This Python package is intended to assist with summarization of landscape information to stream watershed drainages (local summaries). Methods are built in a generalized way and are intended to support efforts for any stream network having polygon based drainage watersheds. The output of these methods can be used to calculate stream network summaries using xstrm.
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
The Dam Removal Information Portal (DRIP) contains information about the geographic locations of dam removals and any associated scientific studies evaluating outcomes to physical, biological, and water quality parameters. This application uses Python DASH to help distribute and visualize information from the Dam Removal Information Portal API (DRIP API).
This package handles retrieval and preparation of the source data for DRIP. Source data currently come from two sources. The Dam Removal Science Database is distributed by USGS in ScienceBase (https://doi.org/10.5066/P9IGEC9G) and a complete list of dam removals is distributed by American Rivers in Figshare. We provide these efforts as a package in order to support full transparency on what we a
Python package to assist with stream network summarization. This package is intended to support efforts for any stream network having general topology (i.e. to/from nodes). Specifically this package was built to support fisheries based analyses using multiple versions of the National Hydrography Database Plus (NHDPlus) representing streams within the United States along with HydroBasins which repr
Understanding how data are used across the scientific community provides many benefits to data authors, including building a better awareness and comprehension of 1) a dataset's scientific impact, 2) use cases to direct future versions, and 3) related efforts. Effectively tracking when and how data are used in the literature through time can be challenging. This is in part due to a lack of consis
This R package contains functions for downloading and munging data from the North American Breeding Bird Survey (BBS) via FTP (Pardieck et al. 2018; J. R. Sauer et al. 2017). This package was created to allow the user to bulk-download the BBS point count and related (e.g., route-level conditions) via FTP, and to quickly subset the data by taxonomic classifications and/or geographical locations. Th
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