Final Report: Development and Evaluation of Chemical Indicators for Monitoring Ecological Risk

EPA Grant Number: R828675C005
Subproject: this is subproject number 005 , established and managed by the Center Director under grant R828675
(EPA does not fund or establish subprojects; EPA awards and manages the overall grant for this center).

Center: EAGLES - Great Lakes Environmental Indicators Project
Center Director: Niemi, Gerald J.
Title: Development and Evaluation of Chemical Indicators for Monitoring Ecological Risk
Investigators: Swackhamer, Deborah L. , Mount, David , Ankley, Gary , Burkhard, Lawrence , Simcik, Matthew , Cook, Philip , Erickson, Russell , Diamond, Steven
Institution: University of Minnesota , U.S. Environmental Protection Agency
EPA Project Officer: Packard, Benjamin H
Project Period: January 10, 2001 through January 9, 2005 (Extended to January 9, 2006)
RFA: Environmental Indicators in the Estuarine Environment Research Program (2000) RFA Text |  Recipients Lists
Research Category: Ecological Indicators/Assessment/Restoration , Water , Ecosystems

Objective:

The objectives of this research project were to identify and validate effective contaminant indicators of adverse impacts on estuarine ecosystem health. Indicators were developed in the Great Lakes but are also applicable to both marine and freshwater ecosystems. These contaminant indicators will be used to evaluate ecological condition. Specifically, we focused on the evaluation of two indicators: (1) indicator polycyclic aromatic hydrocarbons (PAHs) of photo-induced toxicity to fish and benthic organisms; and (2) organic chemical indicators of xenoestrogenic exposure to fishes. Our final analysis produced an indicator for PAH photo-induced toxicity to fish.

The assessment of ecological condition in an effective manner is best accomplished using integrative indicators of condition. These indicators should be cost-effective, applicable across multiple scales, and provide useful information for environmental managers. Within the omnibus project, this contaminants subproject focused on contaminant indicators that could provide a measure of the condition of the estuarine ecosystem. These indicators also served as diagnostic indicators that will identify the primary stressors affecting the specific ecological endpoint of concern. We focused on PAH compounds and environmental estrogens because they are ubiquitous in the environment and have existing sources, and thus are of current concern.

The specific hypotheses we tested were: (1) specific PAHs in combination with UV penetration are indicators of potential loss of vulnerable species within coastal fish and/or benthic communities; and (2) specific chemicals are indicators of endocrine disruption in fish via the estrogen receptor. Data collected to test these hypotheses was used to demonstrate the degree of usefulness of these two groups of indicator compounds as diagnostic indicators for estuarine ecosystems.

Summary/Accomplishments (Outputs/Outcomes):

Our overall approach to this project is summarized as follows. For both indicators, we compared contaminant concentrations to a biological endpoint or condition across a gradient of nondegraded to highly degraded sites in approximately 25 locations that were studied by the other indicator project groups in the program. For the PAH photo-induced toxicity indicator, we collected the necessary field data to test the model developed in the lab by the collaborators at U.S. Environmental Protection Agency (EPA) Mid-Continent Ecology Division (MED). These data included the concentrations of PAHs in sediment, larval fish, and oligochaetes (to determine the sediment-biota accumulation factor [BSAF] and to provide the doses for the model); sediment photo-induced toxicity potential (assayed in the laboratory using the aquatic annelid Lumbriculus [laboratory test organism] and field sediments); and UV dose (obtained from field measurements). The toxicity that was predicted from the model was compared to that measured in the lab assay. Results were used to calibrate the model and to provide guidance and boundaries for how this model can be applied as an indictor.

The xenoestrogen indicator was examined in an analogous manner. Our intent was to measure a suite of potential xenoestrogens in fish tissue, sediment, and/or water and compare them to vitellogenin induction in wild and caged male fish (a bioindicator of individual estrogen exposure) at the same gradient of sites. The low levels of contaminants except near point sources combined with the complexity of the biological response from xenoestrogen exposures prevented acceptable development of a simple indicator of xenoestrogen impacts.

