JSEM: A Framework for Identifying and Evaluating Indicators

There are two issues in indicator development that have not been adequately addressed: (1) how to select an optimal combination of potentially redundant indicators that together best represent an endpoint, given cost constraints; (2) how to identify and evaluate indicators when the endpoint is unmeasured. This paper presents an approach to identifying and evaluating combinations of indicators when the mathematical relationships between the indicators and an endpoint may not be quantified, a limitation common to many ecological assessments. The approach uses the framework of Structural Equation Modeling (SEM), which combines path analysis withmeasurement models, to formalize available informationabout potential indicators and to evaluate their potential adequacy for representing an endpoint. Unlike traditional applications of SEM which require data on all variables, our approach – judgement-based SEM (JSEM) – can utilize expert judgement regarding the strengths and shapes of indicator-endpoint relationships. JSEM is applied in two stages. First, a conceptual model that relates variables in a network of direct and indirect linkages is developed, and is used to identify indicators relevant to an endpoint. Second, an index of indicator strength – i.e., the strength of the relationship between the endpoint and a set of indicators – is calculated from estimates of correlation between the modeled variables, and is used to compare alternative sets of indicators. The second stage is most appropriate for large, long-term assessments. Although JSEM is not a statistical technique, basing JSEM on SEM provides a structure for validating the conceptual model and for refining the index of indicator strength as data become available. Our main objective is to contribute to a rigorous and consistent selection of indicators even when knowledgeabout the ability of indicators to represent an endpoint is limited to expert judgement.     

Comparisons of Geochemical Signatures of Biotransformation of Fuel Hydrocarbons in Groundwater

Biotransformation processes play an active role in reducing the environmental impact of fuel hydrocarbon releases to groundwater. Because monitoring data at release locations are typically sparse, spatial variations in geochemical indicator parameters are often called upon as indirect evidence of biotransformation. These parameters include concentrations of electron acceptors (O₂, NO₃ ^-, SO> ₄ ^2- , reduced redox reaction by-products (Fe²⁺, Mn²⁺, CH₄), as well as bicarbonate alkalinity, pH and E_h. However, background variability in a number of these parameters complicates the task of data interpretation, particularly in the case of small data sets. In this study, correlation analyses are applied to geochemical indicator data at six hydrocarbon groundwater contamination sites in California to identify which parameters are the most reliable indicators. The results of the analyses suggest that the most direct indicators of the local redox environment – Fe²⁺, Mn²⁺, CH₄, E_h – yield the most consistent evidence of hydrocarbon biotransformation. Indicators which rely largely on mass balance – O₂, NO ₃ ^- , SO ₄ ^2- , alkalinity – appear to be less reliable. These findings may provide guidance in both the collection and interpretation of groundwater monitoring data at hydrocarbon contamination sites.     

A comparison of emission calculations using different modeled indicators with 1-year online measurements

The overall measurement of farm level greenhouse gas (GHG) emissions in dairy production is not feasible, from either an engineering or administrative point of view. Instead, computational model systems are used to generate emission inventories, demanding a validation by measurement data. This paper tests the GHG calculation of the dairy farm-level optimization model DAIRYDYN, including methane (CH₄) from enteric fermentation and managed manure. The model involves four emission calculation procedures (indicators), differing in the aggregation level of relevant input variables. The corresponding emission factors used by the indicators range from default per cow (activity level) emissions up to emission factors based on feed intake, manure amount, and milk production intensity. For validation of the CH₄ accounting of the model, 1-year CH₄ measurements of an experimental free-stall dairy farm in Germany are compared to model simulation results. An advantage of this interdisciplinary study is given by the correspondence of the model parameterization and simulation horizon with the experimental farm’s characteristics and measurement period. The results clarify that modeled emission inventories (2,898, 4,637, 4,247, and 3,600 kg CO₂-eq. cow^?1 year^?1) lead to more or less good approximations of online measurements (average 3,845 kg CO₂-eq. cow^?1 year^?1 (±275 owing to manure management)) depending on the indicator utilized. The more farm-specific characteristics are used by the GHG indicator; the lower is the bias of the modeled emissions. Results underline that an accurate emission calculation procedure should capture differences in energy intake, owing to milk production intensity as well as manure storage time. Despite the differences between indicator estimates, the deviation of modeled GHGs using detailed indicators in DAIRYDYN from on-farm measurements is relatively low (between ?6.4 % and 10.5 %), compared with findings from the literature.     

