Rapid survey protocol that provides dynamic information on reef condition to managers of the Great Barrier Reef

Managing to support coral reef resilience as the climate changes requires strategic and responsive actions that reduce anthropogenic stress. Managers can only target and tailor these actions if they regularly receive information on system condition and impact severity. In large coral reef areas like the Great Barrier Reef Marine Park (GBRMP), acquiring condition and impact data with good spatial and temporal coverage requires using a large network of observers. Here, we describe the result of ~10 years of evolving and refining participatory monitoring programs used in the GBR that have rangers, tourism operators and members of the public as observers. Participants complete Reef Health and Impact Surveys (RHIS) using a protocol that meets coral reef managers’ needs for up-to-date information on the following: benthic community composition, reef condition and impacts including coral diseases, damage, predation and the presence of rubbish. Training programs ensure that the information gathered is sufficiently precise to inform management decisions. Participants regularly report because the demands of the survey methodology have been matched to their time availability. Undertaking the RHIS protocol we describe involves three ~20 min surveys at each site. Participants enter data into an online data management system that can create reports for managers and participants within minutes of data being submitted. Since 2009, 211 participants have completed a total of more than 10,415 surveys at more than 625 different reefs. The two-way exchange of information between managers and participants increases the capacity to manage reefs adaptively, meets education and outreach objectives and can increase stewardship. The general approach used and the survey methodology are both sufficiently adaptable to be used in all reef regions.     

Framework for designing sampling programs

A general framework for designing sampling programs is described. As part of the sampling program the problem of concern, or reason for sampling, needs to be clearly stated and objectives specified. The development of a conceptual model will assist the clarification of objectives and the choice of indicators to be sampled.Objectives can then be stated as testable hypotheses and decisions made about the samallest difference/changes that are to be detected/observed by the sampling.To allow the collection of representative samples, and the statistical analysis of data to be collected, the potential sources of variability in the data must be considered. Site, selection, frequency and replication must account for the expected variability.Before field collection of samples occurs, the sample collection device needs to be tested as to its efficiency to collect a representative sample. It also will usually be necessary to consider how samples are to be preserved to inhibit biological and chemical change. All sample programs require a quality assurance program to identify, measure and control errors.As well as the above the cost-effectiveness of the program should be evaluated in terms of maximizing the information obtained/cost.     

Outline of an environmental information system

The development of an environmental information system necessitates a phased implementation approach. Phase 1 includes the elements that are traditionally viewed as comprising monitoring and assessment activities. Analysis tools for interpretive work are identified including statistics, modelling, and GIS. Phase 2 follows the information flow beyond project reporting to examine the process of decision making. The inclusion of other forms of knowledge beyond the strictly scientific is necessary where the development of multi-sectoral decisions must be made. Phase 3 extends the decision-making process to the policy development and implementation field. This is accomplished by the inclusion of expert systems as advanced decision support systems which enable the manager to test various hypotheses and policy options prior to commitment. In addressing water resource issues, the importance of setting achievable and enforceable sectoral criteria and standards for industrial, agricultural, and drinking water supplies is discussed with reference to both usage and effluent criteria. Quality assurance and control is an area which must be critically addressed in any water resource project. The implementation of quality control programs must extend from the field sampling procedures and laboratory standard methods to both inter- and intra-laboratory tests and the development and maintenance of databases.     

A framework for assessment and monitoring of small mammals in a lowland tropical forest

Development projects in tropical forests can impact biodiversity.Assessment and monitoring programs based on the principles of adaptive management assist managers to identify and reduce suchimpacts. The small mammal community is one important component ofa forest ecosystem that may be impacted by development projects. In 1996, a natural gas exploration project was initiated in a Peruvian rainforest. The Smithsonian Institution's Monitoring andAssessment of Biodiversity program cooperated with Shell Prospecting and Development Peru to establish an adaptive management program to protect the region's biodiversity. In thisarticle, we discuss the role of assessing and monitoring small mammals in relation to the natural gas project. We outline theconceptual issues involved in establishing an assessment andmonitoring program, including setting objectives, evaluating the results and making appropriate decisions. We also summarizethe steps taken to implement the small mammal assessment, provideresults from the assessment and discuss protocols to identifyappropriate species for monitoring.     

