resources, on‐the‐ground solutions are likely to focus increasingly on actions that support resilience at finer spatial scales, and that are tightly linked to ecosystem goods and services.     

区域生态风险评价的关键问题与展望

区域生态风险评价具有多风险因子、多风险受体、多评价终点、强调不确定性因素以及空间异质性的特点,它与传统的生态风险评价在风险源、胁迫因子和评价尺度上具有明显区别。尝试建立了一个基于陆地生态系统的区域生态风险评价框架,同时针对目前区域生态风险评价的研究现状,指出不确定性分析、尺度外推难、评价指标不统一、评价标准不统一、风险因子筛选及优先排序、区域内污染物复合、水生过渡到陆生生态系统风险评价、特殊的人为因素等是目前区域生态风险评价存在的关键问题及难点所在,并提出解决这些问题可能所需的工具、手段和理论方法突破。最后指出区域生态风险观测与数据采集加工、区域生态风险指标体系的统一与整合、区域生态风险评价方法论、区域生态风险的空间分布特征与表达以及区域生态风险评价反馈与管理机制5个方面是区域生态风险评价未来的研究重点。     

A Procedure for Ecological Tiered Assessment of Risks (PETAR)

Several procedures for Ecological Risk Assessment (ERA) have been suggested. The use of these existing procedures often relies on availability of existing data and/or on large resources for acquisition of new ones. This paper presents a three-tiered procedure for retrospective evaluation of risks adapted to limited resources and scarce background information of relevance for risk assessments, such as in developing countries. The tiers require successively more detailed investigations. The approach assures that resources available for site-specific investigations are directed towards well-formulated questions raised during previous stages of the assessment. The first tier, the preliminary assessment, is a qualitative evaluation of existing information on anthropogenic stressors, sources of stressors and expected ecological effects. The second tier is a regional risk assessment; a semi-quantitative evaluation of ecological risks, over large geographical areas, which results in a ranking of sources and stressors having the greatest potential for ecological impact and ranking of subareas inside the study area more likely to be impacted. The final tier is a site-specific and quantitative risk assessment, at a smaller scale and requiring more resources, that incorporates methodologies for establishing causality between exposure to multiple stressors and effects on specific endpoints of ecological and societal relevance.     

Ecological Indicators in Risk Assessment: Workshop Summary

Ecological indicators can be defined as relatively simple measurements that relay scientific information about complex ecosystems. Such indicators are used to characterize risk in ecological risk assessment (ERA) and to mark progress toward resource management goals. In late 1997, scientists from the U.S. Environmental Protection Agency and from the Chemical Manufacturers Association (CMA) held a workshop to explore opportunities for collaborative research and scientific exchange on the development and application of ecological indicators. Several scientific challenges were identified as they relate to problem formulation, exposure and effects assessment, and risk characterization. Chief among these were a better understanding of multiple stressors (both chemical and non-chemical), characterization of reference sites and natural variability, extrapolation of measures to ecologically relevant scales, development of comprehensive, ecosystem-based models that incorporate multiple stressors and receptors, and a consistent system for evaluating ecological indicators.     

Regional Ecological Risk Assessment of a Near Shore Marine Environment: Cherry Point,WA

We conducted a regional ecological risk assessment for a near shore marine environment in northwestern Washington State using the Relative Risk Model. The objectives of this study were threefold: (1) to analyze cumulative impacts from multiple sources of chemical and non-chemical stressors in the near shore region and upland watersheds of Cherry Point (2) to determine the utility of Monte Carlo type uncertainty analysis in a rank-based regional risk assessment and (3) to investigate the effects of model habitat characterization on risk estimates. We used geographic information systems to compile and compare spatial data to determine ranks for sub-regions within the study area. By quantitatively combining ranks with exposure and effects filters, we estimated total relative risk between sub-regions and relative contributions of stressors. Finally, we used Monte Carlo analysis and an alternative ranking scheme to evaluate the effects of model and parameter uncertainty on risk predictions. The regional risk assessment results suggest the major contributors of risk are vessel traffic, upland urban and agricultural land use and shoreline recreational activities. This assessment demonstrated the applicability of regional risk assessment to marine near shore regions and the benefit of Monte Carlo analysis in describing uncertainty in a Relative Risk Model regional risk assessment.     

