Reference Site Data Research Articles

IEA Wind Task 49: Reference Site Conditions for Floating Wind Arrays

Abstract The commercial-scale deployment of floating offshore wind (FOW) projects is expected to take place in a diverse range of sites that may differ significantly from existing fixed-bottom projects. FOW farms are particularly sensitive to the water depth and the meteorological and oceanographic (metocean) and geotechnical conditions at the project site due to the wave-induced system motions and loads as well as the anchoring system constraints imposed by the seafloor conditions. Uncertainty around the site conditions will permeate through all aspects of project design, leading to suboptimal and overly conservative designs, increased costs, and adversely affected performance. As FOW expands into a global industry, metocean and geotechnical conditions will increasingly vary for projects located in different geographic regions or in far-from-shore, deep-water sites. This study represents the outputs of work package 1 of International Energy Agency Wind Task 49, which focuses on the integrated design of floating wind arrays. The primary goal of this study is to establish the type of parameters and constraints required to characterize FOW array reference sites; provide a realistic and publicly available set of reference site conditions to the FOW community as a baseline set of data for individual research projects; identify and categorize any critical gaps in the existing data or methodologies required to define reference site characteristics; and inform and support the design of reference FOW arrays. A building block concept was developed for synthesizing reference sites for the design of FOW arrays. The building blocks include three classes of site conditions focusing on the techno-economic design of FOW projects: metocean conditions, seabed conditions, and coastal infrastructure. All reference site data produced and collected in this study are publicly available.

Mobile air quality monitoring and comparison to fixed monitoring sites for instrument performance assessment.

Air pollution monitoring using mobile ground-based measurement platforms can provide high quality spatiotemporal air pollution information. As mobile air quality monitoring campaigns extend to entire fleets of vehicles and integrate smaller scale air quality sensors, it is important to address the need for assessing these measurements in a scalable manner. We explore collocation-based evaluation of air quality measurements in a mobile platform using fixed regulatory sites as a reference. We compare two approaches - a standard collocation assessment technique where the mobile platform is parked near the fixed regulatory site for a period of time and an expanded approach using measurements while the mobile platform is in motion in the general vicinity of the fixed regulatory site. Based on the availability of fixed reference site data, we focus on three pollutants (ozone, nitrogen dioxide, and nitric oxide) with distinct atmospheric lifetimes and behaviors. We compare measurements from a mobile laboratory with regulatory site measurements in Denver, Colorado, USA and in the San Francisco Bay Area, California, USA. Our one-month Denver dataset includes both parked collocation periods near the fixed regulatory sites as well as general driving patterns around the sites, allowing a direct comparison of the parked and mobile collocation techniques on the same dataset. We show that the mobile collocation approach produces similar performance statistics, including coefficients of determination and mean bias errors, as the standard parked collocation technique. This is particularly true when the comparisons are restricted to specific road types, with residential streets showing the closest agreement and highways showing the largest differences. We extend our analysis to a larger (year-long) dataset in California, where we explore the relationships between the mobile measurements and the fixed reference sites on a larger scale. We show that using a 40-hour running median converges to within ±4 ppbv of the fixed reference site for nitrogen dioxide and ozone and up to about 8 ppbv for nitric oxide. We propose that this agreement can be leveraged to assess instrument performance over time during large-scale mobile monitoring campaigns. We demonstrate an example of how such relationships can be used during large-scale monitoring campaigns using small sensors to identify potential measurement biases.

Investigation of Inlaid Pavement Marker Performance and Safety Effectiveness

The objectives of this study were to assess inlaid pavement marker (IPM) performance and estimate their safety effectiveness in St. Louis, Missouri. IPM performance was evaluated through a count of marker presence and a feedback survey from participants who viewed dry and wet night videos of IPM sections in the St Louis area. The safety effectiveness of IPMs was evaluated using a rigorous state-of-the-art empirical Bayes (EB) before–after crash analysis. The marker presence assessment, unfortunately, did not provide any conclusive trends in IPM performance. Newer IPM sections had higher percentages of missing markers than older sections, and there were too many unknown variables to determine the source of the unexpected differences. The unanimous conclusion of the nighttime video visibility survey was that drivers and passengers traveling on a wet night feel that IPMs are very important to the visibility of the roadway’s lane lines. For the EB analysis, installation and reference site data were used to examine the effects for specific crash types, including total, fatal and injury, wet pavement, nighttime, nighttime wet pavement, lane departure, wet pavement lane departure, and nighttime lane departure. Based on the aggregate results, IPMs, when installed with pavement resurfacing, significantly reduce all crash types examined.

