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The point data file ("Soda Fire Point and Pasture Data (2016).Point Data.csv") includes 2016 vegetative cover values of exotic annual grass and perennial grass measured within three different types of plots for 75 pastures in the Soda Fire, which burned in 2015: 6m² plot using a grid-point intercept photo software, SamplePoint (Booth et al. 2006), 1m² quadrat using an unguided rapid ocular estimate in the field, 531m² circular plot using an unguided rapid ocular estimate in the field. Smaller plots were nested within larger plots. The pasture data file ("Soda Fire Point and Pasture Data (2016).Pasture Data.csv") includes pasture level metrics of area, elevation, precipitation, slope, heatload, soils, and herbicide...
This dataset provides timeseries data on water quality and quantity, as collected or computed from outside sources. The format is many tables with one row per time series observation (1 tab-delimited file per site-variable combination, 1 zip file per site). This compilation of data is intended for use in estimating or interpreting metabolism. Sites were included if they met the initial criteria of having at least 100 dissolved oxygen observations and one of the accepted NWIS site types ('ST','ST-CA','ST-DCH','ST-TS', or 'SP'). This dataset is part of a larger data release of metabolism model inputs and outputs for 356 streams and rivers across the United States (https://doi.org/10.5066/F70864KX). The complete release...
Land management practices often directly alter vegetation structure and composition, but the degree to which ecological processes such as herbivory interact with management to influence biodiversity is less well understood. We hypothesized that intensive forest management and large herbivores have compounding effects on early-seral plant communities and plantation establishment (i.e., tree survival and growth), and the degree of such effects is dependent on the intensity of management practices. We established 225 m2 wild ungulate (deer and elk) exclosures nested within a manipulated gradient of management intensity (no-spray Control, Light herbicide, Moderate herbicide and Intensive herbicide treatments), replicated...
Categories: Data;
Types: Citation;
Tags: Lincoln County, Oregon,
Oregon,
Oregon Coast Range,
Pacific Northwest,
Polk County, Oregon,
The dataset supports a larger study that examined the impacts of three tackifiers (guar, psyllium, and polyacrylamide) on growth of two dryland mosses (Bryum argenteum and Syntrichia ruralis). Moss fragments were grown in petri dishes and subjected to individual tackifiers in one of three possible concentrations (0.5x, 1x, or 2x) of the respective manufacturer's recommended application rate. Distilled water was used as a control treatment, giving a total of ten treatments (nine tackifier-concentration combinations and a water control). Bryum fragments were watered four times daily for six weeks and Syntrichia fragments were watered twice daily for five weeks, after which the experiments were concluded. Shoot length,...
These data represent simulated soil temperature and moisture conditions for current climate, and for future climate represented by all available climate models at two time periods during the 21st century. These data were used to: 1) quantify the direction and magnitude of expected changes in several measures of soil temperature and soil moisture, including the key variables used to distinguish the regimes used in the R and R categories; 2) assess how these changes will impact the geographic distribution of soil temperature and moisture regimes; and 3) explore the implications for using R and R categories for estimating future ecosystem resilience and resistance.
Fifteen fires from the Chronosequence dataset (see Knutson et al. 2014) were visited in 2012 and 2013 and surveyed for cover of lichens and mosses. Fires were selected to cover the range of average precipitation for each of three water years following fire, fire severity, time since fire, season of ignition, total acres burned and grazing intensity. Cattle grazing was characterized by distance from water sources for cattle, cow dung density counts and Animal Unit Months from the Rangeland Administration System of the Bureau of Land Management. Fire was characterized by whether or not a site burned, time since fire, the area burned, and an estimated amount of shrub cover consumed by the fire as compared to seemingly...
Data includes satellite derived pre-fire functional group cover of annual and perennial herbaceous, shrubs, bareground and litter across four rangeland megafires in the Western US, as well as field estimated invasive annual grass measurements from the 2nd to 3rd years post-fire. Additional landscape and restoration treatment covariates hypothesized to influence post-fire invasive annual grass cover are included.