A Multivariate Analysis of Biophysical Parameters of Tallgrass Prairie Among Land Management Practices and Years

Six treatments of eastern Kansas tallgrass prairie – native prairie, hayed, mowed, grazed, burned and untreated – were studied to examine the biophysical effects of land management practices on grasslands. On each treatment, measurements of plant biomass, leaf area index, plant cover, leaf moisture and soil moisture were collected. In addition, measurements were taken of the Normalized Difference VegetationIndex (NDVI), which is derived from spectral reflectance measurements. Measurements were taken in mid-June, mid-July and late summer of 1990 and 1991. Multivariate analysis of variance was used to determine whether there were differences in the set of variables among treatments and years. Follow-up tests included univariate t-tests to determine whichvariables were contributing to any significant difference. Results showed a significant difference (p < 0.0005) among treatments in the composite of parameters during each of the months sampled. In most treatment types, there was asignificant difference between years within each month. The univariate tests showed, however, that only some variables, primarily soil moisture, were contributing to this difference. We conclude that biomass and % plant cover show the best potential to serve as long-term indicators of grassland condition as they generally were sensitive to effects ofdifferent land management practices but not to yearlychange in weather conditions. NDVI was insensitive to precipitation differences between years in July for most treatments, but was not in the native prairie. Choice of sampling time is important for these parameters to serve effectively as indicators.     

Fractionation of butyltin species during sample extraction and preparation for analysis

Solvent extraction and evaporative concentration steps are often used in procedures for the measurement of butyltins in environmental samples. As part of a larger study utilizing radiolabeled butyltins, the loss and fractionation of butyltins during sample preparation was investigated. TBT, DBT, and MBT were extracted from acidified seawater by hexane with efficiencies of about 95–99, 50–60 and 11% respectively. In addition, losses of about 70% of DBT were found during evaporative concentration of hexane. A variety of sediment extraction procedures were tested and none were found to be highly efficient for total butyltin extraction.     

Effect of El Nĩno on demographic,morphological, and chemical parameters in turtle-grass (Thalassia testudinum): an unexpected test of indicators

We examined the response of demographic, morphological, and chemical parameters of turtle grass (Thalassia testudinum), to much-higher-than-normal rainfall associated with an El Niño event in the winter of 1997–1998. Up to 20 inches of added rain fell between December 1997 and March 1998, triggering widespread and persistent phytoplankton blooms along the west coast of Florida. Water-column chlorophyll concentrations estimated from serial SeaWiFS imagery were much higher during the El Niño event than in the previous or following years, although the timing and magnitude of phytoplankton blooms varied among sites. Seagrass samples collected in 1997, 1998, and 1999 provided an excellent opportunity to test the responsiveness of Thalassia to decline and subsequent improvement of water quality and clarity in four estuaries. Using a scoring technique based on temporal responsiveness, spatial consistency, and statistical strength of indicators, we found that several morphological parameters (Thalassia shoot density, blade width, blade number, and shoot-specific leaf area) were responsive and consistent measures of light stress. Some morphological parameters, such as rhizome apex density, responded to declines and subsequent improvement in water clarity, but lacked the statistical discriminating power necessary to be useful indicators. However, rhizome sugar, starch, and the total carbohydrate concentrations also exhibited spatially and temporally consistent variation as well as statistical strength. Because changes in shoot density, as well as water clarity, affect rhizome carbohydrate levels, a composite metric based on Thalassia shoot density and rhizome carbohydrate levels together is probably more useful than either parameter alone as an indicator of seagrass health.     

Monitoring the Conservation of Grassland Habitats, Prairie Ecozone, Canada

The Prairie Ecozone contains 5% of Canada's land area and represents 16% of the Great Plains of North America. Current estimates indicate that 25–30% of original Canadian grassland habitats remain, largely concentrated in southeastern Alberta and southwestern Saskatchewan with fragments distributed throughout southern Manitoba. The size, distribution and condition of native grasslands serve as valuable indicators of the ecological integrity and the sustainability of those landscape types. With so little native grasslands remaining, areas that conserve grasslands serve as core sites for indicators such as gaps in ecosystem and wildlife habitat protection, i.e. which ecosystems are well-represented, poorly represented or have no representation. Such gap analyses helps to determine where protection efforts need to be placed in the future. Overall, about 3.5% of the Prairie Ecozone of Canada is under some form of conservation area status. This paper reports, relative to the ecoregions and political jurisdictions of the Prairie Ecozone, on the amount and distribution of various types of conservation areas and native grasslands. Relationships between the occurrence of conservation areas and grasslands are presented. Implications for conservation area planning and management are discussed within regional, national and international contexts. The issue of which characteristics of conservation areas should be assessed and monitored to address conservation objectives for sustainability is also discussed.     

