John F. Paul

Developing and applying a benthic index of estuarine condition for the Virginian Biogeographic Province

A benthic index of estuarine condition was constructed for the Virginian Biogeographic Province (from Cape Cod, Massachusetts, to the mouth of Chesapeake Bay, Virginia) with data collected during summers of 1990 through 1993 by the US EPA’s Environmental Monitoring and Assessment Program (EMAP). Forty-eight metrics, based on attributes of the macrobenthos, were considered for the index, including measures of biodiversity, community condition, individual health, functional organization, and taxonomic composition. Salinity was correlated significantly with some of the metrics. Therefore, some metrics were normalized for salinity. The data used to develop the index (the calibration data) included equal numbers of reference and degraded sites, distributed equally across three salinity zones ( 18‰). An independent set of data was used for validation. Linear discriminant analysis identified combinations of metrics that could best discriminate reference from degraded sites. The targets for correct classification were 90% of the sites for the calibration data and 80% for the validation data. Six combinations of metrics were identified. The final index was based on the ecological interpretation and relevance of the individual metrics and the ability to meet the calibration and validation targets. The final index consisted of three metrics: a positive contribution from salinity-normalized Gleason’s D (a biodiversity metric), and negative contributions from two taxonomic composition metrics, abundances of spionid polychaetes and of salinity-normalized tubificid oligochaetes. The index correctly classified 87% of reference and 90% of degraded sites in the calibration data and 88% of reference and 81% of degraded sites in the validation data. The index correctly classified sites over the full range of salinity (tidal-fresh to marine waters) and across grain sizes (silt–clay to sand).

Misfit between sediment toxicity and chemistry

In the United States, the EPA EMAP-Estuaries Program and the NOAA Bioeffects Surveys provide large data sets with which to test proposed relationships between sediment chemistry and toxicity. The conclusion is that no chemical measurement reliably predicts sediment toxicity. These findings challenge the use of chemical data to imply biological hazard and the way toxicity data are used in sediment management.

Ecological condition of US Mid-Atlantic estuaries, 1997-1998

The Mid-Atlantic Integrated Assessment (MAIA-Estuaries) evaluated ecological conditions in US Mid-Atlantic estuaries during the summers of 1997 and 1998. Over 800 probability-based stations were monitored in four main estuarine systems--Chesapeake Bay, the Delaware Estuary, Maryland and Virginian coastal bays, and the Albemarle-Pamlico Estuarine System. Twelve smaller estuaries within the four main systems were also assessed to establish variance at the local scale. A subset of the MAIA-Estuaries data is used here to estimate the extent of eutrophication, sediment contamination, and benthic degradation in mid-Atlantic estuaries. An Environmental Report Card and Index of Environmental Integrity summarize conditions in individual estuaries, the four estuarine systems, and the entire MAIA region. Roughly 20-50% of the region showed signs of eutrophication (high nutrients, excessive production of organic matter, poor water clarity, or depleted dissolved oxygen), 30% had contaminated sediments, and 37% had degraded benthic communities. Compared with the Environmental Monitoring and Assessment Program (EMAP)-Virginian Province study in 1990-1993, larger fractions of Chesapeake Bay (17%) and Delaware River (32%) had increased metals or organics in sediments.

Relationships between watershed stressors and sediment contamination in Chesapeake Bay estuaries

Three methods for assessing the relationships between estuarine sediment contaminant levels and watershed Stressors for 25 Chesapeake Bay sub-estuaries were compared. A geographic information system (GIS) was used to delineate watersheds for each sub-estuary and analyze land use pattern (area and location of developed, herbaceous and forested land) and point source pollution (annual outflow and contaminant loading) using three landscape analysis methods: (1) a watershed approach using the watershed of the estuary containing the sampling station. (2) a ‘partial watershed’ approach using the area of the watershed within a 10 km radius of the sampling station and (3) a ‘weighted partial watershed’ approach where Stressors within the partial watershed were weighted by the inverse of their linear distance from the sampling station. Nine sediment metals, 16 sediment organics and seven metals loading variables were each reduced to one principal component for statistical analyses. Relationships between the first principal components for sediment metals and organics concentrations and watershed stressor variables were analyzed using rank correlation and stepwise multiple regression techniques. For both metals and organics, the watershed method yieldedR2 values considerably lower than the partial and weighted partial watershed analysis methods. Regression models using Stressor data generated by the weighted partial watershed landscape analysis method explained 76% and 47% of the variation in the first principal component for sediment metals and organics concentrations, respectively. Results suggest that the area of developed land located in the watershed within 10 km of the sediment sampling station is a major contributing factor in the sediment concentrations of both metals and organics.