The RCMAP (Rangeland Condition Monitoring Assessment and Projection) dataset quantifies the percent cover of rangeland components across the western U.S. using Landsat imagery from 1985-2021. The RCMAP product suite consists of nine fractional components: annual herbaceous, bare ground, herbaceous, litter, non-sagebrush shrub, perennial herbaceous, sagebrush, shrub, and tree, in addition to the temporal trends of each component. Several enhancements were made to the RCMAP process relative to prior generations. First, we have trained time-series predictions directly from 331 high-resolution sites collected from 2013-2018 from Assessment, Inventory, and Monitoring (AIM) instead of using the 2016 “base” map as an intermediary....
This data release documents proposed updates to geologic inputs (faults) for the upcoming 2023 National Seismic Hazard Model (NSHM). This version (1.0) conveys differences between 2014 NSHM fault sources and those recently released in the earthquake geology inputs for the U.S. National Seismic Hazard Model (NSHM) 2023, version 1.0 data release by Hatem et al. (2021). A notable difference between the 2014 and 2023 datasets is that slip rates are provided at points for 2023 instead of generalized along the entire fault section length as in 2014; consequently, slip rates are not provided for fault sections in the draft 2023 dataset. Geospatial data (shapefile, kml and geojson) are provided in this data release with...
Categories: Data;
Types: Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Shapefile;
Tags: Arizona,
California,
Colorado,
Idaho,
Nevada,
The Murderer’s Creek mule deer herd winters south of U.S. Route 26 in river valleys near Canyon Creek, Murderer’s Creek, and the South Fork John Day River. The herd’s winter ranges are characterized by western juniper, big sagebrush, and Columbia Basin grassland communities, with medusahead and other non-native grasses invading lower elevations. In the spring, mule deer mainly migrate southeast to summer ranges distributed throughout Gilbert Ridge and the Aldrich Mountains, some traveling as far south as Devon Ridge and east to Ironside Mountain. Summer ranges in these areas contain mixed-conifer forests, ponderosa pine, and low sagebrush communities. A smaller portion of this herd migrates northeast in the spring,...
Categories: Data;
Types: Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Shapefile;
Tags: John Day,
Oregon,
United States,
animal behavior,
biota,
The Trout Creek mule deer herd is composed of residents and migrants that make short-range elevational migrations. Mule deer mainly winter at lower elevations surrounding Blue Mountain and the slopes of the Oregon Canyon Mountains. In spring, some of these mule deer migrate to higher elevations in the Oregon Canyon Mountains. Other members of the herd winter in the southwestern portion of the herd’s range, inhabiting areas near Hawks Mountain, the Pueblo Mountains, and the foothills of the Trout Creek Mountains. These mule deer migrate to summer ranges on the crests of Holloway Mountain and the Trout Creek Mountains. Notably, one mule deer formerly wintering on the Trout Creek Mountains migrated south from a summer...
Categories: Data;
Types: Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Shapefile;
Tags: Fields,
Oregon,
United States,
animal behavior,
biota,
The Trout Creek mule deer herd is composed of residents and migrants that make short-range elevational migrations. Mule deer mainly winter at lower elevations surrounding Blue Mountain and the slopes of the Oregon Canyon Mountains. In spring, some of these mule deer migrate to higher elevations in the Oregon Canyon Mountains. Other members of the herd winter in the southwestern portion of the herd’s range, inhabiting areas near Hawks Mountain, the Pueblo Mountains, and the foothills of the Trout Creek Mountains. These mule deer migrate to summer ranges on the crests of Holloway Mountain and the Trout Creek Mountains. Notably, one mule deer formerly wintering on the Trout Creek Mountains migrated south from a summer...
Categories: Data;
Types: Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Shapefile;
Tags: Fields,
Oregon,
United States,
animal behavior,
biota,
April through May (spring) and August through September (fall) locations for tule greater white-fronted geese (Anser albifrons elgasi) marked with GPS collars at Summer Lake Wildlife Area, OR in 2018 and 2019. Locations may include pre-migration and post-migration designations. Locations occurring between September 11, 2020, and arrival at, or within 50 kilometers of the Summer Lake Wildlife Area stopover location also provided with elevation information and smoke concentrations derived from the experimental HRRR-Smoke model. Median predicted smoke concentrations extrapolated from ground level through 5,000 meters also provided. These data supports the following publication: Overton, C.T., Lorenz, A.A., James,...
