Prospective Aquatic Risk Assessment for Mixed Land Use Catchments: A Tool to Combine Multi-Source Chemical Emissions Over Time
SETAC Session Title: Improving the Environmental Assessment of Complex Composition Substances and Mixtures for Chemicals Management
Presentation Date: Thursday November 16, 2017
Presentation Time: 3:40 PM
Location: Session Room 101BI
In 2015, a SETAC Pellston® workshop was held to help inform decision making around aquatic mixture risk assessments of chemicals using exposure scenarios for agricultural, domestic, and urban scenarios. Prospective emissions of 37 chemicals were estimated and combined into daily mixture profiles over a 10-year period. The mixture risk assessment looked at daily individual substance risk quotients (RQs) and multiple substance ∑RQ (assuming concentration addition), along with implementation of the Maximum Cumulative Ratio (MCR) approach. Risk was examined at the bottom of a hypothetical catchment containing a changeable configuration of sub-catchments defined by three land use types (agricultural, city [domestic + urban], natural). An underlying spreadsheet-based model was developed to integrate daily loadings of individual chemicals from each sub-catchment, combined with a simplified hydrologic model, to produce a time series of mixture profiles at the catchment outlet. Catchment configuration is changed by varying the placement, type and number of sub-catchments in the system. Model results show a high spatio-temporal variability of individual chemical concentrations and their mixtures based on catchment configuration. Even constant emissions of household chemicals showed variability in concentration related to river flow driven by rain events. The outcome of the overall Pellston study demonstrated that a scenario-based approach can be used to determine whether mixtures of chemicals pose risks over and above any identified using existing approaches for single chemicals, how often and to what magnitude, and ultimately which mixtures (and dominant chemicals) cause greatest concern. In this talk focusing on the underlying catchment model, mixture risk results for different catchment configurations will be presented.
Christopher Holmes (Waterborne Environmental), Colin Brown (University of York), Dick De Zwart (Mermayde), Jerome Diamond (Tetra Tech), Scott Dyer (The Procter & Gamble Company), Stuart Marshall (Unilever), Leo Posthuma (RIVM; Radboud University). Prospective Aquatic Risk Assessment for Mixed Land Use Catchments: A Tool to Combine Multi-Source Chemical Emissions Over Time. Platform SETAC 2017. Minneapolis, MN.
Using Population Models to Gain Insights into Direct and Indirect Effects of Pesticides on Listed Fish Populations
SETAC Session Title: Ecosystem Services, Stakeholder Values, and Sustainability
Poster Date: Thursday November 16, 2017
Location: Exhibit Hall
The U.S. Endangered Species Act has the goal of protecting the continued existence and diversity of species as part of the natural heritage of the nation. The law recognizes this ecosystem service provided by endangered species that may be valued for cultural, aesthetic, recreational or other reasons. The protection goal for listed species is generally the long-term survival and recovery of species populations. Ecological models provide a tool to evaluate this protection goal as part of the total services provided by an ecosystem. We present a population model for the threatened Slackwater darter (Etheostoma boschungi) to identify stressors and assess levels of stress that may affect population decline. The model describes Slackwater darter population trends by considering indirect effects of stressors on the food web and food availability. Using readily available information in the published scientific literature, we incorporated relationships between reduced food availability and body size, survival, and fecundity in fish into the Slackwater darter model. We analyzed exposure-effects relationships of a pesticide with the model to estimate exposure levels that could cause long-term effects on population growth and abundance. Further, we assessed the applicability of the modeling approach to a second listed fish species to explore the application of a species-specific model to related species with similar life histories. By combining information on life history and direct and indirect effects, population models can provide a valuable tool to assess potential risks of pesticides to populations of listed and other non-target species over ecologically relevant time periods.
Amelie Schmolke, Brian Kearns, Colleen Moloney, Katherine Kapo, Matthew Kern (Waterborne Environmental), Alan Samel (DuPont), Valery Forbes (University of Minnesota), Aldos Barefoot (DuPont). Using Population Models to Gain Insights into Direct and Indirect Effects of Pesticides on Listed Fish Populations. Platform SETAC 2017. Minneapolis, MN.