Sampling of Sparse Species with Probability Proportional to Prediction

In this article, a 3P sampling (Probability Proportional to Prediction) approach is presented for surveying sparse species connected to certain types of substrates. The method uses the surveyors judgement of the probability of finding the species on a substrate as the base for selection of substrates for species inventories. The method is presented together with estimators, variances and variance estimators. The method is first presented for sampling based on all substrates in a study area and then as a subsampling technique in a two-stage design in which plots or strips are selected in a first stage. The presented approach was evaluated as a subsampling technique in a strip survey of calicioid lichen species associated with coarse broadleaf trees. In comparison with a simple random subsampling without replacement, 3P subsampling was in one study area found to be an improvement with 30–55% in terms of standard errors. The improvement was more modest in the other study area, only between 10–16%. The strip survey with 3P subsampling was more cost-efficient than a strip survey without subsampling except in one case. Based on the results in the test, 3P sampling seems to have a potential for sampling sparse species.     

Towards a Regional Index of Biological Integrity: the Example of Forested Riparian Ecosystems

Our premise is that measures of ecological indicators and habitat conditions will vary between reference standard sites and reference sites that are impacted, and that these measures can be applied consistently across a regional gradient in the form of a Regional Index of Biological Integrity (RIBI). Six principles are proposed to guide development of any RIBI: 1) biological communities with high integrity are the desired endpoints; 2) indicators can have a biological, physical, or chemical basis; 3) indicators should be tied to specific stressors that can be realistically managed; 4) linkages across geographic scales and ecosystems should be provided; 5) reference standards should be used to define target conditions; and 6) assessment protocols should be efficiently and rapidly applied. To illustrate how a RIBI might be developed, we show how four integrative bioindicators can be combined to develop a RIBI for forest riparian ecosystems in the Mid-Atlantic states: 1) macroinvertebrate communities, 2) amphibian communities, 3) avian communities, and 4) avain productivity, primarily for the Louisiana waterthrush (Seirius motacilla). By providing a reliable expression of environmental stress or change, a RIBI can help managers reach scientifically defensible decisions.     

On the estimation of phosphorus from the Niagara River to Lake Ontario

A predictive or model based approach to making inferences about the loading of a contaminant from a point source is presented and illustrated by estimating the total phosphorus, TP, loading from the Niagara River to Lake Ontario for the years 1967 to 1982. Information about explanatory variables and/or autodependence among successive observations can be easily included in the model and this allows more accurate inferences to be made. The results of the application to the Niagara River show a major decrease in TP loadings has occurred during the study period.     

Addressing statistical and operational challenges in designing large-scale stream condition surveys

Implementing a statistically valid and practical monitoring design for large-scale stream condition monitoring and assessment programs can be difficult due to factors including the likely existence of a diversity of ecosystem types such as ephemeral streams over the sampling domain; limited resources to undertake detailed monitoring surveys and address knowledge gaps; and operational constraints on effective sampling at monitoring sites. In statistical speak, these issues translate to defining appropriate target populations and sampling units; designing appropriate spatial and temporal sample site selection methods; selection and use of appropriate indicators; and setting effect sizes with limited ecological and statistical information about the indicators of interest. We identify the statistical and operational challenges in designing large-scale stream condition surveys and discuss general approaches for addressing them. The ultimate aim in drawing attention to these challenges is to ensure operational practicality in carrying out future monitoring programs and that the resulting inferences about stream condition are statistically valid and relevant.     

Detection of sulphur dioxide in the air using Scotch pine needles

Air quality is especially important in surface layers, for it is this layer that provides the living components of environment with the needed oxygen and carbon dioxide. Various air polluting gases penetrate cells affecting and contaminating them. Chloroplast shell of some pine species, for instance, doubles under the impact of carbon dioxide which is followed by tillacoids swelling and reduction.Literature provides opinions of some authors, who consider Scotch pine needle to be a biological indicator of sulphur dioxide. Others object to it basing on the observations of physiological development.The property of a Scotch pine as that of biological indicator manifests in SO₂ absorption by its needles. The analysis of total content of SO₂ in the needles shows an increase of SO₂ concentration.Sulphur in the needles is found in the form of organically bound sulphur, aminoacids, hormones as well as in the form of sulphates.Basing on our previous analysis we have generalized the data on the correlation concentrations of sulphur dioxide in the air and general concentrations of sulphur in the needles. We have supplemented the observations with the analyses of organically bound sulphur and concentrations of nonorganic sulphur. According to research data, needles contain a characteristic and rather stable quantity of organically bound sulphur.So we may state that the SO _inf4 ^sup2– concentration and the amount of SO₂ absorbed from the air are interdependent.Some authors state that SO _inf4 ^sup2– content in the soil doesn't affect sulphur content in pine needles. That is why we studied the affect of SO _inf4 ^sup2– content in the soil on sulphur content in Scotch pine needles.We could prove this statement by means of various kinds of analyses only partially. The ion transport is affected by the presence of other ions, pH and a lot of other factors.What may be said for sure is that different qualities of soils gave only minor and insignificant deviations.Hence our assumption about the SO₂ contamination from air, proved by its effect on the soils, turns to suit approximate measurements.     

