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Join Us at the American Chemical Society's Fall 2024 Meeting

Jan 1, 2015

Stone is excited to again be participating in the American Chemical Society's (ACS) Fall 2024 Meeting, from Sunday, August 18, to Thursday, August 22, in Denver, Colorado.

We have been a longtime supporter of the conference and this year we'll be a platinum sponsor of the ACS Division of Agrochemicals (AGRO) symposia. Our employee-owners are eager to share another year's worth of experience in 12 presentations across six symposia within AGRO. Our scientists and modelers will cover diverse topics such as spray drift from unmanned aerial systems, pesticide loss mitigation, ecological risk assessments, and GLP field studies.

For more information on our participation and to connect with our team at the conference, please see the details below.

SYMPOSIA AND PRESENTATIONS

(All presentations are in Mountain Daylight Time.)

Sunday, August 18

Symposium: Evaluation of Pesticide Mitigation Effectiveness for Endangered Species Risk Assessments (2 to 6 p.m., Room 605, Colorado Convention Center)

4:15 to 4:40 p.m.

Presentation: Development and application of an approach to quantitatively evaluate the impacts of field level mitigation practices on pesticide loss (4107871)

Jody Stryker (Presenter), Michael Winchell, Bettina Miguez (Stone Environmental, Inc.), Lula Ghebremichael, Tony Burd, Zhenxu Tang, Richard Brain, Robin Sur, Tilghman Hall.

Mitigations are being proposed as an a priori mechanism to offset potential risks posed by pesticide registration to “listed” (threatened and endangered) species, though the effectiveness of individual practices has not been thoroughly evaluated. Here we use the USDA supported Agricultural Policy/Environmental eXtender model in an approach for evaluating the impacts of individual and combined mitigation practices, along with the mitigating influence of site-specific field conditions, on pesticide runoff loss. A comparison is made with a regulatory-based scenario, representing vulnerable field conditions. Baseline scenarios were derived from standard EPA Pesticide Water Calculator ecological exposure scenarios for 10 EPA crop groups. A sampling of nationwide datasets was conducted to create thousands of spatially explicit soil/weather/crop use combinations, where for each combination a regionally specific regulatory-based baseline scenario is assigned, and a site-specific scenario developed. For each combination, two pesticides (low Koc and high Koc) were simulated. Scenario-based and site-specific baseline simulations were simulated with the same agronomic operation schedule representative of conventional management, developed using a national dataset of management operations at the state and crop level. Reductions in pesticide loss between the site-specific and baseline scenarios for corresponding field locations were evaluated to better understanding how site-specific factors contribute to variability in both mitigation practices effectiveness and mitigation needs. A common suite of mitigation practices, including contour farming, cover cropping, no-till, conservation-tillage, terracing, in-field vegetative filter strips (VFS), grassed waterways, and edge-of-field VFS were applied to the same sampling of field sites. This enables the quantification of practice effectiveness and the characterization of associated variability attributable to soil characteristics, weather conditions, topography, and cropping systems. We demonstrate that mitigation effectiveness is dependent on site-specific factors and that an approach based on site-specific evaluation could facilitate more targeted, feasible, and informed implementation of practices to support environmental protection goals.

4:40 to 5:05 p.m.

Presentation: Application of the pesticide mitigation assessment tool (PMAT) for evaluating the effectiveness of field-level mitigation practices in reducing off-field pesticide Transport for protection of endangered species (4100719)

Michael Winchell (Presenter), Jody Stryker, Bettina Miguez, (Stone Environmental, Inc.), Lula Ghebremichael, Tony Burd, Zhenxu Tang, Richard Brain, Robin Sur, Tilghman Hall.

Over the past decade, the rise in concern over the potential effects of pesticide use on threatened and endangered species in the United States has spurred research and method development in effective and efficient ecological risk assessment approaches. More recently, emphasis has shifted to determining the mitigations required to reduce off-target pesticide movement and meet endangered species protection goals, with a current focus on quantifying the effectiveness of agricultural use mitigations. Determining both the level of mitigation required and the effectiveness of mitigation options is challenging. Many site-specific factors contribute to the variability in both requirements and effectiveness, including weather conditions, soil characteristics, topography, and cropping systems. While generalized mitigation requirements and effectiveness assumptions can be made and implemented into a regulatory framework with beneficial results, the advantages afforded by a site-specific mitigation effectiveness assessment make a compelling case for adopting such an approach. The Pesticide Mitigation Assessment Tool (PMAT) is a site-specific agronomic modeling tool that predicts pesticide runoff and erosion from agricultural fields based on site-specific conditions. Based on the USDA-supported APEX model, PMAT evaluates both the mitigation requirements for a field and the mitigation effectiveness of a range of common agricultural conservation practices, including combinations of mitigation practices. PMAT automatically evaluates the effectiveness of all feasible mitigation practice combinations, providing the user with a menu of options that meet the requirements for pesticide use and protection of endangered species. The site-specific approach offered by PMAT enables more efficient use of conservation resources, guiding the appropriate level of mitigation and avoiding unnecessary changes in agricultural practices when ecological protection goals are already met. A demonstration of PMAT will be provided with a case study context.