Population Model for the Mead’s Milkweed: A Tool for Pesticide Risk Assessment for a Threatened Plant
SETAC Session Title: Aquatic and Terrestrial Plants in Ecotoxicology and Risk Assessment
Presentation Date: Thursday November 16, 2017
Presentation Time: 8:40 AM
Location: Session Room 200BC
Population models can address the potential impacts of pesticides on populations or species rather than individuals, and have been identified as necessary tools for pesticide risk assessment of species listed under the Endangered Species Act (ESA). Few examples of population models developed for this specific purpose are found in the scientific literature, especially population models addressing potential risks of pesticides to listed plants. We present a population model for Mead’s milkweed (Asclepias meadii), a species listed as threatened under the ESA throughout its range across the Midwestern US, as an example of a long-lived and slow-reproducing herbaceous plant species. With the model, we test different herbicide dose-response curves as derived from standard test species to assess a range of realistic organism-level responses and their relationships to population-level outcomes. We combine assumptions about organism-level toxicity of the herbicides with realistic exposure scenarios over extended time periods. Population dynamics and abundances over time with and without exposure to herbicides are compared. With the population model of the listed milkweed, we can estimate potential effects of herbicides to populations which represent an ecologically relevant endpoint for risk assessments. Scenarios relating to the toxicity of pesticides to the species, spatial and temporal exposure patterns, and assumptions about other stressors affecting populations of the species can be assessed. To assess hypothetical mitigation scenarios, buffers (i.e. setback herbicide spraying distances from species locations) are imposed within the model in order to evaluate their corresponding influence on population metrics as a function of distance.
Amelie Schmolke (Waterborne Environmental), Richard Brain (Syngenta), Valery Forbes (University of Minnesota). Population Model for the Mead’s Milkweed: A Tool for Pesticide Risk Assessment for a Threatened Plant. Platform SETAC 2017. Minneapolis, MN.
PresentationsAgriculture and Food2017
Prospective Methods for Characterizing Likelihood of Pollinator Protection Resulting from Programmatic Conservation Initiatives
SETAC Session Title: Assessing the Role of Contaminants in the Decline of Prairie Complex Pollinators
Presentation Date: Tuesday November 14, 2017
Presentation Time: 10:40 AM
Location: Session Room 101AJ
Over 4,000 species of native bees are responsible for crop pollination activity in the United States, the majority in solitary nests. County-, State-, and Federal-scale initiatives and programs have been put in motion toward programmatic protection of pollinators. Programmatic initiatives tend to focus on habitat creation, preservation, or restoration and should be accounted for in conservation efforts to protect pollinator species. These habitat initiatives may be a simple means to rapidly respond to pressures to implement protection measures, but may be less impactful or less appropriate for certain species of pollinators than others. A methodology for evaluating programmatic conservation initiatives and associated impact on pollinator protection is warranted and would require more specific identification of species that are the recipients of protection. The specific characteristics and requirements of the identified species should be addressed. Difficult and important discussions about cost-benefit and likelihood of protection success may be more fruitful if a common methodology is followed. We present preliminary methods that benchmark characteristics of land use change/management and pollinator life history features through programmatic conservation initiatives that yield the most benefit for pollinator protection. Land use change, prompted by potential conservation efforts, is systematically compared to focal species’ requirements according to their life history traits and habitat requirements. As an example, we use the Rusty Patched Bumble Bee (Bombus affinis), a species recent listed as endangered, as a test case for benchmarking potential protection through the introduction of different conservation initiatives, such as creation of conservation reserve program land, pollinator corridor creation, cover crops, and integrated pest management.
Daniel Perkins (Waterborne Environmental), Amelie Schmolke (Waterborne Environmental), Farah Abi-Akar (Waterborne Environmental), Andrew Jacobson (Waterborne Environmental). Prospective Methods for Characterizing Likelihood of Pollinator Protection Resulting from Programmatic Conservation Initiatives. Platform SETAC 2017. Minneapolis, MN.