Integrating animal behaviour into research on multiple environmental stressors: a conceptual framework

While a large body of research has focused on the physiological effects of multiple environmental stressors, how behavioural and life-history plasticity mediate multiple-stressor effects remains underexplored. Behavioural plasticity can not only drive organism-level responses to stressors directly but can also mediate physiological responses. Here, we provide a conceptual framework incorporating four fundamental trade-offs that explicitly link animal behaviour to life-history-based pathways for energy allocation, shaping the impact of multiple stressors on fitness. We first address how small-scale behavioural changes can either mediate or drive conflicts between the effects of multiple stressors and alternative physiological responses. We then discuss how animal behaviour gives rise to three additional understudied and interrelated trade-offs: balancing the benefits and risks of obtaining the energy needed to cope with stressors, allocation of energy between life-history traits and stressor responses, and larger-scale escape from stressors in space or time via large-scale movement or dormancy. Finally, we outline how these trade-offs interactively affect fitness and qualitative ecological outcomes resulting from multiple stressors. Our framework suggests that explicitly considering animal behaviour should enrich our mechanistic understanding of stressor effects, help explain extensive context dependence observed in these effects, and highlight promising avenues for future empirical and theoretical research.     

Counting on β-Diversity to Safeguard the Resilience of Estuaries

Coastal ecosystems are often stressed by non-point source and cumulative effects that can lead to local-scale community homogenisation and a concomitant loss of large-scale ecological connectivity. Here we investigate the use of β-diversity as a measure of both community heterogeneity and ecological connectivity. To understand the consequences of different environmental scenarios on heterogeneity and connectivity, it is necessary to understand the scale at which different environmental factors affect β-diversity. We sampled macrofauna from intertidal sites in nine estuaries from New Zealand’s North Island that represented different degrees of stress derived from land-use. We used multiple regression models to identify relationships between β-diversity and local sediment variables, factors related to the estuarine and catchment hydrodynamics and morphology and land-based stressors. At local scales, we found higher β-diversity at sites with a relatively high total richness. At larger scales, β-diversity was positively related to γ-diversity, suggesting that a large regional species pool was linked with large-scale heterogeneity in these systems. Local environmental heterogeneity influenced β-diversity at both local and regional scales, although variables at the estuarine and catchment scales were both needed to explain large scale connectivity. The estuaries expected a priori to be the most stressed exhibited higher variance in community dissimilarity between sites and connectivity to the estuary species pool. This suggests that connectivity and heterogeneity metrics could be used to generate early warning signals of cumulative stress.     

Ecosystem stability in space: α, β and γ variability

The past two decades have seen great progress in understanding the mechanisms of ecosystem stability in local ecological systems. There is, however, an urgent need to extend existing knowledge to larger spatial scales to match the scale of management and conservation. Here, we develop a general theoretical framework to study the stability and variability of ecosystems at multiple scales. Analogously to the partitioning of biodiversity, we propose the concepts of alpha, beta and gamma variability. Gamma variability at regional (metacommunity) scale can be partitioned into local alpha variability and spatial beta variability, either multiplicatively or additively. On average, variability decreases from local to regional scales, which creates a negative variability–area relationship. Our partitioning framework suggests that mechanisms of regional ecosystem stability can be understood by investigating the influence of ecological factors on alpha and beta variability. Diversity can provide insurance effects at the various levels of variability, thus generating alpha, beta and gamma diversity–stability relationships. As a consequence, the loss of biodiversity and habitat impairs ecosystem stability at the regional scale. Overall, our framework enables a synthetic understanding of ecosystem stability at multiple scales and has practical implications for landscape management.     