PAH Phototoxicity

The indicator that we have developed is one that managers can use to estimate whether larval fish populations at a given site are potentially at risk from photo-induced toxicity. Photo-induced toxicity of PAHs to larval fish is a function of exposure to both PAHs and ultraviolet-A (UV-A) light (Figure 1). Users of this indicator will need to estimate PAH exposure to fish by measuring specific PAH compounds in sediment and estimate UV-A dose by measuring absorbance of water with a spectrophotometer and measuring suspended particulate matter gravimetrically. These measurements are then put into a simple model that provides an estimate of the risk of photo-induced toxicity.

UV-A exposure depends on factors such as light intensity, dissolved organic carbon, and total suspended solids. We have developed a model for measuring UV-A attenuation in the water column of the coastal Great Lakes. This model involves the measurement of spectral attenuation using a spectrophotometer (a simple piece of equipment common to most laboratories) and suspended particulate matter. Because of the ease of the measurements and incorporation of the influence of suspended particulate matter on attenuation, we have created a useful tool for managers of the coastal Great Lakes. Our method can be used to evaluate the UV-A exposure setting at other sites around the Great Lakes and more importantly, predict how changes in suspended particulate matter might affect UV-A attenuation. For instance, the introduction of zebra mussels has reduced dramatically the amount of suspended particulate matter in the coastal areas and, therefore, may have a commensurate increase in UV-A exposure to larval fish in those areas (Adams, 2005). Two field measurements are needed, suspended particulate matter (SPM) and the irradiance attenuation coefficient from 334 nm to 370 nm (κa334-370). The SPM is determined by filtering 1 L of surface water through a preweighed 0.4 um polycarbonate filter, drying the filter to constant weight, and dividing the dry mass of particulates by the exact volume of water filtered. κa334-370 is determined by filtering approximately 250 mL of surface water through a 0.7 precombusted glass fiber filter and measuring the absorbance from 280 nm to 400 nm at 2 nm intervals, across a 1-cm pathlength, and relative to a blank containing organic-free water. The κa334-370 is then calculated according to Adams (2005). κd is then estimated as follows:

κd= 1.55 (κa334-370) + 0.204 (SPM) + 0.656

The UV-A dose is calculated as (2800 uW/cm2 * 0.935 * 14/24 * 0.75 * T), where T is the fraction transmittance at 10 cm in the water column for a given UV absorbance measurement. The percent transmittance is calculated as T = e(-κd*depth/100). The equation above is the product of the midday intensity * surface reflectance * hours of sun * cloud factor correction * T.

Organization Chart

Figure 1. Overall Model of Indicator for Photo-Induced Toxicity of PAHs to Aquatic Organisms

PAH exposure is a function of partitioning of PAHs from the water column into larval fish, and usually the PAH in water is a result of partitioning from contaminated sediments to water. Because PAHs are measured more readily in sediments compared to water, we are using the concept of BSAF. The BSAF describes the relationship between PAHs in lipids of biota and PAHs in sediment organic carbon and is expressed as the ratio of the lipid-normalized concentration of PAHs in biota to the organic carbon normalized concentration of PAHs in sediment. We collected sediments and larval fish at each of our study sites and measured the BSAFs to test whether this approach would work for this indicator. The BSAFs for two compounds, fluoranthene and pyrene, were the most consistent across sites and were incorporated into our indicator. It is assumed that this BSAF is representative for coastal sites throughout the Great Lakes. Thus, the user of the indicator will measure a suite of nine photo-toxic PAHs and organic carbon in sediments, normalize them to the organic carbon fraction of the sediment, multiply their sum by our measured BSAF of 0.16 to estimate the sum of photo-toxic PAHs in fish lipid, and multiply the value by the lipid fraction of the larval fish of interest (10% is a good default). This gives a photo-toxic PAH concentration in the fish tissue, in dry mass concentration. The nine PAHs that are phototoxic are dibenzothiophene, anthracene, 4-methyldibenzothiophene, 2-mehtylanthracene, 1-methylanthracene, 9-methylanthracene, 9,10-dimethylanthracene, fluoranthene, pyrene, benz[a]anthracene, benzo[bjk]fluoranthene, and benzo[a]pyrene.

