An overview of sustainability assessment methodologies

Sustainability indicators and composite index are increasingly recognised as a useful tool for policy making and public communication in conveying information on countries and corporate performance in fields such as environment, economy, society, or technological improvement. By visualizing phenomena and highlighting trends, sustainability indicators simplify, quantify, analyse and communicate otherwise complex and complicated information.There are number of initiatives working on indicators and frameworks for sustainable development (SD). This article provides an overview various sustainability indices applied in policy practice. The paper also compiles the information related to sustainability indices formulation strategy, scaling, normalisation, weighting and aggregation methodology.     

Uncertainty and sensitivity analysis of West Java Water Sustainability Index – A case study on Citarum catchment in Indonesia

Water sustainability indices have been recently used to measure the sustainability of water resources within a catchment. Developing a sustainability index involves various steps, some of which have uncertainties associated with them. For the recently developed West Java Water Sustainability Index (WJWSI), three sources of uncertainties were identified, namely uncertainties in the thresholds of non-categorical indicators and sub-indicators, in the weighting schemes, and in the aggregation methods. This paper presents the uncertainty and sensitivity analysis of WJWSI, based on the application of WJWSI to Citarum catchment in West Java, Indonesia. The results of the uncertainty analysis, measured by the coefficient of variation of the thresholds and the sub-indices, indicates that minimum thresholds of Land Use Changes, Coverage, Education, Poverty, Health Impact and Sanitation, and the maximum threshold of Water Quality have higher variation when compared to variation of the other thresholds. The results of the sensitivity analysis, measured by the correlation coefficients between the final index and the thresholds, indicate that changes in the thresholds of WJWSI indicators have not significantly affected the sub-index values of most indicators and sub-indicators. The sensitivity analysis also concluded that either the equal or non-equal weighting scheme can be used for future use of the aggregation of WJWSI indicators and sub-indicators, as changes from equal to non-equal weighting scheme did not significantly affect the final index. However, it was found that the final index values were most sensitive to the aggregation method used (i.e. arithmetic and geometric methods), shown by the significant changes in the final index value when the aggregation method was changed from arithmetic to geometric. The uncertainty and sensitivity analysis presented in this study will not just assist in the efficient use of the WJWSI, but will also help undertake similar analysis for other indices.     

Comparison of methods for calculation of sustainability indices for alternative sewerage systems—Theoretical and practical considerations

City planners need practical methods to assess and compare the sustainability of different alternatives for urban infrastructure. This article presents the consequences of selecting different methods to normalize the values of sustainability indicators, and the influence of selecting different indicators and different weighting techniques. Chosen indicators represent use of resources, environment, health and safety, psycho/sociological situation. Infrastructure costs are not included in the indicators, since it is more convenient to weigh them against the sustainability indices of the different systems. All indicators are aggregated into one system index. A nature-based sewerage system is compared to a conventional system. The article demonstrates that the method used to normalize the indicators, the choice of relevant indicators and the weighting technique have considerable influence on which system is found to be the more sustainable.     

When to use what: Methods for weighting and aggregating sustainability indicators

ContextSustainability indices (SIs) have become increasingly important to sustainability research and practice. However, while the validity of SIs is heavily dependent on how their components are weighted and aggregated, the typology and applicability of the existing weighting and aggregation methods remain poorly understood.ObjectivesTo close the knowledge gap regarding when to use which weighting and aggregation methods for constructing SIs, we review the most commonly used methods for weighting and aggregating SIs, discuss their benefits and drawbacks, and suggest a process-oriented approach for choosing appropriate weighting and aggregation methods depending on research objectives.MethodsOur review synthesis was based on peer-reviewed journal articles, books, and reports by international organizations, governmental agencies, and research institutions. After carefully examining their principles, characteristics, and applications, we selected and classified the frequently used methods for indicator weighting and aggregation.ResultsWe systematically discuss the benefits and drawbacks of nine weighting methods and three aggregation methods. We propose a four-step process for choosing the most suitable weighting and aggregation methods based on: research purposes, spatial and temporal scales, and sustainability perspectives.ConclusionsIn this research, we chose the most commonly used methods for weighting and aggregating SIs and analyzed the characteristics, strengths and weaknesses of each method. We found that choosing appropriate weighting and aggregation methods for a specific sustainability assessment project is an extremely important and challenging task. To meet this challenge, we propose a process-oriented approach for properly selecting methods according to the purpose, scale and sustainability concept. This approach can facilitate the proper selection of these methods in sustainability research and practice.     