An Ecological Basis for Integrated Environmental Management

Historically, approaches to environmental management activities have been reactive rather than proactive. Environmental laws and regulations have been generated primarily in response to particular issues (e.g., chemical contamination), creating a piecemeal approach for managing the environment. Responsibilities for managing different resources (e.g., water, air, forests, wildlife) have been assigned to different agencies or groups within government, further fragmenting environmental management. Proactive approaches that recognize the interconnectedness of environmental components are necessary to address complex and long-term environmental management issues. This Perspective proposes an environmental management approach that is comprehensive and systematic, while still being comprehensible to decision-makers and other stakeholders. The proposed approach is based on ecology and environmental values related to decision-making. It considers interrelationships among and between living organisms (including humans) and their physical environment. The proposed approach builds on the ecological risk assessment (ERA) paradigm, including goal (or problem) identification, values identification (ecological and human) for the environment being managed, and data collection and analysis focused on management decision-making. Stakeholder involvement and active participation are essential elements. As demonstrated herein, application of the proposed framework has enabled environmental managers to achieve workable solutions and to avoid or resolve environmental conflicts at both local and regional scales. The proposed framework is demonstrably transportable across political boundaries, applicable to all environments involving natural resources, independent of any particular ideology, and applicable to environmental management activities at all scales.     

Multivariate geostatistical methods for analysis of relationships between ecological indicators and environmental factors at multiple spatial scales

As all biodiversity-related variables, ecological indicators are influenced by environmental factors working at different spatial scales. However, assessing the relationship between environmental factors and ecological indicators is limited to a set of spatial scales determined a priori. This a priori assumption can hide important relationships, especially for ecological indicators with a complex spatial structure that can be driven, for example, by the influence of multiple pollutants with different dispersion ranges or by the influence of local and regional factors such as land-cover and climate. To relate ecological indicators and environmental factors without assuming a priori spatial scales of analysis, we used a Linear Model of Coregionalization. This method has been used in literature to analyze the joint distribution of biodiversity variables. Here we show that it can be used to gain insight into spatial patterns of relationships between ecological indicators and underlying environmental factors. We applied this method to a region of south-west Europe, relating data from land-cover, altitude and climate with an ecological indicator, the abundance of fruticose lichen species, known to be very sensitive to multiple environmental factors. Based on variogram analysis we identified distinct spatial scales of relationships between the ecological indicator and environmental factors. For each spatial scale we described relationships using Principal Component Analysis applied to the coregionalization matrices. This way we could assess how strong the relationship between each environmental factor and ecological indicator at each spatial scale was: at medium scales (c. 15 km) open spaces areas (a proxy for particle emissions) were more important; at larger scales (c. 45 km) open spaces, artificial areas (a proxy for gaseous pollutants) and also climate were preponderant. Thus, multivariate geostatistics provided a tool to improve knowledge on relationships between ecological indicators and environmental factors at multiple spatial scales without setting a priori spatial scales of analysis.     

The bright side of ecological stressors

Ecological stressors are considered to negatively affect biological systems; however, corresponding responses to stressors can be complex, depending on the ecological functions and the number and duration of the stressors. Mounting evidence indicates potential benefits of stressors. Here, we develop an integrative framework to understand stressor-induced benefits by clarifying three categories of mechanisms: seesaw effects, cross-tolerance, and memory effects. These mechanisms operate across various organizational levels (e.g., individual, population, community) and can be extended to an evolutionary context. One remaining challenge is to develop scaling approaches for linking stressor-induced benefits across organizational levels. Our framework provides a novel platform for predicting the consequences of global environmental changes and informing management strategies in conservation and restoration practices.     