Developing Population Models for Pesticide Risk Assessment: A Systematic Approach Using the Example of Herbaceous Plants
SETAC Session Title: 21st Century Approaches for Capturing Diversity in Species Sensitivity to Chemicals
Presentation Date: Monday November 13th, 2017
Presentation Time: 10:40 AM
Location: Auditorium 1
The sensitivity of populations to stresses from chemical exposure is not linearly related to sensitivities of individuals, but depend on a species’ life history, population dynamics, and various other factors. Population models provide a means to assess stressors in the context of population-level dynamics, species and habitat characteristics. They are increasingly recognized as important tools in pesticide risk assessment and were recently identified as essential for endangered species assessment in the U.S. However, few population models for this specific purpose have been developed to date. Developing such models in a systematic and transparent way would increase their applicability and credibility and reduce development efforts.
We present a systematic and transparent approach to developing population models. The guidance informs the model developer on necessary steps that consider the specific questions to be addressed by the model through four phases. In the first phase, the model developer systematically reviews details of the model objectives. Data available for the modeled species and stressor(s) are compiled in table format during the second phase. Starting with a conceptual model of the species’ life history in the third phase, seven decision steps guide the model developer through decisions on what and how details should be represented in the model based on the model objectives and data availability. Decision steps may need to be revisited iteratively during the third phase. In the fourth phase, the model developer compiles a summary of the conceptual model including any underlying assumptions. Uncertainties arising from data and model assumptions are also explicitly characterized. We provide an example decision guide for the development of population models of herbaceous plants applied in pesticide risk assessment. We emphasize how different species’ characteristics are represented in population models, and how they can inform species-specific chemical risk assessment. The adaptation of the approach to developing population models for other taxonomic groups and applications will be discussed.
Amelie Schmolke (Waterborne Environmental), Katherine Kapo (Waterborne Environmental), Pamela Rueda-Cediel (University of Minnesota), Pernille Thorbek (Syngenta), Richard Brain (Syngenta), Valery Forbes (University of Minnesota). Developing Population Models for Pesticide Risk Assessment: A Systematic Approach Using the Example of Herbaceous Plants. Platform SETAC 2017. Minneapolis, MN.
Prospective Risk Assessment for Mixtures of Agricultural Chemicals in Surface Water: Results of Two Case Studies
In 2015, a SETAC Pellston workshop was held to help inform decision making around aquatic mixture risk assessments of chemicals using exposure scenarios. The efforts were grouped into three areas of chemical origination: agriculture, domestic, and urban influences. The agricultural land use combined effect measures with exposure scenarios of chemical mixtures for field and catchment-scale using procedures that are recognized and used in regulatory schemes in the U.S., Europe and other parts of the world. Chemicals modeled were those used in crop protection and livestock production, and were considered to occur as mixtures (in time and space). These assessments considered inputs from spray drift, surface runoff and erosion on a daily basis. Case studies included a single unit scenario modeled as a wheat field in the UK, consisting of crop protection applications of 13 substances annually over the course of 20 years. This scenario used standard FOCUS soil, weather and receiving water body information for consistency with regulatory assessments. A second case study of a multi-unit catchment scenario consisted of a combination of corn fields, pasture, and feedlot inputs based in part on the US EPA Iowa corn scenario used in pesticide registration evaluations. Manure from treated cattle containing two pharmaceutical substances was applied to corn fields as fertilizer, and also originated from pastured cattle. Twelve different active substances for crop protection were modeled. A mixture risk assessment looked daily individual substance risk quotients (RQs) and multiple substance ∑RQ, along with implementation of the Maximum Cumulative Ratio (MCR) approach. When assessed on the basis of Tier 1 effects data using the most sensitive of three taxonomic groups and assuming concentration addition, potential risk from individual chemicals and mixtures (even in cases when no single substance triggered risk, i.e., MCR Group III) was quantified in magnitude and duration. Consideration of the sensitivity of individual different taxa in a Tier II assessment reduced the reported risk from chemical mixtures in both case studies. Results demonstrate that a prospective scenario-based approach can be used to determine the potential for mixtures of chemicals to pose risks over and above any identified using existing approaches for single chemicals, how often and to what magnitude, and ultimately which mixtures produced greatest concern.
