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These BioLake raster data provide global estimates (~10.0 x 12.4 km resolution) of twelve bioclimatic variables based on estimated lake temperature. Eleven of these twelve variables (BioLake01 - BioLake11) are estimated for each of three lake strata: lake mix (surface) layer, lake bottom, and total lake water column. These eleven variables correspond to CHELSA (Climatologies at high resolution for the earth's land surface areas) bioclimatic variables BIO1 - BIO11, except that these BioLake variables are based on lake water temperature and CHELSA BIO1 - BIO11 variables are based on air temperature. CHELSA BIO is also calculated a finer spatial resolution (~1 x 1 km). The twelfth variable (BioLake20; months with non-zero...
Vegetation change is an important issue facing managers at Isle Royale National Park (ISRO). These data were created using high-resolution imagery collected in the winter of 2017 which was compared to the vegetation map of the National Park published in 2000 (project imagery collected in 1994 and 1996). These data review where vegetation cover type, density, and pattern have changed since imagery collection for the 2000 publication and provide a proposed reason for the change.
These data include dissolved silicon concentration and yield from 60 rivers across North America, the Caribbean, and Antarctica from 1964-2021 and are associated with the publication “Long-term change in concentration and yield of riverine dissolved silicon from the poles to the tropics”. Data were compiled from multiple public sources including the Long-term Ecological Research Network, Great Arctic Rivers Observatory, Upper Mississippi River Restoration program, and the U.S. Geological Survey. Concentration and yield estimates were generated by the Weighted Regressions on Time, Discharge and Season model (WRTDS; Hirsch et al. 2010). The dataset includes six files: discrete dissolved silicon data and daily discharge...
Categories: Data;
Tags: Antarctica,
North America,
Puerto Rico,
USGS Science Data Catalog (SDC),
Water Resources,
The Maumee River transports huge loads of nitrogen (N) and phosphorus (P) to Lake Erie. The increased concentrations of N and P are causing eutrophication of the lake, creating hypoxic zones, and contributing to phytoplankton blooms. It is hypothesized that the P loads are a major contributor to harmful algal blooms that occur in the western basin of Lake Erie, particularly in summer. The Maumee River has been identified by the United States Environmental Protection Agency as a priority watershed where action needs to be taken to reduce nutrient loads. This study quantified rates of biogeochemical processes affecting downstream flux of N and P by 1) measuring indices of potential sediment P retention and 2) measuring...
These data were collected to support the development of detection and classification algorithms to support Bureau of Ocean Energy Management (BOEM) studies and assessments associated with offshore wind energy production. There are 3 child zip files included in this data release. 01_Codebase.zip contains a codebase for using deep learning to filter images based on the probability of any bird occurrence. It includes instructions and files necessary for training, validating, and testing a machine learning detection algorithm. 02_Imagery.zip contains imagery that were collected using a Partenavia P68 fixed-wing airplane using a PhaseOne iXU-R 180 forward motion compensating 80-megapixel digital frame camera with...
During summer 2019, botanists with the Maine Natural Areas Program collected data from 94 vegetation plots for plant community characterization. The sampling data were entered into the National Park Service PLOTS version 4.0 (National Park Service 2018) for analyses to characterize vegetation associations in the U.S. National Vegetation Classification. An accuracy assessment was performed on the draft version of the vegetation map layer. During the summer of 2020, field crews collected data from 107 stratified and randomly selected sites for evaluating the accuracy of the vegetation map layer for those map classes representing U.S. National Vegetation Classification associations. The accuracy assessment field data...