Small-scale field trials identify optimal habitat restoration options on exclosed nuclear sites

Degradation of cliff-top habitats due to industrial activity is infrequent, leading to unique challenges when activity ceases and a site requires remediation. Dounreay, an ex-nuclear power facility on the north coast of Scotland, is currently being decommissioned prior to complete demolition of all buildings. A small area of the site will then be covered in a 1000 mm capping layer to prevent contamination of bioreceptors at the surface from below ground contaminants. Topsoil replacement is frequently used in such instances, however, limited availability of topsoil in the region means that other materials are sought to mitigate against undesirable ecological and economic costs. We tested combinations of differentially graded rocks and topsoil to assess their suitability in supporting re-vegetation. The vegetation response was measured as richness (numbers of species), ground cover, species diversity, and biomass. Wider ecosystem function was assessed by measuring invertebrate numbers and diversity, and comparing these to locally relevant reference site data. Fine crushed rock supported native vegetation establishment and growth, though cover, diversity, and biomass (after three years) were significantly below levels found when topsoil was used instead. Initial establishment on the fine crushed rock may be limited by the low water retention and nutrient availability of the material. We suggest that a rich heterogeneous habitat able to support a wide range of native vegetation and invertebrates may be provided by mixing topsoil with the fine crushed rock in the future. This mosaic combination would also allow for significant ecological and financial cost savings (against topsoil only remediation) and could be tested on larger scales.

The Extraction of Ocean Tidal Loading from ASAR Differential Interferograms

The spatiotemporal crustal non-tectonic deformation caused by ocean tidal loading (OTL) can reach the centimeters scale in coastal land areas. The temporal variation of the site OTL displacements can be estimated by the global positioning system (GPS) technique, but its spatial variation needs to be further determined. In this paper, in order to analyze the spatial characteristics of the OTL displacements, we propose a multi-scale decomposition method based on signal spatial characteristics to derive the OTL displacements from differential interferometric synthetic aperture radar (D-InSAR) measurements. The method was tested using long-term advanced synthetic aperture radar (ASAR) data and GPS reference site data from the Los Angeles Basin in the United States, and we compared the results with the FES2014b tide model. The experimental results showed that the spatial function of the OTL displacements in an ASAR image can be represented as a higher-order polynomial function, and the spatial trends of the OTL displacements determined by the InSAR and the GPS techniques are basically consistent with the FES2014b tide model. The root-mean-square errors of the differences between the spatial OTL displacements of these two methods and the FES2014b tide model are less than 0.8 mm. The results indicate that the OTL displacement extracted from InSAR data can accurately reflect the spatial characteristics of the OTL effect, which will help to improve the spatial resolution and accuracy of the OTL displacement in coastal areas.

Assessing edge-of-field nutrient runoff from agricultural lands in the United States: How clean is clean enough?

Excess nutrient loading from numerous sources (e.g., agricultural and urban runoff, treatment plant discharge, and streambank erosion) continues to adversely impact water resources, and determination of the cause(s) of accelerated nutrient enrichment has become a contentious and litigious issue in several US regions. This paper addresses one fundamental question: What are acceptable levels of nutrients in runoff from agricultural fields? It focuses on the field scale where farmers and ranchers make management decisions. Not answering this question limits the effectiveness of on-farm management and policy alternatives to address agriculture9s contribution. To answer the question, some might suggest “direct comparison” with reference site data, existing criteria/standards, or measured data compilations. Alternatively, “indirect assessments” using soil test phosphorus (P) levels, P indices, field-scale models, or certainty programs might be suggested. Thus, to provide a scientific basis for policy debate and management decisions related to nutrient runoff from agricultural fields, we evaluated “direct comparisons” with measured data from case studies and evaluated “indirect assessment” alternatives. While acknowledging that scientific challenges and practical realities exist for each alternative, we concluded that certainty programs offer the most promise for ensuring acceptable nutrient runoff, and that field-scale models linked with watershed decision support tools are the most promising for assessing impacts on downstream water quality. Recognizing the reality that some nutrient loss is unavoidable from natural and anthropogenic sources, agriculture, industry, and municipalities are each encouraged to commit to implementing enhanced management where needed to minimize their sector9s contribution to excess nutrients in our nation9s waters.