Tuesday, August 20

Symposium: Food Security: Impact of Climate Change on Agriculture & Tackling World Hunger CCC (8 a.m. to noon, Room 603, Colorado Convention Center)

11:05 to 11:30 a.m.

Presentation: Evaluation of carbon sequestration and soil health indicators across a range of agricultural conditions to prioritize adoption of conservation practices (4108031)

Bettina Miguez (Presenter), Jans Kiesel, Jody Stryker (Stone Environmental, Inc.)

Multiple government agencies are actively supporting research and the implementation of programs that encourage the adoption of climate-smart strategies and build resilience in our agricultural systems, including investing in soil health and promoting practices that sequester carbon in agricultural lands. These conservation practices are already being implemented with the goal of improving water quality and reducing off-field impacts of agrochemicals. However minimal quantitative data exist as to the effectiveness of practices or alternative management operations on soil health and carbon sequestration. We use the USDA supported Agricultural Policy/Environmental eXtender model (APEX) in an approach to quantify the impacts of conservation practices and alternative management operations on field and farm-level greenhouse gas (GHG) emissions, carbon sequestration, and key soil health metrics across a range of agricultural field conditions. Spatially explicit field conditions were sampled across the state of Vermont to include a range of soil types, slopes, and weather in agricultural land uses. An initial set of simulations was conducted using these sampled field conditions to evaluate model performance with respect to key soil health metrics (e.g., soil organic matter, bulk density, soil respiration) based on comparison of statistical measures of model outputs with the same statistical measures derived from an observed dataset. A subsequent sensitivity analysis used the same field simulations and added conservation practices and/or management changes to evaluate model response with respect to soil health metrics, GHG fluxes, and carbon sequestration. This work will inform development of an approach and tool to quantity the environmental co-benefits of climate-smart agricultural practices, including improvements in water quality, enhancing soil health, reducing GHG emissions, increasing carbon storage, and mitigating agrochemical impacts on endangered species.

Wednesday, august 21

Symposium: Beyond Honeybees: Exposure, Toxicity & Risk Assessment for Pollinator Insects, Including Species of Conservation Concern (8 a.m. to noon, Room 605, Colorado Convention Center)

8:55 to 9:20 a.m.

Presentation: Development of a risk assessment framework and methodology for non-target terrestrial organisms potentially exposed to plant protection products in Europe (4107935)

Scott Teed (Presenter), Hendrik Rathjens, Dwayne Moore, Michael Winchell (Stone Environmental, Inc.)

Pesticide use often raises concerns about potential impacts on non-target arthropods (NTAs), including pollinators and pesticide registration has required risk assessments for some non-target organisms. However, evaluation schemes need to consider new practices and changes in scientific knowledge. NTAs play a pivotal role in ecosystem services such as maintaining biodiversity, regulating pest populations, and contributing to agroecosystem health. In the European Union (EU), the concept of Specific Protection Goals (SPGs) has been developed to define which ecosystem services need protection and at what temporal and spatial scales. These SPGs are now evaluated through the lens of effect and exposure assessment goals, which are assessed in a tiered approach that progresses from simple and conservative to more complex and realistic. We conducted a review of the current literature and existing gaps in regulatory science and an analysis of EU NTA guidance and its link to SPGs. We then developed recommendations for a systematic and progressive approach to NTA risk assessment exposure and effects analyses that fill existing gaps and align more closely with the EU’s specific protection goals. In this presentation, we will discuss our recommendations including the use of standardized test protocols and species with ecologically relevant endpoints to represent a range of NTA functional groups from various habitat types and feeding guilds. We also discuss next steps, including ideas to establish practical guidance for exposure model selection, predicting exposure over time in three dimensions, and validating NTA exposure models.

11:05 to 11:30 a.m.

