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Endangered Species

Models and Tools for National Level Listed Species Biological Evaluations of Carbaryl and Methomyl

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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. The first application of these tools was to BEs conducted on carbaryl and methomyl. All models and tools included on this page were subjected to a quality assurance and quality control review.

A brief description 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

Pesticides Water Calculator (PWC)

The Pesticide 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 USEPA 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 Water Calculator (PWC) ESA Automation Tool, v. 2.0 (XLSX) (1 pg, 37K) Free Viewers

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-S and AB-PN). 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. 3.0 (ZIP) (1 pg, 318 K) Free Viewers

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, sugarcane];
    • other row crops [e.g., peanuts, sugar beet, sunflower, tobacco]; 
    • soybeans;
    • vegetables and ground fruit; and 
    • wheat
  • 11 nonagricultural uses:
    • adulticide;
    • developed commercial areas,
    • developed open space [e.g., recreational areas];
    • golf;
    • impervious;
    • 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 is selected for each HUC2-crop combination based on runoff potential, and 30 years of representative weather (from the Solar and Meteorological Surface Observation Network [SAMSON]) are used based on the station within each Hydrologic Unit HUC2 with the median cumulative precipitation. 

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.

PWC Postprocessor, v. 2.0 (XLSM)(1 pp, 2.26 MB)(1 pg, 3.50 MB) Free Viewers

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 draft BEs. The tool allows the user to compare estimated environmental concentrations (EECs) to aquatic thresholds and summarize EECs by HUC2 and bin combination, as well as by species. The tool also allows the user to evaluate individual PWC runs conducted in support of the draft BEs. 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 Non-ag Postprocessor, v. 2.0 (XLSM) (1 pp, 5.37 MB) Free Viewers

The PWC Non-ag Postprocessor is a spreadsheet that postprocesses the residential, impervious, and rights-of-way time series generated in the PWC and allows for the generation of the 1-in-10 year and 1-in-15 year EECs.  For some of the chemicals, non-agricultural uses (e.g., applying to gardens, lawns, around commercial buildings, etc.) have been modeled using multiple PWC scenarios which represent the variety of surface types that could occur in a nonagricultural setting (e.g., turf, impervious, right-of-way).  The time series for the individual runs are normally combined afterwards to generate a time series and 1-in-10 or 1-in-15 year statistics to represent the non-agricultural use.  This spreadsheet automates this process.  Additional instructions and information regarding data processing can be found in the “ReadMe” worksheet within the workbook.  Note: This tool should be run prior to using the PWC Postprocessor so that the results can be incorporated into the analysis.

PWC Edge of Field Calculator, v. 2.0 (XLSM) (1 pg, 1.12 MB) Free Viewers

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 Endangered Species assessments.

PWC Daily Avg. Processor, v. 1.0 (XLSM) (1 pg, 2.20 MB) Free Viewers

The Daily Average Processor tool will create new 1-in-15 year summary files, similar to those created by PWC, to include the daily average concentration to the annual estimates provided for years 1 through 30. This information is required for use in the MAGtool, where the 30 annual values are used in a probabilistic analysis. The tool uses the daily time series files created by PWC to generate these new files.

PWC 90-day postprocessor, v. 1.0 (XLSM) (1 pg, 782 K) Free Viewers

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.

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Effects Tools

Data Array Builder (DAB), v. 1.0 (XLSM) (1 pg, 240 K) Free Viewers

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 and 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 Exit. The required version is the Windows 64-bit MCR for Matlab release 2018b.

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MAGtool (Magnitude of Effect Tool), v. 2.1 

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 which are potentially 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. Users should note that the output generated is the potential number of individuals that could be impacted under the model assumptions, not a prediction that they will be impacted.

A zip file containing the MAGtools is available for carbaryl (ZIP) (1 pg, 295 MB) and methomyl (ZIP) (1 pg, 231 MB.  Each zip file contains the aquatic and terrestrial MAGtools and input files, as well as a Read Me file and associated model documentation.

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Spatial Analysis Tools

Use Site Generation, v. 2.1 (ZIP) (1 pg, 627 K)

This tool takes Cropland Data Layer (CDL) to generate the 13 general crop classes used for the Use Data Layers (UDL) and combines all UDLs to create the chemical action area.

Use Data Layers represent the application sites for agricultural and non-agricultural label uses. The best available data to spatially characterize specific agricultural crops is the Cropland Data Layer (CDL), 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 were aggregated to account for crop rotations. The final categorially and temporally aggregated layer are referred to Use Data Layers (UDLs). Use Data Layer 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. 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.

Processed GIS Data – Species Spatial Files, v. 1.1 (ZIP) (1 pg, 102 K)

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 include individual population of a species, each population are processed as individually entities. 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.

Co-occurrence Inputs- Species/Use Co-occurrence and Supporting Tables, v. 1.1 (ZIP) (1 pg,  457 K)

This tool generates the input spatial and tabular 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 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 Independent Co-occurrence Results - Parent Use Overlap Tables, v. 1.1 (ZIP) (1 pg, 454 K)

The Chemical Independent Co-occurrence Results-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 additional 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. 1.1 (ZIP)(1 pg, 791 K)

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 chemical independent and provides results for the species with no chemical 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 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.

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