Evaluating AUSRIVAS predictive model performance for detecting simulated eutrophication effects on invertebrate assemblages

AbstractConfidence in any bioassessment method is related to its ability to detect ecological improvement or impairment. We evaluated Australian River Assessment (AUSRIVAS)-style predictive models built using reference-site data sets from the Australian Capital Territory (ACT), the Yukon Territory (YT; Canada), and the Laurentian Great Lakes (GL; North America) area. We evaluated model performance as ability to correctly assign reference condition with independent reference-site data. Evaluating model ability to detect human disturbance is generally more problematic because the actual condition of test sites is usually unknown. Independent reference-site data underwent simulated impairment by varying the proportions of sensitive, intermediate, and tolerant taxa to simulate degrees of eutrophication. Model performance was related to differences in data sets, such as number and distribution of invertebrate taxa. Sensitive taxa tended to have lower expected probabilities of occurrence than more-tolerant taxa...

Performance of the standard CABIN method: comparison of BEAST models and error rates to detect simulated degradation from multiple data sets

The objective of this study was to evaluate the performance of 3 bioassessment models for reference data sets collected from the Australia Capital Territory (ACT), the Yukon River Basin (YT), and the Laurentian Great Lakes (GL) built following the standard Canadian Aquatic Biomonitoring Network (CABIN) method. To evaluate the models, we used validation reference-site data, which were artificially impaired to simulate 3 levels of eutrophication by varying the proportions of sensitive, intermediate, and tolerant taxa. Models correctly classified 56 to 62% of reference sites. Type 1 errors (assessing reference sites as degraded) were high for all data sets and ranged from 30 to 75%, in part because the biological communities of the validation sites extended to or beyond the range of the reference-site data used to build the models. Capturing the full range of ecological variation with adequate sample size is critical for reference-condition approach (RCA)-type models. Type 2 errors (assessing degraded sites as in reference condition) varied greatly among data sets and for each reference group within each data set. Resource managers must carefully consider the risks associated with making errors. Thus, standard methods for quality assurance of assessment models should include simulated data so that error rates and adjusted assessment thresholds can be reported to ensure that degradation can be detected and that undisturbed sites are not mistakenly subjected to unnecessary management action.

MCP방법을 이용한 장기간 풍속 및 풍력에너지 변동 특성 분석

Wind resource data of short-term period has to be corrected a long-term period by using MCP method that Is a statistical method to predict the long-term wind resource at target site data with a reference site data. Because the field measurement for wind assessment is limited to a short period by various constraints. In this study, 2 different MCP methods such as Linear regression and Matrix method were chosen to compare the predictive accuracy between the methods. Finally long-term wind speed, wind power density and capacity factor at the target site for 20 years were estimated for the variability of wind and wind energy. As a result, for 20 years annual average wind speed, Yellow sea off shore wind farm was estimated to have 4.29% for coefficient of variation, CV, and -9.57%~9.53% for range of variation, RV. It was predicted that the annual wind speed at Yellow sea offshore wind farm varied within .

Ecological response differentials: an alternative benchmark to inform stream and river bioassessment