Christopher Holmes (Waterborne Environmental), Mick Hamer (Syngenta), Colin Brown (University of York), Russell Jones (Bayer CropScience), Lorraine Maltby (The University of Sheffield), Eric Silberhorn (CVM/USDA), Jerold Teeter (Elanco Animal Health), Michael Warne (Queensland Government), Lennart Weltje (BASF). Prospective Risk Assessment for Mixtures of Agricultural Chemicals in Surface Water: Results of Two Case Studies. Platform ACS 2017. Washington DC.
Approaches for Defining Spatially Explicit Habitat in the Absence of Federally Declared Critical Habitat
Of the approximately 1,800 listed species in the U.S., nearly 660 terrestrials and 140 aquatics are without federally-declared Critical Habitat (spring 2017) suitable for use in assessing the potential impact that pesticides may have on a species or its habitat. To provide information important in filling this data gap, scientifically-defensible approaches for defining spatially-explicit, sub-county habitat locations were assessed. Thirty aquatic and terrestrial species from within each of the taxonomic groups, some inhabiting wide ranges and others with more specific habitat requirements, were chosen as case studies. The intent was to develop a scalable workflow informed by any number of scenarios that may be faced when mapping the habitats of listed species.
Both deductive and inductive mapping approaches were used to identify locations potentially suitable for a species. Inductive habitat mapping was performed via the Maxent© maximum entropy model which requires a set of input habitat variables determined a priori relevant to the species, in conjunction with species occurrence records, to generate a continuous occurrence prediction map within the defined species range. Deductive mapping, on the other hand, does not require species occurrence data, but rather expert knowledge of a species’ habitat requirements. The modeler must interpret textual habitat descriptors and extract quantitative thresholds specific to the species.
This presentation will discuss the organizational challenges faced when generating spatial habitat data for a large number of species. While the habitat generated in this study does not represent “Critical Habitat”, it is representative of the physical and biological features required by a species and is of appropriate accuracy and resolution for use with the potential pesticide use sites in pesticide risk assessments. Look for a companion poster in this session that elaborates on the technical approaches taken to map the habitats of aquatic species without Critical Habitat.
Joshua Amos, Brian Kearns (Waterborne Environmental), Steve Kay (Pyxis Regulatory Consulting). Approaches for Defining Spatially Explicit Habitat in the Absence of Federally Declared Critical Habitat. Platform ACS 2017. Washington DC.
Inductive Habitat Modeling as a Tool to Predict Listed Aquatic Species’ Occurrence in the Absence of Critical Habitat
Approximately 1,800 species are listed as threatened or endangered within the U.S.; of those, approximately 400 live primarily in aquatic habitats. Although federally declared Critical Habitat has been defined for some species, approximately 450 do not have sub-county habitat other than observations noted in listing documents (spring 2017). While listed terrestrial species face a similar dilemma, an increasingly robust suite of spatial datasets has enabled the estimation of spatially explicit habitat using deductive mapping (e.g. USGS GAP). Defining the habitat of aquatic species is particularly challenging given the complex relationship between aquatic ecosystems and the terrestrial landscape (i.e., watershed) contributing to the habitat. For this study, over a dozen listed aquatic species were assessed for the purposes of developing a methodology for defining sub-county, spatially-explicit habitat in the absence of federally declared Critical Habitat.
The Maxent© species distribution model (SDM) was used to inductively determine species occurrence likelihood for aquatic species within the counties and HUC-08 watersheds of known occurrence. Species observation records from USFWS documents were used in conjunction with textual habitat descriptions to train the model to predict occurrence likelihood. The NHDPlus was used as the modelling framework, which captures hydrologic variation at the catchment basin scale and describes physical variables including velocity, flow, and stream order. Other habitat variables like runoff potential and dam density from the StreamCAT database, also built around NHDPlus, were also used in the model. Ultimately, a habitat suitability map was generated and while it is not officially “Critical Habitat”, setting prediction thresholds to show where species are likely to occur may allow conservation managers and pesticide risk assessors to make informed decisions based on a higher resolution species habitat than currently available. This presentation pairs with another in the same session discussing the larger mapping effort of thirty aquatic and terrestrial species without Critical Habitat.