Presentation: Common eastern bumble bee (Bombus impatiens) colony health following exposure to an insecticide in a semi-field colony feeding study: Test design and lessons learned (4109003)

Dwayne Moore (Presenter), John Hanzas (Stone Environmental, Inc.), Ana Cabrera, Pamela Jensen, Ph.D., Dr. Daniel R Schmehl

Ecological risk assessment is a key component of the regulatory process required for registration of crop protection products around the world. The western honey bee (Apis mellifera) is the model organism for pollinator risk assessments, yet there is uncertainty over whether it is predictive of risks to other bee species. Consequently, efforts are underway to adapt test methodologies for non-Apis bees. In 2020, we conducted a semi-field colony feeding study in central Vermont with common eastern bumble bee (Bombus impatiens) colonies. The purpose of the study was to assist in the development of a colony-level methodology for this and other bumble bee species. We exposed commercially available bumble bee colonies to five concentrations of an insecticide delivered via supplemental sugar solution for six weeks. Each treatment group was represented by one colony at each of 10 sites. We collected data on various individual- and colony-level endpoints relevant to bumble bee life history on a weekly basis, including production of female reproductive (gyne) offspring, colony mass, foraging activity, and consumption of provisioned sugar solution. Our results indicated that the test design could be used to derive dose-response relationships for several endpoints including the most sensitive endpoint, colony mass. That said, there were lessons learned that could be used to refine the test design. Example lessons include: (1) Unlike honey bees, bumble bees are quite aggressive when disturbed during the daytime necessitating Colony Condition Assessments being conducted at sunset rather than during the daytime, and (2) There was evidence of intra-colony raiding between treatments at each site indicating that spacing of within-site colonies greater than 10 m is necessary. It was also difficult to monitor larvae and determine colony strength during the study because of the structure of bumble bee colonies. In this talk, we will describe the methodology, discuss the lessons learned and make recommendations to facilitate development of formal test guidance for semi-field bumble bee colony studies in the future.

11:30 to 11:55 a.m.

Presentation: Risk assessment for a double stranded RNA product that controls Varroa mite in honeybee hives (4108952)

Dwayne Moore (Stone Environmental, Inc.), Miriam Frugis, Laurent Mezin 

Varroa mites are a serious pest of western honeybee colonies and a primary reason behind the large colony losses reported by beekeepers in recent years. Although there are options for Varroa control, no method has so far proven effective, safe and non-persistent in the environment. Recently, a double stranded RNA product, EP15 (vadescana), was developed to control Varroa mites in honeybee hives by blocking the expression of calmodulin protein in reproductive mites through the RNAi mechanism. EP15 has a nucleotide sequence specific to the calmodulin messenger RNA of Varroa mites and thus exhibits little to no cross-toxicity to other organisms. EP15 is formulated as a sugar solution in a perforated pouch to be placed inside the honeybee hive in the spring and fall. We conducted a risk assessment to determine whether EP15 poses a risk to honeybees. In laboratory chronic studies, effects on adult and larval bees were observed at the highest proposed formulation concentration due to the viscosity of the formulation which resulted in limited feeding. These studies involved feeding bees ad libitum and thus were worst-case scenarios because the only available dietary source was the treated test solution. In the real world, honeybees forage extensively outside the hive. Studies of residues in outdoor honeybee hives indicated that dilution in nectar cells ranged from 2 to 250-fold. Dilution in brood food was 1,400 to 10,000-fold. Thus, larval and adult bees in treated hives would be exposed to EP15 concentrations well below those included in the laboratory studies. A honeybee brood colony study conducted in the field demonstrated no adverse effects at concentrations 10-fold higher than proposed for the EP15 formulations. The available fate and ecotoxicity studies demonstrated that EP15 residues outside the hive are negligible, and what little EP15 is available outside the hive is rapidly degraded. We thus conclude that the proposed EP15 formulations do not pose a risk concern for honeybees and other pollinators.

Symposium: Environmental Fate, Transport & Modeling of Agriculturally-related Chemicals (8 a.m. to 6 p.m., Room 501, Colorado Convention Center)

10:40 to 11:05 a.m.

Presentation: Novel design for rainwater collection and sampling across the Midwestern and Southern United States (4109950)

Chloe Eggert (Presenter), Jacob Mitchell, Brent Toth (Stone Environmental, Inc.)

In late winter of 2022, Stone Environmental began planning and designing the field equipment for a regional monitoring study to quantify the amount of off-target crop protection products in the environment in agricultural areas beginning in the spring of that year. This presentation will describe the approach taken to collect the required samples given the timeframe and the supply chain challenges at that time. We will discuss the mixture of off-the-shelf and customized equipment options employed, the remote monitoring performed, the measures taken to ensure sample integrity, as well as the various data collection methods and the approach to link them together while maintaining consistency across all monitoring locations.

