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Located in the northern tropical Pacific Ocean, Majuro is the capital of the Republic of the Marshall Islands. Majuro Atoll consists of a large, narrow landmass and a set of smaller perimeter islands surrounding a lagoon that is over 100 square miles in size. The waters surrounding the Majuro Atoll land areas are relatively shallow with poorly mapped bathymetry. However, the Pacific Ocean on the exterior of the coral atoll and the lagoon within its interior consist of deep bathymetry with steep slopes. The highest elevation of the Majuro Atoll is estimated at only 3-meters above sea level, which is the island community of Laura located on the western part of the atoll. At the eastern edge of the atoll lies the capital...
Categories: Data;
Tags: 3D Elevation Program,
3DEP,
American Society of Photogrammetry and Remote Sensing,
Base Maps,
Bathymetric,
Prescribed burning is a critical tool for managing wildfire risks and meeting ecological objectives, but its safe and effective application requires that specific meteorological criteria are met. This dataset contains results from a study examining the potential impacts of projected climatic change on prescribed burning in the southeastern United States. A set of burn window criteria (suitable weather conditions within which burning may occur based on maximum daily temperature, daily average relative humidity, and daily average wind speed), were applied to projections from an ensemble of Global Climate Models (GCM) under two greenhouse gas emission scenarios, as well as past observations for comparison. Data are...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Alabama,
Arkansas,
Florida,
Georgia,
Kentucky,
Prescribed burning is a critical tool for managing wildfire risks and meeting ecological objectives, but its safe and effective application requires that specific meteorological criteria are met. This dataset contains results from a study examining the potential impacts of projected climatic change on prescribed burning in the southeastern United States. A set of burn window criteria (suitable weather conditions within which burning may occur based on maximum daily temperature, daily average relative humidity, and daily average wind speed), were applied to projections from an ensemble of Global Climate Models (GCM) under two greenhouse gas emission scenarios, as well as past observations for comparison. Data are...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Alabama,
Arkansas,
Florida,
Georgia,
Kentucky,
This study monitored soil surface elevation change from mangrove forests fertilized with nitrogen and phosphorus from 2018-2021. The mangroves selected at Ding Darling National Wildlife Refuge (NWR) have been previously exposed to high nutrient loading from agricultural discharge into the Caloosahatchee River, which elevated soil phosphorus levels to 3-4 times ambient before treatments were impose. Sea-level rise vulnerability with additional nitrogen and phosphorus is a concern for these mangrove ecosystems.
Categories: Data;
Tags: Ecology,
Florida,
Gulf of Mexico,
Sanibel Island,
USGS Science Data Catalog (SDC),
The dataset summarizes total area (km2) and proportion of Central Valley waterbird habitat, summed across individual waterbird habitats (i.e., wetland and cropland types), that was available for each of 17 projected scenarios. The dataset also includes relatively recent (year 2005) area of existing habitat (i.e., “existing area”) for comparison with areas based on scenarios. Analysis was conducted for the projection period including water-years 2006–2099 (water-year defined as October-December and January–September of the following year). Because habitat areas vary through the season with timing of crop harvest and flooding of wetlands and post-harvested fields, annual areas and proportions represent summation...
Categories: Data;
Tags: Central Valley of California,
climate change,
cropland,
habitat,
urbanization,
This dataset is a continuous parameter grid (CPG) of normal (average) annual precipitation data for the years 1981 through 2010 in the Pacific Northwest. Source precipitation data was produced by the PRISM Climate Group at Oregon State University.
These datasets are continuous parameter grids (CPG) of permeability (and impermeability) of surface geology in the Pacific Northwest. Source data come from work by Chris Konrad, U.S. Geological Survey (USGS), and geologic map databases produced by USGS scientists.
Low-lying island environments, such as the Majuro Atoll in the Republic of the Marshall Islands, are particularly vulnerable to inundation (coastal flooding) whether the increased water levels are from episodic events (storm surge, wave run-up, king tides) or from chronic conditions (long term sea-level rise). Land elevation is the primary geophysical variable that determines exposure to inundation in coastal settings. Accordingly, coastal elevation data are a critical input for assessments of inundation exposure and vulnerability. Previous research has demonstrated that the quality of data used for elevation-based assessments must be well understood and applied to properly model potential impacts. The vertical...
The RTK survey, using a Trimble unit, was conducted in August 2021 in the coastal plains region (1002 area) of the Arctic National Wildlife Refuge, as part of a landscape vulnerability assessment. A total of six transects are included in the data, including five research sites and one transect collected at the camp site. Mean horizontal precision was 0.006m, mean vertical precision was 0.011m.
Categories: Data;
Tags: Arctic,
Arctic National Wildlife Refuge,
Climatology,
Geography,
Geomorphology,
Daily HOBO Pro V.2 soil temperature measurements at the Great Dismal Swamp National Wildlife Refuge (2015-2017). Data collected in Great Dismal Swamp National Wildlife Refuge in Southern VA and Northern NC from 9 plot sites representing three general forest types: Atlantic White Cedar, Pocosin Pine, and Maple and Gum.