Characterizing soils for hazardous waste site assessments

This paper provides a review and justification of the minimum data needed to characterize soils for hazardous waste site assessments and to comply with the Comprehensive Environmental Response, Compensation and Liability Act (CERCLA). Scientists and managers within the regulatory agency and the liable party need to know what are the important soil characteristics needed to make decisions about risk assessment, what areas need remediation and what remediation options are available. If all parties involved in characterizing a hazardous waste site can agree on the required soils data set prior to starting a site investigation, data can be collected in a more efficient and less costly manner. Having the proper data will aid in reaching decisions on how to address concerns at, and close-out, hazardous waste sites.This paper was prepared to address two specific concerns related to soil characterization for CERCLA remedial response. The first concern is the applicability of traditional soil classification methods to CERCLA soil characterization. The second is the identification of soil characterization data type required for CERCLA risk assessment and analysis of remedial alternatives. These concerns are related, in that the Data Quality Objective (DQO) process addresses both. The DQO process was developed in part to assist CERCLA decision-makers in identifying the data types, data quality, and data quantity required to support decisions that must be made during the remedial investigation/feasibility study (RI/FS) process. Data Quality Objectives for Remedial Response Activities: Development Process (US EPA, 1987a) is a guidebook on developing DQOs. This process as it relates to CERCLA soil characterization is discussed in the Data Quality Objective Section of this paper.     

Developing an indicator for the chronic health impact of traffic-related pollutant emissions

The goal of this study is to develop an emission based indicator for the health impact of the air pollution caused by traffic. This indicator must make it possible to compare different situations, for example different Urban Travel Plans, or technical innovations. Our work is based on a literature survey of methods for evaluating health impacts and, more particularly, those which relate to the atmospheric pollution caused by transport. We then define a health impact indicator based on the traffic emissions, named IISCEP for Chronic health impact indicator of pollutant emission. Here health is understood in a restricted meaning, excluding well-being. Only primary pollutants can be considered, as the inputs are emission data and an indicator must be simple. The indicator is calculated as the sum of each pollutant emission multiplied by a dispersion and exposition factor and a substance specific toxicity factor taking account of the severity.Last, two examples are shown using the IISCEP: comparison between petrol and diesel vehicles, and Nantes urban district in 2008 vs 2002.Even if it could still be improved, IISCEP is a straightforward indicator which can be used to gauge the chronic effects of inhaling primary pollutants. It can only be used in comparisons, between different scenarios or different technologies. The quality of the emissions data and the choice of the pollutants that are considered are the two essential factors that determine its validity and reliability.     

A pilot project to detect and forecast harmful algal blooms in the northern Gulf of Mexico

More timely access to data and information on the initiation, evolution and effects of harmful algal blooms can reduce adverse impacts on valued natural resources and human health. To achieve this in the northern Gulf of Mexico, a pilot project was initiated to develop a user-driven, end-to-end (measurements to applications) observing system. A key strategy of the project is to coordinate existing state, federal and academic programs at an unprecedented level of collaboration and partnership. Resource managers charged with protection of public health and aquatic resources require immediate notice of algal events and a forecast of when, where and what adverse effects will likely occur. Further, managers require integrated analyses and interpretations, rather than raw data, to make effective decisions. Consequently, a functional observing system must collect and transform diverse measurements into usable forecasts. Data needed to support development of forecasts will include such properties as sea surface temperature, winds, currents and waves; precipitation and freshwater flows with related discharges of sediment and nutrients; salinity, dissolved oxygen, and chlorophyll concentrations (in vivo fluorescence); and remotely-sensed spatial images of sea surface chlorophyll concentrations. These data will be provided via a mixture of discrete and autonomous in situ sensing with near real-time data telemetry, and remote sensing from space (SeaWiFS), aircraft (hyperspectral imagery) or land (high-frequency radar). With calibration across these platforms, the project will ultimately provide a 4-dimensional visualization of harmful algae events in a time frame suitable to resource managers.     