2:30 to 2:55 p.m.

Presentation: Overlap analysis in Endangered Species risk assessments: Current status and future directions (4097301)

Hendrik Rathjens (Presenter), Michael Winchell, Scott Teed (Stone Environmental Inc.) 

Spatial overlap analysis between pesticide use sites and endangered species is an essential component in the U.S. EPA’s endangered species risk assessment framework and their biological evaluations. This analysis quantifies the overlap between species ranges or critical habitat (CH) and pesticide use sites and the furthest distance from treated sites where effects on listed species or CH are reasonably expected to occur (i.e., action area). The EPA’s approach typically examines three scenarios: a conservative assumption that 100% of the potential areas are treated (100% PCT), and two refined analyses incorporating upper bound (maximum) and central (median) usage scenarios. The 100% PCT scenario provides a screening-level quantification of the co-occurrence between potential pesticide action areas with the listed species ranges and CH. Previous studies have demonstrated the importance of incorporating pesticide usage data into risk assessments to achieve more accurate, reasonable, and realistic risk estimations. The EPA acknowledges this through usage-based refinements applied to listed species or CHs with at least 1% overlap with the potential action area. The maximum usage scenario is primarily used to refine the overlap analysis and evaluate the likelihood of exposure for those species. This presentation explores the EPA’s methodologies and introduces a compatible approach that registrants can proactively use to identify potentially high-risk uses for streamlining the registration or re-registration process. This presentation critically discusses the assumptions made for the maximum usage scenario and their implications for the risk assessment outcome. Further, it introduces an alternative probabilistic approach aimed at enhancing accuracy and replacing the EPA’s maximum and median usage scenarios. Our findings underscore the critical role of the EPA’s assumptions in the maximum scenario and demonstrate how usage data can substantially refine overlap estimates. Our advanced approach, in turn, facilitates a probabilistic characterization of the likelihood of exposure and a more accurate risk determination for listed species and their CH and thus a methodological evolution for endangered species risk assessment.

2:55 to 3:20 p.m.

Presentation: Machine learning-based streamflow prediction for large-scale pesticide exposure assessments (4104709)

J. Kiesel (Presenter), M. Winchell, (Stone Environmental, Inc.) C. Hassinger

Depending on the location and physical properties of water bodies, they exhibit a different vulnerability to the application of pesticides on nearby agricultural areas. Vulnerability of water bodies to pesticide exposure decreases with increasing distance from the water body to the application area. If streams are exposed to pesticides, the magnitude of streamflow additionally governs mixing and dilution, and therefore the potential impacts on aquatic life. A common and conservative hydrological indicator for exposure assessments is the streamflow rate that is exceeded 90% of the time during and after the application period (Q10). For selected pesticide application areas across six provinces of New Zealand, the calculation of representative Q10 streamflow rates was required for a higher-tier exposure assessment in which flowing water bodies were in close proximity to agricultural fields and thus could be impacted by spray drift and/or runoff. However, particularly in such large-scale, country-wide assessments, the quantification of streamflow rates in proximity to individual application areas is challenging due to the high spatial resolution needed to resolve a fine headwater stream network and the general lack of gaged streamflow locations covering the diversity of stream characteristics of interest, particularly for small streams. Therefore, four different modeling approaches were applied, tested and validated to predict the Q10 hydrologic indicator for the entire stream network relevant for the application areas. Data required to drive the models involved streamflow gauge data from more than 500 gauges, which were thoroughly quality controlled, processed, and sub-selected. In addition, environmental characteristics were described by 78 predictor variables derived from soil, landuse, climatic, and topographic datasets. Among the four models, a Random Forest (RF) machine learning algorithm performed best in predicting the Q10 indicator on the high-resolution stream network and additionally provided a quantification of prediction variable importance to allow an analysis of the driving hydrological processes. The presented methodology is transferable to other regions and provides an efficient and reliable approach to estimate streamflow rates for large-scale pesticide exposure assessments.

4:40 to 5:05 p.m.

