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Conservation tillage has been promoted as an effective practice to preserve soil health and enhance agroecosystem services. Changes in tillage intensity have a profound impact on soil nitrogen cycling, yet their influence on nitrate losses at large spatiotemporal scales remains uncertain. This study examined the effects of tillage intensity on soil nitrate losses in the US Midwest from 1979-2018 using field data synthesis and process-based agroecosystem modeling approaches. Our results revealed that no-tillage (NT) or reduced tillage intensity (RTI) decreased nitrate runoff but increased nitrate leaching compared to conventional tillage. These trade-offs were largely caused by altered water fluxes, which elevated total nitrate losses. The structural equation model suggested that precipitation had more pronounced effects on nitrate leaching and runoff than soil properties (i.e., texture, pH, and bulk density). Reduction in nitrate runoff under NT or RTI was negatively correlated with precipitation, and the increased nitrate leaching was positively associated with soil bulk density. We further explored the combined effects of NT or RTI and winter cover crops and found that incorporating winter cover crops into NT systems effectively reduced nitrate runoff but did not significantly affect nitrate leaching. Our findings underscore the precautions of implementing NT or RTI to promote sustainable agriculture under changing climate conditions. This study provides valuable insights into the complex relationship between tillage intensity and nitrate loss pathways, contributing to informed decision-making in climate-smart agriculture.

According to classic stomatal optimization theory, plant stomata are regulated to maximize carbon assimilation for a given water loss. A key component of stomatal optimization models is marginal water‐use efficiency (mWUE), the ratio of the change of transpiration to the change in carbon assimilation. Although the mWUE is often assumed to be constant, variability of mWUE under changing hydrologic conditions has been reported. However, there has yet to be a consensus on the patterns of mWUE variabilities and their relations with atmospheric aridity. We investigate the dynamics of mWUE in response to vapor pressure deficit (VPD) and aridity index using carbon and water fluxes from 115 eddy covariance towers available from the global database FLUXNET. We demonstrate a non‐linear mWUE‐VPD relationship at a sub‐daily scale in general; mWUE varies substantially at both low and high VPD levels. However, mWUE remains relatively constant within the mid‐range of VPD. Despite the highly non‐linear relationship between mWUE and VPD, the relationship can be informed by the strong linear relationship between ecosystem‐level inherent water‐use efficiency (IWUE) and mWUE using the slope,m*. We further identify site‐specificm* and its variability with changing site‐level aridity across six vegetation types. We suggest accurately representing the relationship between IWUE and VPD using Michaelis–Menten or quadratic functions to ensure precise estimation of mWUE variability for individual sites.

As a supplementary or the only water source in dry regions, dew plays a critical role in the survival of organisms. The new hydrological tracer¹⁷O-excess, with almost sole dependence on relative humidity, provides a new way to distinguish the evaporation processes and reconstruct the paleoclimate. Up to now, there is no published daily dew isotope record on δ²H, δ¹⁸O, δ¹⁷O, d-excess, and¹⁷O-excess. Here, we collected daily dew between July 2014 and April 2018 from three distinct climatic regions (i.e., Gobabeb in the central Namib Desert with desert climate, Nice in France with Mediterranean climate, and Indianapolis in the central United States with humid continental climate). The δ²H, δ¹⁸O, and δ¹⁷O of dew were simultaneously analyzed using a Triple Water Vapor Isotope Analyzer based on Off-Axis Integrated Cavity Output Spectroscopy technique, and then d-excess and¹⁷O-excess were calculated. This report presents daily dew isotope dataset under three climatic regions. It is useful for researchers to use it as a reference when studying global dew dynamics and dew formation mechanisms.

Monitoring dryland vegetation trends and examining the drivers are of great importance to understand the dryland vegetation response to future climate changes. Recent findings through satellite data indicate that vegetation greenness has increased in several regions worldwide. These greening patterns are driven by human activities or combined human activities and environmental factors. However, the analyses of greenness trend for regions without direct human activities and shrub expansion in drylands are still lacking. To this end, this study investigates the vegetation trend across the Namib sand sea over March 2000 to December 2018 using monthly Normalized Difference Vegetation Index (NDVI) and examines several potential drivers including precipitation, temperature and atmospheric CO₂concentration. For the NDVI time series across the whole study region, a significant greening trend was found over March 2000 to September 2012 based on Mann–Kendall test but not over the whole study period. Structural equation modelling results indicated that precipitation and CO₂were the dominant drivers of greening. Temperature showed negative effects on vegetation greenness, indicating warming would reduce plant growth in the study region. Spatially, 75% of the region showed statistically significant greening over March 2000 to September 2012 and 39.30% for March 2000 to December 2018. The different vegetation trend results between the entire region and the pixel scale implied that location‐specific greening could be masked by an overall trend. Our study suggested that precipitation (especially the large episodic precipitation events) and CO₂are dominant drivers of the observed greening in the Namib. Our findings fill an important knowledge gap of vegetation dynamics in regions without direct human activities.

Most fog detection from space cannot differentiate fog and low stratus clouds, and cannot estimate fog deposition. This study assessed the feasibility of using spaceborne lidar observations from the Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) in fog detection and estimation. We tested the method in the central Namib Desert, Namibia, where frequent fog events occur and fog observations are available. Results showed the CALIPSO backscatter signal at 532 nm can differentiate low clouds and fog due to its high‐resolution vertical profiles. Backscatter signals during fog events were significantly higher than those during non‐fog periods. TheR²between backscatter signals and fog observations was 0.85. Moreover, the backscatter signal was also sensitive to relative humidity variation (R² = 0.66). These results indicate that the CALIPSO data are feasible to estimate fog occurrence and deposition, providing a new perspective for space‐based fog studies.