Detection of ecological change in stream macroinvertebrate assemblages using single metric,multimetric or multivariate approaches

The effects of nutrients on aquatic ecosystems are widespread and trying to understand the reaction of different response indicators is a complex issue. In this study, we used a data set of 21 stream site-samples situated in southern Sweden to assess the strength of single and multimetric indices and multivariate approaches for detecting the effects of nutrient enrichment on stream ecosystems using benthic macroinvertebrate communities. Our results showed both multimetric and multivariate approaches to be reliable tools for detecting the effects of nutrient enrichment on stream macroinvertebrate communities, superior to single metric approaches. In particular, the multimetric DJ index and the multivariate CA scores were sensitive (high coefficients of determination) to the stressor gradient and had high precision (low error). The Saprobic index was the ‘best’ of the six single metric approaches tested here. However, due to differences in the way taxa lists are managed in multimetric and multivariate approaches, we recommend that, if possible, both methods should be used in assessing the effects of nutrient enrichment of stream ecosystems.     

Composite Subsidence Vulnerability Assessment Based on an Index Model and Index Decomposition Method

The threat of damage to buildings and other infrastructures resulting from land subsidence associated with groundwater pumping in urbanized areas is an ongoing problem requiring assessment. An important goal of subsidence vulnerability assessment is to construct a composite subsidence vulnerability index (SVI) that is represented by a set of indicators that focuses on four different thematic factors: physical, social, economic, and environmental vulnerability. These indicators are evaluated on the basis of indicator selection principles and then weighted by their contribution rate to the overall index. The weights reflect different measures assigned to the township-specific conditions. A complete and composite subsidence vulnerability assessment is developed in which future vulnerability management decision-making processes can be readily made. The vulnerability assessment includes not only the construction of the SVI, which involves selecting, assigning value to, weighting, and aggregating the vulnerability indicators, but also the presentation of the SVI decomposition. Research results demonstrate that a composite subsidence vulnerability assessment method can be made by first constructing and then decomposition-presenting the overall SVI. This allows for the relative comparison of subsidence vulnerability and the identification of the main vulnerable indicators; thus providing subsidence risk, which represents an important step toward vulnerability management of water resources.     

Using the biomasses of soil nematode taxa as weighting factors for assessing soil food web conditions

We propose the use of nematode generic biomasses as weighting factors for calculation of nematode community indices. Three data sets were used to calculate the indices using guild-based weighting (i.e., fixed weighting of nematode guilds) and genus-based weighting (i.e., weighting based on the nematode generic biomasses). The genus-based weighting factors were quadratically correlated with guild-based weighting factors, but the genus-based weighting factors were highly variable within each nematode guild, indicating that important information was likely missing when guild-based weighting was used. Although variation patterns of in the indices in response to management practices and land use were often similar for the two weighting systems, they sometimes differed substantially, and the specific index values frequently differed depending on which weighting system was used. In addition, the absolute values of the indices were frequently found to be different between the two weighting systems. Based on the comparison of indices from the two systems, we found that the genus-based system was complementary rather than superior to the guild-based system. It was suggested that both weighting systems should be used for the calculation of the nematode community indices in a study in order to better distinguish the treatment effects.     

The Mixing Triangle: Correlation and Graphical Decision Support for LCA-based Comparisons

Recent developments within life-cycle impact assessment (LCIA) allow direct modeling of changes to predefined safeguard subjects that represent the environment to be protected. These changes are often expressed in a few damage indicators and calculated for each product alternative to be compared. This article analyzes the correlation among damage indicators within one specific LCIA methodology, assesses the implications of such correlation for the use of weighting methods, and proposes a method for graphically displaying choices with respect to weighting.     

Freshwater ecosystem structure–function relationships: from theory to application

1. In this issue we aimed to answer the questions: (i) under what circumstances are functional variables better than structural ones for assessing ecosystem health? and (ii) are there good indicators of change in ecological functioning along perturbation gradients?
2. Of the numerous functional indicators tested in this issue, several show a response to anthropogenic stress and could be included in assessments of ecosystem health and integrity in running waters.
3. In three of eight studies, function showed a stronger response to anthropogenic stress than structure, whereas one study showed a response in structure and not function, and four studies showed responses in both structure and function. Thus structure alone could not detect all types of impairment and functional aspects should also be included and further developed for assessing running-water ecosystem health and integrity. Functional variables may be especially useful in situations where there is a stronger response among organisms not usually included in stream assessment (e.g. fungi and bacteria) than the commonly used invertebrate, macrophytes and fish indicators.
4. Leading research questions related to the use of functional indicators in running waters include: (i) how large is natural and operator-induced variation for functional indicators? (ii) how small of an effect size (delta) can be detected using structural versus functional indicators? and (iii) how do we efficiently improve theories as well as predictive ability for functional measures to assess the effects of anthropogenic stressors?
5. To advance the use of functional indicators in applied running-water studies, we need to supplement the approach of using large-scale datasets and correlation with ecosystem manipulations.     