Watershed Landscape Indicators of Estuarine Benthic Condition

Do land use and cover characteristics of watersheds associated with small estuaries exhibit a strong enough signal to make landscape metrics useful for identifying degraded bottom communities? We tested this idea with 58 pairs of small estuaries (<260 km2) and watersheds in the U.S. Mid-Atlantic coastal plain (Delaware Bay to Chesapeake Bay). We considered 34 landscape metrics as potential explanatory variables and seven estuarine parameters as response variables. We developed three logistic regression models: one to calculate the probability of degraded benthic environmental quality (BEQ), as defined by chemical parameters, and two for the probability of degraded estuarine bottom communities, one using a benthic index (BI) and a second using the total number of bottom-dwelling species (TNBS, consisting of benthic macroinvertebrates and fishes). We evaluated the discriminatory power of the models with ROC (receiver operating characteristic) curves of sensitivity and specificity. All three models showed excellent discrimination of high and low values. A model using the sum of all human land uses and percent wetlands correctly classified BEQ in 86% of the cases; low benthic index and low total number of bottom species were each associated with degraded BEQ (p<0.01). The BI model used percent riparian urban, riparian wetlands, and agriculture on steep slopes (76% correct classification) and correctly predicted high-low benthic index of an independent data set 79% of the time (p<0.05). The TNBS model used percent wetlands, riparian wetlands, and riparian agriculture (74% correct classification). Watersheds with higher percentages of urban and agricultural land uses were associated with lower benthic environmental quality, benthic index, and biodiversity, whereas those with higher percentages of wetlands were associated with higher numbers. As human development of watersheds increases, statistical prediction rules developed from landscape metrics could be a cost-effective method to identify potentially threatened estuaries.

Incidence of Stress in Benthic Communities along the U.S. Atlantic and Gulf of Mexico Coasts within Different Ranges of Sediment Contamination from Chemical Mixtures

Synoptic data on concentrations of sediment-associated chemical contaminants and benthic macroinfaunal community structure were collected from 1,389 stations in estuaries along the U.S. Atlantic and Gulf of Mexico coasts as part of the nationwide Environmental Monitoring and Assessment Program (EMAP). These data were used to develop an empirical framework for evaluating risks of benthic community-level effects within different ranges of sediment contamination from mixtures of multiple chemicals present at varying concentrations. Sediment contamination was expressed as the mean ratio of individual chemical concentrations relative to corresponding sediment quality guidelines (SQGs), including Effects Range-Median (ERM) and Probable Effects Level (PEL) values. Benthic condition was assessed using diagnostic, multi-metric indices developed for each of three EMAP provinces (Virginian, Carolinian, and Louisianian). Cumulative percentages of stations with a degraded benthic community were plotted against ascending values of the mean ERM and PEL quotients. Based on the observed relationships, mean SQG quotients were divided into four ranges corresponding to either a low, moderate, high, or very high incidence of degraded benthic condition. Results showed that condition of the ambient benthic community provides a reliable and sensitive indicator for evaluating the biological significance of sediment-associated stressors. Mean SQG quotients marking the beginning of the contaminant range associated with the highest incidence of benthic impacts (73-100% of samples, depending on the province and type of SQG) were well below those linked to high risks of sediment toxicity as determined by short-term toxicity tests with single species. Measures of the ambient benthic community reflect the sensitivities of multiple species and life stages to persistent exposures under actual field conditions. Similar results were obtained with preliminary data from the west coast (Puget Sound).

