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PostersCrop Protection2018

Applying a mechanistic honey bee colony model to assess multiple factors impacting colony overwintering survival

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Abstract:
Honey bee colony feeding studies are one type of Tier II semi-field studies designed to determine potential effects of pesticides on free-foraging whole colonies during and after dietary intake of a known pesticide concentration. These studies represent a progressively more realistic level of refinement for pollinator studies compared to individual laboratory-based studies since they are intended to reflect a worst-case exposure scenario in the field. Colony feeding studies are designed to test toxicity over a foraging season and following overwintering period. However, such studies are very cost- and time-intensive to conduct, and high overwintering losses of control hives have been observed in some studies. Loss of control colonies indicates that stressors other than pesticides, e.g. resource availability, weather, diseases and beekeeping activities, likely influence colony overwintering survival, confounding the assessment of impacts caused by pesticides. Honey bee colony models have been gaining interest as tools in pesticide risk assessment to inform study design and ultimately, colony-level risks to honey bees. In the current study commissioned by the Pollinator Research Task Force, we apply the honey bee colony model BEEHAVE to simulate colony dynamics observed in negative control colonies from multiple colony feeding studies. Detailed landscape-level data inform the resource availability for the simulated foragers in the model. In addition, weather data, initial colony condition and feeding patterns were analyzed across studies and translated to model inputs. In a calibration step, we adjusted parameters in BEEHAVE to achieve simulated dynamics corresponding to colony conditions reported in the studies. Study data collected in summer and fall were analyzed for predictors of overwintering success of individual colonies. BEEHAVE simulations with different combinations of external factors were used to assess their importance for colony condition. Colony conditions at study initialization and feeding patterns both influenced the colony condition in the fall, and thus, the probability of overwintering survival. Model simulations can be used to estimate colony-level outcomes under conditions deviating from those in the studies to inform study design and extend the use of the available data. Pesticide effects can be included in future model analyses, and analyzed in the context of multiple factors that impact colony health and overwintering success.

Amelie Schmolke (Waterborne Environmental), Farah Abi-Akar (Waterborne Environmental), Nika Galic (Syngenta), Silvia Hinarejos (Sumitomo). Applying a mechanistic honey bee colony model to assess multiple factors impacting colony overwintering survival. Platform SETAC 2018. Sacramento, CA.

PostersWater/Wastewater Assessments2018

Influence of particle size on prospectively modeled environmental concentrations of microplastics in the Sandusky River watershed

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Abstract:
The presence of nano- and microplastics (MPs; particles < 5 mm) in the aquatic environment is a topic of increasing discussion and research. Although measurement and monitoring data are indispensable, there is a need to prospectively estimate concentrations to enable forward-looking assessments and to guide analysis of retrospective ecological analyses. For traditional chemicals, fate and exposure models have been proven to be very helpful and are widely used. However, to date few models exist that simulate the transport and fate of MPs in freshwater systems. This presentation presents simulations of the transport and fate of various-sized MPs emitted from wastewater treatment plants into freshwater riverine systems, and tracks concentrations moving downstream from headwater into Lake Erie. We linked the NanoDUFLOW model (a detailed MP aggregation-sedimentation model integrated in a hydrological and particle transport model) with iSTREEM® (developed to estimate chemical concentration distributions for all rivers receiving WWTP discharges in the US) for a range of particle sizes. This combines the mechanistic realism of NanoDUFLOW, accounting for formation and settling of heteroaggregates, with the US well-established iSTREEM implementation. Depth dependent in-stream first order removal rate constants simulated with NanoDUFLOW were combined with standard iSTREEM output which simulated the emission, transport and water column concentrations of different MP sizes. We modeled floating as well as non-buoyant MP, for sizes ranging from 100 nm to 1000 µm. We also modeled a combined mixture of particle sizes based on effluent measurements from Mason et al (2016). Simulations were spatially explicit with MP concentrations being modeled for the Sandusky River watershed in Ohio containing over 300 miles of river downstream of 20 WWTPs. Modelling results show the effects of population density, MP size and environmental conditions on riverine concentrations and export to Lake Erie. Buoyant as well as the smallest non-buoyant MP fractions can be transported over long distances, reaching receiving waters such as the Great Lakes. In contrast, larger non-buoyant MPs settle more locally in the vicinity of the WWTPs.