Once the UV-A dose and photo-toxic PAH concentration are estimated, they can be used to calculate an LT-50, meaning the time (in hours) that it takes for 50 percent of the population to die. This is done by dividing the mean potency coefficient for the phototoxic PAHs (63,000; from EPA-MED) by the product of the photo-toxic PAH concentration and the UV-A dose, and to obtain a photo-toxic potency. The inverse of this value is the LT-50.

LT-50, hours = 63000/[(PAH conc, μg/g dw) * (UV-A, uW/cm2)]

To provide a context and further interpretation for this LT-50, it is useful to consider two graphs. The first graph is a plot of the predicted LT-50 as a function of depth in the water column, for the fixed UV-A dose for that site (see Figure 2 for an example). This provides information as to how the risk of photo-induced toxicity might vary with depth in the water column. Thus, one can relate the actual depth of light penetration at the specific site to risk. This is a useful graph on a site-specific basis.

To compare the risk across sites, one can prepare a second graph that plots photo-toxic PAH concentration versus UV-A dose, assuming a given light penetration depth (we used 10 cm as a default). The isopleths on this plot are LT-50s (Figure 3). An LT-50 greater than 300 hrs is not considered to be a risk, as the repair mechanisms likely are activated by this time and should offset the photo-toxic cell damage. One can plot the data for several sites and see if they fall above or below the isopleth for LT-50 = 300 hours.

This indicator can be used to prioritize sites for further investigation—where calculated LT-50s are small (< 100 hours), further investigation may be warranted; where calculated LT-50s are very large (> 1000 hours), there is minimal risk and additional investigation may not be warranted.

Figure 2. The Effect of Changing the UV-A Dose (by Varying the Depth of Light Penetration) on the Predicted LT-50 for a Constant PAH Concentration (500 ng/g) and Moderate Light Attenuation (Kd = 6). A predicted LT-50 greater than 300 is indicated there.

Figure 3. Relationship of Varying PAH and UV-A Exposures (Assuming Constant Depth of 10 cm), With Isopleths Indicating Predicted LT-50s of 100, 300, and 1000 Hours for Reference

Validation of Indicator. We have calculated the LT-50s for all the sites that were sampled as part of our field work, and the results of this are shown in Figure 4. This analysis assumed a constant depth of 10 cm, and actual risk for photo-induced toxicity would depend on actual light transmission with depth. Approximately one-half of our sites had predicted LT-50s less than 300 hours, indicating that these sites have potential risk for photo-induced toxicity of larval fish.

Figure 4. Calculated Potency (1/LT-50) of PAHs to Larval Fish at Sites Around the Great Lakes. The red bars indicate a potential risk of photo-induced toxicity to larval fish. It was assumed that light transmission was to 10 cm.

Environmental Estrogens

An indicator of estrogenicity was not developed. We provide an assessment of why this indicator failed to be transferred from the laboratory to the field. Two manuscripts from the Ph.D. dissertation of Randy Lehr address these issues and are summarized below.

The first manuscript provides a comprehensive review and critical assessment of the tools that have been developed to assess estrogenic exposures and response in fish, from the measurement of chemical concentrations in fish tissue to the proteomic and genomic measurements that indicate a response at the cellular or molecular level. To establish exposure-effect relationships, researchers have identified several measurement endpoints that characterize signal transduction at many intermediary steps throughout the estrogen response pathway. However, development of these assays has not followed a standardized approach and different measurement endpoints have been quantified using different analytical techniques and exposure scenarios. As a result, the sensitivity and diagnostic and predictive potential for these assay systems is different. In general, assays that characterize estrogen signal transduction at lower levels of biological organization are the most amenable to high throughput and diagnostic analysis but the poorest predictors of potential effects at individual and population levels. Conversely, assays that characterize estrogen signal transduction at higher levels of biological organization are the best predictors of potential effects but the least amenable to high throughput, diagnostic analysis. This complicates the linkage of exposure and effect using a single endpoint and requires the analysis of multiple endpoints to mechanistically link exposure and effect. This approach is recommended but is not amenable to adopt as a monitoring approach for the end-users of this project. At the beginning of this project, the complexity of the estrogen response pathway was not fully appreciated nor were these tools fully developed.

