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An official USGS software project is code reviewed and approved at the bureau-level for distribution.

Filter Total Items: 523

Did You Feel It?

Did You Feel It? (DYFI) collects information from people who felt an earthquake and creates maps that show what people experienced and the extent of damage.

Predicting climate change impacts on poikilotherms using physiologically guided species abundance models

R code and .stan files for fitting physiologically guided abundance models for predicting climate change impacts on poikilotherms.

Software to Process and Preserve Legacy Magnetotelluric Data

The USGS Crustal Geophysics and Geochemistry Science Center (CGGSC) collaborated with the USGS Data at Risk (DaR) team to preserve and release a subset of magnetotelluric data from the San Andreas Fault in Parkfield, California. The San Andreas Fault data were collected by the Branch of Geophysics, a precursor to the now CGGSC, between 1989 and 1994. The magnetotelluric data selected for this pres

Mercury Condition Index Tool

The Mercury Condition Index Tool uses existing data of mercury concentrations in invertebrates, fish, and birds within national parks to estimate a park level Condition Index (and associated uncertainty) for mercury, based on its potential risk to fish and wildlife health. The tool employs a series of logic steps to convert provided data into standardized units, based upon both basic stoichiometr

Interactive PHREEQ-N-AMDTreat+REYs water-quality modeling tools to evaluate potential attenuation of rare-earth elements and associated dissolved constituents by aqueous-solid equilibrium processes (software download)

Software utilizing PHREEQC with user interface. The PHREEQ-N-AMDTreat+REYs geochemical modeling tools have the fundamental capability to simulate and predict key reactions related to the treatment of acid mine drainage and the formation of treatment solids, including the adsorption of rare-earth elements plus yttrium (REYs) onto hydrous iron, aluminum, and manganese oxides. These new tools were e

GSpy: Geophysical Data Standard in Python

This package provides functions and workflows for standardizing geophysical datasets based on the NetCDF file format. The current implementation supports both time and frequency domain electromagnetic data, raw and processed, 1-D inverted models along flight lines, and 2-D/3-D gridded layers.

Wildlife Wrangler

The abundance of wildlife occurrence datasets that are currently accessible can be valuable for efforts such as species distribution modeling and range delineation. However, the task of downloading and filtering occurrence records is often complex due to errors and uncertainties that are present in datasets. This repository provides a high-level framework for acquiring and filtering occurrence dat

Multi-objective Modeling as a Decision-support Tool for Feral Horse Management

Decisions related to controversial problems in natural resource management receive the greatest support when they account for multiple objectives of stakeholders in a structured and transparent fashion. In the United States, management of feral horses (Equus caballus) is a controversial multi-objective problem because disparate stakeholder groups have varying objectives and opinions about how to m

Abstraction Layer for Ephemerides

Abstraction Layer for Ephemeride version 0.8.7

Abstraction Layer for Ephemerides

Abstraction Layer for Ephemerides version 0.9.0

Science-based Management of Ravens Tool (SMaRT)

The Science-based Management of Ravens Tool (SMaRT) supports a science-based adaptive management framework that incorporates recent quantitative analyses and mapping products for addressing areas with elevated common raven (Corvus corax) numbers and minimizing potential adverse impacts to sensitive species, agricultural damage, and human safety (Dettenmaier et al. 2021). This is a web-based applic

Code to analyze Capture-Mark-Recapture data of San Francisco gartersnakes (Thamnophis sirtalis tetrataenia)

Code files "growth_analysis.R" -An R script to fit the von Bertalanffy growth model to growth data from San Francisco gartersnakes. The von Bertalanffy growth model is fit using JAGS software (Plummer 2003), and is based on the model presented in Armstrong and Brooks (2013). "survival_analysis.R" -An R script to fit the robust-design Cormack-Jolly-Seber model to capture-mark-recapture data from