Christopher Holmes (Waterborne Environmental), Albert Koelmans (Wageningen University), Scott Dyer (Waterborne Environmental). Influence of particle size on prospectively modeled environmental concentrations of microplastics in the Sandusky River watershed. Poster SETAC 2018. Sacramento, CA.

PostersCrop Protection2018

Spatial and temporal variations of national cropping patterns for higher-tier pesticide exposure assessment

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Abstract:
Pesticides are used on numerous agricultural crops across the United States to control pests and improve food yield and quality. This presentation focuses on the spatial and temporal aspects of a national scale assessment conducted by the Pyrethroid Working Group (PWG) to characterize the potential for pyrethroids to enter flowing surface waters based on a spatially explicit analysis of crop proximity to surface waters using multi-year data on diverse agricultural production patterns. Standard exposure calculations in the USEPA EFED regulatory risk assessment framework assume that 100% of the area around the water body (the Tier II pond) is cropped and treated, and therefore subject to drift and runoff entry. Over two million catchments within the National Hydrography Dataset (NHDPlus) were characterized using geospatial data to develop national or regional metrics related to potential surface water exposure related to crop proximity for more than 10 crop types. Crop locations were based on five years of data from USDA NASS Cropland Data Layer. Results highlight the variability of cropping density at the catchment scale across different geographies and scales, as well as situations in which density of potentially highly exposing crop (e.g., within 200m of surface water) may not match ‘entire catchment’ cropping density patterns. Variations in cropping density (as a proxy for potential exposure) across multiple years will be discussed in relation to how this variability may influence exposure estimates. When examining all catchments containing a specific crop, the 90th percentile crop density values (based on the 200m proximity zone) ranged from 1.3% (for vegetables in FL) to 44.4% (for tree nuts in CA). The resulting datasets provide a useful set of metrics across multiple crops which can be applied to pesticide exposure assessments that may need spatially-explicit refinements related to crop-water interactions. Because the crop proximity results are linked to the NHD+ framework, including these specific attributes into other NHD+-based analyses is extremely efficient.

Christopher Holmes, Joshua Amos (Waterborne Environmental), Paul Hendley (Phasera, Ltd.), Russell Jones (Bayer CropScience), Scott Jackson (Valent). Spatial and temporal variations of national cropping patterns for higher-tier pesticide exposure assessment. Poster SETAC 2018. Sacramento, CA.

PostersCrop Protection2018

A generalized life-history model for assessing indirect effects of pesticides on fish populations

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Abstract:
Assessing population-level effects of stressors, such as pesticides, across species is challenging because effects are influenced not only by individual-level toxicity but also by species’ life history characteristics, ecology, and the duration, magnitude, and frequency of stressor exposure. Additionally, potential indirect population-level effects of stressor exposure (for example, effects resulting from changes in food availability) add further complexity to the assessment. To address these challenges, we developed a generalized population model for small fishes for assessing potential indirect effects of pesticide exposure on population dynamics. We applied the model to 17 species of darter (Percidae: Etheostomatinae) for which life history and diet data were readily available. The selected darter species (including two species listed under the Endangered Species Act) cover a range of life history strategies and diet compositions within the subfamily. We simulated several scenarios of pesticide exposure to assess how potential impacts of a pesticide on various prey species (invertebrates) included in the diets of selected darter species might affect darter population dynamics over extended time periods. We also investigated correlations between life history characteristics and population responses to the exposure scenarios. This analysis provides a framework for predicting food web mediated effects of pesticides on darter species for which little life history information is available. By combining life history variability in fish with estimates of potential indirect effects of pesticides on their prey, our model can provide a valuable tool for incorporating ecological complexity into the assessment process to quantify population-relevant risks to listed and non-target species of small fish.

