Filters: Tags: Sonoran Desert (X) > partyWithName: U.S. Geological Survey - ScienceBase (X)
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These data were compiled to evaluate the reproductive ecology of Agassiz's desert tortoises (Gopherus agassizzi) in the Sonoran Desert of California using two populations within Joshua Tree National Park, including five reproductive seasons that spanned 20 years (1997-1999, 2015-2016). Compared to their conspecifics inhabiting the Mojave Desert, the reproductive ecology of G. agassizii in the Sonoran Desert is understudied. Climatic variation between the two deserts can affect reproductive ecology, including fecundity and clutch phenology. Mature female tortoises (straight-line carapace length ≥ 20 cm) outfitted with radiotransmitters were located and X-radiographed approximately every 10-14 days during the reproductive...
Categories: Data;
Tags: Agassiz's desert tortoise,
California,
Ecology,
Geography,
Gopherus agassizii,
Five principal components are used to represent the climate variation in an original set of 12 composite climate variables reflecting complex precipitation and temperature gradients. The dataset provides coverage for future climate (defined as the 2040-2070 normal period) under the RCP4.5 emission scenarios. Climate variables were chosen based on their known influence on local adaptation in plants, and include: mean annual temperature, summer maximum temperature, winter minimum temperature, annual temperature range, temperature seasonality (coefficient of variation in monthly average temperatures), mean annual precipitation, winter precipitation, summer precipitation, proportion of summer precipitation, precipitation...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Arizona,
California,
Colorado,
Colorado Plateau,
Great Basin,
Climate Distance Mapper is an interactive web mapping application designed to facilitate informed seed sourcing decisions and to aid in directing regional seed collections. Implemented as a shiny web application (Chang et al. 2017), Climate Distance Mapper is hosted on the web at: https://usgs-werc-shinytools.shinyapps.io/Climate_Distance_Mapper/. The application is designed to guide restoration seed sourcing in the desert southwest by allowing users to interactively match seed sources with restoration sites climatic differences – in the form of multivariate climate distance values – between restoration sites and the surrounding landscape. Climatic distances are based on a combination of variables likely to influence...
Five principal components are used to represent the climate variation in an original set of 12 composite climate variables reflecting complex precipitation and temperature gradients. The dataset provides coverage for future climate (defined as the 2040-2070 normal period) under the RCP8.5 emission scenarios. Climate variables were chosen based on their known influence on local adaptation in plants, and include: mean annual temperature, summer maximum temperature, winter minimum temperature, annual temperature range, temperature seasonality (coefficient of variation in monthly average temperatures), mean annual precipitation, winter precipitation, summer precipitation, proportion of summer precipitation, precipitation...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Arizona,
California,
Colorado,
Colorado Plateau,
Great Basin,
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....
These data were compiled for a networked field-trial restoration experiment (RestoreNet) that spans the southwestern US, including 21 distributed field sites. The objective of our study was to understand the environmental factors and restoration practices (including seed mixes and soil manipulation) that increase plant establishment and survival to ultimate improve restoration outcomes in dryland environments. These data represent point-in-time plant density and height measurements at our field sites at the time of monitoring. These data were collected at 21 arid and semi-arid sites, located throughout Arizona, Utah, New Mexico, and California. These data were collected by USGS Restoration Assessment and Monitoring...
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 study uses growth in vegetation during the monsoon season measured from LANDSAT imagery as a proxy for measured rainfall. NDVI values from 26 years of pre- and post-monsoon season Landsat imagery were derived across Yuma Proving Ground (YPG) in southwestern Arizona, USA. The LANDSAT imagery (1986-2011) was downloaded from USGS’s GlobeVis website (http://glovis.usgs.gov/). Change in NDVI was calculated within a set of 2,843 Riparian Area Polygons (RAPs) up to 1 km in length defined in ESRI ArcMap 10.2.
Categories: Data;
Types: Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
Shapefile;
Tags: Arizona,
Landsat TM,
NDVI,
Normalized Difference Vegetation Index,
Sonoran Desert,
The U.S. Geological Survey collected groundwater samples from 38 wells used for domestic and small system drinking water supply in the Coachella Valley of California in 2020. The wells were sampled for the Coachella Valley Basin (CODA) Domestic Aquifer Study Unit of the California State Water Resources Control Board Groundwater Ambient Monitoring and Assessment (GAMA) Program Priority Basin Project’s assessment of the quality of groundwater resources used for domestic and small system drinking water supplies. Coachella Valley is located in the Desert hydrogeologic province (Johnson and Belitz, 2003) and is structurally divided into four subbasins by the San Andreas fault: the Indio subbasin, the Mission Creek subbasin,...
Categories: Data;
Tags: California,
Coachella Valley,
GAMA,
Groundwater Ambient Monitoring and Assessment Program,
Hydrology,
The RCMAP (Rangeland Condition Monitoring Assessment and Projection) dataset quantifies the percent cover of rangeland components across western North America using Landsat imagery from 1985-2023. The RCMAP product suite consists of ten fractional components: annual herbaceous, bare ground, herbaceous, litter, non-sagebrush shrub, perennial herbaceous, sagebrush, shrub, tree, and shrub height in addition to the temporal trends of each component. Several enhancements were made to the RCMAP process relative to prior generations. First, high-resolution training was revised using an improved neural-net classifier and modelling approach. These data serve as foundation to the RCMAP approach. The training database was...