Categories: Data;
Types: Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Shapefile;
Tags: Accuracy Assessment,
Data Collection,
Katahdin Woods and Waters National Monument,
Maine,
Map,
Data used in the Maumee River omics publication, Multi-omics responses in tree swallow (Tachycineta bicolor) nestlings from the Maumee Area of Concern, Maumee River, Ohio. Tseng et al. 2023 Sci. Total Environ. 856:159130
Categories: Data;
Tags: EROD,
Ecology,
Environmental Health,
USGS Science Data Catalog (SDC),
Wildlife Biology,
This dataset includes high-frequency sensor data collected during four consecutive summers from buoys deployed at main channel and backwater sites in Pool 8 of the Upper Mississippi River from 2015-2018. It also includes the event-specific concentration-discharge metrics (hysteresis and slope) calculated by combining the water quality sensor data with discharge data from a nearby USGS gage in Winona, MN (05378500). High-frequency sensor data were collected using water quality buoys (PISCES monitoring platforms; EMM350 Water Monitoring Pontoon Platform | ysi.com | ysi.com; Yellow Springs, Ohio) set up with EXO2 Multiparameter Sondes (YSI, Inc, Yellow Springs, Ohio) to monitor hourly or bi-hourly concentrations of...
Categories: Data;
Tags: Mississippi River,
USGS Science Data Catalog (SDC),
Water Quality,
chlorophyll a,
dissolved organic matter,
This data set represents initial forest communities developed for Isle Royale National Park. LANDIS-II requires an input data layer that contains the ages of each species cohort present within each cell of the landscape. To develop this layer, we matched the composition of forest inventory plots to a map of forest types, and randomly imputed U.S. Department of Agriculture Forest Inventory plots within each matching forest type
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Forest Succession,
Isle Royale National Park,
Lake Superior,
Michigan,
USGS Science Data Catalog (SDC),
Twenty-eight sites that consisted of either predominantly agricultural land in the watershed, predominantly agricultural land in the watershed with natural land cover in the riparian zone, or predominantly natural land cover in the watershed were sampled three times during the growing season.
Floodplain forest species are presumed to interact strongly with the environment, as evidenced by pronounced spatial variation in flood-driven abiotic constraints and forest composition. These data describe functional diversity and environmental characteristics for 156 forest assemblages sampled on floodplain landforms within transects from the lower peninsula of Michigan. The functional diversity of each assemblage is characterized by two metrics of functional richness (Convex Hull Volume/CHV and Trait Onion Peeling/TOP), one metric of functional dispersion (FDis), and community weighted mean functional trait values. Functional diversity metrics were calculated from 12 quantitative and qualitative functional traits...
This study deployed acoustic telemetry into a red swamp crayfish-infested water retention pond (1.0 ac) near Novi, Michigan to document the movements and behavior of telemetered red swamp crayfish (Procambarus clarkii). Telemetry was setup in the pond for approximately 3 months. Spreadsheets include telemetry data with position estimates for individual crayfish.
Categories: Data;
Tags: Acoustic telemetry,
Aquatic Biology,
Aquatic biology,
Invasive crayfish,
Invasive species,
During summer 2019, botanists with the Maine Natural Areas Program collected data from 94 vegetation plots for plant community characterization. The sampling data were entered into the National Park Service PLOTS version 4.0 (National Park Service 2015) for analyses to characterize vegetation associations in the U.S. National Vegetation Classification. An accuracy assessment was performed on the draft version of the vegetation map layer. During the summer of 2020, field crews collected data from 107 stratified and randomly selected sites for evaluating the accuracy of the vegetation map layer for those map classes representing U.S. National Vegetation Classification associations. The accuracy assessment field data...
Categories: Data;
Tags: Accuracy Assessment,
Data Collection,
Katahdin Woods and Waters National Monument,
Maine,
Map,
The Katahdin Woods and Waters National Monument Seboeis Unit Vegetation Mapping Project was initiated in the fall of 2019 by a grant through the USGS Natural Resource Preservation Program to classify and map vegetation types of the Seboeis Unit thereby providing resource managers and biological researchers with useful baseline vegetation information. The Study Area Boundary (SAB) for this project is similar to, but not exactly the same as, the official boundary for the Seboeis Unit. Because of uncertainty on the exact location of the Seboeis Unit boundary, mapping may have occurred beyond the official boundary. Additionally, this SAB is based upon the Seboeis Unit boundary as it appeared in September of 2019.