Representation of the environmental quality profile of a metropolitan area

The spatially and temporally varying environmental quality of a metropolitan area is described by means of empirically derived environmental indices. The approach is based on the principles of benefit analysis and consists of a number of logical steps including the selection, the measurement and determination of the spatial distribution, and the normalization (scaling) of the selected environmental indicators. To derive composite indices, the normalized indicators are weighted, based on the Delphi technique and subsequently aggregated. The results are given by means of isopleths, including single and composite index isopleths plotted by computer on common maps.World Health Organization     

A comparison of rapid and conventional measures of indicator bacteria as predictors of waterborne protozoan pathogen presence and density

E. coli and enterococci in recreational waters are monitored as indicators of fecal contamination, pathogen presence, and health risk. Quantitative polymerase chain reaction (qPCR) tests for fecal indicator bacteria can provide beach managers with same-day information about water quality, unlike culture methods which provide that information the following day. The abilities of qPCR measurements of indicator bacteria, as compared to culture measurements of indicator bacteria, as predictors of pathogen presence or density in surface waters are not well understood. The purpose of this study was to make such comparisons between water samples collected from Chicago area surface waters, including rivers, inland lakes, Lake Michigan, and the Chicago Area Waterways System, which is dominated by wastewater effluent. A total of 294 twenty-litre samples were collected and analyzed for Giardia and Cryptosporidium. qPCR and membrane filtration methods were used to quantify E. coli and enterococci. Correlation, logistic regression, and zero-inflated Poisson modeling were utilized to evaluate associations between indicators and parasites. qPCR and culture measures of the indicator bacteria were similar in their ability to predict parasite presence and density. Correlations between parasites and indicators were generally stronger at waters not dominated by effluent. Associations between indicator density and Giarida presence were observed more consistently than between indicator density and Cryptosporidium presence. Associations between enterococci and parasites were generally stronger than associations between E. coli and parasites. The use of qPCR monitoring in our setting would generate more timely results without compromising the ability to predict parasite presence or density.     

A European Sustainable Tourism Labels proposal using a composite indicator

The tourism sector in Europe faces important challenges which it must deal with to promote its future development. In this context, the European Commission considers that two key issues must be addressed. On the one hand, a better base of socio-economic knowledge about tourism and its relationship with the environment is needed, and, on the other hand, it is necessary to improve the image of European areas as quality sustainable tourism destinations. In this paper we present analytical tools that cover these needs. Specifically, we define a system of sustainable tourism indicators and we obtain a composite indicator incorporating weights quantified using a panel of experts. Employing the values of this global indicator as a basis, we define a Sustainable Tourism Country-Brand Ranking which assesses the perception of each country-brand depending on its degree of sustainability, and a system of sustainable tourism labels which reward the management carried out.     

Statistical and nonstatistical considerations for environmental monitoring studies

In environmental studies statistics is too often used as a salvage operation, or as an attempt to show significance in the absence of any clear hypothesis. Good design is needed, not fancier statistics. Too often we pursue short-term problems that are in fashion rather than study long-term environmental deterioration that really matters. Since change-often unpredictable change-is an intrinsic part of nature, it is pointless to fight all environmental change. We must choose our level of concern and then influence environmental change where we can. The judgement on whether a given change is bad cannot be left to the statistician or to statistical tests; the politician in consultation with the ecologist are responsible for it. The statistical significance of a hypothesized impact-related change should be tested against year-to-year variation in the unimpacted situation rather than against replicate sampling error. This is another argument for long-term studies. Attributes of good design and appropriate criterion and predictor variables are discussed.Paper presented at a Symposium held on 20–21 April 1982, in Edmonton, Alberta, Canada.     