Summary Contemporary patterns of land development mean that suitable reference sites for low‐gradient stream and non‐wadeable river biomonitoring are difficult to locate, requiring alternative approaches for benchmarking human impacts. We use two strongly harmonised macroinvertebrate data sets for wadeable streams (180 sites) and non‐wadeable rivers (30 sites) to (i) quantify metric response differentials across a regional landcover pressure gradient in northern New Zealand; (ii) interpolate reference condition for waterway types lacking comparable reference sites and (iii) inform development of narrative condition bands for data‐poor waterway types. Cumulative distribution functions of per cent waterway length indicated that near‐shore littoral samples from non‐wadeable rivers had fewer total and EPT (Ephemeroptera, Plecoptera and Trichoptera) taxa than wadeable streams, which had higher % EPT abundance and lower % Crustacea abundance. Community composition differed significantly among non‐wadeable river and wadeable hard‐bottom and soft‐bottom stream samples, reflecting factors associated with catchment altitude, slope, rainfall and landuse intensity. Ephemeroptera, Plecoptera and Trichoptera richness was the only metric evaluated that significantly reflected landcover across all waterway types. The intercept of the 60th percentile quantile regression line at 100% native vegetation cover provided the best approximation of median EPT taxa richness in an independent reference site data set for hard‐bottom streams. Applying the same interpolation to samples from soft‐bottom streams and non‐wadable rivers that lacked regional reference sites indicated median reference expectations of 9 and 11 EPT taxa, respectively, and a consistent differential across the pressure gradient relative to hard‐bottom streams of seven taxa and five taxa, respectively. The derived response differentials enabled the development of narrative bands for directly comparing ecological condition of data‐poor stream and river types. Quantification of ecological response differentials can provide an alternative means of benchmarking macroinvertebrate metrics in the absence of suitable reference sites.

Striving for consistency in a national assessment: the challenges of applying a reference-condition approach at a continental scale

One of the biggest challenges when conducting a continental-scale assessment of streams is setting appropriate expectations for the assessed sites. The challenge occurs for 2 reasons: 1) tremendous natural environmental heterogeneity exists within a continental landscape and 2) reference sites vary in quality both across and within major regions of the continent. We describe the process used to set expectations for the multimetric index of biotic integrity (MIBI) and observed/expected (O/E) indices generated from predictive models used to assess stream condition for the US Wadeable Streams Assessment (WSA). The assessment was based on a reference-site approach, in which the least-disturbed sites in each region of the US were used to establish benchmarks for assessing the condition of macroinvertebrate assemblages at other sites. Reference sites were compiled by filtering WSA sample sites for disturbance using a series of abiotic variables. Additional reference sites were needed and were obtained from other state, university, and federal monitoring programs. This pool of potential reference sites was then assessed for uniformity in site quality and comparability of macroinvertebrate sample data. Ultimately, 1625 sites were used to set reference expectations for the WSA. Reference-site data were used to help define 9 large ecoregions that minimized the naturally occurring variation in macroinvertebrate assemblages associated with continental-wide differences in biogeography. These ecoregions were used as a basis for developing MIBI and O/E indices and for reporting results. A least-disturbed definition of reference condition was used nationally, but we suspect that the quality of the best extant sites in ecoregions, such as the Northern Plains and Temperate Plains, was lower than that of sites in other ecoregions. For the MIBI assessment, we used a simple modeling approach to adjust scores in ecoregions where gradients in reference-site quality could be demonstrated conclusively. The WSA provided an unparalleled opportunity to push the limits of our conceptual and technical understanding of how to best apply a reference-condition approach to a real-world need. Our hope is that we have learned enough from this exercise to improve the technical quality of the next round of national assessments.

Comparability of biological assessments derived from predictive models and multimetric indices of increasing geographic scope

The increasing demand for tools that can score biological condition from aquatic community data has spurred the creation of many predictive models (e.g., observed/expected [O/E] indices) and multimetric indices (MMIs). The geographic and environmental scopes of these indices vary widely, and coverages often overlap. If indices developed for large environmentally heterogeneous regions provide results equivalent to those developed for smaller regions, then regulatory entities could adopt indices developed for larger regions rather than fund the development of multiple indices within a region. We evaluated this potential by comparing the performance (precision, bias, responsiveness, and sensitivity) of benthic macroinvertebrate O/E indices and MMIs developed for California (CA) with that of indices developed for 2 large-scale condition assessments of US streams: the Environmental Monitoring and Assessment Program Western Pilot Study (EMAP-West) and the western portion of the Wadeable Streams Assessment (WSA-West). WSA-West and EMAP-West O/E scores were weakly correlated with CA O/E scores, had lower precision than CA O/E scores, were influenced by 2 related natural gradients (% slope and % fast-water habitat) that did not influence CA O/E scores, and disagreed with 21 to 22% of impairment decisions derived from the CA O/E index. The WSA-West O/E index produced many fewer impairment decisions than did the CA O/E index. WSA-West and EMAP-West MMI scores were strongly correlated with the CA MMI scores. However, the WSA-West and EMAP-West MMIs produced many fewer determinations of impairment than did the CA MMI. EMAP-West and WSA-West MMIs were biased and differed in responsiveness compared with CA MMI. Thus, they might produce estimates of regional condition different from those from indices calibrated to local conditions. The lower precision of the EMAP-West and WSA-West indices compromises their use in site-specific assessments where both precision and accuracy are important. However, the magnitude of differences in impairment decisions was sensitive to the thresholds used to define impaired conditions, so it might be possible to adjust some of the systematic differences among the models to make the large-scale models more suitable for local application. Future work should identify the geographic and environmental scales that optimize index performance, determine the factors that most strongly influence index performance, and identify ways to specify accurate reference condition from geographically extensive reference-site data sets.

