A generalized life-history model for assessing indirect effects of pesticides on fish populations
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.
Model the effectiveness of vegetated filter strips in reducing contaminants in feedlot runoff
The National Pollutant Discharge Elimination System (NPDES) regulations require concentrated animal feeding operations (CAFO) with greater than 1000 head beef cattle to contain feedlot runoff in settling basins designed to hold runoff from a 25-year 24-hour rainfall. CAFO with less than 1000 head may discharge feedlot runoff to nearby waters under NDPES permits if there are certain best management practices (BMPs) in place like settling basins or vegetated filter strips. Runoff from feedlots may contain nutrients or veterinary pharmaceutical residues excreted in animal waste, which under some circumstances could be potentially harmful to aquatic organisms if released directly to nearby surface waters. The objective of this presentation is to model the effectiveness of vegetated filter strips (VFS) in reducing contaminants in feedlot runoff using the WINPRZM and VFSMOD models. Effectiveness of VFS in reducing nutrient concentrations in feedlot runoff will be presented as a case study. WINPRZM was enhanced to simulate runoff from an earthen or concrete uncovered beef feedlot. The model predicts the daily edge-of-field mass of nutrients and other constituents in runoff generated on a feedlot due to precipitation. The feedlot algorithm can model daily manure accumulation, various chemical administration patterns, and the periodic scraping of feedlots. The model uses the SCS curve number method to estimate runoff, a non-uniform mixing model to extract constituents from manure, and the manure erosion equation from the APEX model. The daily edge-of-field mass loadings estimated by WINPRZM are then input to the VFSMOD model which estimates the reduction of loadings based on the size of VFS and the resulting concentrations in runoff discharging from the VFS.
Ishadeep Khanijo, Marty Williams, Amy Ritter, Mark Cheplick (Waterborne Environmental), and Dawn Merritt (Zoetis). Model the effectiveness of vegetated filter strips in reducing contaminants in feedlot runoff. Platform SETAC 2018. Sacramento, CA.
Development of a spatially resolved global mean annual flow dataset for use in environmental risk assessment: A case study for China
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.
Development of a global environmental exposure modeling framework for risk assessment of chemicals disposed down the drain: A case study for China
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.
A new tool for the toolbox: Predicting multi-pathway emission and fate of contaminants entering freshwater systems in Europe
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.
Leveraging national compensatory mitigation conservation offset strategies to proactively address endangered species section 7 authorized take of residual, unavoidable impacts permitted within national scale pesticide biological opinions
The release of the three organophosphate (and pending carbamate) national scale endangered species assessments have presented new challenges to the USEPA, NMFS, and USFWS. The biological evaluations (BEs) have identified many species and/or critical habitats as “may affect, likely to adversely affect” (LAA) which lead to extensive and costly Biological Opinions (BiOPs). The NMFS opinions indicated jeopardy and adverse modification and therefore the production of Recommended Prudent Alternatives (RPAs) which were designed to broadly reduce pesticide loadings with either significant use restrictions or significant drift and runoff controls. The extensive and complex burden on growers will result in significant impact on use of these important crop protection products, with unclear benefit to the specific listed species. Industry and the evaluating agencies are entrusted to both protect species populations while also support sound scientific decisions regarding federal actions related to crop protection chemical use in US agriculture. In some cases, localized use restrictions and buffers may offer adequate protections for a specific species population. In other cases, conservation offsets, of a similar spatial and temporal nature to the authorized take may provide for the agricultural use of crop protection products while improving the viability of the listed species. This talk will focus on the transfer of extensive experience in leveraging national compensatory mitigation strategies (Clean Water Act Section 404, Endangered Species Act Section 7) to mitigate the potential effect of an action and therefore providing both the ability to proceed with the action, providing an offset to address the authorized take provided to the applicant and associated parties, and working toward the species protection and recovery goal. The national application footprint of crop protection products offer risk assessment challenges, but solutions may be found and offramps to avoid expensive and potentially ineffective risk assessment refinements if all parties involved use creativity and tested approaches to holistically integrate the risk assessment findings and recovery plan options. The effect is to better leverage both the ESA and EPA authorization processes, resulting in improved endangered species viabilities (less listings, increased recoveries) and national scale pesticide risk assessments that are more practically linked to the landscape.