This dataset provides early estimates of 2021 exotic annual grasses (EAG) fractional cover predicted on May 3rd. We develop and release EAG fractional cover map with an emphasis on cheatgrass (Bromus tectrorum) but it also includes number of other species, i.e., Bromus arvensis L., Bromus briziformis, Bromus catharticus Vahl, Bromus commutatus, Bromus diandrus, Bromus hordeaceus L., Bromus japonicus, Bromus madritensis L., Bromus racemosus, Bromus rubens L., Bromus secalinus L., Bromus texensis (Shear) Hitchc., and medusahead (Taeniatherum caput-medusae. The dataset was generated leveraging field observations from Bureau of Land Management (BLM) Assessment, Inventory, and Monitoring data (AIM) plots; Harmonized...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Arizona,
California,
Colorado,
Great Basin,
Harmonized Landsat Sentinel,
Across the country, public land managers make hundreds of decisions each year that influence landscapes and ecosystems within the lands they manage. Many of these decisions involve vegetation manipulations known as land treatments. Land treatments include activities such as removal or alteration of plant biomass, seeding burned areas, and herbicide applications. Data on these land treatments historically have been stored at local offices and gathering information across large spatial areas was difficult. These valuable data needed to be centralized and stored for Federal agencies involved in land treatments because these data are useful to land managers for policy and management and to scientists for developing...
Prior research has shown that sediment budgets, and therefore stability, of microtidal marsh complexes scale with areal unvegetated to vegetated marsh ratios (UVVR) suggesting these metrics are broadly applicable indicators of microtidal marsh vulnerability. This effort has developed the UVVR metric using readily available satellite imagery for the coastal areas of the contiguous United States (CONUS). These datasets provide annual averages of 1) developed, 2) vegetated, 3) unvegetated ratios and 4) an unvegetated to vegetated ratio (UVVR) at 30-meter resolution over the coastal areas of the contiguous United States for the years 2014-2018. Additionally, multi-year average values of vegetated ratio, its standard...
Prior research has shown that sediment budgets, and therefore stability, of microtidal marsh complexes scale with areal unvegetated to vegetated marsh ratios (UVVR) suggesting these metrics are broadly applicable indicators of microtidal marsh vulnerability. This effort has developed the UVVR metric using readily available satellite imagery for the coastal areas of the contiguous United States (CONUS). These datasets provide annual averages of 1) developed, 2) vegetated, 3) unvegetated ratios and 4) an unvegetated to vegetated ratio (UVVR) at 30-meter resolution over the coastal areas of the contiguous United States for the years 2014-2018. Additionally, multi-year average values of vegetated ratio, its standard...
Climate change over the past century has altered vegetation community composition and species distributions across rangelands in the western United States. The scale and magnitude of climatic influences are largely unknown. We used fractional component cover data for rangeland functional groups and weather data from the 1985 to 2023 reference period in conjunction with soils and topography data to develop empirical models describing the spatio-temporal variation in component cover. To investigate the ramifications of future change across the western US, we extended models based on historical relationships over the reference period to model landscape effects based on future weather conditions from two emissions scenarios...
This child item describes Python code used to estimate average yearly and monthly tourism per 1000 residents within public-supply water service areas. Increases in population due to tourism may impact amounts of water used by public-supply water systems. This data release contains model input datasets, Python code used to develop the tourism information, and output estimates of tourism. This dataset is part of a larger data release using machine learning to predict public supply water use for 12-digit hydrologic units from 2000-2020. Output from this code was used as an input feature in the public supply delivery and water use machine learning models. This page includes the following files: tourism_input_data.zip...
This child item describes a public supply delivery machine learning model that was developed to estimate public-supply deliveries. Publicly supplied water may be delivered to domestic users or to commercial, industrial, institutional, and irrigation (CII) users. This model predicts total, domestic, and CII per capita rates for public-supply water service areas within the conterminous United States for 2009-2020. This child item contains model input datasets, code used to build the delivery machine learning model, and national predictions. This dataset is part of a larger data release using machine learning to predict public-supply water use for 12-digit hydrologic units from 2000-2020. This page includes the following...
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