Another manuscript was directed at providing advice to environmental managers who wish to monitor for environmental estrogens (EEs). Management of chemical contaminants is highly dependent on the establishment of exposure-effect relationships. Establishment of exposure-effect relationships for EEs is complicated by many factors and as such, the management of EEs presents several challenges. To aid the management process, researchers have developed a variety of assays to establish exposure-effect relationships, and each of these assays is likely to be best suited for different aspects of the management process. Assays that quantify exposure and effect at higher levels of biological organization integrate EE exposure and are likely to be more appropriate for assessment of ecosystem condition and long-term monitoring. Assays that assess exposure and effect at lower levels of biological organization are more mechanistically diagnostic and thus likely to be more appropriate for the identification of specific chemicals of concern and design of management interventions. The unique physical-chemical and toxicological properties of EEs also affect the design of management plans and the ability to communicate management results.

In summary, the complexity of the estrogen response pathway necessitates having indicators that can both assess exposure and assess an integrated measure of the response elicited as a result of that exposure. The tools available do not do both of these well, and a monitoring program requires the use of multiple tools to assess exposure as well as assess specific and integrated responses to provide the link of exposure and effect. Furthermore, tools are needed to bridge the assessment of individuals to populations and communities. These tools still are largely in the research and development phase, and few have been used effectively to assess effects of EEs to fish populations in the field.

Journal Articles:

No journal articles submitted with this report: View all 22 publications for this subproject

Supplemental Keywords:

Great Lakes, monitoring, indicators, risk assessment, stressor, ecological effects, animal, plant, diatoms, toxics, aquatic ecosystem, aquatic ecosystems, atmospheric pollutant loads, climate variability, coastal ecosystem, coastal environments, diatoms, ecological assessment, ecological condition, ecological response, ecosystem assessment, ecosystem impacts, ecosystem indicators, ecosystem stress, environmental consequences, environmental stressor, environmental stressors, estuarine ecosystems, hierarchically structured indicators, human activities, hydrologic models, hydrological, hydrological stability, nutrient stress, nutrient supply, nutrient transport, toxic environmental contaminants,, RFA, Scientific Discipline, ENVIRONMENTAL MANAGEMENT, Geographic Area, ECOSYSTEMS, Ecosystem Protection/Environmental Exposure & Risk, exploratory research environmental biology, Ecosystem/Assessment/Indicators, Ecosystem Protection, Monitoring/Modeling, Ecological Effects - Environmental Exposure & Risk, Environmental Monitoring, Ecological Monitoring, Ecological Risk Assessment, Ecology and Ecosystems, Great Lakes, Ecological Indicators, Risk Assessment, ecological condition, coastal ecosystem, anthropogenic stress, biodiversity, ecosystem assessment, environmental measurement, coastal environments, PAH, ecological assessment, ecosystem indicators, analytical chemistry, estuarine ecoindicator, xenoestrogen indicators, aquatic ecosystems, ecological risk, environmental stress, water quality, environmental estrogens, ecological models, fish models, ecological response

Relevant Websites:

http://glei.nrri.umn.edu Exit

Progress and Final Reports:

Original Abstract
  • 2001
  • 2002
  • 2003 Progress Report
  • 2004 Progress Report

  • Main Center Abstract and Reports:

    R828675    EAGLES - Great Lakes Environmental Indicators Project

    Subprojects under this Center: (EPA does not fund or establish subprojects; EPA awards and manages the overall grant for this center).
    R828675C001 Great Lakes Diatom and Water Quality Indicators
    R828675C002 Vegetative Indicators of Condition, Integrity, and Sustainability of Great Lakes Coastal Wetlands
    R828675C003 Testing Indicators of Coastal Ecosystem Integrity Using Fish and Macroinvertebrates
    R828675C004 Development and Assessment of Environmental Indicators Based on Birds and Amphibians in the Great Lakes Basin
    R828675C005 Development and Evaluation of Chemical Indicators for Monitoring Ecological Risk