Wayne White (W-Squared Consulting), Jody Bickel, Nathan J. Snyder, Matt Kern (Waterborne Environmental). Leveraging national compensatory mitigation conservation offset strategies to proactively address endangered species section 7 authorized take of residual, unavoidable impacts permitted within national scale pesticide biological opinions. ACS 2018. Presentation. Boston, MA.
PresentationsCrop Protection, Water/Wastewater Assessments2018
Atrazine Ecological Monitoring Program: Study design and conduct
Room: Ballroom East – Theater 4
Date: Monday August 22, 2018
Start Time: 8:35AM
Presentation Code: AGRO 228
A high sampling frequency watershed monitoring program, Atrazine Ecological Monitoring Program (AEMP), which began in 2004, has collected over 28,000 water samples representing 284 site years from 75 watersheds across 13 states in the Midwest and the South. The AEMP consists of compliance-based, targeted monitoring in small watershed (< 40 mi2) headwater streams, and is designed to identify environmental conditions in corn and sorghum agricultural watersheds that are susceptible to high surface runoff potential. The AEMP sampling design captured atrazine runoff events following chemical applications to corn and sorghum agriculture when residue levels in the receiving stream are expected to be at their maximum. The breadth of atrazine concentration data from water samples accompanied by watershed characteristics, meteorological data and agronomic data provide a comprehensive understanding of atrazine transport mechanism. The AEMP monitoring data quantifies the upper 20th centile of potential aquatic exposure to atrazine in corn and sorghum growing areas in the United States. The presentation will provide an overview of the site selection process, study design, sample and data collection process, and a summary of important findings.
Jennifer Trask, Les Carver, Megan Cox, Kate Marincic (Waterborne Environmental), Sun Mao Chen (Syngenta Crop Protection). Atrazine Ecological Monitoring Program: Study design and conduct. ACS 2018. Presentation. Boston, MA.
PresentationsCrop Protection, Water/Wastewater Assessments2018
Interpreting water quality monitoring observations through modeling: PRZM/SWAT and SEAWAVE-Q
Room: Ballroom East – Theater 4
Date: Wednesday August 22, 2018
Start Time: 10:35AM
Presentation Code: AGRO 231
Water quality monitoring data, specifically pesticides, can represent best-available exposure profiles related to ecological risk assessment; however, there are challenges in synthesizing these data toward making strong conclusions about the nature of the potential range of risk. Some of these challenges include: data collection frequency, monitoring period duration, interpreting exposure profiles from one location to another, and monitoring system scale. To address these challenges, statistical approaches may be applied to characterize empirical trends. Additionally, process-based numerical systems modeling approaches can offer a different perspective on synthesis and interpretation of monitoring data. A comparison of a statistical and process-based numerical model was conducted to evaluate strengths and weaknesses of representing, synthesizing, and conclusions from monitoring data. This comparison was developed from pesticide measurements of six intensively-monitored HUC12 headwater watersheds in the Midwest. SEAWAVE-Q is a regression model that incorporates a linear trend term, covariates accounting for seasonality, and a transformation of flow to represent a long-term pesticide trend at a specific monitoring location. PRZM/SWAT (pesticide root zone model/soil water assessment tool) is a spatially-distributed hydrologic and chemical transport numerical model that combines upland chemical and hydrologic processes from PRZM and stream flow and chemical transport processes from SWAT. The predictive quality and limitations of these two models was assessed against observed, daily concentration measurements as well as hypothetical data collection frequency and timing (derived from sub-sampling the same data sets). Results suggest that a process-based modeling approach, such as PRZM/SWAT, may be more advantageous when calibration data are available.