Remotely-sensed indicators for monitoring the general condition of “natural habitat” in watersheds: an application for Delaware’s Nanticoke River watershed

Over the past two decades there has been increasing interest in developing indicators to monitor environmental change. Remote sensing techniques have been primarily used to generate information on land use/land cover changes. The US Fish and Wildlife Service has used this technology to monitor wetland trends and recently developed a set of remotely-sensed indicators to characterize and assess trends in the integrity of natural habitat in watersheds. The indices largely focus on the extent of “natural” cover throughout a given watershed, with an emphasis on locations important to fish, wildlife, and water quality. Six indices address natural habitat extent and four deal with human-caused disturbance. A composite index of natural habitat integrity combining the habitat extent and habitat disturbance indices may be formulated to provide an overall numeric value for a watershed or subbasin. These indices facilitate comparison between watersheds (and subbasins) and assesssment of trends useful for environmental monitoring. This paper describes the indices and presents an example of their application for characterizing and assessing conditions of subbasins within Delaware’s Nanticoke River watershed.     

An algorithmic and information-theoretic approach to multimetric index construction

The use of multimetric indices (MMIs), such as the widely used index of biological integrity (IBI), to measure, track, summarize and infer the overall impact of human disturbance on biological communities has been steadily growing in recent years. Initially, MMIs were developed for aquatic communities using pre-selected biological metrics as indicators of system integrity. As interest in these bioassessment tools has grown, so have the types of biological systems to which they are applied. For many ecosystem types the appropriate biological metrics to use as measures of biological integrity are not known a priori. As a result, a variety of ad hoc protocols for selecting metrics empirically has developed. However, the assumptions made by proposed protocols have not be explicitly described or justified, causing many investigators to call for a clear, repeatable methodology for developing empirically derived metrics and indices that can be applied to any biological system. An issue of particular importance that has not been sufficiently addressed is the way that individual metrics combine to produce an MMI that is a sensitive composite indicator of human disturbance. In this paper, we present and demonstrate an algorithm for constructing MMIs given a set of candidate metrics and a measure of human disturbance. The algorithm uses each metric to inform a candidate MMI, and then uses information-theoretic principles to select MMIs that capture the information in the multidimensional system response from among possible MMIs. Such an approach can be used to create purely empirical (data-based) MMIs or can, optionally, be influenced by expert opinion or biological theory through the use of a weighting vector to create value-weighted MMIs. We demonstrate the algorithm with simulated data to demonstrate the predictive capacity of the final MMIs and with real data from wetlands from Acadia and Rocky Mountain National Parks. For the Acadia wetland data, the algorithm identified 4 metrics that combined to produce a −0.88 correlation with the human disturbance index. When compared to other methods, we find this algorithmic approach resulted in MMIs that were more predictive and comprise fewer metrics.     

Assessing Progress towards Public Health,Human Rights,and International Development Goals Using Frontier Analysis

Indicators to measure progress towards achieving public health, human rights, and international development targets, such as 100% access to improved drinking water or zero maternal mortality ratio, generally focus on status (i.e., level of attainment or coverage) or trends in status (i.e., rates of change). However, these indicators do not account for different levels of development that countries experience, thus making it difficult to compare progress between countries. We describe a recently developed new use of frontier analysis and apply this method to calculate country performance indices in three areas: maternal mortality ratio, poverty headcount ratio, and primary school completion rate. Frontier analysis is used to identify the maximum achievable rates of change, defined by the historically best-performing countries, as a function of coverage level. Performance indices are calculated by comparing a country’s rate of change against the maximum achievable rate at the same coverage level. A country’s performance can be positive or negative, corresponding to progression or regression, respectively. The calculated performance indices allow countries to be compared against each other regardless of whether they have only begun to make progress or whether they have almost achieved the target. This paper is the first to use frontier analysis to determine the maximum achievable rates as a function of coverage level and to calculate performance indices for public health, human rights, and international development indicators. The method can be applied to multiple fields and settings, for example health targets such as cessation in smoking or specific vaccine immunizations, and offers both a new approach to analyze existing data and a new data source for consideration when assessing progress achieved.     

