Software
This webpage has descriptions of and links to computer programs that can be downloaded online. To view USGS-series publications related to software, please visit the publications webpage of this website.
Filter Total Items: 32
Identifying Pareto-efficient eradication strategies for invasive populations
Invasive species are a major cause of biodiversity loss and are notoriously expensive and challenging to manage.
We developed a decision-analytic framework for evaluating invasive species removal strategies, given objectives of maximizing eradication probability and minimizing costs. The framework uses an existing estimation model for spatially referenced removal data – one of the most accessible
North American Bat Monitoring Program: R Data Connection Package (Version 1.1.0)
The North American Bat Monitoring Program: R Data Connection Package can be used to extract and upload data to the NABat Monitoring Program through the GQL API. This software is written as a wrapper around the NABat GQL API. Documentation for the database and API can be found at https://sciencebase.usgs.gov/. This code includes the ability to reformat NABat data, upload NABat data, create reports,
grsg_lekdb: Compiling and standardizing greater sage-grouse lek databases (version 1.3.0)
Greater sage-grouse (Centrocercus urophasianus; hereafter referred to as sage-grouse) are landscape-scale sagebrush obligate species and an important gamebird and iconic species of the West (Hanser & Knick, 2011; Rowland et al., 2006). They occupy the sagebrush biome in western North America, extending east of the Sierra Nevada/Cascade Mountain ranges to the western regions of the Great Plains of
veg_sim: Modeling Greater sage-grouse habitat suitability 15-years post simulated fire event and sagebrush transplanting (2015-2030)
To assess the degree to which transplanting sagebrush (Artemisia spp.) could quickly restore former Greater sage-grouse (Centrocercus urophasianus; hereafter, sage-grouse) habitat and the strategies by which sage-grouse habitat restoration is best accomplished, we linked vegetation transitions with habitat selection models to evaluate habitat recovery. There are few data-driven approaches to ident
Ecosystems-nabat-FPabund: software for fitting false-positive N-mixture models using NABat mobile acoustic data (version 1.0.0)
The primary purpose of this software is to document the analytical methods and code used to fit false-positive N-mixture models and make status and trends predictions from: "Using mobile acoustic monitoring and false-positive N-mixture models to estimate abundance and trends for three bat species affected by White-nose syndrome" by Udell et al. 2024. In particular, these methods were used to analy
dem_getter Python tool for acquiring digital elevation models and derivatives from The National Map
This repository houses a set of Python tools to expedite the acquisition of 3DEP DEM data. These tools were designed to help geologists in the National Cooperative Geologic Mapping Program more efficiently produce high-resolution base maps and tailored derivative products that help identify and characterize geologic features. These derivatives include hillshades and slope maps, as well as more com
North American Bat Monitoring Program: NABat Acoustic ML (version 2.0.0)
Bats play crucial ecological roles, and provide valuable ecosystem services, yet many populations face serious threats from various ecological disturbances. The North American Bat Monitoring Program (NABat) aims to assess status and trends of bat populations, while developing innovative and community-driven conservation solutions using its unique data and technology infrastructure. To support scal
Software for Bayesian Mapping of Regionally Grouped, Sparse, Univariate Earth Science Data (Program BMRGSU)
BMRGSU is software developed by the U.S. Geological Survey for Bayesian mapping of regionally-grouped, sparse, univariate, Earth-science data. This software implements an algorithm that smooths the estimated property across regions so that the deleterious effects of sparse data are mitigated. The algorithm can account for measurements that are censored, it can process multiple datasets with differ
HOPS: Hyperparameter optimization and predictor selection
We developed the hyperparameter optimization and predictor selection (HOPS) software to optimize hyperparameters and predictor selection while limiting correlation among the selected predictors for machine learning models. Including correlated predictors in machine learning models can distort model estimation and prediction and introduce bias in predictor importance estimates. The HOPS software ex
grsg_lekdb: Compiling and standardizing greater sage-grouse lek databases, version 1.2.0
Greater sage-grouse (Centrocercus urophasianus; hereafter referred to as sage-grouse) are landscape-scale sagebrush obligate species and an important gamebird and iconic species of the West (Hanser & Knick, 2011; Rowland et al., 2006). They occupy the sagebrush biome in western North America, extending east of the Sierra Nevada/Cascade Mountain ranges to the western regions of the Great Plains of
Scenario Analysis of Management Alternatives for Free-roaming Horse Populations (Version 1.0.0)
PopEquus is a predictive modeling tool to support decisions related to the management of free-roaming horse populations. It permits the simulation and comparison of how management alternatives influence horse population size and metrics associated with management. This repository uses R scripts with predictive functions from the PopEquus model to simulate how management alternatives (e.g., removin
Software for SIR 'Effect of Data Pooling on Predictions From the Three-Part Method for Quantitative Mineral Resource Assessment-An Investigation of a Previous U.S. Geological Survey Assessment'
The Three-Part Method for Quantitative Mineral Resource Assessment has been used by the USGS to predict mineral resources since at least 1975. These predictions use pooled data, and the effects of the pooling on the predictions is investigated and reported in the forthcoming USGS publication. The calculations and figures for this report are performed with software that will be permanently stored i