Undesirable specialization in the construction of composite policy indicators: The Environmental Performance Index

The non-parametric Data Envelopment Analysis approach is increasingly used to construct composite indicators for country performance monitoring, benchmarking, and policy evaluation in a large variety of fields. The flexibility in the definition of aggregation weights is praised as the method's most important advantage: DEA allows each evaluated country to look for its own optimal weights that maximize the composite indicator relative to the other countries. However, this flexibility also carries a potential disadvantage as it may allow countries to appear as a brilliant performer in a manner that is hard to justify: by ignoring or overemphasizing one or multiple of the judiciously selected performance indicators. To illustrate this issue of undesirable specialization in DEA-based evaluations, this paper compares the Environmental Performance Index (EPI) as computed by the optimistic and pessimistic version of the DEA-model as proposed by Zhou et al. (2007). Based on both computed composites, undesirable specialization in performance is identified.     

Modelling the Valuesphere and the Ecosphere:

Methods for Life Cycle Impact Assessment have to cope with two critical aspects, the uncertainty in values and the (unknown) system behaviour. LCA methodology should cope explicitly with these subjective elements. A structured aggregation procedure is proposed that differentiates between the technosphere and the ecosphere and embeds them in the valuesphere. LCA thus becomes a decision support system that models and combines these three spheres. We introduce three structurally identical types of LCA, each based on one coherent but different set of values. These sets of values can be derived from the Cultural Theory and are labeled as ‘egalitarian’, ‘individualistic’, and ‘hierarchic’. Within Life Cycle Impact Assessment, a damage oriented assessment model is complemented with both a newly developed precautionary indicator designed to address unknown damage and an indicator for the manageability of environmental damages. The indicators for unknown damage and for manageability complete the set of indicators judged to be relevant by decision makers. The weights given to these indicators are also value-dependent. The framework proposed here answers the criticisms that present LCA methodology does not strictly enough separate subjective from objective elements and that it fails to accurately model environmental impacts.     

Modelling the valuesphere and the ecosphere: Integrating the decision makers’ perspectives into LCA

Methods for Life Cycle Impact Assessment have to cope with two critical aspects, the uncertainty in values and the (unknown) system behaviour. LCA methodology should cope explicitly with these subjective elements. A structured aggregation procedure is proposed that differentiates between the technosphere and the ecosphere and embeds them in the valuesphere. LCA thus becomes a decision support system that models and combines these three spheres. We introduce three structurally identical types of LCA, each based on one coherent but different set of values. These sets of values can be derived from the Cultural Theory and are labeled as ‘egalitarian’, ‘individualistic’, and ‘hierarchic’. Within Life Cycle Impact Assessment, a damage oriented assessment model is complemented with both a newly developed precautionary indicator designed to address unknown damage and an indicator for the manageability of environmental damages. The indicators for unknown damage and for manageability complete the set of indicators judged to be relevant by decision makers. The weights given to these indicators are also value-dependent. The framework proposed here answers the criticisms that present LCA methodology does not strictly enough separate subjective from objective elements and that it fails to accurately model environmental impacts.     

Modelling the Valuesphere and the Ecosphere: Integrating the Decision Makers' Perspectives into LCA

Methods for Life Cycle Impact Assessment have to cope with two critical aspects, the uncertainty in values and the (unknown) system behaviour. LCA methodology should cope explicitly with these subjective elements. A structured aggregation procedure is proposed that differentiates between the technosphere and the ecosphere and embeds them in the valuesphere. LCA thus becomes a decision support system that models and combines these three spheres. We introduce three structurally identical types of LCA, each based on one coherent but different set of values. These sets of values can be derived from the Cultural Theory and are labeled as ‘egalitarian’, ‘individualistic’, and ‘hierarchic’. Within Life Cycle Impact Assessment, a damage oriented assessment model is complemented with both a newly developed precautionary indicator designed to address unknown damage and an indicator for the manageability of environmental damages. The indicators for unknown damage and for manageability complete the set of indicators judged to be relevant by decision makers. The weights given to these indicators are also value-dependent. The framework proposed here answers the criticisms that present LCA methodology does not strictly enough separate subjective from objective elements and that it fails to accurately model environmental impacts.     