A novel bacterial community index to assess stream ecological health

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Monitoring change in biodiversity through composite indices

The need to monitor trends in biodiversity raises many technical issues. What are the features of a good biodiversity index? How should trends in abundance of individual species be estimated? How should composite indices, possibly spanning very diverse taxa, be formed? At what spatial scale should composite indices be applied? How might change-points--points at which the underlying trend changes--be identified? We address some of the technical issues underlying composite indices, including survey design, weighting of the constituent indices, identification of change-points and estimation of spatially varying time trends. We suggest some criteria that biodiversity measures for use in monitoring surveys should satisfy, and we discuss the problems of implementing rigorous methods. We illustrate the properties of different composite indices using UK farmland bird data. We conclude that no single index can capture all aspects of biodiversity change, but that a modified Shannon index and the geometric mean of relative abundance have useful properties.     

The invertebrate species index (ISI) for streams in southeast Queensland,Australia

The invertebrate species index (ISI) is a new biotic index to assess stream health in southeast Queensland, Australia, using benthic macroinvertebrates. The index aims to refine stream monitoring, in particular for eutrophication, as nutrient input is a major stressor of streams in the region. Biotic indices previously used for the region were based on sensitivity scores for macroinvertebrate families and orders, and were valid for all streams across the continent. The ISI is based on species level and tailored to the specific traits of southeast Queensland, thus yielding an increased level of detection of biological change. This will improve monitoring of environmental impact on a regional and local scale. The ISI is a site-specific index calculated as the weighted average (WA) of species’ sensitivity scores (S₁₀), with a species-specific indicator weight (W) and the abundance (A) of each species used as weights. S₁₀ scores for 203 species of benthic macroinvertebrates ranging from 10 (species most sensitive to pollution) to 1 (tolerant of excessive pollution) were derived by means of WA regression and calibration using site scores representing an environmental impact gradient. W measures the indicator strength of the species, and was derived from the weighted standard deviation of the S₁₀. The initial site scores for the WA modeling were derived using canonical correspondence analysis (CCA) to ordinate the sites along a gradient associated with 12 abiotic variables. The data on benthic macroinvertebrates are based on 212 quantitative samples collected in wadeable freshwater streams in southeast Queensland. Two major stream types, (1) small creeks, mainly of uplands and (2) larger streams and rivers of lowlands, were recognised for the region, and for both types the ISI range representing reference condition was established. These reference conditions can be used to establish ecological quality ratios by comparing observed to expected indices and to define ecological quality classes. The ISI is the first biotic index for streams in Australia that uses sensitivity scores and indicator weights for macroinvertebrate species. There is a growing trend in Australia to identify stream macroinvertebrates to species level and to study their specific traits and ecological requirements. The reasons for this are manifold; assessing and monitoring stream health is only one of them. For most regions of Australia, no common ground exists, so far, on how to use species data for stream health assessment. The new biotic index fills this gap for southeast Queensland in providing a standard for the use of species level data in stream health assessment.     

河流水质的景观组分阈值研究进展

土地利用/覆被变化产生的区域生态环境负面效应已引起国内外研究者的广泛关注,其中,河流水质对景观组分变化的响应已在区域及更大尺度的研究中,成为热点。探讨河流水质的景观组分阈值,可以弥补非点源污染研究在区域尺度上的景观变化影响水质问题研究中的不足,而这是当前流域水环境管理及土地利用规划与管理的主要依据之一。从景观组分指数与水质指标出发,分析了当前研究的常用指标,认为:具有明确物理意义的景观组分指数,如不透水表面指数、植被指数等,受到水质的景观组分阈值研究的青睐;在水质指标中,水化学指标应用最为广泛,同时,表征水生生态系统条件的如生物类指标、综合生物类与非生物类指标,也逐渐受到重视,方兴未艾。尽管河流水质的景观组分阈值是当前的研究重点,但在区域以及更大尺度上,阈值的差异较大。在今后的研究中,水质退化的景观组分阈值还需在研究尺度、水质指标及阈值标准等问题上进一步深化,而景观格局指数的应用将会促进对水质退化受景观组分空间配置影响的研究。对水质的景观组分阈值研究进行综述,可以为区域尺度上开展水质保护、流域水环境管理及土地利用规划提供前沿信息。     