江苏省环境监测站标准化建设成效评价

江苏省在2013年底通过了国家环境监测站标准化建设整体验收,成为全国第一个整体达到国家建设标准的省份。在总结江苏省主要建设经验的基础上,为定量评估江苏省各级环境监测站标准化建设成效水平,以《国家环境监测站标准化验收评分办法》评价指标为基础,尝试构建环境监测站建设成效评价指标体系,并应用层次分析法确定指标及其权重,共设1项一级指标、5项二级指标和12项三级指标。通过专家综合决策打分,确定各项评价指标的权重值,赋值计算综合成效评价指数。结果表明,全省实验室条件、仪器设备、监测数据、论文发表、能力认证等方面发展迅速,但人员扩编有待进一步加强。该方法为政府部门考核财政资金投入绩效、优化管理决策提供了定量评价参考。     

Tropical cyclone losses in the USA and the impact of climate change — A trend analysis based on data from a new approach to adjusting storm losses

Economic losses caused by tropical cyclones have increased dramatically. Historical changes in losses are a result of meteorological factors (changes in the incidence of severe cyclones, whether due to natural climate variability or as a result of human activity) and socio-economic factors (increased prosperity and a greater tendency for people to settle in exposed areas). This paper aims to isolate the socio-economic effects and ascertain the potential impact of climate change on this trend. Storm losses for the period 1950–2005 have been adjusted to the value of capital stock in 2005 so that any remaining trend cannot be ascribed to socio-economic developments. For this, we introduce a new approach to adjusting losses based on the change in capital stock at risk. Storm losses are mainly determined by the intensity of the storm and the material assets, such as property and infrastructure, located in the region affected. We therefore adjust the losses to exclude increases in the capital stock of the affected region. No trend is found for the period 1950–2005 as a whole. In the period 1971–2005, since the beginning of a trend towards increased intense cyclone activity, losses excluding socio-economic effects show an annual increase of 4% per annum. This increase must therefore be at least due to the impact of natural climate variability but, more likely than not, also due to anthropogenic forcings.     

Impact significance determination—Designing an approach

The question of how best to go about determining the significance of impacts has, to date, only been addressed in a partial and preliminary way. The assumption tends to be made that it is either only necessary to provide explicit, justified reasons for a judgment about significance and/or to explicitly apply a prescribed procedure—a procedure usually involving the staged application of thresholds and/or criteria. The detailed attributes, strengths and limitations of such approaches and possible alternative approaches have yet to be explored systematically.This article addresses these deficiencies by analyzing the characteristics, specific methods and positive and negative tendencies of three general impact significance determination approaches—the technical approach, the collaborative approach and the reasoned argumentation approach. A range of potential composite approaches are also described. With an enhanced understanding of these approaches, together with potential combinations, EIA practitioners and other EIA participants can be in a better position to select an approach appropriate to their needs, to reinforce the positive tendencies and offset the negative tendencies of the selected approach and to combine the best qualities of more than one approach.     

The creation of an historical meteorological database for environmental dose assessment

The focus of this study is to develop wind data for the SavannahRiver Site (SRS) between 1955 and 1961 to be used in an assessment of estimates of atmospheric dispersion and downwindrisk at the Savannah River Site. In particular, a study of theuncertainties of radioiodine dosimetry from the late 1950sprovides the underlying motivation for developing historicalwindroses at the Savannah River Site (SRS). Wind measurement towers did not exist at the SRS until theearly 1970s. Three relatively simple methods were used to createa 1955–1961 meteorological database for the SRS for a dosereconstruction project. The winds were estimated from onsitemeasurements in the 1990s and National Weather Service (NWS)observations in the 1990s and 1950s using (1) a linear regressionmethod, (2) a similarity theory approach, and (3) a simplestatistical differences method. The criteria for determining success were based on (1) howwell the mean values and standard deviations of the predictedwind speed agree with the known SRS values from the 1990s, (2) the shape of the predicted frequency distribution functions forwind speed, and (3) how closely the predicted windroses resembledthe SRS windrose for the 1990s. The linear regression model's wind speed distribution functionwas broad, flat, and skewed too much toward higher wind speeds.The similarity theory approach produced a wind speed distributionfunction that contained excess predicted speeds in the range 0–1.54 m s^-1 (0–3 kts) and had `excluded' bins caused bypredictions being made from integer values of knots in the NWSdata. The distribution function from the mean difference methodwas smooth with a shape like a Weibull distribution with a shapeparameter of 2 and appearedto resemble closely the SRS 1992–1996 distribution.The wind directions for all three methods of approach weresuccessfully based on the mean difference method. It wasdifficult to discern differences among the wind roses produced bythe three methods so the wind speed distribution functions needto be examined in order to make an informed choice for dose reconstruction.