Sustainable tourism indicators as planning tools in cultural destinations

Sustainable tourism is being consolidated at an international level as an approach that should be used to make all types of tourism more environmentally, socially and economically beneficial. A common practice is to use an indicator system for designing and implementing tourism models that focuses on the sustainability approach. Indicators are considered as useful tools that allow tourism managers to diagnose the situation of the destination, and to identify and evaluate issues that require addressing to improve the level of sustainability of the tourist activities. However, these indicator systems usually do not provide a practical guide to establish how to interpret information and how to integrate it into the decision-making. In this paper we present an indicator system to evaluate sustainable tourism at cultural destinations. Likewise, we suggest a method based on goal programming to construct composite indicators. The definition of the indicator system and composite indicators is completed providing guidelines that establish how to use these tools in tourism sector planning. Specifically, we propose three basic practical uses for these tools: the formulation of general action plans at a regional level, the definition of short-term strategies for destinations and the establishment of destination benchmarking practices. Each practical use is illustrated using the case of cultural tourism destinations in the Andalusia region (Spain).     

植物生活史型定量划分及其权重配置方法——以四棱豆生活史型划分为例

植物生活史型定量划分方法研究是植物生活史型研究的重要内容。现有的生活史型定量划分方法是基于主成分分析法(PCA)建立起来的,未考虑性状指标之间的相互影响,因此需要探索适用于"网状"结构指标体系的植物生活史型划分新方法。根据植物生活史型划分指标的层次性特点,以攀援型和矮生型四棱豆(Psophocarpus tetragonolobus)为例,分别采用主成分分析法(PCA)、层次分析法(AHP)和网络层次分析法(ANP)对性状指标进行权重配置,计算性状指标的综合得分和生活史型划分参数,结果如下:与ANP相比,PCA计算的V型(营养生长型)参数值偏低(x在0.39以下),S型(有性生殖型)参数值偏高(z在0.453以上);AHP计算的V型参数值偏高(x在0.614以上),S型参数值偏低(z在0.088以下);3种方法计算的生活史型划分参数差异明显。由于PCA、AHP均要求性状指标之间相互独立,不能排除性状指标之间的关联,因此基于PCA、AHP的四棱豆生活史型划分结果均出现了偏差,表明性状指标之间的相关性影响了生活史型划分结果。ANP的指标体系为"网状"结构,其控制层、网络层各个指标之间均存在关联。构建ANP的判断矩阵时提取了性状指标的相关矩阵信息,权重配置反映了性状指标之间的相关关系。基于ANP方法对攀援型和矮生型四棱豆生活史型的划分结果分别为V0.517C0.327S0.156和V0.416C0.43S0.154。当性状指标之间的相关不显著时,可采用PCA和AHP法分配权重;当性状指标之间存在显著相关时,采用ANP法进行权重配置更为恰当。综上所述,基于ANP的植物生活史型划分方法解决了性状指标之间相互影响问题,为植物生活史型定量研究提供了新的有效方法。     

The quantitative research of composite immune indicator for crustacean

Through analyzing the immunity indicators in recent crustacean research, two defects are pointed in comprehensive immunity evaluation, 1) the integrant indicators cannot comprehensively reflect the change of immunity, and 2) the conclusions that obtained from different indicators of immunity level cannot be compared objectively and scientifically. Basing on that, the paper firstly indicated that the immunity system could be regarded as a composite indicator. Secondly, the paper gave the specific definition of the composite immunity indicator (CII), and discussed the methods of calculation, especially provided two calculation methods of the weights, that is, the Analytic Hierarchy Process (AHP) and the Principal Component Analysis (PCA). Finally, examples were given to clarify the specific steps to compute the composite immunity indicator. The computing results gave the quantitative evaluation, which were in concordance with the existing conclusions.     