Brian Kearns, Joshua Amos (Waterborne Environmental), Steve Kay (Pyxis Regulatory Consulting). Inductive Habitat Modeling as a Tool to Predict Listed Aquatic Species’ Occurrence in the Absence of Critical Habitat. Poster ACS 2017. Washington DC.
Comparison of Surface Water Pesticide Environmental Risk Assessment Tools in U.S. and China
Given the emerging regulatory development in pesticide environmental exposure risk assessments, China has established a set of ecological risk assessment guidelines for its pesticide registration regulation. There are established tools for rice paddy and groundwater exposure risk assessment, but a higher tier risk assessment tool for pesticide exposure in surface water from dryland crops has not been finalized yet. The Pesticide Risk Assessment Exposure Simulation Shell (PRAESS) model is a platform designed to evaluate the potential for pesticide exposure to occur in surface water resources in China. The Pesticide Root Zone Model (PRZM) component in the PRAESS model has been accepted as the tool to evaluate potential pesticide exposure to soil organisms. The PRAESS model was evaluated systematically with comparisons to the existing U.S. and E.U. regulatory surface water models (i.e. Pesticide Water Calculator (PWC) from the U.S. and FOCUS SWASH model from the E.U.). Respective standard crop scenarios were modeled to understand the PRAESS results in relative comparison to the distribution of those from U.S. and E.U. modeling results. Surface water runoff and pesticide concentrations from the PRAESS and PWC models are also compared to each other under the same weather, crop and soil settings. In addition, the PWC and PRAESS models are evaluated against past small plot field runoff study data. The evaluation is expected to provide scientific and technical support for the tested models to be used as surface water exposure assessment tools with understood predictability for regulatory decision-making.
Dazhi Mao, Mark Cheplick (Waterborne Environmental), Wenlin Chen (Syngenta). Comparison of Surface Water Pesticide Environmental Risk Assessment Tools in U.S. and China. Platform ACS 2017. Washington DC.
Using Population Models to Gain Insights into Direct and Indirect Effects of Pesticides on Listed Fish Populations
The current approach of assessing risks to fish from exposure to pesticides relies on effects data on individuals. However, the effect of a single stressor on populations may depend on multiple factors including a species’ life history, which life-history traits are impacted by the stressor and to what degree, the duration and frequency of stress occurrence, and variability in population dynamics. Population models can combine effects of stressors observed on organisms with species-specific life histories and variability in population dynamics, and project population-level outcomes over extended time periods. In this study, we used an existing matrix population model of the Slackwater darter (Etheostoma boschungi), a species listed as threatened under the U.S. Endangered Species Act, to assess stress levels that may cause population decline. We represented direct effects as changes in survival and fecundity, and indirect effects as decreased food availability. From the scientific literature, we used information on the relationships between reduced food availability, body size and survival and fecundity in fish, and incorporated these relationships in the Slackwater darter model. We analyzed exposure-effects relationships of a pesticide with the model to estimate exposure levels that could cause long-term impacts on population abundance and persistence. Further, we assessed the applicability of the modeling approach to a range of species by analyzing model predictions for potential pesticide impacts on survival and reproductive rates for related fish species with similar life histories. By combining information on life history and direct and indirect effects, population models can provide a valuable tool to assess potential risks of pesticides to populations of listed and other non-target species over ecologically relevant time periods.
Amelie Schmolke, Brian Kearns, Matthew Kern, Katherine Kapo, Colleen Moloney (Waterborne Environmental), Valery Forbes ( University of Minnesota), Aldos Barefoot (DuPont Crop Protection), Hugo Ochoa-Acuna. Using Population Models to Gain Insights into Direct and Indirect Effects of Pesticides on Listed Fish Populations. Poster ACS 2017. Washington DC.