Metadata Development for the Integration of CEOP Satellite-Observation Data

CEOP (Coordinated Enhanced Observing Period) is currently establishing an integrated global observation system for the water and energy cycles to meet both scientific and social needs. To integrate various CEOP data such as satellite products, reference site data, and model output such as Model Output Location Time Series (MOLTS), it is necessary to exactly represent or reconstruct the geometric conditions involved in observing or acquiring the data via space-borne sensors etc. Information that contains a description or reconstruction of the observation conditions is usually represented by metadata. The standardization of metadata and imagery metadata is being undertaken by several international organizations, including ISO/TC 211. This paper reviews the present status of documents that contain metadata specifications and proposes the CEOP/ISO metadata model for the development of standardized metadata to fulfill the requirements of integrating CEOP data and to conform to metadata standards. The results are developed and presented in terms of satellite metadata, reference-site metadata, and MOLTS metadata. We also present the metadata application architecture that describes how to use these metadata to establish a data service and data discovery on a local or wide-area network for the integration of satellite observation data.

Evaluation of Surface Water and Energy Cycles in the Met Office Global NWP Model Using CEOP Data

Components of the surface water and energy balance are evaluated in the Met Office global Numerical Weather Prediction (NWP) 00-36 hour forecasts using (i) GEWEX Continental Scale Experiment (CSE) reference site data provided by the Coordinated Enhanced Observing Period (CEOP) project and (ii) other earth observing datasets from satellites and in-situ measurements. The global hydrological cycle in the model is in reasonable balance in recent model versions. However, comparison against available observations suggest that both precipitation and evaporation are overestimated over both land and ocean, with largest errors over the tropical oceans. Comparison of the model's seasonal and diurnal cycles of surface fluxes, temperature, precipitation, and moisture against the GEWEX/CEOP CSE sites during October 2002 to September 2003 reveals several issues concerning model parametrization performance. For the high latitude (Arctic) sites low cloud is overestimated during boreal winter leading to an enhanced greenhouse effect and too warm near surface temperatures in the model. Snow melt occurs too early in boreal spring in the model forecasts which currently have no snow analysis component. Possible reasons for early snow melt are discussed including the specification of albedo over heterogeneous terrain and excessive sublimation of snow in the model. The mid-latitude CEOP sites all show excessive evaporation and precipitation during boreal spring and early summer and comparison with the International Satellite Cloud Climatology (ISCCP) products show systematic under prediction of cloud cover over mid-latitude land in summer. Some of the largest biases in mid-latitude surface fluxes in summer are during daytime on non-precipitating cloudy days where the model overestimates the downward SW radiation, latent and sensible heat fluxes. Finally, over tropical land we see a tendency to underestimate precipitation which is in direct contrast to tropical oceans where precipitation accumulations are too large. We have also used the CEOP data to investigate structural errors in the vertical profiles of tropical humidity which suggest deficiencies in the convection scheme.