Presentation: Wide area (landscape level) exposure risks from agricultural application of volatile compounds. (4110179)

Marco Propato (Presenter), Michael Winchell, (Stone Environmental, Inc.), S. McMaster

Depending on the location and physical properties of water bodies, they exhibit a different vulnerability to the application of pesticides on nearby agricultural areas. Vulnerability of water bodies to pesticide exposure decreases with increasing distance from the water body to the application area. If streams are exposed to pesticides, the magnitude of streamflow additionally governs mixing and dilution, and therefore the potential impacts on aquatic life. A common and conservative hydrological indicator for exposure assessments is the streamflow rate that is exceeded 90% of the time during and after the application period (Q10). For selected pesticide application areas across six provinces of New Zealand, the calculation of representative Q10 streamflow rates was required for a higher-tier exposure assessment in which flowing water bodies were in close proximity to agricultural fields and thus could be impacted by spray drift and/or runoff. However, particularly in such large-scale, country-wide assessments, the quantification of streamflow rates in proximity to individual application areas is challenging due to the high spatial resolution needed to resolve a fine headwater stream network and the general lack of gaged streamflow locations covering the diversity of stream characteristics of interest, particularly for small streams. Therefore, four different modeling approaches were applied, tested and validated to predict the Q10 hydrologic indicator for the entire stream network relevant for the application areas. Data required to drive the models involved streamflow gauge data from more than 500 gauges, which were thoroughly quality controlled, processed, and sub-selected. In addition, environmental characteristics were described by 78 predictor variables derived from soil, landuse, climatic, and topographic datasets. Among the four models, a Random Forest (RF) machine learning algorithm performed best in predicting the Q10 indicator on the high-resolution stream network and additionally provided a quantification of prediction variable importance to allow an analysis of the driving hydrological processes. The presented methodology is transferable to other regions and provides an efficient and reliable approach to estimate streamflow rates for large-scale pesticide exposure assessments.

Symposium: Unmanned Aerial Systems (aka Drones): Pesticide Spraying & Other Agricultural Applications (2 to 6 p.m., Room 406, Colorado Convention Center)

2:30 to 2:55 p.m.

Presentation: Study design, methods, and data collection from UAV spray drift studies conducted in 2023 for the Unmanned Aerial Pesticide Application System Task Force (UAPASTF) (4104815)

Aaron Rice (Presenter), Ben Brayden, Brent Toth, Chloe Eggert, Jacob Mitchell, Meghan Arpino, Tim Dupuis (Stone Environmental, Inc.)

In support of the Unmanned Aerial Pesticide Application System Task Force (UAPASTF) focus on off-site movement, five GLP UAV drift trials were conducted in five countries during 2023 to generate relevant and reliable data in different geographic and regulatory regions. Study specific protocols were developed in adherence to the UAPASTF Proposed Guidance Protocol, Requirements & Specifications for Field Drift Trials when using Unmanned Aerial Vehicles (UAVs) and field trials were successfully completed in Canada, Brazil, Hungary, Spain, and the US. This presentation will focus on study design, methods, and data collection for the 2023 trials. Topics covered may include swath pattern testing, measuring and recording inflight UAV spray pressure, pairing UAV and reference ground sprayer events, logistical challenges and solutions, fluorometric analysis, and results.

4:40 to 5:05 p.m.

Presentation: Evaluation of a mechanistic model for simulating spray drift from unmanned aerial system (4108500)

Sebastian Castro, Michael Winchell (Stone Environmental, Inc.), Z. Tang, (Presenter)

The integration of Unmanned Aircraft Systems (UASs) into agricultural practices marks a significant technological leap in crop management and protection strategies. The phenomenal growth of UAS pesticide applications has raised questions about their impact on off-target movement of crop protection products through spray drift. Using field studies, we evaluated a mechanistic model AGDISPpro on spray drift prediction for two unmanned aerial systems (UAS), and the results demonstrated good performance of the model in simulating in-swath and off-field deposition from UAS. However, there are different types of UAS varied by weight, number of rotors, payload and other characteristics. Few data in the scientific literature have investigated the impact of these characteristics on spray drift. To further assess the model performance on varied UAS, we expanded our evaluation to include additional UASs using published field studies. Customized UASs used in the field studies were incorporated in AGDISPpro and applied in the model simulations. Specifically, we modeled datasets developed from field applications using the following UASs: the PV35X (PrecisionVision) and TTAM6E (Beijing TT Aviation Technology)- both hexacopters, and the TTAM8A (Beijing TT Aviation Technology) which has 8 rotors. Model parameterization and predictions compared against field measurements will be presented, along with a comparison of spray drift potential of different types of UAS. This work will inform regulation development in selecting representative UASs for off-target spray drift exposure assessments.

CONNECT WITH US DURING THE CONFERENCE

If you're also attending, join us for one of our presentations or contact Michael Winchell, John Hanzas, or Scott Teed directly to set up a time to connect.

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