Assessing impacts of power plants on fish populations: A general strategy

Environmental impact statements are often characterized by extraneous data collection, irrelevant statistical procedures, misapplied models and concomitant ambiguity in conclusions. Impact assessment is difficult but when explicit objectives are not stated and specific tasks are not linked to these objectives, assessment becomes impossible. We emphasize a flexible approach that can be adapted to site-specific requirements. The strategy consists of six steps: (1) Conceptualization of the ecosystem, (2) design and execution of pilot studies, (3) refinement of conceptualization, (4) design of a study plan, (5) execution of the study plan and (6) evaluation of impact. Development of a conceptual model leads to specification of testable hypotheses directly linked to the objectives of impact assessment. Deterministic and stochastic simulation modeling can be coupled effectively with traditional statistical methods to reduce the probability of decisions which impose unnecessary risks on the environment or costs to industry.     

A framework for assessment and monitoring of arthropods in a lowland tropical forest

By applying principles of adaptive management, and by using the valuable information that arthropods provide from assessment and monitoring programs, managers can identify and reduce possible impacts on biodiversity in development projects. In 1996, the Smithsonian Institution's Monitoring and Assessment of Biodiversity program worked together with Shell Prospecting and Development Peru to establish an adaptive management program to protect biodiversity in a natural gas exploration project in a Peruvian rainforest. In this paper, we outlined the conceptual steps involved in establishing an assessment and monitoring program for arthropods, including setting objectives, evaluating the results and making decisions. We also present the results of the assessment using some of groups of arthropods, and summarize the steps taken to identify appropriate groups for monitoring.     

Adapting forest health assessments to changing perspectives on threats—a case example from Sweden

A revised Swedish forest health assessment system is presented. The assessment system is composed of several interacting components which target information needs for strategic and operational decision making and accommodate a continuously expanding knowledge base. The main motivation for separating information for strategic and operational decision making is that major damage outbreaks are often scattered throughout the landscape. Generally, large-scale inventories (such as national forest inventories) cannot provide adequate information for mitigation measures. In addition to broad monitoring programs that provide time-series information on known damaging agents and their effects, there is also a need for local and regional inventories adapted to specific damage events. While information for decision making is the major focus of the health assessment system, the system also contributes to expanding the knowledge base of forest conditions. For example, the integrated monitoring programs provide a better understanding of ecological processes linked to forest health. The new health assessment system should be able to respond to the need for quick and reliable information and thus will be an important part of the future monitoring of Swedish forests.     

Statistical Issues for Monitoring Ecological and Natural Resources in the United States

The United States funds a number of national monitoring programs to measure the status and trends of ecological and natural resources. Each of these programs has a unique focus; the scientific objectives are different as are the sample designs. However, individuals and committees, all well aware of the cost of ecological monitoring, have called for more effective monitoring programs. The objective of this paper is to summarize existing programs' statistical designs and discuss potential alternatives for improvement in national monitoring. Can we improve the current situation by providing an overall framework for the design or analysis of data from these disparate surveys? First, the paper summarizes the objectives of these surveys, compares and contrasts their survey designs as currently implemented, and determines what variables they collect. Through this process we identify commonalities and issues that impact our ability to combine information across one or more of the surveys. Three potential alternatives are presented, leading to comprehensive monitoring in the United States.     

Choosing how to choose: Comparing amalgamation methods for environmental impact assessment

Amalgamation, in which disparate impacts are combined so that alternatives can be ranked, has become an important part of many impact assessments. Such methods can help make decisions more rational by systematically combining great amounts of information into more digestible forms. They can also facilitate public participation and ease documentation of decisions. The intent of this article is to give an overview of amalgamation methods and to propose four criteria for choosing among them: the purpose to be served, ease of use, validity, and results compared to other methods. Because experiments have repeatedly shown that the method chosen can significantly affect what decision is made, EIA practitioners should place more emphasis on the last two criteria than they have in the past. Finally, recent results in psychology and management science are discussed for practitioners facing the question “how do we choose how to choose?”     