Nicholas Green, Amelie Schmolke, Brian Kearns, Colleen Roy, Katherine Kapo, Matthew Kern (Waterborne Environmental), Alan Samel (FMC), Valery Forbes (University of Minnesota). A generalized life-history model for assessing indirect effects of pesticides on fish populations. Poster SETAC 2018. Sacramento, CA.

PostersWater/Wastewater Assessments2018

Development of a spatially resolved global mean annual flow dataset for use in environmental risk assessment: A case study for China

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Abstract:
Environmental exposure models for chemicals used widely across large geographic areas and disposed of down the drain are important tools for informing ecological risk assessments. One important element of these models is understanding the dilution of wastewater treatment plant (WWTP) effluent into the receiving stream (dilution factors) which allows for the estimation of in-stream environmental concentrations based on either estimated flow of receiving waters. In the U.S., the iSTREEM model (American Cleaning Institute) estimates dilution of WWTP effluent into receiving streams through the incorporation of a spatial hydrologic network with associated flow data (National Hydrography Dataset Plus) into the exposure model to spatially associate (and route) local WWTP emissions with corresponding local flows. A similar approach for generating localized dilution factors can be employed on the global scale to integrate the chemical emissions component of the model with a hydrologically-connected global river network with associated flow values. The HydroSHEDS and HydroBASINS datasets (Lehner et al. 2008 and 2013) provide a global hydrology dataset that can be used as a spatial hydrologic framework, including a network of streams and rivers and watershed and catchment boundaries. However, flow estimates corresponding to the global river network are a critical attribute that must still be incorporated for exposure modeling. Using China as a case study, a mean annual flow dataset to correspond with the HydroSHEDS and HydroBASINS global data was developed using the well-established Curve Number (CN) approach developed by Natural Resources Conservation Service (NRCS, USDA). The CN approach integrates environmental and landscape features including best available and high-resolution precipitation, soils, and land use characteristics to estimate surface runoff over the land area. The high-resolution runoff grid was spatially combined with hydrology datasets to derive flow estimates across a river network. Global datasets were utilized for model parameters so that the approach could be extrapolated to the global scale, while also providing the flexibility to incorporate best-available data. This presentation will provide a detailed overview of the runoff methodology, validation against measured flow data, and the resulting river flow dataset for China.

Raghu Vamshi, Katherine Kapo, Amy Ritter, Brian Kearns (Waterborne Environmental), and Kathleen McDonough (Procter & Gamble). Development of a spatially resolved global mean annual flow dataset for use in environmental risk assessment: A case study for China. Poster SETAC 2018. Sacramento, CA.

PostersWater/Wastewater Assessments2018

Development of a global environmental exposure modeling framework for risk assessment of chemicals disposed down the drain: A case study for China

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Abstract:
Environmental exposure assessment of chemicals that are disposed down the drain (such as consumer product ingredients) at the global scale within a consistent and accessible framework has remained a challenge over the years, despite advancements in exposure modeling and global and local data resources. Historically, assessment efforts have been tailored and applied to specific geographies and used simplistic approaches rather than to build a spatially resolved global assessment infrastructure. Challenges such as inconsistent, scarce, or rapidly-evolving data resources, particularly for developing countries where assessment needs are high, have further complicated the evolution of spatially resolved global exposure assessment tools. However, through strategic integration of existing global data resources and established modeling tools, a standardized framework and methodology for GIS-based exposure modeling can be developed for the global scale. In this study, we present a spatially resolved global environmental exposure model approach designed to incorporate best-available data and modeling tools, using China as a case study. The global hydrology network from HydroSHEDS and HydroBASINS (Lehner et al. 2008 and 2013), global river flow and population estimates, and best-available country-specific water use and wastewater treatment information were integrated with the GIS-ROUT exposure model (Wang et al. 2005) and iSTREEM® model framework (American Cleaning Institute) to provide a means of estimating the distribution of concentrations of a chemical disposed down the drain across a river network based on chemical production volume and consumer usage estimates. Both wastewater treatment plant effluent and direct discharge are accounted for by the model through estimation of catchment-specific emissions. The spatial nature of the model provides a robust means for estimating variability in environmental exposures. Details of the various model components and generated output for China are overviewed, as well as considerations and discussion regarding on-going extrapolation to the global scale. The framework developed as part of this model is highly adaptable to countries with an abundance of data (e.g., North America, Western Europe, etc.) or those scarce with data (e.g., developing countries) available to parametrize the model.