Integrated municipal waste management systems: An indicator to assess their environmental and economic sustainability

Tools based on Life Cycle Thinking (LCT) are routinely used to assess the environmental and economic performance of integrated municipal solid waste (MSW) management systems. Life Cycle Assessment (LCA) is used to quantify the environmental impacts, whereas Life Cycle Costing (LCC) allows financial and economic assessments. These tools require specific experience and knowledge, and a large amount of data.The aim of this project is the definition of an indicator for the assessment of the environmental and economic sustainability of integrated MSW management systems. The challenge is to define a simple but comprehensive indicator that may be calculated also by local administrators and managers of the waste system and not only by scientists or LCT experts.The proposed indicator is a composite one, constituted by three individual indicators: two of them assess the environmental sustainability of the system by quantifying the achieved material and energy recovery levels, while the third one quantifies the costs. The composite indicator allows to compare different integrated MSW management systems in an objective way, and to monitor the performance of a system over time.The calculation of the three individual indicators has been tested on the integrated MSW management systems of the Lombardia Region (Italy) as well as on four of its provinces (Milano, Bergamo, Pavia, and Mantova).     

A quantitative indicator framework for stand level evaluation and monitoring of environmentally sustainable forest management

An indicator framework was designed as an operational science-based tool for the evaluation of the environmental aspects of sustainable forest management at stand level in Flanders (Belgium). The framework aims to assess the effects of forest management on forest composition, structure and functioning. It consists of seven principles and 19 criteria, to which 157 potential indicators, selected from literature, were assigned; 40 of these were considered as suitable by an expert panel, based on 10 operational selection criteria. All indicators were quantitative variables measurable in the field.After elaboration of a measurement protocol, the indicator framework was validated in 115 forest stands, distributed over the three main forest types of Flanders. The new indicator framework exhibited greater sensitivity to forest management practices and demonstrated better discriminating power than the method that is currently used by the Flemish forest administration to estimate the naturalness and environmental quality of a forest stand. Following a detailed cost calculation of each indicator and based on the sensitivity of each indicator to forest management practices, the indicator framework was further reduced to a final set of 29 indicators. This framework can also be applied in other regions, provided that local threshold values are defined to convert indicator values to indicator scores.The selection procedure and the possible contribution of this set to the forest management in Flanders are discussed.     

Sustainability indicator systems within urban governance: Usability analysis of sustainability indicator systems as boundary objects

While sustainability indicator systems (SIs) have proven to be valuable rational tools for improving the availability of information related to the relationship of cities and communities to natural limits, the indicators movement has achieved limited instrumental uptake in policy. This paper begins from a recognition that instrumental use of sustainability indicator systems is rare. Greater potential impact exists for SIs designed to be much more attentive to their conceptual and political values within their particular social and political context. In other words, greater attention to what has been called the governance of indicator systems, or the ways in which SIs fit as policy tools within a multilevel and multiactor governance context, is key to increasing their utility. This is particularly true given the need for decisive policy change, or even the introduction of a new development path, which is asserted within the sustainability agenda.Understanding the real and potential utility of indicator systems within multiactor governance processes, in which their roles are primarily rhetorical, conceptual and political, is facilitated by thinking about indicator systems as boundary objects, tools which open up dialogue, information sharing, learning and consensus-building across different policy boundaries: between experts and nonexperts, formal government and different nongovernment actors, higher-order governments and lower-order governments. This paper offers a comparative analysis of three sustainability indicator systems in the North American context – Vancouver's Vital Signs (Vancouver Foundation), Seattle's Happiness Initiative, and LEED-ND (US Green Building Council) – all of which have shown some success in operationalizing a new policy boundary as a means of making conceptual and political contributions to governance practices. The specific boundaries operationalized, the different approach taken by each project, and the usability demonstrated by each project at that boundary in terms of salience, legitimacy and credibility, are assessed comparatively. In general, the trajectory in design and use of ecological and sustainability indicators demonstrates an increase in appetite, aptitude and numbers of channels for use in processes of governance; however, these factors vary with the local social–political opportunity structure. This analysis presents the advances made as well as the tradeoffs evident in these cases across the gamut of different forms of usability of nongovernmental indicator systems designed for use as boundary objects, and suggests a path forward for indicator work which aims to change policy, from a governance perspective.     

