Carbon dioxide release during soil organic carbon (SOC) turnover is a pivotal component of atmospheric CO2 concentrations and global climate change. However, reliably measuring SOC turnover rates on large spatial and temporal scales remains challenging. Here we use a natural carbon isotope approach, defined as beta (β), which was quantified from the δ13C of vegetation and soil reported in the literature (176 separate soil profiles), to examine large-scale controls of climate, soil physical properties and nutrients over patterns of SOC turnover across terrestrial biomes worldwide. We report a significant relationship between β and calculated soil C turnover rates (k), which were estimated by dividing soil heterotrophic respiration rates by SOC pools. ln( - β) exhibits a significant linear relationship with mean annual temperature, but a more complex polynomial relationship with mean annual precipitation, implying strong-feedbacks of SOC turnover to climate changes. Soil nitrogen (N) and clay content correlate strongly and positively with ln( - β), revealing the additional influence of nutrients and physical soil properties on SOC decomposition rates. Furthermore, a strong (R2 Combining double low line 0.76; p < 0.001) linear relationship between ln( - β) and estimates of litter and root decomposition rates suggests similar controls over rates of organic matter decay among the generalized soil C stocks. Overall, these findings demonstrate the utility of soil δ13C for independently benchmarking global models of soil C turnover and thereby improving predictions of multiple global change influences over terrestrial C-climate feedback.

Maaz et al. argue that inconsistencies across scales of observation undermine our working hypothesis that soil NO _x emissions have been substantially overlooked in California; however, the core issues they raise are already discussed in our manuscript. We agree that point measurements cannot be reliably used to estimate statewide soil NO _x emissions-the principal motivation behind our new modeling/airplane approach. Maaz et al.'s presentation of fertilizer-based emission factors (a nonmechanistic scaling of point measures to regions based solely on estimated nitrogen fertilizer application rates) includes no data from California or other semiarid sites, and does not explicitly account for widely known controls of climate, soil, and moisture on soil NO _x fluxes. In contrast, our model includes all of these factors. Finally, the fertilizer sales data that Maaz et al. highlight are known to suffer from serious errors and do not offer a logically more robust pathway for spatial analysis of NO _x emissions from soil.

Nitrogen oxides (NO _x = NO + NO₂) are a primary component of air pollution-a leading cause of premature death in humans and biodiversity declines worldwide. Although regulatory policies in California have successfully limited transportation sources of NO _x pollution, several of the United States' worst-air quality districts remain in rural regions of the state. Site-based findings suggest that NO _x emissions from California's agricultural soils could contribute to air quality issues; however, a statewide estimate is hitherto lacking. We show that agricultural soils are a dominant source of NO _x pollution in California, with especially high soil NO _x emissions from the state's Central Valley region. We base our conclusion on two independent approaches: (i) a bottom-up spatial model of soil NO _x emissions and (ii) top-down airborne observations of atmospheric NO _x concentrations over the San Joaquin Valley. These approaches point to a large, overlooked NO _x source from cropland soil, which is estimated to increase the NO _x budget by 20 to 51%. These estimates are consistent with previous studies of point-scale measurements of NO _x emissions from the soil. Our results highlight opportunities to limit NO _x emissions from agriculture by investing in management practices that will bring co-benefits to the economy, ecosystems, and human health in rural areas of California.

Higher aridity and more extreme rainfall events in drylands are predicted due to climate change. Yet, it is unclear how changing precipitation regimes may affect nitrogen (N) cycling, especially in areas with extremely high aridity. Here we investigate soil N isotopic values (δ(15)N) along a 3,200 km aridity gradient and reveal a hump-shaped relationship between soil δ(15)N and aridity index (AI) with a threshold at AI=0.32. Variations of foliar δ(15)N, the abundance of nitrification and denitrification genes, and metabolic quotient along the gradient provide further evidence for the existence of this threshold. Data support the hypothesis that the increase of gaseous N loss is higher than the increase of net plant N accumulation with increasing AI below AI=0.32, while the opposite is favoured above this threshold. Our results highlight the importance of N-cycling microbes in extremely dry areas and suggest different controlling factors of N-cycling on either side of the threshold.

Nitrogen is a critical component of the economy, food security, and planetary health. Many of the world's sustainability targets hinge on global nitrogen solutions, which, in turn, contribute lasting benefits for: (i) world hunger; (ii) soil, air and water quality; (iii) climate change mitigation; and (iv) biodiversity conservation. Balancing the projected rise in agricultural nitrogen demands while achieving these 21^st century ideals will require policies to coordinate solutions among technologies, consumer choice, and socioeconomic transformation.

Nitrogen is a critical component of the economy, food security, and planetary health. Many of the world's sustainability targets hinge on global nitrogen solutions, which, in turn, contribute lasting benefits for: (i) world hunger; (ii) soil, air and water quality; (iii) climate change mitigation; and (iv) biodiversity conservation. Balancing the projected rise in agricultural nitrogen demands while achieving these 21^st century ideals will require policies to coordinate solutions among technologies, consumer choice, and socioeconomic transformation.