Data Releases

These data identify the mean population growth rate and ratio change in abundance of common raven (Corvus corax; ravens) populations from 1966 through 2018, delineated by ecoregions defined by the U.S. Environmental Protection Agency. This enables researchers and land managers to identify regions which may be more heavily affected by growing raven populations. These data support the following p

We generated a spatially explicit map of categories of expected occurrence and density associated with predicted concentrations of resident and transient common ravens (Corvus corax; ravens) using the residuals from a generalized linear regression between the occurrence and density parameters. These data support the following publication: Webster, S.C., O'Neil, S.T., Brussee, B.E., Coates, P.S.,

This is the landing page for all versions of the United States Register of Introduced and Invasive Species (US-RIIS). The US-RIIS is comprised of three lists, one each for Alaska (AK), Hawaii (HI), and the conterminous United States (L48). Each list includes taxonomic and ecological information about introduced (non-native), established (reproducing) taxa that: are, or may become, invasive (harm

Introduced (non-native) species that becomes established may eventually become invasive, so tracking introduced species provides a baseline for effective modeling of species trends and interactions, geospatially and temporally. The United States Register of Introduced and Invasive Species (US-RIIS) is comprised of three lists, one each for Alaska (AK, with 532 records), Hawaii (HI, with 6,075 re

This data set is comprised of 4 files consisting of field observations, morphological measurements, and water quality measurements relevant to a publication on the classification and population status of the WV Spring salamander, Gyrinophilius subterraneus.

The Shenanadoah Salamander (Plethodon shenandoah) is an endangered salamander found only in the mountains of Shenandoah National Park. Field surveys of the salamander were conducted from 2007-2022 using daytime cover object surveys. In order to capture the totality of P. shendandoah’s range we sampled from low to high elevation across a broad geographic range. We created a spatial generalized addi

These data are from joint visual encounter and environmental DNA (eDNA) surveys conducted for northwestern pond turtles (Actinemys marmorata) in streams on privately-owned timberlands in northern California.

This raster dataset contains 1-meter lidar-derived imagery of 7.5 minute quadrangles in karst areas of Puerto Rico and was created using geographic information systems (GIS) software. Lidar-derived elevation data, acquired between 2015 and 2017, were used to create a 1-meter resolution working digital elevation model (DEM). To create this imagery, a hillshade was applied and a topographic position

This raster dataset contains 1-meter lidar-derived imagery of 7.5 minute quadrangles in karst areas of Puerto Rico and was created using geographic information systems (GIS) software. Lidar-derived elevation data, acquired in 2018, were used to create a 1-meter resolution working digital elevation model (DEM). To create this imagery, a hillshade was applied and a topographic position index (TPI) r

Frequency domain electromagnetic induction (FDEM) data were collected in September 2016 near the Agashashok River and its tributaries, within the Noatak National Preserve near Kotzebue, AK to aid in local permafrost mapping. Data were collected with a GEM-2 instrument (1.6 m coil separation, Geophex, Ltd.); a broadband sensor that measures the bulk conductivity and magnetic susceptibility of the s

In cooperation with the New York City Department of Environmental Protection (NYC DEP), the U.S. Geological Survey (USGS) collected water and bed sediment samples along Alley Creek (Queens, New York) to help determine likely sources of fecal bacteria to the creek and Little Neck Bay. Potential terrestrial sources include stormwater, sewage via combined sewer overflow (CSO) and compromised infrastr

This dataset was developed in partnership with the Tennessee Department of Environmental Conservation to determine the susceptibility of selected Tennessee reservoirs to eutrophication and potential harmful algal blooms. A R script, based on recursive partitioning and the model-based boosting routine, was used to generate regression trees that grouped Tennessee reservoirs into five endpoints along