Software
An official USGS software project is code reviewed and approved at the bureau-level for distribution.
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Conservation Efforts Database Batch Upload Template and User Manual (Gunnison Sage-grouse Recovery Module) Conservation Efforts Database Batch Upload Template and User Manual (Gunnison Sage-grouse Recovery Module)
This ArcGIS Pro project template is being provided to support scientists who wish to upload data to the Conservation Efforts Database (CED). This software release contains all of the source code and instructions to use the project template, including the tools that come with it, to upload large quantities of data to the CED.
Winter Drawdown Winter Drawdown
The Google Earth Engine (GEE) code was written in JavaScript which can derive water area and water level time series data of multiple lakes for specified date range. Data derived from GEE code were used in classifying winter drawdown lakes and to derive winter drawdown metrics (using python code in Jupyter Notebook) in our submitted manuscript to the Journal of Environmental Management...
U.S. Geological Survey Hydrologic Toolbox version 1.1.0 software archive U.S. Geological Survey Hydrologic Toolbox version 1.1.0 software archive
This is version 1.1.0 of the Hydrologic Toolbox software.
ModelMuse Version 5.2 ModelMuse Version 5.2
This version of ModelMuse adds support for MODFLOW-OWHM version 2, SUTRA version 4, and additional packages in MODFLOW 6.
Comparing maximum likelihood and Bayesian methods for fitting Hidden Markov Models to multi-state capture recapture data of invasive Silver Carp in the Illinois River Comparing maximum likelihood and Bayesian methods for fitting Hidden Markov Models to multi-state capture recapture data of invasive Silver Carp in the Illinois River
This repository contains the data, code for modeling and analysis, and publication markdown documents for a comparison of various methods for fitting multi-state models, including maximum likelihood and Bayesian approaches via R.
Evaluating the effectiveness of joint species distribution modeling for riverine fish communities Evaluating the effectiveness of joint species distribution modeling for riverine fish communities
Species Distribution Models (JSDMs) allow for accounting for both environmental predictors and species dependencies within a single statistical modeling frameworks. However, it is unclear under what conditions incorporating residual species dependencies (conditional predictions) might outperform predictions made using only environmental information (marginal predictions). Here, we...