A null model for the expected macroinvertebrate assemblage in streams

Predictive models such as River InVertebrate Prediction And Classification System (RIVPACS) and AUStralian RIVer Assessment System (AUSRIVAS) model the natural variation across geographic regions in the occurrences of macroinvertebrate taxa in data from streams that are in reference condition, i.e., minimally altered by human-caused stress. The models predict the expected number of these taxa at any stream site, assuming that site also is in reference condition. A significant difference between the ratio of observed (O) and expected (E) taxa (O/E) and 1.0 indicates that the site is not in reference condition. The standard deviation (SD) of O/E values estimated for a set of reference sites is a measure of predictive-model precision, with a small SD indicating that the model accounts for much of the variability in E that is associated with natural factors such as stream size and elevation. We propose a null model for E that assumes fixed occurrence probabilities for individual taxa across reference sites. The null model explains none of the variability in E caused by natural factors, so the SD of its O/E predictions is the upper limit attainable by any predictive model. We also derive a theoretical lower limit for SD of O/E that is caused only by replicate-sampling variation among predictions from a perfect model. Together, the null-model and replicate-sampling SDs estimate the minimum and maximum precision, respectively, attainable by any predictive model for a given set of reference-site data. A predictive model built from data at 86 reference sites in the Mid-Atlantic Highlands region, USA, had SD = 0.18 for O/E across those sites, while the corresponding null model had SD = 0.20, indicating relatively little gain from the predictive-model effort. In contrast, a model built from 209 sites in North Carolina, USA, had predictive- and null-model SDs of 0.13 and 0.28, respectively, indicating that the North Carolina predictive model had relatively high gain in precision over the null model. Replicate-sampling SDs of O/E for the Mid-Atlantic and North Carolina data were 0.09 and 0.11, respectively, suggesting that the North Carolina predictive model had little room for further improvement, in contrast to the Mid-Atlantic model. The precisions of null-model estimates were lower than those of predictive models, so null models somewhat underestimated the percentages of 447 and 1773 test assemblages from the Mid-Atlantic region and North Carolina, respectively, that differed significantly from reference conditions. The estimates illustrate how a simple and easily built null model provides a lower bound for the prevalence of impaired streams within a region.

Geochemical and geophysical monitoring of salinewater intrusion in Korean paddy fields

The saline water intruded zone in paddy fields near the seashore can be diagnosed accurately by joint exploration with geophysical and geochemical methods. Using the electromagnetic (EM) sounding technique, the weakly consolidated zone which introduces saline water into such an area of near seashore paddy fields in Korea was detected from the variation of electrical conductivity distribution following field irrigation. Vertical electrical sounding (VES) with Schlumberger array and chemical analysis of top soils, and groundwater in the study area verified the intruded zone near the surface. The VES results showed that the intrusion of seawater occurred in the form of a channel down to 30 m below sea level. Geochemical analysis of the top soil samples for the six major elements found in seawater indicated that the region showing high concentrations is concordant with the weakly consolidated zone near the surface. The degree of contamination in the study area was investigated by comparing the soil data with those from a nearby old reclamation field. If remediation work is not done for this intrusion zone, the sodicity degree in the paddy soil is expected to increase compared with the reference site data.

USING REFERENCE SITES AND SIMPLE LINEAR REGRESSION TO ESTIMATE LONG‐TERM WATER LEVELS IN COASTAL PLAIN FORESTS1

ABSTRACT: The ability of regulators, resource managers, and consultants to assess accurately wetland hydrology is crucial when identifying and delineating wetlands. In this study, simple linear regression and long‐term (ten year) New Jersey Pinelands stream gaging and pitch pine lowland water‐level data sets were used to estimate long‐term hydroperiods at lowland test sites with short‐term (two year) records. Separate regression equations were developed for each test site using reference site data and stream gaging data, and two sets of equations for selected test sites were produced using two different short‐term periods of record. Test sites had long‐term records ranging from four to ten years, allowing validation of the regression models. Measured and predicted test site growing season water levels were similar regardless of which short‐term period of record was used. The results based on the stream gaging site data were similar, although the difference between measured and estimated growing season water levels was greater when this approach was used. Excellent agreement was found between measured and estimated frequencies of near‐surface saturation at test sites for each growing season month, and these relationships improved when cumulative, seasonal frequencies were considered. The reference wetland approach used in this study may have its greatest value in regions with both high development pressures and problem wetlands and may provide an effective way of resolving costly wetland delineation disputes.

