Exposure and Exposure Modeling

Exposure to contaminants in the environment is quantified through the ecological risk assessment (ERA) process which provides a framework for the development and implementation of environmental management decisions. The ERA uses available toxicological and ecological information to estimate the probability of occurrence for a specified undesired ecological event or endpoint. The level for these endpoints depends on the objectives and the constraints imposed upon the risk assessment process; therefore, multiple endpoints at different scales may be necessary. ERAs Ecotoxicology | Exposure and Exposure Assessment 1527Author\u27s personal copy often rely on the link between these undesired endpoints to a threshold of exposure to specific toxicants and toxicant mixtures. Oral reference doses (RfD), inhalation reference concentrations (RfC), and carcinogenicity assessments are the usual way these links are expressed in the ERA, and unfortunately most of these thresholds have been developed for human health assessments and not ecosystem integrity. However, since these studies often use animal models, in many cases the original empirical data can be used when trying to apply these findings to ecological consequences or to establish ecological screening values (ESVs). The ecological exposure assessment often begins by comparing constituent concentrations in media (surface water, sediment, soil) to ESVs. The ESVs are derived from ecologically relevant criteria and standards. For example, in the United States the United States Environmental Protection Agency (USEPA) Screening Values and National Ambient Water Quality Criteria (NAWQC) are often used based on ‘no observed adverse effect levels’ (NOAELs) or ‘lowest observed adverse effect levels’ (LOAELs) derived from literature to assess exposure. Radionuclide comparisons for ecological screening are typically dose-based for population level effects. In addition to the ecological threshold comparison, constituents that may bioaccumulate/bioconcentrate are identified during initial screening processes. This is done to account for toxicants that may not be present at levels exceeding ESVs, but must be considered due to trophic transfer of toxicants that may concentrate in higher-trophic-level organisms. Constituents that exceed ESV comparisons (present with means, maximums, or 95% upper confidence levels (UCLs)) are evaluated using a lines-of-evidence approach based on (1) a background evaluation, (2) a bioaccumulation/ bioconcentration potential and ecotoxicity evaluation, (3) a frequency and pattern-of-exceedances evaluation based on review of exceedances to the ESVs, and (4) an evaluation of existing biological data. From this information, ecosystems can be prioritized in terms of risk and focused for proper exposure assessments. This article presents a scientific overview and review of how toxicant exposure is estimated and applied to assess ecosystem integrity

Modelling and mapping heavy metal and nitrogen concentrations in moss in 2010 throughout Europe by applying Random Forests models

Objective: This study explores the statistical relations between the concentration of nine heavy metals(HM) (arsenic (As), cadmium (Cd), chromium (Cr), copper (Cu), mercury (Hg), nickel (Ni), lead (Pb),vanadium (V), zinc (Zn)), and nitrogen (N) in moss and potential explanatory variables (predictors)which were then used for mapping spatial patterns across Europe. Based on moss specimens collected in 2010 throughout Europe, the statistical relation between a set of potential predictors (such as the atmospheric deposition calculated by use of two chemical transport models (CTM), distance from emission sources, density of different land uses, population density, elevation, precipitation, clay content of soils) and concentrations of HMs and nitrogen (N) in moss (response variables) were evaluated by the use of Random Forests (RF) and Classification and Regression Trees (CART). Four spatial scales were regarded: Europe as a whole, ecological land classes covering Europe, single countries participating in the European Moss Survey (EMS), and moss species at sampling sites. Spatial patterns were estimated by applying a series of RF models on data on potential predictors covering Europe. Statistical values and resulting maps were used to investigate to what extent the models are specific for countries, units of the Ecological Land Classification of Europe (ELCE), and moss species. Results: Land use, atmospheric deposition and distance to technical emission sources mainly influence the element concentration in moss. The explanatory power of calculated RF models varies according to elements measured in moss specimens, country, ecological land class, and moss species. Measured and predicted medians of element concentrations agree fairly well while minima and maxima show considerable differences. The European maps derived from the RF models provide smoothed surfaces of element concentrations (As, Cd, Cr, Cu, N, Ni, Pb, Hg, V, Zn), each explained by a multivariate RF model and verified by CART, and thereby more information than the dot maps depicting the spatial patterns of measured values. Conclusions: RF is an eligible method identifying and ranking boundary conditions of element concentrations in moss and related mapping including the influence of the environmental factors

Assessing contaminated sediments in the context of multiple stressors

Sediments have a major role in ecosystem functioning but can also act as physical or chemical stressors. Anthropogenic activities may change the chemical constituency of sediments and the rate, frequency, and extent of sediment transport, deposition, and resuspension. The importance of sediments as stressors will depend on site ecosystem attributes and the magnitude and preponderance of co-occurring stressors. Contaminants are usually of greater ecological consequence in human-modified, depositional environments, where other anthropogenic stressors often co-occur. Risk assessments and restoration strategies should better consider the role of chemical contamination in the context of multiple stressors. There have been numerous advances in the temporal and spatial characterization of stressor exposures and quantification of biological responses. Contaminated sediments causing biological impairment tend to be patchy, whereas more pervasive anthropogenic stressors, such as alterations to habitat and flow, physical disturbance, and nutrient addition, may drive large-scale ecosystem responses. A systematic assessment of relevant ecosystem attributes and reference conditions can assist in understanding the importance of sediments in the context of other stressors. Experimental manipulations then allow for the controlled study of dominant stressors and the establishment of causal links. This approach will result in more effective management of watersheds and waterways. Environ. Toxicol. Chem. 2010;29:2625–2643. © 2010 SETACPeer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/78293/1/332_ftp.pd

Assessing the Effect of Disturbances on Ectomycorrhiza Diversity

Ectomycorrhiza (ECM) communities can be described on a species level or on a larger scale at an ecosystem level. Here we show that the species level approach of successional processes in ECM communities is not appropriate for understanding the diversity patterns of ECM communities at contaminated sites. An ecosystem based approach improves predictability since different biotic and abiotic factors are included. However, it still does not take into account the hierarchical structure of the ecosystem. We suggest that diversity patterns of ECMs communities in forests can best be investigated at three levels. This hypothetical approach for investigation can be tested at sites of secondary succession in areas contaminated with metals. Once the diversity patterns are appropriately described by a hierarchical ecosystem approach, to the species level is used to explain these patterns by populational and ecotoxicological mechanisms