A framework for guiding sustainability assessment and on-farm strategic decision making

Responding to future challenges and societal needs, various actions are taken in agriculture to evolve towards more sustainable farming practices. These actions imply strategic choices and suppose adequate sustainability assessments to identify, measure, evaluate and communicate sustainable development. However, literature is scarce on the link between strategic decision making and sustainability assessment. As questions emerge on how, what and when to measure, the objective of this paper is to construct a framework for guiding sustainability assessment and on-farm strategic decision making. Qualitative research on own experiences from the past and a recent project revealed four categories of actual needs farmers, advisors and experts have regarding sustainability assessment: context, flexibility, focus on farm and farmer and communication. These stakeholders' needs are then incorporated into a two-dimensional framework that marries the intrinsic complexity of sustainability assessment tools and the time frame of strategic decision making. The framework allows a farm-specific and flexible approach leading to harmonized actions towards sustainable farming. As this framework is mainly a procedural instrument to guide the use of sustainability assessment tools within strategic decision making, it fits to incorporate, even guide, future research on sustainability assessment tools themselves and on their adoption on farms.     

Impact significance determination—Back to basics

Impact significance determination is widely recognized as a vital and critical EIA activity. But impact significance related concepts are poorly understood. And the quality of approaches for impact significance determination in EIA practice remains highly variable. This article seeks to help establish a sound and practical conceptual foundation for formulating and evaluating impact significance determination approaches.It addresses the nature (what is impact significance?), the core characteristics (what are the major properties of significance determination?), the rationale (why are impact significance determinations necessary?), the procedural and substantive objectives (what do impact significance determinations seek to achieve?), and the process for making impact significance judgments (how is impact significance determination conducted?). By identifying fundamental attributes and key distinctions associated with impact significance determinations, a basis is provided for designing and evaluating impact significance determination procedures at both the regulatory and applied levels.     

废水中有机污染指标监测方法的选择

综合考察了废水中各种有机污染物综合指标的测试对象、干扰、准确度、精确度及其分析测试技术等各种因素 ,对实现其自动化连续测量的影响。针对某些监测技术产生的严重二次污染问题 ,提出了绿色 (清洁 )监测技术的概念。文章认为在重点废水污染源安装在线监测系统实行总量控制的过程中 ,应避免使用造成严重二次污染的 CODCr在线监测仪 ,而应当采用臭氧氧化法在线监测仪 ,或其他综合指标 ,如 TOC     

Visual techniques for the detection of water quality trends: Double-mass curves and cusum functions

There is a great need for quantitative techniques to assess changes in water quality related to progressive watershed land-use developments, water-related impoundments or to evaluate the impact of recent sanitation programs. In choosing a physically representative variate for the water quality of the run-off, both concentrations and fluxes of pollutants must be taken into account. The importance of the climatic seasonal and hydrological factors associated with unstable event-related contributions of point and non-point pollution sources of the pollutants has lead us to simultaneously study water-discharge and pollutant flux time-series. The mass-discharge time-series are, in practice, far from being ideal for the application of classical trend analysis: they are relatively short and inaccurate: their distribution, orginating from mixed parent populations is very often highly skewed; they show a high level of serial dependence and the seasonal effects represent a large percentage of the variance, concealing possible long-term trends. Faced with the poor structure of these series which prohibits the use of statistical tests, experiments have been carried out with progressive-regressive inertial techniques, which imply the stationarity of water discharges. The double-mass technique was developed originally as a visual technique, to assess the homogeneity of precipitation records and was extended to study variations in sediment transport in modified watersheds. More recently confidence ‘rails’ and slope change detection have rendered its use more quantitative. Based on the same inertial principles, the Cumulative Sum (CUSUM) functions allow simultaneous evaluation of the covariability of the two series. An example involving weekly sampled nitrate concentrations and continuously monitored water discharges is developed.     

