An approach for estimating ecological risks from organochlorine pesticides to terrestrial organisms at rocky mountain arsenal

Banton, Marcy I.; Klingensmith, J S; Barchers, Daniel E.; Clifford, Philip A.; Ludwig, David F.; Macrander, Annecke; Sielken, Robert L.; Valdez‐Flores, Ciriaco

doi:10.1080/10807039609383629

Cited by 11 publications

(6 citation statements)

References 23 publications

(15 reference statements)

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“…Several studies ( − ) have indicated that the relative spatial positions of receptors and contaminated media can strongly influence estimates of exposure and hence of risk. Inclusion of the spatial relationship of receptors, their habitats, and contaminants can result in more representative, and possibly more ecologically relevant, risk assessments ( − ).…”

Section: Introductionmentioning

confidence: 99%

Spatial Variability and Uncertainty in Ecological Risk Assessment: A Case Study on the Potential Risk of Cadmium for the Little Owl in a Dutch River Flood Plain

Kooistra

Huijbregts

Ragas

et al. 2005

Environ. Sci. Technol.

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This paper outlines a procedure that quantifies the impact of different sources of spatial variability and uncertainty on ecological risk estimates. The procedure is illustrated in a case study that estimates the risks of cadmium for a little owl (Athene noctua vidalli) living in a Dutch river flood plain along the river Rhine. A geographical information system (GIS) was used to quantify spatial variability in contaminant concentrations and habitats. It was combined with an exposure and effect model that uses Monte Carlo simulation to quantify parameter uncertainty. Spatial model uncertainty was assessed by the application of two different spatial interpolation methods (classification and kriging) and foraging ranges. The results of the case study show that parameter uncertainty is the main type of uncertainty influencing the risk estimate, and to a lesser extent spatial variability, while spatial model uncertainty was of minor importance. Compared to the deterministically calculated hazard index for the little owl (0.9), inclusion of spatial variability resulted in a median hazard index that can vary between 0.8 and 1.4. It is concluded that a single estimator for a whole flood plain may over- or underestimate risks for specific parts within the flood plain. Further research that expands the procedure presented in this paper is necessary to improve the incorporation of spatial factors in ecological risk assessment.

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Section: Introductionmentioning

confidence: 99%

Spatial Variability and Uncertainty in Ecological Risk Assessment: A Case Study on the Potential Risk of Cadmium for the Little Owl in a Dutch River Flood Plain

Kooistra

Huijbregts

Ragas

et al. 2005

Environ. Sci. Technol.

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“…However, dieldrin levels in birds and mammals were adequately predicted by a model that incorporated distributions of tissue:soil BAFs derived from site-specific data [12]. Likewise, estimates of mercury and polychlorinated biphenyl residues in great blue heron (Ardea herodias) eggs made with a stochastic food web model were in reasonable agreement with concentrations measured in a limited number of egg samples [7].…”

Section: Introductionmentioning

confidence: 54%

“…Menzie et al [11] modeled DDT residues in birds and small mammals with tissue:food bioaccumulation factors, but predictions were plagued by large uncertainties, and validation was limited by small sample sizes. However, dieldrin levels in birds and mammals were adequately predicted by a model that incorporated distributions of tissue:soil BAFs derived from site-specific data [12]. Likewise, estimates of mercury and polychlorinated biphenyl residues in great blue heron (Ardea herodias) eggs made with a stochastic food web model were in reasonable agreement with concentrations measured in a limited number of egg samples [7].…”

Section: Introductionmentioning

confidence: 57%

Testing of metal bioaccumulation models with measured body burdens in mice

Torres

Johnson

2001

Enviro Toxic and Chemistry

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Estimates of chemical accumulation in prey organisms can contribute considerable uncertainty to predictive ecological risk assessments. Comparing body burdens calculated in food web models with measured tissue concentrations provides essential information about the expected accuracy of risk indices. Estimates of arsenic, cadmium, copper, lead, and nickel body burdens in house mice (Mus musculus) inhabiting a seasonal wetland were generated with two small mammal bioaccumulation models. Published soil-to-small mammal bioaccumulation regression models produced accurate estimates of arsenic and lead body burdens but failed to adequately predict copper and nickel levels in mice. Incorporating conservative prediction intervals in the regression models shows potential for successful applications in screening-level risk assessments. A simple mechanistic cumulative ingestion bioaccumulation model overpredicted lead levels in mice generally by less than one order of magnitude but greatly overpredicted concentrations of arsenic, copper, and nickel. Better estimates of absorption and elimination of ingested metals and knowledge of specific arthropod taxa in house mouse diets are likely to improve the accuracy of the cumulative ingestion model. Applying Monte Carlo simulations to the soil-small mammal regression models generated probabilistic estimates of body burdens that were consistent with deterministic results. However, deterministic minimum and maximum predictions of the ingestion model were excessively conservative (widely spaced) relative to lower and upper probabilistic percentiles. Metal levels predicted in individual mice on the basis of mouse-specific parameter values and exposures were not significantly more accurate than bioaccumulation predictions for the sitewide population.

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“…This model includes stochasticity in pollutant effects, sublethal end points, exposure estimates, and pesticide fate discriminated on the basis of landscape structure and time‐scaled treatment of pollutant fate and persistence within exposed biota. Examples of geographic information system approaches using data on real landscapes and population behavior have also been presented [87–89].…”

Section: Metapopulationsmentioning

confidence: 99%

Time and space issues in ecotoxicology: Population models, landscape pattern analysis, and long‐range environmental chemistry

Ares

2003

Enviro Toxic and Chemistry

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Abstract-Advances in ecotoxicology addressing problems of time and spatial scales are presented and interpreted in the frame of concepts on population/community dynamics and landscape pattern analysis. Example deterministic/probabilistic modeling experiments are used to illustrate key concepts. Space and time scales analyzed are single and multigenerations of local populations, metapopulations, community, and ecosystem/landscape. Most population models used in recent ecotoxicology studies are deterministic and do not include a formal treatment of spatial processes, like migration or local random extinction. Some metapopulation models have been applied with success. Upscaling of ecotoxicological results at the community level is less developed, probably because of the inherent complexity of indirect and direct coactions among organisms. Community and ecosystem toxicity end points that could find a broad use in regulatory applications have not yet been identified. Some practical issues like the estimation of the potential for the natural attenuation of toxicity and the transport of contaminants along food chains must be addressed at these scales/levels of biological complexity. The estimation of ecotoxicological effects has been increasingly evolving to integrate modeling and monitoring contaminant transport and fate, landscape pattern analysis, and spatially explicit population dynamics (including direct and indirect communal interactions).

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An approach for estimating ecological risks from organochlorine pesticides to terrestrial organisms at rocky mountain arsenal

Cited by 11 publications

References 23 publications

Spatial Variability and Uncertainty in Ecological Risk Assessment: A Case Study on the Potential Risk of Cadmium for the Little Owl in a Dutch River Flood Plain

Spatial Variability and Uncertainty in Ecological Risk Assessment: A Case Study on the Potential Risk of Cadmium for the Little Owl in a Dutch River Flood Plain

Testing of metal bioaccumulation models with measured body burdens in mice

Time and space issues in ecotoxicology: Population models, landscape pattern analysis, and long‐range environmental chemistry

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