The Austrian Forest Biodiversity Index: All in one

Forest biodiversity cannot be measured and monitored directly. Indicators are needed to tackle this task and must be based on scientifically valid relationships concerning different levels of biodiversity. In addition, indicators must provide tangible goals for forest policy and other relevant stakeholders. Here, we propose a single aggregated measure – the Austrian Forest Biodiversity Index (AFBI) – which is composed of different indicator values being weighed depending on their significance for the maintenance of forest species richness and genetic diversity. The AFBI consists of nine state and four response indicators. Selection of state indicators was based on the general hypothesis that forests which mimic natural conditions or are characterised by structural elements of old-growth forests maintain a high number of forest dependent species and a high genetic richness therein. Among the response indicators we considered the establishment of natural forest reserves, genetic reserve forests, seed stands and seed orchards as most relevant. Proposed operational tools, especially for state indicators, are mainly based on the Austrian forest inventory. The sum of all weighted indicator measures is rescaled as a total score that may vary from 0 to 100, so that the AFBI is simple to communicate and straightforward to apply. The AFBI gives certain weight to genetic parameters which are often neglected in previous approaches.     

A PCA-based method for construction of composite sustainability indicators

Purpose

Sustainable manufacturing is practiced globally as a comprehensive strategy for improving the sustainability performance of the manufacturing industry. While sustainability is characterized into such three dimensions as economic, environmental, and social, currently, there is no quantitative method yet to measure the so-called ??sustainability?? in the manufacturing industry. The objective of this research is to develop a comprehensive and effective quantitative method to measure the overall sustainability performance of manufacturing companies.

Methods

In this paper, an integrated methodology is presented for the development of composite sustainability indicators based on principal component analysis (PCA). In developing this integrated approach, both industry and academia surveys are conducted to identify what sustainability indicators are favored by the sustainable manufacturing community. A unique index is then generated to measure the overall sustainability performance of industrial practices. The methodology can be used for benchmarking the overall sustainability performance of various manufacturing companies.

Results

A case study is conducted on a total of 11 global electronic manufacturing companies. The overall sustainability performance of these companies are measured, benchmarked, and ranked. The results showed that PCA is an effective approach for constructing composite sustainability indicators across environmental, economic, and social dimensions.

Conclusions

From this research, it is found that industry and academia have different views on the sustainability measurement, evidenced by different weights put on the same indicator in industry and academia. The case study demonstrated that the methodology presented in this paper is an effective tool for comprehensive measurement of sustainability performance of manufacturing companies. Strengths and weaknesses of each company can be identified. Then, the recommended improvements can be suggested based on the study of each of the individual indicators.     

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.     

Multiple Citation Indicators and Their Composite across Scientific Disciplines

Many fields face an increasing prevalence of multi-authorship, and this poses challenges in assessing citation metrics. Here, we explore multiple citation indicators that address total impact (number of citations, Hirsch H index [H]), co-authorship adjustment (Schreiber Hm index [Hm]), and author order (total citations to papers as single; single or first; or single, first, or last author). We demonstrate the correlation patterns between these indicators across 84,116 scientists (those among the top 30,000 for impact in a single year [2013] in at least one of these indicators) and separately across 12 scientific fields. Correlation patterns vary across these 12 fields. In physics, total citations are highly negatively correlated with indicators of co-authorship adjustment and of author order, while in other sciences the negative correlation is seen only for total citation impact and citations to papers as single author. We propose a composite score that sums standardized values of these six log-transformed indicators. Of the 1,000 top-ranked scientists with the composite score, only 322 are in the top 1,000 based on total citations. Many Nobel laureates and other extremely influential scientists rank among the top-1,000 with the composite indicator, but would rank much lower based on total citations. Conversely, many of the top 1,000 authors on total citations have had no single/first/last-authored cited paper. More Nobel laureates of 2011–2015 are among the top authors when authors are ranked by the composite score than by total citations, H index, or Hm index; 40/47 of these laureates are among the top 30,000 by at least one of the six indicators. We also explore the sensitivity of indicators to self-citation and alphabetic ordering of authors in papers across different scientific fields. Multiple indicators and their composite may give a more comprehensive picture of impact, although no citation indicator, single or composite, can be expected to select all the best scientists.     