Kathleen McDonough (Procter & Gamble), Katherine Kapo (Waterborne Environmental), and Raghu Vamshi (Waterborne Environmental). Development of a global environmental exposure modeling framework for risk assessment of chemicals disposed down the drain: A case study for China. Poster SETAC 2018. Sacramento, CA.

PostersWater/Wastewater Assessments2018

A new tool for the toolbox: Predicting multi-pathway emission and fate of contaminants entering freshwater systems in Europe

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Abstract:
Exposure models help to prospectively assess the potential for ecological exposures from releases of substances into the environment. Availability of newer data, increasing computing power and improved methods provide continuing opportunity to improve our ability to predict environmental exposures through models and add to our “toolbox”. We present a new model designed to encompass multi-pathway environmental emissions coupled with environmental fate components, contained in a modular and transparent framework which is scalable and portable to multiple geographies. This spatially-explicit model (presented here for Europe) is based on publicly available datasets, combined with a hydrologic framework containing geographically variable emissions linked to a river network simulating environmental transport via surface water. The hydrologic framework is based on a set of basins and rivers (WWF HydroSHEDs) linked to emission characteristics for each sub-basin (more than 37,000 in the EU-30). Emissions characteristics are derived from point-source wastewater data (EEA Waterbase) as well as diffuse source inputs, accounting for the potential of urban storm water runoff or other overland flow constituents. Concentrations of contaminants are routed through the river network based on local river attributes combined with assumptions about chemical fate in the aquatic environment. Multi-year, high-resolution data on river flow (FLO1K) are leveraged for an expanded set of possible modeling scenarios. Transparency is critical for model understanding and acceptance. Model documentation follows standard documentation protocol proposed by the European Committee for Standardization (CEN) as described in the 2016 CEN workshop: “Promoting the acceptance and use of chemical exposure models through transparent documentation”. Several scenarios will be presented covering different use/emission situations and substance fate characteristics, including the relative importance of different emission pathways (e.g., down-the-drain, urban storm water, land-based diffuse runoff) and environmental media. While the presented material is an example of environmental emission and fate of different substances, it represents a working framework implemented for Europe with viable application to other geographies.

Christopher Holmes, Joshua Amos, Amy Ritter, and Marty Williams (Waterborne Environmental). A new tool for the toolbox: Predicting multi-pathway emission and fate of contaminants entering freshwater systems in Europe. Poster SETAC 2018. Sacramento, CA.

PostersVeterinary Medicines2018

Assessing the environmental risk of pesticides, biopesticides, and anthelmintics used in managing vector-borne diseases

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Abstract:
Insecticides, biopesticides, and parasitical agents are among the arsenal of tools used to control the transmission of vector-borne diseases. In the United States, these products are regulated by the U.S. Environmental Protection Agency under the Federal Insecticide, Fungicide, and Rodenticide Act (FIFRA) or by the Food and Drug Administration under the Federal Food, Drug, and Cosmetic Act (FD&C Act). Chemical and biological releases to the environment can occur from a variety of mechanisms including aerial or ground applications of pesticides to the landscape, wash-off of ectoparasiticides or excretion of anthelmintics from livestock or pets, and down-the-drain discharges from washing treated clothing. Approaches to evaluating the different delivery mechanisms and their potential adverse impacts to non-target organisms are presented through case studies.