Indexing variability: A case study with climate change impacts on ecosystems

We developed a methodology to index statistical changes in the variance of ecological measures over time. While ecological indicators are used to assess ecosystem health, vulnerability, risk and damage to ecosystems, their primary focus has been on changes to the mean of the ecological state or process. Little work has been done on incorporating variability into ecological indices. The methodology developed here is based on the Modified Levene's test of variance and a moving block where an initial time period (block) of ecosystem behavior is compared to the moving block. This allows for the detection of not only shifts in variance but also the magnitude of the shift on a continuous basis. Our results compared well with the benchmarked results from the Centered Cumulative Sum of Squares Algorithm (CUSUM) for detection of variance changes in fixed time series. The output from this methodology is a continuous stream of parameters (significant variance shift, magnitude of the shift, and the direction of the variance shift) suitable for indexing variance or integrating into an index measuring ecosystem change. Results suggest that the block interval widths should be at least 50 and that a smoothing factor of five be used to avoid false positives. We used modeled vegetation carbon output to analyze the utility of the methodology, illustrating that different model assumptions and CO₂ regimes affect the variability of the ecological response. The degree of risk resource managers may want to explore can be altered by choices in the block length, the length of the string used to smooth variance shifts, the assumption that the initial period has constant variance and the alpha levels used to determine statistical significance.     

Three-Dimensional Framework of Vigor,Organization, and Resilience (VOR) for Assessing Rangeland Health: A Case Study from the Alpine Meadow of the Qinghai-Tibetan Plateau,China

Rangeland health assessments play an important role in providing qualitative and quantitative data about ecosystem attributes and rangeland management. The objective of this study is to test the feasible of a modified model and visualize the health in a three-dimensional model. A modified Costanza model was employed, and eight indicators, including the biomass, biodiversity, and carrying capacity [associated with the vigor, organization, and resilience (VOR)] were applied. An entropy method was also developed to calculate the weight of each indicator, and a three-dimensional framework was applied to visualize the indicators and health index. The conceptual model was demonstrated using data from a case study on the alpine rangeland of the Qinghai-Tibetan Plateau, one of the globally important grassland biomes being severely degraded by natural and human factors. The health indices of four grassland plots at different levels of degradation were calculated using a modified approach to measuring their VOR. The results indicated that the least disturbed plot was relatively healthy compared to the other plots. In addition, the health indices presented in the three-dimensional VOR framework decreased in a consistent manner across the four plots along the disturbance gradients. Such rangeland health assessments should be integrated with management efforts to insure their long-term sustainable use.     

Sustainable livelihood security index in a developing country: A tool for development planning

The paper presents an overview of the existing indicators of development and positions them within the environmental, economic, and social dimensions of sustainable development. It presents empirical evidence of sustainable livelihood security index (SLSI) at the district level in Gujarat. SLSI is a composite index having three component indices, i.e. the ecological security index (ESI), the economic efficiency index (EEI), and the social equity index (SEI). It finds that the SLSI based on its simplicity and flexibility, is one of the most comprehensive yet simple indices for measuring long-term livelihood security in rural areas. For instance, the eastern districts of the state, dominated by scheduled tribes’ population have very low EEI and SEI rankings, although they have high ESI ranking. These districts also have very low ranks in gender development index, education index, health index and housing index. Thus, the SLSI not only identifies the general priorities for development but also the nature and types of policies to be pursued in each study unit to enhance livelihood security. The SLSI facilitates consensus among different partisan groups like economists, environmentalists, and egalitarians by balancing their mutual concerns, could provide guidelines for achieving sustainable development. It can function as an educational and a policy tool for promoting a holistic perspective among planners, administrators, and development workers.     

Weights and importance in composite indicators: Closing the gap

Composite indicators are very popular tools for assessing and ranking countries and institutions in terms of environmental performance, sustainability, and other complex concepts that are not directly measurable. Because of the stakes that come with the media attention of these tools, a word of caution is warranted. One common misconception relates to the effect of the weights assigned to indicators during the aggregation process. This work presents a novel series of tools that allow developers and users of composite indicators to explore effects of these weights. First, the importance of each indicator to the composite is measured by the nonlinear Pearson correlation ratio, estimated by Bayesian Gaussian processes. Second, the effect of each indicator is isolated from that of other indicators using regression analysis, and examined in detail. Finally, an optimisation procedure is proposed which allows weights to be fitted to agree with pre-specified values of importance. These three tools together give developers considerable insight into the effects of weights and suggest possibilities for refining and simplifying the aggregation. The added value of these tools are shown on three case studies: the Resource Governance Index, the Good Country Index, and the Water Retention Index.