Categories: Data;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: Climate,
Great Dismal Swamp National Wildlife Refuge,
Soil Sciences,
USGS Science Data Catalog (SDC),
Wetland
Daily lake surface temperatures estimates for 185,549 lakes across the contiguous United States from 1980 to 2020 generated using an entity-aware long short-term memory deep learning model. In-situ measurements used for model training and evaluation are from 12,227 lakes and are included as well as daily meteorological conditions and lake properties. Median per-lake estimated error found through cross validation on lakes with in-situ surface temperature observations was 1.24 °C. The generated dataset will be beneficial for a wide range of applications including estimations of thermal habitats and the impacts of climate change on inland lakes.
Accurate elevation data in coastal wetlands is crucial for planning for sea-level rise. Elevation surveys were conducted across southwest Florida wetlands to provide ground validation of LiDAR as well as target long-term monitoring stations (surface elevation tables). Surveys were conducted in June 2021 across Ding Darling National Wildlife Refuge, Clam Bay, Rookery Bay National Estuarine Research Reserve, and Ten Thousand Islands National Wildlife Refuge. A combination of post-processed kinematic GPS and differential levelling survey techniques were employed, depending on the canopy cover.
Categories: Data;
Tags: Clam Bay,
Ding Darling National Wildlife Refuge,
Florida,
GPS measurement,
RTK GPS,
Inland fishes provide important ecosystem services to communities worldwide and are especially vulnerable to the impacts of climate change. Fish respond to climate change in diverse and nuanced ways which creates challenges for practitioners of fish conservation, climate change adaptation, and management. Although climate change is known to affect fish globally, a comprehensive online, public database of how climate change has impacted inland fishes worldwide and adaptation or management practices that may address these impacts does not exist. We conducted an extensive, systematic primary literature review to identify peer-reviewed journal publications describing projected and documented examples of climate change...
This data release contains inputs for and outputs from hydrologic simulations for the conterminous United States (CONUS) using the Precipitation Runoff Modeling System (PRMS) version 5.1.0 and the USGS National Hydrologic Model Infrastructure (NHMI, Regan and others, 2018). Historical simulations using the Maurer forcings (Maurer and others, 2002) were conducted for the period 1950-2010. This metadata record documents the simulation output files for simulations ran using the dynamic parameters file. The output files are aggregated at the HUC4 level and are grouped and downloadable by HUC2 hydrologic region. Each zip folder contains identical information, just for a different region and set of hydrologic response...
This dataset details individual species and natural habitat vulnerability rankings, including contextual study-specific information. This data was collected from original publications found through a literature search. Information is cumulative to include climate change vulnerability assessment (CCVA) results summarized in Staudinger et al. (2015) and published as of December 2023.
Categories: Data;
Tags: CCVA,
Climate Change Vulnerability Assessment,
Climatology,
Connecticut,
Delaware,
This data release is comprised of tidal marsh biomass data and spatial predictions of peak biomass and Julian day of peak biomass using data from the Landsat archive. Aboveground biomass dry weight of mixed-species plots (25x50 cm) at a tidal marsh in Willapa Bay, Washington were used to establish a relationship between biomass and tasseled cap greeness (TCG). The julian day of annual peak greenness and the value of annual peak greenness for 32 years at Bandon National Wildlife Refuge (NWR), Grays Harbor NWR, and Nisqually NWR was calculated by fitting a Gaussian function to the TCG values for a given year. The value of each 30 meter pixel is the Julian day of maximum predicted TCG or the maximum predicted TCG....
This dataset provides model specifications used to estimate water temperature from a process-based model (Hipsey et al. 2019). The format is a single JSON file indexed for each lake based on the "site_id". This dataset is part of a larger data release of lake temperature model inputs and outputs for 68 lakes in the U.S. states of Minnesota and Wisconsin (http://dx.doi.org/10.5066/P9AQPIVD).
This dataset includes model inputs that describe local weather conditions for Sparkling Lake, WI. Weather data comes from two sources: locally measured (2009-2017) and gridded estimates (all other time periods). There are two comma-delimited files, one for weather data (one row per model timestep) and one for ice-flags, which are used by the process-guided deep learning model to determine whether to apply the energy conservation constraint (the constraint is not applied when the lake is presumed to be ice-covered). The ice-cover flag is a modeled output and therefore not a true measurement (see "Predictions" and "pb0" model type for the source of this prediction). This dataset is part of a larger data release of...
Multiple modeling frameworks were used to predict daily temperatures at 0.5m depth intervals for a set of diverse lakes in the U.S. states of Minnesota and Wisconsin. Process-Based (PB) models were configured and calibrated with training data to reduce root-mean squared error. Uncalibrated models used default configurations (PB0; see Winslow et al. 2016 for details) and no parameters were adjusted according to model fit with observations. Deep Learning (DL) models were Long Short-Term Memory artificial recurrent neural network models which used training data to adjust model structure and weights for temperature predictions (Jia et al. 2019). Process-Guided Deep Learning (PGDL) models were DL models with an added...
This dataset includes model inputs that describe weather conditions for the 68 lakes included in this study. Weather data comes from gridded estimates (Mitchell et al. 2004). There are two comma-separated files, one for weather data (one row per model timestep) and one for ice-flags, which are used by the process-guided deep learning model to determine whether to apply the energy conservation constraint (the constraint is not applied when the lake is presumed to be ice-covered). The ice-cover flag is a modeled output and therefore not a true measurement (see "Predictions" and "pb0" model type for the source of this prediction). This dataset is part of a larger data release of lake temperature model inputs and outputs...
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