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Variability of the terrestrial global carbon sink is largely determined by the response of dryland productivity to annual precipitation. Despite extensive disturbance in drylands, how disturbance alters productivity-precipitation relationships remains poorly understood. Using remote-sensing to pair more than 5600 km of natural gas pipeline corridors with neighboring undisturbed areas in North American drylands, we found that disturbance reduced average annual production 6 to 29% and caused up to a fivefold increase in the sensitivity of net primary productivity (NPP) to interannual variation in precipitation. Disturbance impacts were larger and longer-lasting at locations with higher precipitation (>450 mm mean annual precipitation). Disturbance effects on NPP dynamics were mostly explained by shifts from woody to herbaceous vegetation. Severe disturbance will amplify effects of increasing precipitation variability on NPP in drylands.

 

This dataset contains cover and biomass data collected starting in 2012 for a long-term precipitation variability manipulation experiment at the Jornada Basin LTER site in southern New Mexico, U.S.A. The study was designed to assess the effect of interannual variability in precipitation on average aboveground net primary productivity (ANPP) in Chihuahuan Desert grasslands. The study began in 2009, has five annual precipitation treatments, and contains 50 plots (10 per treatment). This experiment uses precipitation shelters and irrigation treatments to manipulate water inputs to 2.5 x 2.5 meter plots in a desert grassland. There are high, low, and ambient (control) precipitation variability treatments. Ambient plots receive natural precipitation each year, while variability treatments alternate between 20% and 180% (high variability), or 50% and 150% (low variability) of ambient precipitation each year. Plant cover measurements are made annually in each plot, from which biomass or net primary production are derived. This is an ongoing study and the dataset will be updated yearly. 

This dataset contains perennial grass tiller and stolon counts collected starting in 2012 for a long-term precipitation variability manipulation experiment at the Jornada Basin LTER site in southern New Mexico, U.S.A. The study was designed to assess the effect of interannual variability in precipitation on average aboveground net primary productivity (ANPP) in Chihuahuan Desert grasslands. The study began in 2009, has five annual precipitation treatments, and contains 50 plots (10 per treatment). This experiment uses precipitation shelters and irrigation treatments to manipulate water inputs to 2.5 x 2.5 meter plots in a desert grassland. There are high, low, and ambient (control) precipitation variability treatments. Ambient plots receive natural precipitation each year, while variability treatments alternate between 20% and 180% (high variability), or 50% and 150% (low variability) of ambient precipitation each year. Perennial grass tiller and stolon counts were made annually in each plot from 2012-2014. This is an ongoing study and the dataset will be updated as needed. 

This dataset contains soil moisture data from a study at the Jornada Experimental Range (JER) in southern New Mexico. The study was designed to assess the effect of interannual variability in precipitation on average aboveground net primary productivity (ANPP) in Chihuahuan Desert grasslands. The study began in 2009 and has five precipitation treatments (see Methods). While the study began in 2009, contains 50 plots (10 per treatment) and is ongoing, these data have only been collected since July 2011 in a subset of 20 plots (4 per treatment). This dataset is intended to provide information about the amount of water in surface and deep soil layers, as well as verify that experimental precipitation manipulations are effective. This is an ongoing dataset that will be updated yearly. 

This dataset contains data and analysis code for the paper entitled “Acclimation of the nitrogen cycle to changes in precipitation" by Currier et al. As the frequency of precipitation extremes are expected to increase, especially in arid regions, we asked how prolonged shifts in water availability facilitate acclimation of the N cycle in a semiarid grassland. Using natural abundances of stable nitrogen isotopes for dominant plants and soils and rainfall manipulation experiments, we tested the hypothesis that N cycling will interact with water availability further amplifying the openness of the N cycle through time. For the dominant plant species, we found the relationship for N availability vs. ambient annual precipitation to be significantly positive, contrary to global spatial models. We also considered the temporal dynamics of our experiments, which imposed directional rainfall manipulations in duration ranging from 5 to 14 years. The slopes of these relationships decreased (became less positive) with more time since the onset of the directional precipitation extremes. These data and metadata supplement long-term foliar and soil isotope data from the Jornada LTER (Dataset ID: knb-lter-jrn.210586001) with a large spatial dataset from NEON data package DP1.10026.001 and Craine et al. 2018 (https://doi.org/10.5061/dryad.v2k2607). 

As rainfall extremes are expected to increase in novel magnitude and frequency, especially in dryland regions, we asked how prolonged and directional shifts to water availability may affect ecosystem carbon and nitrogen dynamics. This data set includes foliar and soil carbon and nitrogen stable isotope and concentration data collected from multiple long-term rainfall manipulation experiments at the Jornada Basin LTER. Datasets also include rainfall data adjusted to rainfall manipulation intensities. Collection dates range from 5 to 14 years since the onset of experimental treatments. The primary plant species targeted for this study were the dominant grass, Bouteloua eriopoda, and the dominant shrub, Prosopis glandulosa. 

This dataset contains soil volumetric water content data collected starting in 2011 for a long-term precipitation and nutrient manipulation experiment at the Jornada Basin LTER site in southern New Mexico, U.S.A. This experiment uses precipitation shelters and irrigation treatments to manipulate water inputs, and fertilization treatments to alter nitrogen input to 2.5 x 2.5 meter plots in a desert grassland. Soil sensors are installed at surface and deep soil layers in each plot and collect hourly averages of volumetric water content using a time-domain reflectometry method. This dataset contains daily averages. This is an ongoing study and the dataset will be updated yearly. 

This dataset contains cover and biomass data collected starting in 2006 for a long-term precipitation and nutrient manipulation experiment at the Jornada Basin LTER site in southern New Mexico, U.S.A. This experiment uses precipitation shelters and irrigation treatments to manipulate water inputs, and fertilization treatments to alter nitrogen input to 2.5 x 2.5 meter plots in a desert grassland. Plant cover measurements are made annually in each plot, from which biomass or net primary production are derived. This is an ongoing study and the dataset will be updated yearly. 

This dataset contains perennial grass tiller and stolon counts collected starting in 2012 for a long-term precipitation and nutrient manipulation experiment at the Jornada Basin LTER site in southern New Mexico, U.S.A. This experiment uses precipitation shelters and irrigation treatments to manipulate water inputs, and fertilization treatments to alter nitrogen input to 2.5 x 2.5 meter plots in a desert grassland. Tillers and stolons of perennial grasses were counted in each plot in 2012, 2013 and 2014. This is an ongoing study and the dataset will be updated as needed. 

This dataset contains water level data collected at 18 playas starting in June 2016 for a long-term study of playa inundation at the Jornada Basin LTER site in southern New Mexico, U.S.A. Playas are located throughout the Jornada Basin and are instrumented with dataloggers and attached pressure transducers located at the lowest point of each playa. Instantaneous measurements of surface water level are made every 15 minutes. Data are processed to flag errors and identify periods of playa inundation (floods). This is an ongoing study and the dataset will be updated yearly.