Local and Regional Impacts of Pollution on Coral Reefs along the Thousand Islands North of the Megacity Jakarta,Indonesia

Worldwide, coral reefs are challenged by multiple stressors due to growing urbanization, industrialization and coastal development. Coral reefs along the Thousand Islands off Jakarta, one of the largest megacities worldwide, have degraded dramatically over recent decades. The shift and decline in coral cover and composition has been extensively studied with a focus on large-scale gradients (i.e. regional drivers), however special focus on local drivers in shaping spatial community composition is still lacking. Here, the spatial impact of anthropogenic stressors on local and regional scales on coral reefs north of Jakarta was investigated. Results indicate that the direct impact of Jakarta is mainly restricted to inshore reefs, separating reefs in Jakarta Bay from reefs along the Thousand Islands further north. A spatial patchwork of differentially degraded reefs is present along the islands as a result of localized anthropogenic effects rather than regional gradients. Pollution is the main anthropogenic stressor, with over 80% of variation in benthic community composition driven by sedimentation rate, NO₂, PO₄ and Chlorophyll a. Thus, the spatial structure of reefs is directly related to intense anthropogenic pressure from local as well as regional sources. Therefore, improved spatial management that accounts for both local and regional stressors is needed for effective marine conservation.     

生态风险评价方法述评

生态风险是由环境的自然变化或人类活动引起的生态系统组成、结构的改变而导致系统功能损失的可能性。生态风险评价是定量预测各种风险源对生态系统产生风险的或然性以及评估该风险可接受程度的方法体系,因而是生态环境风险管理与决策的定量依据。在介绍了生态风险概念的基础上,按照风险源性质的分类标准将生态风险划分为化学污染类风险源、生态事件类风险源、复合类风险源3类,并分别论述了3类生态风险对应评价方法的特点与发展的方向。另外,针对生态风险评价研究的现状,讨论了我国生态风险研究的优先领域,包括建立急性、慢性毒理数据库,构建外来生物入侵风险评价标准等,同时,建议将综合概率统计学、复杂系统理论与遥感技术等手段引入生态风险评价方法中,以进一步提高风险评价结果在生态风险管理中的有效性。     

Types of Integration in Risk Assessment and Management,And Why They Are Needed

Risk-based decision making requires that the decision makers and stakeholders are informed of all risks that are potentially significant and relevant to the decision. The International Programme on Chemical Safety of the World Health Organization has developed a framework for integrating the assessment of human health and ecological risks. However, other types of integration are needed to support particular environmental decisions. They are integration of exposure and effects, of multiple chemicals and other hazardous agents, of multiple routes of exposure, of multiple endpoints, multiple receptors, multiple spatial and temporal scales, a product's life cycle, management alternatives, and socioeconomics with risk assessment. Inclusion of all these factors in an integrated assessment could lead to paralysis by analysis. Therefore, it is important that assessors be cognizant of the decision process and that decision makers and those who will influence the decision (stakeholders) be involved in planning the assessment to ensure that the degree of integration is necessary and sufficient.     

高潜水位煤矿区生态风险识别与评价

生态风险评价是生态环境保护与管理的重要研究内容,并广泛运用于流域与较大范围的区域尺度的研究。以区域生态风险评价理论为基础,结合高潜水位煤矿区生态环境以及煤炭开采对生态系统造成的危害的特点,通过分析风险源、风险受体、生态终点以及暴露—响应过程,对高潜水位煤矿区生态风险的识别与评价方法进行了研究,构建了典型高潜水位煤矿区的生态风险识别与评价概念模型与空间分析框架,分析了煤矿区生态风险识别的主要技术手段与方法,并构建了以缓冲为主要手段的综合生态风险评价方法。选择山东东滩煤矿作为研究对象,针对研究区内存在的采煤塌陷、洪涝、污染、景观及社会等生态风险类型,定量评价其空间差异,并提出相应的风险防范措施。案例分析结果表明,研究区综合生态风险重度、中度、一般、轻度分别占到研究区的4.70%,64.00%,24.09%,7.20%。生态风险较高的区域主要位于矿区中西部,为煤矸石山、裸露煤炭堆积与发电厂分布区域;中度风险是研究区主要的风险类型。从降低生态风险保障矿区生态安全角度,在未来矿区规划与生态治理过程中,提出了具体的应对措施,包括:(1)注重源头控制;(2)建立高生态风险区域阻隔带;(3)加强污染的监测与控制;(4)采用边开采边治理技术。建议加强生态风险高区域的阻隔,建立生态缓冲带,减缓对整个矿区的综合影响,构建东滩煤矿生态风险防范的空间结构。     