Categories: Data;
Types: Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Shapefile;
Tags: Katahdin Woods and Waters National Monument,
Maine,
Map,
NVCS,
National Park Service,
This dataset uses the ITIS recommended Ortmanniana pectorosa, Conrad, 1834 in place of Actinonaias pectorosa, which was used in the Richard et al. 2020 manuscript. Biologists monitoring freshwater mussel (Order Unionida) populations rely on behavioral, often subjective, symptoms to identify “sick” or stressed animals, such as gaping valves and slow response to probing and lack clinical indicators to support a diagnosis. As part of a multi-year study to investigate causes of reoccurring mortality of pheasantshell (Ortmanniana pectorosa, Conrad 1834) in the Clinch River, Virginia and Tennessee, USA, we analyzed the hemolymph metabolome of a subset of mussels from the 2018 sampling period. Mussels at the mortality...
Categories: Data;
Tags: Aquatic Biology,
Clinch River, VA, USA,
USGS Science Data Catalog (SDC),
Wildlife Biology,
biota
Between 1900 and 1932, a copper (Cu) mine operated near Gay, Michigan, along the shore of Lake Superior, discharged approximately 22.8 million metric tons of waste material known as ‘stamp sands’ (SS) to a nearby beach. This pile of SS has migrated via wind and rain along the beaches in northern Grand Traverse Bay and into Buffalo Reef, an important spawning area for Lake Trout and Lake Whitefish. During their first summer, these newly spawned fish consume benthic invertebrates and zooplankton in nearby beach habitats. SS contain elevated concentrations of metals (especially Cu) that are toxic to many invertebrate taxa, and studies have observed very few benthic taxa in areas with very high SS. Here, we sampled...
Categories: Data;
Tags: Aquatic Biology,
Keweenaw Bay NE,
Lake Superior,
Michigan,
Southcentral Lake Superior,
The dataset accompanies the scientific article, "Reconstructing missing data by comparing interpolation techniques: applications for long-term water quality data." Missingness is typical in large datasets, but intercomparisons of interpolation methods can alleviate data gaps and common problems associated with missing data. We compared seven popular interpolation methods for predicting missing values in a long-term water quality data set from the upper Mississippi River, USA.
Categories: Data;
Tags: Information Sciences,
Mississippi River,
North America,
USGS Science Data Catalog (SDC),
Upper Mississippi River,
The datasets are to accompany a manuscript describing the prediction of submersed aquatic vegetation presence and its potential vulnerability and recovery potential. The data and accompanying analysis scripts allow users to run the final random forests predictive model and reproduce the figures reported in the manuscript. Files from several data sources (aqa_2010_lvl3_pct_oute_joined_VEG_BARCODE.csv, eco_states_near_SAV.csv, ltrm_vegsrs_thru2019_GEOMORPHIC_METRICS_final.csv, vegetation_data.csv, and water_full.csv) were combined into a single .csv file (analysis_data_for_SAV_RandomForest.csv) used as the input for the random forest model. When intersecting points with geomorphic metrics some sites were moved slightly...
This dataset contains the input (temperature and precipitation from climate models) and output from the Soil and Water Assessment Tool (SWAT) model runs using the Hydrologic and Water Quality System (HAWQS) platform (https://hawqs.tamu.edu/). The HAWQS platform is an online tool developed by Texas A&M and US EPA to allow scientists and decision-makers to run large scale watershed simulation models using the Soil & Water Assessment Tool (SWAT) model without the need to download/install software, gather input data, perform initialization steps, or use up local computer resources. We ran the model at the Hydrologic Unit Code-8 scale over Region 3 of the United States Fish and Wildlife Service (Illinois, Indiana, Iowa,...
This georeferenced thermal infrared mosaic of Pool 8 was collected at 0.5 meters/pixel on November 20, 2017 using a mid-wave infrared camera (SC8343, FLIR Systems, Inc., Nashua, NH). This camera was mounted in a Partenavia P68 Observer aircraft and flown at 915m above ground level using a 25mm lens. GPS and inertial measurement unit (IMU) sensors tracked horizontal and vertical position and the IMU tracked sensor orientation (roll, pitch, and heading). These values, along with a 10 meter/pixel resolution digital elevation model, allowed us to orthorectify each frame of thermal imagery to the earth. These orthoimages were then mosaicked into a single image for the entire pool.
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