The hydrodynamic radii of macromolecules and their effect on red blood cell aggregation

The effects of nonionic polymers on human red blood cell (RBC) aggregation were investigated. The hydrodynamic radius (Rh) of individual samples of dextran, polyvinylpyrrolidone, and polyoxyethylene over a range of molecular weights (1,500-2,000,000) were calculated from their intrinsic viscosities using the Einstein viscosity relation and directly measured by quasi-elastic light scattering, and the effect of each polymer sample on RBC aggregation was studied by nephelometry and low-shear viscometry. For all three polymers, despite their different structures, samples with Rh <4 nm were found to inhibit aggregation, whereas those with Rh >4 nm enhanced aggregation. Inhibition increased with Rh and was maximal at approximately 3 nm; above 4 nm the pro-aggregant effect increased with Rh. For comparison, the Rh of 12 plasma proteins were calculated from literature values of intrinsic viscosity or diffusion coefficient. Each protein known to promote RBC aggregation had Rh >4 nm, whereas those with Rh <4 nm either inhibited or had no effect on aggregation. These results suggest that the influence of a nonionic polymer or plasma protein on RBC aggregation is simply a consequence of its size in an aqueous environment, and that the specific type of macromolecule is of minor importance.     

Methodological challenges in assessing the environmental status of a marine ecosystem: case study of the Baltic Sea

Assessments of the environmental status of marine ecosystems are increasingly needed to inform management decisions and regulate human pressures to meet the objectives of environmental policies. This paper addresses some generic methodological challenges and related uncertainties involved in marine ecosystem assessment, using the central Baltic Sea as a case study. The objectives of good environmental status of the Baltic Sea are largely focusing on biodiversity, eutrophication and hazardous substances. In this paper, we conduct comparative evaluations of the status of these three segments, by applying different methodological approaches. Our analyses indicate that the assessment results are sensitive to a selection of indicators for ecological quality objectives that are affected by a broad spectrum of human activities and natural processes (biodiversity), less so for objectives that are influenced by a relatively narrow array of drivers (eutrophications, hazardous substances). The choice of indicator aggregation rule appeared to be of essential importance for assessment results for all three segments, whereas the hierarchical structure of indicators had only a minor influence. Trend-based assessment was shown to be a useful supplement to reference-based evaluation, being independent of the problems related to defining reference values and indicator aggregation methodologies. Results of this study will help in setting priorities for future efforts to improve environmental assessments in the Baltic Sea and elsewhere, and to ensure the transparency of the assessment procedure.     

An analytic framework for social life cycle impact assessment—part 1: methodology

Purpose

This study aims to develop a new framework of social life cycle impact assessment (SLCIA) method based on the United Nations Environment Program/Society of Environmental Toxicology and Chemistry (UNEP/SETAC) Guidelines for analyzing the social impact in Taiwan, particularly in the electronics industry.

Methods

After reviewing the literature on social life cycle assessment (SLCA), we analyzed existing case studies and developed SLCIA methods based on the UNEP/SETAC Guidelines. We thereafter identified stakeholders, subcategories, and indicators in accordance with the current status of SLCA case studies and opinions from ten experts in the Taiwanese electronics industry. Both quantitative and semi-quantitative indicators were subsequently proposed to assess the social impact of workers in the Taiwanese electronics sector. Each indicator was given the score of 1 to 5 by classifying the social impact percentage of nine scales. To formulate an analytic framework for SLCIA, the weighting values of each subcategory and indicator were determined using the consistent fuzzy preference relations (CFPR) method.

Results and discussion

Seven subcategories and 19 qualitative and quantitative indicators of worker stakeholders for the electronics sector were identified based on the UNEP/SETAC Guidelines. A score of 1 to 5 is assigned to each quantitative indicator by classifying the social impact percentage of nine scales. The data obtained from companies for each quantitative indicator were subsequently transformed into social impact percentage in terms of the statistical data on social situations at the country or industry level. With regard to semi-quantitative indicators, three implementation levels of management efforts on social performance within five elements were identified. The CFPR method was then employed to determine the weights of each indicator by ten experts. Results indicated that preventing forced work practices, protecting children from having to work, and providing minimum and fair wages for workers are the three most important indicators for assessing social impact.

