Models and Tools for National Level Listed Species Biological Evaluations of Neonicotinoid Insecticides
Introduction
The tools and models on this web page were developed for conducting national level biological evaluations (BEs) for pesticides. The methods associated with these tools are described on the Revised Method page. These tools were first applied to the BEs for carbaryl and methomyl. All models and tools included on this page were subjected to a quality assurance and quality control review.
Brief descriptions of tools and models that are used to estimate exposures and risks to listed species and the taxa they depend upon for prey, pollination, habitat and dispersal are provided below. Also provided are tools that are used to characterize effects using available toxicity data.
Models and Tools for Estimating Exposure in Aquatic Habitats
Pesticide in Water Calculator (PWC)
The Pesticide in Water Calculator (PWC), is used to estimate pesticide concentrations in water bodies that result from pesticide applications to land. The PWC is designed to simulate the environmental concentration of a pesticide in the water column and sediment and is used for regulatory purposes by the EPA's Office of Pesticide Programs (OPP). The PWC uses PRZM version 5.0+ (PRZM5) and the Variable Volume Water Body Model (VVWM), replacing the older PE5 shell (last updated November 2006), which used PRZM3 and EXAMS. This updated model can be found on the Models for Pesticide Risk Assessment web page.
Pesticide in Water Calculator (PWC) ESA Automation Tool, v. 3.0 (XLSX)
The PWC ESA Automation Tool is a spreadsheet that has been built to assist in developing the inputs necessary to run the External File Batch Runs feature available in the PWC. Each row below row 2 represents a PWC run. The user enters the appropriate information in the columns that have headers in black (columns A-AI and AQ-RI). The red columns will fill in automatically once the user copies the functions contained in row 3 to the rows being created. Row 1 provides guidance on the information required for some of the column input values. For instance, Column D is the Koc flag, which should be entered as either True or False. Additional instructions and information regarding data processing can be found in the “ReadMe” worksheet within the workbook.
PWC ESA scenarios, v. 3.1 (ZIP)
For aquatic exposure assessments, input scenarios are used to represent a finite set of combinations of soil, weather, hydrology, and management/crop use conditions that are expected to conservatively estimate the potential for pesticides to move into surface water. For aquatic modeling in the BEs under ESA, scenarios were developed for:
- 13 general crop classes:
- citrus;
- corn;
- cotton;
- grapes;
- grassland (pasture and hay);
- other crops [e.g., clover, fallow field, sod/grass for seed];
- other orchards;
- other trees [e.g., managed forests];
- other grains [e.g., barley, buckwheat, canola, rye, sorghum, sugarcane];
- other row crops [e.g., peanuts, sugar beet, sunflower, tobacco];
- soybeans;
- vegetables and ground fruit; and
- wheat
- 11 nonagricultural uses:
- mosquito adulticide;
- developed commercial areas,
- developed open space [e.g., recreational areas];
- golf;
- impervious surfaces;
- unspecified land cover [e.g., nurseries];
- rangeland;
- residential;
- right-of-way;
- wide area use [WAU]; and
- Christmas tree orchards
These agricultural categories are based on the United States Department of Agriculture National Agricultural Statistics Survey (USDA-NASS) Cropland Data Layer. These scenarios are grouped by Hydrologic Unit Code 2 (HUC2) region and crop class. One representative scenario and an associated weather station are selected for each HUC2-crop combination. Scenario selection is based on runoff potential. Weather station selection is based on the median cumulative precipitation using 30 years of representative weather from the Solar and Meteorological Surface Observation Network [SAMSON] station within the HUC2 region.
The zip file below contains the scenarios used for aquatic modeling of ESA chemicals. The scenario files are named using the following convention: crop_group_nameESAHUC2. For example, the corn scenario for HUC2 Region 1 has been named CornESA1.scn. If multiple weather stations are identified for a particular HUC2 region, an “a” or “b” is added to the scenario name.
This file has been updated to include scenarios for HUC 19 (Alaska) as well as scenarios for citrus, grapes, and other orchards, which were modeled in previous ESA assessments using the orchards and vineyards scenarios. The file has also been updated with scenarios for use when conducting runs specifically for use in the Plant Assessment Tool (PAT).
PWC Postprocessor, v. 3.0 (XLSM)
The PWC Postprocessor is a spreadsheet tool that has been built to assist in analyzing the results from the multitude of PWC runs conducted for the final BEs. The tool allows the user to summarize environmental exposure concentrations (EEC) by HUC2 and bin combination, as well as by species. The tool also allows the user to the annual maximum EECs for all 30 years for the PWC runs. Before running the tool, the user should store all of the PWC runs and the summary file in a single directory. Additionally, the user should check the ErrorSummary file, generated when running the External File Batch Runs feature in PWC, and ensure that no errors occurred during the PWC batch run. Additional instructions and information regarding data processing can be found in the “ReadMe” worksheet within the workbook.