Developing A Regional Ecological Risk Assessment: A Case Study of a Tasmanian Agricultural Catchment

A regional ecological risk assessment was conducted for the Mountain River catchment in Tasmania, Australia. The Relative Risk Model was used in conjunction with geographic information systems interpretations. Stakeholder values were used to develop assessment endpoints, and regional stressors and habitats were identified. The risk hypotheses expressed in the conceptual model were that agriculture and land clearing for rural residential are producing multiple stressors that have potential for contamination of local waterbodies, eutrophication, changes in hydrology, reduction in the habitat of native flora and fauna, reductions in populations of beneficial insects in agricultural production systems, increased weed competition in pastures, and loss of aesthetic value in residential areas. In the risk analysis the catchment was divided into risk regions based on topography and land use. Stressors were ranked on likelihood of occurrence, while habitats were ranked on percentage land area. Risk characterization showed risks to the maintenance of productive primary industries were highest across all risk regions, followed by maintenance of a good residential environment and maintenance of fish populations. Sensitivity analysis was conducted to show the variability in risk outcomes stemming from uncertainty about stressors and habitats. Outcomes from this assessment provide a basis for planning regional environmental monitoring programs.     

Ecological assessments with algae: a review and synthesis

Algae have been used for a century in environmental assessments of water bodies and are now used in countries around the world. This review synthesizes recent advances in the field around a framework for environmental assessment and management that can guide design of assessments, applications of phycology in assessments, and refinements of those applications to better support management decisions. Algae are critical parts of aquatic ecosystems that power food webs and biogeochemical cycling. Algae are also major sources of problems that threaten many ecosystems goods and services when abundances of nuisance and toxic taxa are high. Thus, algae can be used to indicate ecosystem goods and services, which complements how algal indicators are also used to assess levels of contaminants and habitat alterations (stressors). Understanding environmental managers' use of algal ecology, taxonomy, and physiology can guide our research and improve its application. Environmental assessments involve characterizing ecological condition and diagnosing causes and threats to ecosystems goods and services. Recent advances in characterizing condition include site‐specific models that account for natural variability among habitats to better estimate effects of humans. Relationships between algal assemblages and stressors caused by humans help diagnose stressors and establish targets for protection and restoration. Many algal responses to stressors have thresholds that are particularly important for developing stakeholder consensus for stressor management targets. Future research on the regional‐scale resilience of algal assemblages, the ecosystem goods and services they provide, and methods for monitoring and forecasting change will improve water resource management.     

Exploratory Cumulative Risk Assessment (CRA) Approaches Using Secondary Data

Cumulative risk assessments (CRAs) include the examination of risks posed by multiple stressors and include population-specific vulnerabilities and susceptibilities. In this case study, we assess potential hearing impairment hazard due to joint exposure from noise and volatile organic compounds (VOCs) in order to examine the strengths and limitations of using secondary data on exposure and health effects for a CRA. Block group-level noise categories were estimated using modeled street-level data. A quantile regression model of sociodemographic and personal predictors from the 1999–2000 U.S. National Health and Nutrition Examination Survey VOC dataset was used along with block group-level sociodemographic and personal variables to estimate VOC exposures. Hazard indices (HIs) for potential hearing impairment due to joint noise and VOC exposures were calculated. County-averaged HIs for hearing impairment ranged from 0.8 (10th total VOCs percentile and 45–60 dB) to 1.7 (90th total VOCs percentile and 71–75 dB). Limitations of the exposure and health effects data included issues combining heterogeneous data and a lack of established threshold levels for combined low-level exposures; yet, this case study illustrates that screening-level CRAs, including non-chemical stressors, can be accomplished with publicly available data and existing methods.     

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。