This dataset contains two phases of research. The first dataset includes several variables that were sampled across aspen stands in the Santa Rosa, Ruby, and Jarbidge mountain ranges (Great Basin, Northern Nevada, USA) in 2010 and 2011. Across 101 aspen sites, several plot-level attributes were collected (e.g. elevation, slope, aspen stand type). For each plot, data describing live trees (both those less than 7.5 cm diameter and those greater than/equal to 7.5 cm) are included, such as species, diameter, and age. The data set also includes information for dead trees greater than/equal to 7.5 cm diameter (e.g. species, location, diameter). The second dataset includes tree ring measurements (for live trees greater than/equal to 7.5 cm diameter) and monthly climate data for a subset of sites (n = 20) that were included in the first phase. For this subset of 20 sites, we analyzed the relationship between tree ring width measurements and climate variables. The climate variables represent monthly total precipitation, average temperature, and climatic moisture index values by year for the period of record.

This dataset contains two phases of research. The first dataset includes several variables that were sampled across aspen stands in the Santa Rosa, Ruby, and Jarbidge mountain ranges (Great Basin, Northern Nevada, USA) in 2010 and 2011. Across 101 aspen sites, several plot-level attributes were collected (e.g. elevation, slope, aspen stand type). For each plot, data describing live trees (both those less than 7.5 cm diameter and those greater than/equal to 7.5 cm) are included, such as species, diameter, and age. The data set also includes information for dead trees greater than/equal to 7.5 cm diameter (e.g. species, location, diameter). The second dataset includes tree ring measurements (for live trees greater than/equal to 7.5 cm diameter) and monthly climate data for a subset of sites (n = 20) that were included in the first phase. For this subset of 20 sites, we analyzed the relationship between tree ring width measurements and climate variables. The climate variables represent monthly total precipitation, average temperature, and climatic moisture index values by year for the period of record.

These data were compiled for research pertaining to the effects of stand density on growth rates in semi-arid forests. Increasing heat and aridity in coming decades is expected to negatively impact tree growth and threaten forest sustainability in dry areas. Maintaining low stand density has the potential to mitigate the negative effects of increasingly severe droughts by minimizing competitive intensity. By inspecting growth rates and the climate and soil moisture conditions that drive these growth rates we can understand better the positive effects of reducing stand density and the specific dynamics that are beneficial to growth.

These data were compiled for research pertaining to the effects of stand density on growth rates in semi-arid forests. Increasing heat and aridity in coming decades is expected to negatively impact tree growth and threaten forest sustainability in dry areas. Maintaining low stand density has the potential to mitigate the negative effects of increasingly severe droughts by minimizing competitive intensity. By inspecting growth rates and the climate and soil moisture conditions that drive these growth rates we can understand better the positive effects of reducing stand density and the specific dynamics that are beneficial to growth.

The dataset includes several variables sampled across 54 recently burned aspen sites, with data collected in 2014 and 2015. Additionally, the dataset includes mean 30-year (1980-2008) and mean six year ‘fire-regen period’ (i.e., fire year and five years after fire) climate values for each site. The climate data presented here were used to calculate explanatory variables used in analysis, as outlined in the publication. Plots were located across a regional climate gradient spanning from the north-central Great Basin to the northeastern portion of the Greater Yellowstone Ecosystem (USA). Several attributes (e.g. tree characteristics, evidence of animal herbivory, shrub cover) were sampled at each plot. All trees present within a plot were counted to determine density. All large trees (stems greater than/equal to 10 cm diameter) were sampled as were all small trees (stems less than 10 cm diameter). Small trees were also divided into two height classes (less than 2 m or greater than/equal to 2 m tall). All trees were identified to species, and all conifers were grouped for analyses.

The dataset includes several variables sampled across 54 recently burned aspen sites, with data collected in 2014 and 2015. Additionally, the dataset includes mean 30-year (1980-2008) and mean six year ‘fire-regen period’ (i.e., fire year and five years after fire) climate values for each site. The climate data presented here were used to calculate explanatory variables used in analysis, as outlined in the publication. Plots were located across a regional climate gradient spanning from the north-central Great Basin to the northeastern portion of the Greater Yellowstone Ecosystem (USA). Several attributes (e.g. tree characteristics, evidence of animal herbivory, shrub cover) were sampled at each plot. All trees present within a plot were counted to determine density. All large trees (stems greater than/equal to 10 cm diameter) were sampled as were all small trees (stems less than 10 cm diameter). Small trees were also divided into two height classes (less than 2 m or greater than/equal to 2 m tall). All trees were identified to species, and all conifers were grouped for analyses.

