DatasetSEV-LTER Mean - Variance Experiment Desert Grassland Soil Moisture and TemperatureRudgers, Jennifer A; Baur, Lauren; Collins, Scott L; Litvak, Marcy E; Newsome, Seth; Pockman, William T; Miller, Tom E.X.; Luo, Yiqi{"Abstract":["We designed novel field experimental infrastructure to resolve the\n relative importance of changes in the climate mean and variance in\n regulating the structure and function of dryland populations,\n communities, and ecosystem processes. The Mean - Variance Climate\n Experiment (MVE) adds three novel elements to prior designs that\n have manipulated interannual variance in climate in the field\n (Gherardi & Sala, 2013) by (i) determining interactive effects\n of mean and variance with a factorial design that crosses reduced\n mean with increased variance, (ii) studying multiple dryland biomes\n to compare their susceptibility to transition under interactive\n climate drivers, and (iii) adding stochasticity to our treatments to\n permit the antecedent effects that occur under natural climate\n variability. This new infrastructure enables direct experimental\n tests of the hypothesis that interactions between the mean and\n variance of precipitation will have larger ecological impacts than\n either the mean or variance in precipitation alone. A subset of\n plots have soil moisture and temperature sensors to evaluate\n treatment effectiveness by addressing, How do MVE manipulations\n alter the mean and variance in soil moisture and temperature? And\n How does micro-environmental variation among plots influence how\n treatments alter soil moisture profiles over three soil depths? This\n data package includes sensor data from the Mean - Variance\n Experiment in the Desert grassland ecosystem at the Sevilleta\n National Wildlife Refuge, Socorro, NM, which is dominated by the\n grass species Bouteloua eriopoda (black grama)."]}Environmental Data Initiative2021-01-0110424095https://doi.org/10.6073/pasta/c98e990b51b0195d7c04c03233a6bbd91655499National Science Foundation