A large‐scale categorization of sites in San Francisco Bay, USA, based on the sediment quality triad, toxicity identification evaluations, and gradient studies

Sediment quality was assessed in San Francisco Bay, California, USA, using a two-tiered approach in which 111 sites were initially screened for sediment toxicity. Sites exhibiting toxicity were then resampled and analyzed for chemical contamination, recurrent toxicity, and, in some cases, benthic community impacts. Resulting data were compared with newly derived threshold values for each of the metrics in a triad-based weight-of-evidence evaluation. Sediment toxicity test results were compared with tolerance limits derived from reference site data, benthic community data were compared with threshold values for a relative benthic index based on the presence and abundance of pollution-tolerant and -sensitive taxa, and concentrations of chemicals and chemical mixtures were compared with sediment quality guideline-based thresholds. A total of 57 sites exceeded threshold values for at least one metric, and each site was categorized based on triad inferences. Nine sites were found to exhibit recurrent sediment toxicity associated with elevated contaminant concentrations, conditions that met program criteria for regulatory attention. Benthic community impacts were also observed at three of these sites, providing triad evidence of pollution-induced degradation. Multi- and univariate correlations indicated that chemical mixtures, heavy metals, chlordanes, and other organic compounds were associated with measured biological impacts in the Bay. Toxicity identification evaluations indicated that metals were responsible for pore-water toxicity to sea urchin larvae at two sites. Gradient studies indicated that the toxicity tests and benthic community metrics employed in the study predictably tracked concentrations of chemical mixtures in Bay sediments.

Evaluation and use of sediment toxicity reference sites for statistical comparisons in regional assessments

Sediment reference sites were used to establish toxicity standards against which to compare results from sites investigated in San Francisco Bay (California, USA) monitoring programs. The reference sites were selected on the basis of low concentrations of anthropogenic chemicals, distance from active contaminant sources, location in representative hydrographic areas of the Bay, and physical features characteristic of depositional areas (e.g., fine grain size and medium total organic carbon [TOC]). Five field-replicated sites in San Francisco Bay were evaluated over three seasons. Samples from each site were tested with nine toxicity test protocols and were analyzed for sediment grain size and concentrations of trace metals, trace organics, ammonia, hydrogen sulfide, and TOC. The candidate sites were found to have relatively low concentrations of measured chemicals and generally exhibited low toxicity. Toxicity data from the reference sites were then used to calculate numerical tolerance limits to be used as threshold values to determine which test sites had significantly higher toxicity than reference sites. Tolerance limits are presented for four standard test protocols, including solid-phase sediment tests with the amphipods Ampelisca abdita and Eohaustorius estuarius and sea urchin Strongylocentrotus purpuratus embryo/larval development tests in pore water and at the sediment-water interface (SWI). Tolerance limits delineating the lowest 10th percentile (0.10 quantile) of the reference site data distribution were 71% of the control response for Ampelisca, 70% for Eohaustorius, 94% for sea urchin embryos in pore water, and 87% for sea urchins embryos exposed at the SWI. The tolerance limits are discussed in terms of the critical values governing their calculation and the management implications arising from their use in determining elevated toxicity relative to reference conditions.

Assessment framework for mid-Atlantic coastal plain streams using benthic macroinvertebrates

A collaborative study among 6 states along the mid-Atlantic seaboard of the USA developed a consistent approach for collecting and interpreting macroinvertebrate data for low-gradient streams of the coastal plain. The study had 3 objectives: 1) to evaluate the validity of aggregating reference site data into a single bioregion, 2) to select biological metrics that best discriminated reference sites from sites impaired by habitat disturbance and organic pollution, and 3) to combine these metrics into an index of biological quality. Macroinvertebrate, physical habitat, and water-quality data were collected in 106 streams during autumn 1995. Fifty-five sites were reference, 34 sites had habitat stresses, and 17 sites had water-quality stresses. Classification of reference sites divided the coastal plain into 3 bioregions, separated north and south by Chesapeake Bay and separated east and west by ecoregion. Five metrics were effective at discriminating impairment: number of taxa, number of Ephemeroptera, Plecoptera, and Trichoptera (EPT) taxa, % Ephemeroptera, Hilsenhoff Biotic Index, and % clinger mode of existence. An aggregated index, the Coastal Plain Macroinvertebrate Index (CPMI), was developed using these metrics. The CPMI accurately identified 86% of impaired sites. The precision of CPMI scores was estimated to be ±10% (3 scoring units out of 30) at the 90% confidence interval. The CPMI accurately assigned both habitat disturbance and water-quality impairment indicating a similar degree of ecological impact from these 2 stressors. Guidance is provided for applying the CPMI to other macroinvertebrate data sets in the region.