Conclusions

A new SLCIA method that incorporates both quantitative and semi-quantitative indicators was proposed for assessing social impact in the electronics sector in Taiwan. Nine quantitative indicators can be easily organized using available social data from government statistics as performance reference points (PRPs) to determine the social impact exerted by companies. The relative weights were determined to allow for an impact assessment and thus solve the limitation of their currently assumed equal weights. The proposed framework is examined to analyze the social impact of three production sites for semiconductor packaging and manufacturing in Taiwan.

     

Robustness and sensitivity of weighting and aggregation in constructing composite indices

A composite index is a combination of various sources of information known as indicators, measured in or of a system in order to provide a summary of the system that is itself not directly measurable. For the index to be useful and meaningful, its construction requires careful consideration of several important aspects of the potentially disparate and multiple indicators that help convey its meaning. In general there are five key steps that should be considered when constructing a composite index, one of which is how the indicators should be weighted and aggregated to form the index. This step is critical in index construction, yet there seems to be no documented evidence about making objective weighting and aggregation choices in constructing indices so that they are robust. This sort of evidence would be particularly helpful for deciding whether any of the existing indices for assessing stream health would suffice for assessing the health of a given set of stream data or whether developing a new index is warranted. Thus we designed a simulation study to test the robustness and sensitivity of the weighting and aggregation choices in four existing stream health indices. The four indices mainly differed in their choices of standardization and weighting and aggregation techniques. The three main general conclusions about these existing approaches are the recommendation to use bootstrapping to approximate the distribution of the stream health index; the standardization technique employed should use all of the available indicators; and the use of reference (or pristine) sites as a standardization tool is not essential. Since the study is based on artificial data, the findings should be applicable and relevant to indices in other fields of study such as economics, social sciences, finance and medicine.     

Using the natural capital index framework as a scalable aggregation methodology for regional biodiversity indicators

There is an increasing need for aggregated biodiversity indicators to inform policy decisions at all levels from local to global. Despite their similar policy goals, low-level (e.g. local, regional) and high-level (e.g. continental, global) indicator development is generally performed independently, and the resulting indicators are often incompatible both in their structure and data requirements. In this paper we focus on a particularly flexible aggregation framework originally developed for global assessments, the Natural Capital Index. We show that with the use of appropriate fine-scale data, the NCI framework can be applied in low-level policy contexts as well. To support this statement, we show that several established low-level indicators are essentially conforming to the NCI framework, and can be seen as existing low-level NCI implementations. The concept is illustrated with an implementation for Hungary, and the potential advantages and shortcomings of low level NCI implementations are discussed. NCI-based low level indicators can be implemented in any region, where a local indicator of ecological quality is systematically surveyed. Given the recent surge in monitoring activities worldwide, fuelled by global change and reporting obligations, fine-scale NCI implementations can become important additions to existing ecological state indicators useful in a wide range of local and regional policy contexts.     

Using a Gulf of Mexico Atlantis model to evaluate ecological indicators for sensitivity to fishing mortality and robustness to observation error

This work provides a formal evaluation of 25 ecological indicators highlighted by the Southeast Fisheries Science Center’s IEA program as useful for tracking ecosystem components in the Gulf of Mexico. Using an Atlantis ecosystem model as an operating model, we select indicators that are quantifiable using simulation outputs and evaluate their sensitivity to changes in fishing mortality. Indicator behavior was examined using a multivariate ordination. The ordination is used to tell how well each indicator describes variation in ecosystem structure (termed ‘importance’) under different levels of fishing mortality and to reveal redundancies in the information conveyed by indicators. We determine importance using sample data from the operating model, with and without observation error added. Indicators whose importance is diminished least by error are considered robust to observational error. We then quantify the interannual noise of each indicator, where annual variability relates to the required sampling frequency in a management application. Red snapper biomass, King mackerel biomass and Reef fish catch ranked in the top 5 most important without error scenarios, and King mackerel biomass and Species richness were in the top 5 most important even after error was added. Red snapper biomass was consistently found to be the most important and most robust among fishing mortality scenarios tested, and all 4 of these indicators were found to have low levels of interannual noise suggesting that they need to be sampled infrequently. Our results provide insight into the usefulness of these indicators for fisheries managers interested in the impacts of fishing on the ecosystem.