PWC Edge of Field Calculator, v. 2.1 (XLSM)
The PWC Edge-of-Field Calculator tool will use the runoff files from PWC runs (ZTS files) and estimate the concentrations of the pesticide in the runoff to be used for evaluation of pesticides in Bins 2 and 5. The tool will generate a summary file and time series file, similar to the ones generated by the PWC, as well as generate summary statistics for all of the runs evaluated and store the results in the Summary_ESA and Summary_ESA_15 worksheets for use in the PWC Postprocessor tool for Biological Evaluations.
PWC 90-day postprocessor, v. 1.0 (XLSM)
The PWC 90-Day Postprocessor tool will use the daily time series files from PWC runs (CSV files) and estimate the 90 highest concentrations of the pesticide around the annual maximum daily concentration for each 30-year simulation. The tool will generate a summary file that can be exported to a CSV file and used in the probabilistic component of the MAGtool for Endangered Species assessments.
Models and Tools for Estimating Exposure in Terrestrial Habitats
Plant Assessment Tool (PAT), v. 2.1 (ZIP)
The Plant Assessment Tool (PAT) employs mechanistic representations of environmental fate (e.g., degradation) and transport (e.g., runoff) processes, using data that are typically available for pesticides, to model runoff and spray drift exposure to terrestrial and wetland environments. For terrestrial plants, runoff and erosion are modeled using PRZM, and spray drift is modeled using AgDRIFT deposition values. The model uses a mixing cell approach to represent water within the active root zone area of soil, and accounts for flow through the terrestrial plant exposure zone (T-PEZ) caused by both treated field runoff and direct precipitation onto the T-PEZ. Pesticide losses from the T-PEZ occur from transport (i.e., washout and infiltration below the active root zone) and degradation. Wetlands are modeled using PRZM/VVWM and are then processed in PAT to estimate aquatic (mass per volume of water) and terrestrial (mass per area) concentrations in the wetland plant exposure zone (W-PEZ). Aquatic plants exposure is modeled using the PRZM/VVWM models and the standard farm pond.
PAT Postprocessor, v. 1.1 (XLSM)
The PAT Postprocessor is a spreadsheet tool that was built to assist in summarizing the results from the PAT tool for use in the MAGtool. The tool allows the user to summarize EECs by HUC2 for the terrestrial and wetland plant exposure zones, as well as by species. Before running the tool, the user should store the summary files from the PAT runs in a single directory. Additional instructions and information regarding data processing can be found in the “ReadMe” worksheet within the workbook.
Effects Tools
Data Array Builder (DAB), v. 1.0 (XLSM)
The DAB generates ecotoxicity data arrays, or graphic representations of effects data, based on formatted data reports from the Ecotoxicology knowledgebase (ECOTOX) and user-entered registrant-submitted studies. Once the data have been inserted into the workbook and formatted according to the tool’s instructions, the DAB allows sorting of the data by user-defined taxonomic group, effect type, and endpoint and generates dot plots presenting the data. The user can also create summary plots by effect type that show the range of values and median concentration for each type of effect. Additional details regarding data processing can be found in the “ReadMe” worksheet within the workbook.
Species Sensitivity Distribution (SSD) toolbox
The SSD toolbox allows the user to fit distributions to toxicity data available for tested species that fall within the same group (e.g., fish, birds, invertebrates). It combines a variety of algorithms to support fitting and visualization of simple SSDs.
The current version of the tool supports six distributions, including:
- normal;
- logistic;
- triangular;
- Gumbel;
- Weibull and
- Burr.
When any of the first four distributions are chosen, the data are first common-log transformed (log10). When the Weibull or Burr distribution is chosen, the data are fit on their measurement scale. The tool also supports fitting distributions using four different methods (maximum likelihood, moment estimators, graphical methods, and Markov Chain Monte Carlo). Guidance on how to use the tool is provided in the User’s Guidance document. Technical details on the methodology employed in this tool are given in the companion Technical Manual.
The SSD Toolbox was designed in Matlab 2018b and requires the Matlab Compiler Runtime (MCR) to be installed on your computer. The SSD Toolbox will not run without the MCR. Due to its size, we are not hosting the MCR on our website. It can be downloaded free of charge from the Mathworks . The required version is the Windows 64-bit MCR for Matlab release 2018b.
MAGtool (Magnitude of Effect Tool)
MAGtool v. 2.3.1
The Magnitude of Effect Tool (MAGtool) was created to assist in the determination of the magnitude of the effect of potential pesticide use on listed species. The output of the tool provides an estimate of the numbers of individuals of a given listed species that could potentially be impacted due to mortality losses or adverse sublethal effects. Additionally, the number of individuals of the listed species potentially impacted due to losses in their prey, pollination, habitat or dispersal (PPHD) vectors is predicted. The MAGtool combines toxicological information, species traits, exposure analysis and spatial results into one tool. Results may be generated for the species or critical habitat under different scenarios including variations in assumptions related to exposure, extent of pesticide usage on a crop, and extent of pesticide usage for the species.
