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Software

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NO3GWT version 1.0.0

A groundwater Nitrate Decision Support Tool (GW-NDST) for wells in Wisconsin was developed to assist resource managers with assessing how legacy and possible future nitrate leaching rates, combined with groundwater lag times and potential denitrification, influence nitrate concentrations in wells (Juckem et al. 2024). The GW-NDST was reviewed and approved by the journal via this official USGS appr

Monosex control within integrated pest management

This repository contains code to simulate the use of YY-males and direct mortality such as harvest or pesticide applicaion as a control tools for different aquatic invasive species.

Simulations for assessing the suitability of YY-males as a control method across life histories

This repository contains code to simulate the use of YY-males as a control tool for different aquatic invasive species. The code uses the Meta-IPM Python package (https://doi.org/10.5066/P9PW673G) The code for this project assumes the reader is familiar with Jupyter Notebooks, enough Conda and Python to install the Meta-IPM package, and population ecology.

SEIcarP

SEIcarP is an R package (R Core Team 2021) implementing the Spatially Explicit Invasive Carp (SEICarP; sometimes stylize as SEIcarP) population model for the Illinois River. This repository contains the SEIcarP model plus two additional packages required for the main model package to run. These are the SEIcarP Bighead Carp (BH) data (SEIcarPdataBHCP) and the SEIcarP Silver Carp (SV) data (SEIcarPd

Application of the SEICarP Model to the Illinois River

This repository contains code to run the Spatially Explicit Invasive Carp Population (SEICarP) model in the Illinois Rive. The code uses the `SEICarP` R package. The code for this project assumes the reader is familiar with R, population modeling, and quantitative fisheries methods.

Example application of MetaIPM to the Illinois River

This repository contains an example application of the `Meta-IPM` Python package (https://doi.org/10.5066/P9PW673G). The specific application focuses on the Illinois River using existing public data.

Indiana mussel metabolomics data analysis

This repository contains code to cluster a sample of Mussels based up their metabolic levels via Non-Metric Multidimensional Scaling (NMDS) and distance based-Redundancy Analysis (db-RDA). Mussel sample is broken down and examined by catch location, sex, and species. The code for this project assumes the reader is familiar with R and clustering techniques.

Calculations of BioLake climate data

Climate data allow people to examine species distributions and possible distributions. This script takes ERA5-Land climate estimates (https://www.ecmwf.int/en/forecasts/datasets/reanalysis-datasets/era5) for precipitation and lake temperature and processes them to create summary climate layers for use with biological organisms in lakes. This code could be modified to use a different subset of year

Interpolating missing water quality data

This repository contains analysis codes to interpolate missing data from the Upper Mississippi River LTRM dataset.

Coregonid

This repository contains code for the analysis from a study that examined mortality and qPCR detection in 4 groups of fish: an uninfected control group, an infected control group, and two treatment groups. The main goals were to determine if their were differences in mortality and qPCR detection of the parasite among the differing groups. Mortality was addressed using a Generalized Linear Mixed M

Analysis of Grass Carp eDNA Data

This product contains code to analyze a dataset that was collected to compare a LAMP assay and a qPCR assay for Grass Carp in a pond study. This repository contains the RMarkdown and R files used to analyze the data. It was created to allow for reproducible results. The code assumes the user is experience with R, especially the Tidyverse, and Stan.

EGRET

An R-package for the analysis of long-term changes in water quality and streamflow, including the water-quality method Weighted Regressions on Time, Discharge, and Season (WRTDS).