Data Releases

Surface water samples (n = 33) were collected in fall of 2023 at stream sites in Scott County Iowa, USA and were analyzed for microbial source tracking markers by quantitative polymerase chain reaction at the Laboratory for Infectious Disease and the Environment (LIDE). Microbial source tracking markers identify fecal sources of contamination by detecting microbes that are specific to...

Data files contain the simulated mean daily environmental conditions experienced by particles (which can be assumed to be planktonic larval alewife or yellow perch) in Lake Michigan during March 15 - July 31 of past and future years. Simulations were generated by integrating a series of climatic, hydrodynamic, biogeochemical, and Lagrangian particle dispersion (LPD) models. For each year...

This is the data archive for the publication Ungulate Migrations of the Western United States, Volume 4 and includes the collection of GIS map files that are mapped and described in the report. These map files are meant to provide a common spatial representation of the mapped migrations and seasonal ranges. This data release provides the means for ungulate migrations to be mapped and...

This data release includes laboratory analyses for fish tissue samples collected from Lake Koocanusa and the Kootenai River Basin in Montana during 2022. Samples were collected by the U.S. Geological Survey (USGS) Wyoming-Montana Water Science Center (WY-MT WSC) in cooperation with Montana Fish, Wildlife and Parks (MT FWP) and Montana Department of Environmental Quality (MT DEQ)...

These data are the collection of generalized linear mixed models run for AIC comparison of the pre- and post-White-nose Syndrome bat mist-net captures and percent juveniles in capture by year, time since White-nose Syndrome at collection set, U.S Fish and Wildlife Service designated geographic units, states or NABAT grid cell, collection site mean temperature, collection site temperature...

High-frequency observations of surface water at fine spatial scales are critical to effectively manage aquatic habitat, flood risk and water quality. We developed inundation algorithms for Sentinel-1 and Sentinel-2 across 12 sites within the conterminous United States (CONUS) covering >536,000 km2 and representing diverse hydrologic and vegetation landscapes. These algorithms were...