Daniel Perkins, Andy Jacobson, Colleen Roy, Farah Abi-Akar (Waterborne Environmental), Wenlin Chen (Syngenta Crop Protection). Interpreting water quality monitoring observations through modeling: PRZM/SWAT and SEAWAVE-Q. ACS 2018. Presentation. Boston, MA.
Evaluation of applied, cross-sector vegetative best management practices in rights-of-way on pollinators
Transmission and pipeline rights-of-way (ROWs) in the U.S. are estimated to occupy approximately 21 million acres, roughly equivalent to the average harvested corn acres in Missouri and Illinois combined. Additionally, there are nearly 4 million miles of roadside ROW and 233 thousand miles of railroad ROW in the U.S. These ROWs dissect agricultural land, urban areas, and natural areas like forests and grasslands. Managed ROWs represent an opportunity to provide habitats for numerous species of plants and animals, including pollinators that provide critical ecosystem services for farms, natural areas, and private homeowners. Strategic creation of pollinator habitat in ROW with respect to cross-sector land management offers large potential benefits to agricultural production, conservation, education, and research. In this work, we hypothesize that the success of managed ROWs to provide quality pollinator habitat is based on a combination of integrated vegetation management (IVM) practices within ROWs, physical habitat characteristics, surrounding land use composition specific to geography/ecoregion characteristics, and pollinators of interest. We evaluate an experimental design aimed at identifying the effects of different IVM practices in ROWs on pollinators. We rely on variabilities in IVM practices and physical characteristics of ROWs reported in literature and other sources to statistically determine which design elements are important to discern potential effects on pollinator habitat quality. The findings will promote informed evaluation of conservation management strategies. Appropriate statistical and field study designs aimed to characterize pollinator success based on IVM practices would allow ROW managers to gain quantitative information to better understand where and when to establish IVMs across spatially explicit, complex and diverse landscapes. Additionally, agricultural land managers may benefit from implementation of certain IVM practices in ROWs that will positively impact crop production while promoting conservation of pollinators and other species.
Farah Abi-Akar, Daniel Perkins, Joshua Amos, Amelie Schmolke (Waterborne Environmental), Stan Vera-Art (Grow With Trees), Iris Caldwell (University of Chicago). Evaluation of applied, cross-sector vegetative best management practices in rights-of-way on pollinators. ACS 2018. Presentation. Boston, MA.
Refined land cover for improving the confidence of pesticide risk assessments
Today, field-scale crop location data are available at higher spatial resolution and classification accuracy than ever before. These data represent “best available scientific data” and can improve the confidence of human health and ecological risk assessments by providing more realistic, site-specific exposure estimates. For example, state-wide agricultural-focused land cover on an annual basis with 56 crop classes and a spatial resolution of ~2 meters is now available in California. Given that California ranks first in total crop receipts in the US and bounds nearly 20% of all federally listed species, increased spatial land use data resolution has the potential for measurable impact in risk assessment. Other novel opportunities exist for incorporating better data by cooperating with specialty crop grower groups who often have field surveys locating their member’s farms (e.g., Florida green beans). High-confidence data can be used to improve Percent Crop Area (PCA) adjustment factors required for estimating drinking water concentrations in human health risk assessments. From a FIFRA/ESA perspective, it is proving difficult to make determinations for many crop-species combinations with any degree of confidence using the spatial information presently available. Although inconvenient, there is arguably a need to incorporate better data as it becomes available.
To demonstrate the impact of the newly-available California land use data, a case study was conducted to contrast the effects of refined crop cover data on spatial proximity to non-target terrestrial species’ habitat. From an aquatic perspective, watershed scale (HUC-12) PCAs calculated using the EPA crop use sites, the 2014 CWS PCA guidance document approach, and the CA DWR land cover will be covered. These results can be used to gauge the impact that higher spatial resolution and classification accuracy can have on pesticide risk assessments relying on crop location information.
Daniel Perkins, Joshua Amos. Refined land cover for improving the confidence of pesticide risk assessments. ACS 2018. Presentation. Boston, MA.