Timing of Increased Autistic Disorder Cumulative Incidence

Autistic disorder (AD) is a severe neurodevelopmental disorder typically identified in early childhood. Both genetic and environmental factors are implicated in its etiology. The number of individuals identified as having autism has increased dramatically in recent years, but whether some proportion of this increase is real is unknown. If real, susceptible populations may have exposure to controllable exogenous stressors. Using literature AD data from long-term (approximately 10-year) studies, we determined cumulative incidence of AD for each cohort within each study. These data for each study were examined for a changepoint year in which the AD cumulative incidence first increased. We used data sets from Denmark, California, Japan, and a worldwide composite of studies. In the Danish, California, and worldwide data sets, we found that an increase in AD cumulative incidence began about 1988-1989. The Japanese study (1988-1996) had AD cumulative incidence increasing continuously, and no changepoint year could be calculated. Although the debate about the nature of increasing autism continues, the potential for this increase to be real and involve exogenous environmental stressors exists. The timing of an increase in autism incidence may help in screening for potential candidate environmental stressors.

Monitoring the ecological condition of estuaries in the United States

The purpose of the Environmental Monitoring and Assessment Program/ Estuaries component (EMAP‐E) is to determine the current status, extent, changes, and trends in ecological indicators of the condition of the nations estuarine resources on a regional and national basis. Monitoring activities in the Virginian (Mid‐Atlantic) and Louisianian (Gulf of Mexico) Provinces focus on measurements describing the benthic community, the fish community, water quality, levels of sediment and tissue contamination, sediment toxicity, wetlands extent/condition, and seagrasses extent/condition. Estuarine monitoring is based on an EMAP‐E probability‐based sampling design conducted over a 60‐day period during July‐September of each year. Monitoring activities in the Virginian Province began in 1990 and have continued annually while monitoring in the Louisianian Province was initiated in 1991. The results of 1990 monitoring in the Virginian Province show that 20% of the sediments of the Mid‐Atlantic region suffered from poor...

Using field data and weight of evidence to develop water quality criteria

ABSTRACT In the United States, ambient aquatic life water quality criteria are derived using guidelines developed in 1985 that include a clear and consistent methodology using data from standard toxicity tests. The methodology from these guidelines has been successful, but a broader methodology is needed because some effects of pollutants do not lend themselves to conventional toxicity testing. Criterion assessment is proposed as that methodology. In criterion assessment, a specific environmental goal is translated into a measurable benchmark of effect that is used together with a modeled exposure–response relationship to estimate a range of exposures that will achieve the specific goal. The model of the exposure–response relationships and the benchmark effect are developed from field data and laboratory data using multiple analytical methods. Then the model is solved for the effect, thereby estimating the criterion, an upper threshold for acceptable exposures. The resulting candidate criteria are synthesized to select criteria and other benchmark values, such as remedial goals. The criterion assessment process is illustrated using the US Environmental Protection Agency Framework for Developing for Suspended and Bedded Sediments Water Quality Criteria, which recommends developing alternative candidate criterion values and then evaluating them to select a final criterion. Candidate criteria may be derived from models of field observations, field manipulations, laboratory tests, or empirical and theoretical models. Final selection of a criterion uses a weight-of-evidence comparison that engenders confidence because causal associations are confirmed on the basis of different assumptions, independent data sets, and varied statistical methods, thereby compensating for the concerns raised by individual studies and methods. Thus, it becomes possible to specify criteria for agents with biological or physical modes of action, as well as those with chemical modes of action, to best achieve environmental goals.

Assessing the Accuracy of National Land Cover Dataset Area Estimates at Multiple Spatial Extents

Site-specific accuracy assessments evaluate fine-scale accuracy of land-use/land-cover (LULC) datasets but provide little insight into accuracy of area estimates of LULC classes derived from sampling units of varying size. Additionally, accuracy of landscape structure metrics calculated from area estimates cannot be determined solely from site-specific assessments. We used LULC data from Rhode Island and Massachusetts as reference to determine the accuracy of area measurements from the National Land Cover Dataset (NLCD) within spatial units ranging from 0.1 to 200 km 2 . When regressed on reference area, NLCD area of developed land, agriculture, forest, and water had positive linear relationships with high r2, suggesting acceptable accuracy. However, many of these classes also displayed mean differences (NLCD - REFERENCE), and linear relationships between the NLCD and reference were not one-to-one (i.e., low r 2 , β 0 ¬= 0, β 1 ¬= 1), suggesting mapped area is different from true area. Rangeland, wetland, and barren were consistently, poorly classified.