A zip file containing the MAGtool files is available for clothianidin (ZIP), imidacloprid (ZIP), and thiamethoxam (ZIP). Each zip file contains the aquatic and terrestrial MAGtools, and input files, as well as a Read Me file and associated model documentation.
Spatial Analysis Tools
Use Site Generation, v. 3.0 (ZIP)
This tool takes Cropland Data Layer (CDL) data to generate the 13 general crop classes used for the Use Data Layers (UDL) and combines all UDLs to create the chemical action area.
UDLs represent the application sites for agricultural and non-agricultural registered pesticide uses. The best available data to spatially characterize specific agricultural crops are the CDL data, produced by the U.S. Department of Agriculture. Several methods have been employed to minimize data errors within the CDL, with errors of omission and commission published at the state-CDL category level for a given year. The CDL is an estimated landcover spatial dataset that has over 100 cultivated classes that were grouped into 13 general crop classes. The process of lumping CDL classes reduces the likelihood of errors of omission and commission between similar crop categories. Additionally, as the CDL is produced annually, multiple years of CDL data were aggregated to account for crop rotations. The final categorially and temporally aggregated layers are referred to UDLs. UDLs for non-agricultural sites and agricultural sites found outside the contiguous United States are also generated. All pertinent UDLs are combined to generate the action area. In addition to the action area, all pertinent UDLs can be merged into a combined drift layer. This drift layer identifies the closest distance to any of the pertinent UDLs in 30 meter increments, starting at 30. Additional information on how files should be organized, and other system requirements are provided with the tool documentation.
A zip file (ZIP) containing the python scripts, tool documentation, and example tabular input files is available for download.
Processed GIS Data – Species Spatial Files, v. 1.2 (ZIP)
This tool standardizes the species location files for use in the co-occurrence analysis.
Species location files are organized by taxonomic group in spatial libraries, one for range and one for critical habitat. The standardization process includes merging a single species information into one file, updating the attribute information to a standard suite of information including date received, and standardized projection. A species listing can an include individual population of a species. Each population is processed as an individual entity. Additional information on how files should be organized, and other system requirements are provided with the tool documentation.
A zip file (ZIP) containing the python scripts, tool documentation, and example tabular input files is available for download.
Co-occurrence Inputs- Species/Use Co-occurrence and Supporting Tables, v. 1.2 (ZIP)
The Co-occurrence Inputs tool generates the spatial and tabular input files used to run the co-occurrence analysis; as a batch by species group.
After finalizing the species’ location files, composite input files used for the co-occurrence analysis are generated. There are two types of composite files generated: merged composites and union composites. This tool generates these composite files and the necessary supporting tables for the co-occurrence analysis. Additional information on how files should be organized, and other system requirements are provided with the tool documentation.
A zip file (ZIP) containing the python scripts, tool documentation, and example tabular input files is available for download.
Chemical Independent Co-occurrence Results - Parent Use Overlap Tables, v. 1.4 (ZIP)
The Parent Use Overlap Tables tool executes the overlap runs for the co-occurrence analysis using the inputs from files generated by the Co-occurrence Inputs tool.
The input files represent species locations as unique zones. Each zone may contain a suite of species in addition to other spatial information used for the spatial analysis such as state/county boundaries, HUC2 locations, or habitat information. After completing the run based on zone this tool will summarize the results to the species by EntityID. Additional information on the how files should be organized, and other system requirements, are provided with the tool documentation.
A zip file (ZIP) containing the python scripts, tool documentation, and example tabular input files is available for download.
Chemical Dependent Co-occurrence Results-MAGtool Tables, v. 1.4 (ZIP)
The Chemical Dependent Co-occurrence Results-MAGtool Tables tool generates the tables for the different overlap scenarios used in the MAGtool. Five different overlap scenarios are generated for consideration in the Weight of Evidence. The first is usage independent and provides results for the species with no "usage specific" adjustment to the overlap. This is followed by incorporating the usage data, scaling for redundancy of the UDLs, and then adding species life history information to the overlap results.
- Overlap Scenario 1: Unadjusted
- Overlap Scenario 2: PCT Overlap
- Overlap Scenario 3: PCT and Redundancy
- Overlap Scenario 4: PCT, Redundancy, Off-site
- Overlap Scenario 5: PCT, Redundancy, Off-site, Habitat (other supplemental information)
Additional information on how files should be organized, and other system requirements are provided with the tool documentation.
A zip file (ZIP) containing the python scripts, tool documentation, and example tabular input files is available for download.