W. Martin Williams, Joshua Amos, Megan White Guevara, Amy M. Ritter. Assessing the environmental risk of pesticides, biopesticides, and anthelmintics used in managing vector-borne diseases. ACS 2018. Poster. Boston, MA.

PostersCrop Protection2018

Using geospatial techniques for effective product stewardship

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Abstract:
The goal of this project was to identify agricultural soils reflected in the acetochlor label use restriction, which overlap with shallow ground water. Acetochlor-based products are labeled for use within the United States to control annual grasses and certain broadleaf weeds and can be applied preplant, at-planting, preemergence and/or postemergence to labeled crops. Acetochlor product labels restrict applications within 50 feet of any well where depth to ground water is ≤ 30 ft. The Acetochlor Registration Partnership (ARP – Dow AgroSciences and Monsanto Company) developed voluntary Best Management Practices (BMPs) for acetochlor to reduce the potential for the active substance and its major environmental metabolites in ground water and surface water, following application to agricultural fields. The ARP offers a website (www.arpinfo.com) with resources for end-users to help ensure the effective use and stewardship of products containing acetochlor. Depth to ground water information is often not readily available, which makes it challenging to depict the spatial distribution of areas where the use restriction should be observed. One can point to privacy concerns as a reason for the lack of ground water depth information available to the public. An assessment was conducted to identify crop lands with potential acetochlor use restrictions in Arizona, using geospatial techniques. Arizona’s Department of Water Resources provides historical ground water depth data for point locations via a public monitoring database (http://www.azwater.gov/azdwr/GIS/). Groundwater depth information was extracted from the monitoring database for the period 1995 to 2015. As a data handling procedure, outliers were removed, then cluster and hotspot analyses were performed. The final dataset contained over 12,000-point observations of ground water depth for a 20-year period. Long-term average depths were calculated for each location. To generate a state-wide average groundwater depth map, a spatial interpolation technique was applied to the GIS vector or point dataset. The final ground water map was overlaid with National Agricultural Statistics Service (NASS) Cropland Data Layer (CDL) data to identify agricultural soils with potential concerns. For cotton, the assessment showed that just 3% of the agricultural areas overlap with shallow ground water.

Amy M. Ritter (Waterborne Environmental), Cornelis Hoogeweg (Waterborne Environmental), Mark Anthony Thomas (Monsanto Company), Annette Kirk (Monsanto Company). Using geospatial techniques for effective product stewardship. ACS 2018. Poster. Boston, MA.

PostersCrop Protection2018

Implications of Dataset Selection and GIS Processing on Modelling (MO143)

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Abstract:
Groundwater assessment guidelines provided by the FOCUS groundwater working group (2009) and EFSA (2014) describe succinctly a multi-tiered modelling framework that includes spatiotemporal assessments in the higher tiers; e.g., tier 3a and 3b. As part of the spatio-temporal assessment several GIS and daily climate datasets were recommended. These recommended datasets, however, have been superseded by new datasets in the past few years. Specifically, daily weather and soils data have undergone significant updates, which are reflective of the considerable effort in Europe to update this spatial information. Not only does dataset choice, but also how datasets are being processed in a geographic information system, impact modeling results. Basic assumptions regarding aggregation of data, data slicing for determining climatic zones and data resolution impact our modelling results. In this poster, we will show the implications of data selection and data processing on a distributed modelling framework centered around GeoPEARL 4R. Specifically we will focus on differences between datasets, data set resolution, capturing variability and ones ability to model at the pan-European level within EFSA’s tier 3 guidelines.

G. Hoogeweg, M. Geuvara (Waterborne Environmental). Implications of Dataset Selection and GIS Processing on Modelling. SETAC EU 2018. Poster.