Development of a landfill model to prioritize design and operating objectives

The application of scientifically based decision making tools to help address solid waste management issues dates back to the early 1960s. Researchers continue to use operations research tools to help optimize landfill design and operating parameters. This paper discusses the application of another type of decision making tool, the analytical hierarchy process (AHP), to address priority ranking for a number of landfill engineering design and operating objectives in developing and developed countries. In this application, the AHP is used to rank, and prioritize, economic, environmental, health and safety, legislative and public perception objectives for landfill design and operations specific to landfill distance from a community, and precipitation levels. Results from a global survey using the Delphi process are included, with a discussion on the survey’s impact on the objective rankings relative to community proximity and precipitation. The Delphi process worked extremely well, and was an excellent tool to use in this application. The initial results from the objective rankings show promise in the development of an integrated model for landfill design and operation.     

A game theory perspective on environmental assessment: What games are played and what does this tell us about decision making rationality and legitimacy?

Game theory provides a useful theoretical framework to examine the decision process operating in the context of environmental assessment, and to examine the rationality and legitimacy of decision-making subject to Environmental Assessment (EA). The research uses a case study of the Environmental Impact Assessment and Sustainability Appraisal processes undertaken in England. To these are applied an analytical framework, based on the concept of decision windows to identify the decisions to be assessed. The conditions for legitimacy are defined, based on game theory, in relation to the timing of decision information, the behaviour type (competitive, reciprocal, equity) exhibited by the decision maker, and the level of public engagement; as, together, these control the type of rationality which can be brought to bear on the decision. Instrumental rationality is based on self-interest of individuals, whereas deliberative rationality seeks broader consensus and is more likely to underpin legitimate decisions. The results indicate that the Sustainability Appraisal process, conducted at plan level, is better than EIA, conducted at project level, but still fails to provide conditions that facilitate legitimacy. Game theory also suggests that Sustainability Appraisal is likely to deliver ‘least worst’ outcomes rather than best outcomes when the goals of the assessment process are considered; this may explain the propensity of such ‘least worst’ decisions in practise. On the basis of what can be learned from applying this game theory perspective, it is suggested that environmental assessment processes need to be redesigned and better integrated into decision making in order to guarantee the legitimacy of the decisions made.     

城市间气态污染物与细颗粒物的相关性分析

通过对沿太行山脉东侧城市间环境空气污染物浓度监测数据分析发现,大气污染是一个区域性问题,相近城市间主要污染物浓度均呈高度正相关。以北京、石家庄、保定和邢台作为研究对象,对其2013年主要大气污染物浓度变化趋势进行分析对比,建立污染物浓度相关性分析模型,并对各污染因子间的相关性进行研究,得到各地区的污染物相关性结果,为区域协同控制大气污染提供决策支持。     

Holistic approach for quantification and identification of pollutant sources of a river basin by analyzing the open drains using an advanced multivariate clustering

Global scarcity of freshwater has been gearing towards an unsustainable river basin management and corresponding services to the humans. It needs a holistic approach, which exclusively focuses on effective river water quality monitoring and quantification and identification of pollutant sources, in order to address the issue of sustainability. These days, rivers are heavily contaminated due to the presence of organic and metallic pollutants released from several anthropogenic sources, such as industrial effluents, domestic sewage, and agricultural runoff. It is astonishing to note that even in many developing countries, most of these contaminants are carried through open drains, which enter river premises without proper treatment. Such practice not only devastates riverine ecosystem but also gives rise to deadly diseases, such as minimata and cancer in humans. Considering these issues, the present study develops a novel approach towards simultaneous identification of major sources of pollution in the rivers, along with critical pollutants and locations using an advanced hierarchical cluster and multivariate statistical analysis. A systematic approach has been developed by agglomerating both R-mode and Q-mode analysis, which develops monoplots, two-dimensional biplots, rotated component matrices, and dendrograms (using “SPSS” and “Analyse It” software) to reveal relationships among various quality parameters to identify the pollutant sources along with clustering of critical sampling sites and pollutants. A case study of the Ganges River Basin of India has been considered to demonstrate the efficacy and usefulness of the model by analyzing 85 open drains. Both organic and metallic pollutants are analyzed simultaneously as well as separately to get a holistic understanding of all the relationships and to broaden the perspective of water characterization. Results provide a comprehensive guidance to the policy makers and water managers to optimize corrective efforts, minimize further damage, and improve the water quality condition to ensure sustainable development of the river basin.