The RCMAP (Rangeland Condition Monitoring Assessment and Projection) dataset quantifies the percent cover of rangeland components across western North America using Landsat imagery from 1985-2023. The RCMAP product suite consists of ten fractional components: annual herbaceous, bare ground, herbaceous, litter, non-sagebrush shrub, perennial herbaceous, sagebrush, shrub, tree, and shrub height in addition to the temporal trends of each component. Several enhancements were made to the RCMAP process relative to prior generations. First, high-resolution training was revised using an improved neural-net classifier and modelling approach. These data serve as foundation to the RCMAP approach. The training database was...
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....
The need to monitor change in sagebrush steppe is urgent due to the increasing impacts of climate change, shifting fire regimes, and management practices on ecosystem health. Remote sensing provides a cost-effective and reliable method for monitoring change through time and attributing changes to drivers. We report an automated method of mapping rangeland fractional component cover over a large portion of the Northern Great Basin, USA, from 1986 to 2016 using a dense Landsat imagery time series. 2012 was excluded from the time-series due to a lack of quality imagery. Our method improved upon the traditional change vector method by considering the legacy of change at each pixel. We evaluate cover trends stratified...
These data were compiled for the creation of a continuous, transboundary land cover map of Bird Conservation Region 33, Sonoran and Mojave Deserts (BCR 33). Objective(s) of our study were to, 1) develop a machine learning (ML) algorithm trained to classify vegetation land cover using remote sensing spectral data and phenology metrics from 2013-2020, over a large subregion of the Sonoran and Mojave Deserts BCR, 2) Calibrate, validate, and refine the final ML-derived vegetation map using a collection of openly sourced remote sensing and ground-based ancillary data, images, and limited fieldwork, and 3) Harmonize a new transboundary classification system by expanding existing land cover mapping resources from the United...
Categories: Data;
Types: Downloadable,
GeoTIFF,
Map Service,
Raster;
Tags: Arizona,
Baja California,
Botany,
California,
Ecology,
The RCMAP (Rangeland Condition Monitoring Assessment and Projection) dataset quantifies the percent cover of rangeland components across western North America using Landsat imagery from 1985-2023. The RCMAP product suite consists of ten fractional components: annual herbaceous, bare ground, herbaceous, litter, non-sagebrush shrub, perennial herbaceous, sagebrush, shrub, tree, and shrub height in addition to the temporal trends of each component. Several enhancements were made to the RCMAP process relative to prior generations. First, high-resolution training was revised using an improved neural-net classifier and modelling approach. These data serve as foundation to the RCMAP approach. The training database was...
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....
The need to monitor change in sagebrush steppe is urgent due to the increasing impacts of climate change, shifting fire regimes, and management practices on ecosystem health. Remote sensing provides a cost-effective and reliable method for monitoring change through time and attributing changes to drivers. We report an automated method of mapping rangeland fractional component cover over a large portion of the Northern Great Basin, USA, from 1986 to 2016 using a dense Landsat imagery time series. 2012 was excluded from the time-series due to a lack of quality imagery. Our method improved upon the traditional change vector method by considering the legacy of change at each pixel. We evaluate cover trends stratified...
The U.S. Geological Survey collected groundwater samples from 38 wells used for domestic and small system drinking water supply in the Coachella Valley of California in 2020. The wells were sampled for the Coachella Valley Basin (CODA) Domestic Aquifer Study Unit of the California State Water Resources Control Board Groundwater Ambient Monitoring and Assessment (GAMA) Program Priority Basin Project’s assessment of the quality of groundwater resources used for domestic and small system drinking water supplies. Coachella Valley is located in the Desert hydrogeologic province (Johnson and Belitz, 2003) and is structurally divided into four subbasins by the San Andreas fault: the Indio subbasin, the Mission Creek subbasin,...
The RCMAP (Rangeland Condition Monitoring Assessment and Projection) dataset quantifies the percent cover of rangeland components across western North America using Landsat imagery from 1985-2023. The RCMAP product suite consists of ten fractional components: annual herbaceous, bare ground, herbaceous, litter, non-sagebrush shrub, perennial herbaceous, sagebrush, shrub, tree, and shrub height in addition to the temporal trends of each component. Several enhancements were made to the RCMAP process relative to prior generations. First, high-resolution training was revised using an improved neural-net classifier and modelling approach. These data serve as foundation to the RCMAP approach. The training database was...
The RCMAP (Rangeland Condition Monitoring Assessment and Projection) dataset quantifies the percent cover of rangeland components across western North America using Landsat imagery from 1985-2023. The RCMAP product suite consists of ten fractional components: annual herbaceous, bare ground, herbaceous, litter, non-sagebrush shrub, perennial herbaceous, sagebrush, shrub, tree, and shrub height in addition to the temporal trends of each component. Several enhancements were made to the RCMAP process relative to prior generations. First, high-resolution training was revised using an improved neural-net classifier and modelling approach. These data serve as foundation to the RCMAP approach. The training database was...
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