In the southwestern US, the meteorological phenomenon known as atmospheric rivers (ARs) has gained increasing attention due to its strong connections to floods, snowpacks and water supplies in the West Coast states. Relatively less is known about the ecological implications of ARs, particularly in the interior Southwest, where AR storms are less common. To address this gap, we compared a chronology of AR landfalls on the west coast between 1989-2011 and between 25-42.5ºN, to annual metrics of the Normalized Difference Vegetation Index (NDVI; an indicator of vegetation productivity) and daily-resolution precipitation data to assess influences of AR-fed winter precipitation on vegetation productivity across the southwestern US. We mapped correlations between winter AR precipitation during landfalling ARs and 1) annual maximum NDVI and 2) area burned by large wildfires summarized by ecoregion during the same year as the landfalls and during the following year. The data produced by this study include four sets of eight raster grids (total = 32 grids) representing Spearman Rank correlation coefficients for four types of comparisons across eight different latitudinal bands. Each dataset is named according to the comparison type and latitude of AR landfall. The four types of comparisons (with corresponding filenames indicated in parentheses) include: 1) annual winter atmospheric river precipitation vs. total annual winter precipitation (AR_WinterPrecip), 2) annual winter atmospheric river precipitation vs. annual maximum NDVI (AR_NDVI), 3) spatially-averaged annual winter atmospheric river precipitation vs. area burned by wildfire during the same year by Level IV ecoregion (AR_Fire_SameYear), and 4) spatially-averaged annual winter atmospheric river precipitation vs. area burned by wildfire with a 1-year lag by Level IV ecoregion (AR_Fire_OneYearLag). The eight landfall latitudes are indicated in filenames as follows: 25N, 27_5N, 30N, 32_5N, 35N, 37_5_N, 40N, 42_5N.

In the southwestern US, the meteorological phenomenon known as atmospheric rivers (ARs) has gained increasing attention due to its strong connections to floods, snowpacks and water supplies in the West Coast states. Relatively less is known about the ecological implications of ARs, particularly in the interior Southwest, where AR storms are less common. To address this gap, we compared a chronology of AR landfalls on the west coast between 1989-2011 and between 25-42.5ºN, to annual metrics of the Normalized Difference Vegetation Index (NDVI; an indicator of vegetation productivity) and daily-resolution precipitation data to assess influences of AR-fed winter precipitation on vegetation productivity across the southwestern US. We mapped correlations between winter AR precipitation during landfalling ARs and 1) annual maximum NDVI and 2) area burned by large wildfires summarized by ecoregion during the same year as the landfalls and during the following year. The data produced by this study include four sets of eight raster grids (total = 32 grids) representing Spearman Rank correlation coefficients for four types of comparisons across eight different latitudinal bands. Each dataset is named according to the comparison type and latitude of AR landfall. The four types of comparisons (with corresponding filenames indicated in parentheses) include: 1) annual winter atmospheric river precipitation vs. total annual winter precipitation (AR_WinterPrecip), 2) annual winter atmospheric river precipitation vs. annual maximum NDVI (AR_NDVI), 3) spatially-averaged annual winter atmospheric river precipitation vs. area burned by wildfire during the same year by Level IV ecoregion (AR_Fire_SameYear), and 4) spatially-averaged annual winter atmospheric river precipitation vs. area burned by wildfire with a 1-year lag by Level IV ecoregion (AR_Fire_OneYearLag). The eight landfall latitudes are indicated in filenames as follows: 25N, 27_5N, 30N, 32_5N, 35N, 37_5_N, 40N, 42_5N.

In the southwestern US, the meteorological phenomenon known as atmospheric rivers (ARs) has gained increasing attention due to its strong connections to floods, snowpacks and water supplies in the West Coast states. Relatively less is known about the ecological implications of ARs, particularly in the interior Southwest, where AR storms are less common. To address this gap, we compared a chronology of AR landfalls on the west coast between 1989-2011 and between 25-42.5ºN, to annual metrics of the Normalized Difference Vegetation Index (NDVI; an indicator of vegetation productivity) and daily-resolution precipitation data to assess influences of AR-fed winter precipitation on vegetation productivity across the southwestern US. We mapped correlations between winter AR precipitation during landfalling ARs and 1) annual maximum NDVI and 2) area burned by large wildfires summarized by ecoregion during the same year as the landfalls and during the following year. The data produced by this study include four sets of eight raster grids (total = 32 grids) representing Spearman Rank correlation coefficients for four types of comparisons across eight different latitudinal bands. Each dataset is named according to the comparison type and latitude of AR landfall. The four types of comparisons (with corresponding filenames indicated in parentheses) include: 1) annual winter atmospheric river precipitation vs. total annual winter precipitation (AR_WinterPrecip), 2) annual winter atmospheric river precipitation vs. annual maximum NDVI (AR_NDVI), 3) spatially-averaged annual winter atmospheric river precipitation vs. area burned by wildfire during the same year by Level IV ecoregion (AR_Fire_SameYear), and 4) spatially-averaged annual winter atmospheric river precipitation vs. area burned by wildfire with a 1-year lag by Level IV ecoregion (AR_Fire_OneYearLag). The eight landfall latitudes are indicated in filenames as follows: 25N, 27_5N, 30N, 32_5N, 35N, 37_5_N, 40N, 42_5N.

These tabular data were compiled for/to monitor vegetation and biocrust cover in a never grazed grassland located in Canyonlands National Park. An objective, or objectives, of our study was to document potential changes in biocrust and vegetation cover and species composition as related to changes in land use and climate change. These data represent a timeseries of long-term vegetation and biocrust monitoring plots, dating from 1996 to 2021. These data were collected at/in Virginia Park, Needles District of Canyonlands National Park, Utah. These data were collected by the U.S. Geological Survey, Southwest Biological Research Center in coordination with the US National Park Service. Data were collected via field observations twice annually, once in the Spring (April-May) and once in fall (Sept.) starting in 1996. A weather station was established in 1998 which recorded hourly temperature and precipitation measurements on a portable data storage module which was switched out and downloaded approximately every 3 months. These data can be used to monitor long term trends and changes in vegetation in a rare, protected and never grazed grassland on the Colorado Plateau, and help with monitoring trends in similar dryland ecosystems.