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Abstract No-till management is often recognized for its environmental and economic benefits, but its potential to reduce climate warming is still uncertain. Beyond ongoing debate over its effects on soil carbon storage, no-till also leaves plant residue on the surface, which can reflect more sunlight. This increase in surface reflectivity, called albedo, may help mitigate climate change by reducing the energy absorbed by the land. Here, we assessed this climate benefit of no-till across the U.S. Corn Belt using conservation survey records, county-level tillage data, and satellite observations. We found that no-till increased land surface brightness during the dormant season, reducing absorbed solar energy by an estimated 50 grams of CO₂equivalent per square meter per year. Regionally, this could add up to 24 teragrams of CO₂equivalent per year in potential climate benefits. Areas with low adoption, especially those with dark, carbon-rich soils, offer the greatest opportunity for further mitigation. 

Nutrient runoff from agricultural regions of the midwestern U.S. corn belt has degraded water quality in many inland and coastal water bodies such as the Great Lakes and Gulf of Mexico. Under current climate, observational studies have shown that winter cover crops can reduce dissolved nitrogen and phosphorus losses from row-cropped agricultural watersheds, but performance of cover crops in response to climate variability and climate change has not been systematically evaluated. Using the Soil & Water Assessment Tool (SWAT) model, calibrated using multiple years of field-based data, we simulated historical and projected future nutrient loss from two representative agricultural watersheds in northern Indiana, USA. For 100% cover crop coverage, historical simulations showed a 31–33% reduction in nitrate (NO3−) loss and a 15–23% reduction in Soluble Reactive Phosphorus (SRP) loss in comparison with a no-cover-crop baseline. Under climate change scenarios, without cover crops, projected warmer and wetter conditions strongly increased nutrient loss, especially in the fallow period from Oct to Apr when changes in infiltration and runoff are largest. In the absence of cover crops, annual nutrient losses for the RCP8.5 2080s scenario were 26–38% higher for NO3−, and 9–46% higher for SRP. However, the effectiveness of cover crops also increased under climate change. For an ensemble of 60 climate change scenarios based on CMIP5 RCP4.5 and RCP8.5 scenarios, 19 out of 24 ensemble-mean simulations of future nutrient loss with 100% cover crops were less than or equal to historical simulations with 100% cover crops, despite systematic increases in nutrient loss due to climate alone. These results demonstrate that planting winter cover crops over row-cropped land areas constitutes a robust climate change adaptation strategy for reducing nutrient losses from agricultural lands, enhancing resilience to a projected warmer and wetter winter climate in the midwestern U.S. 

Rivers and streams contribute to global carbon cycling by decomposing immense quantities of terrestrial plant matter. However, decomposition rates are highly variable and large-scale patterns and drivers of this process remain poorly understood. Using a cellulose-based assay to reflect the primary constituent of plant detritus, we generated a predictive model (81% variance explained) for cellulose decomposition rates across 514 globally distributed streams. A large number of variables were important for predicting decomposition, highlighting the complexity of this process at the global scale. Predicted cellulose decomposition rates, when combined with genus-level litter quality attributes, explain published leaf litter decomposition rates with high accuracy (70% variance explained). Our global map provides estimates of rates across vast understudied areas of Earth and reveals rapid decomposition across continental-scale areas dominated by human activities. 

Abstract. A comprehensive set of measurements and calculated metricsdescribing physical, chemical, and biological conditions in the rivercorridor is presented. These data were collected in a catchment-wide,synoptic campaign in the H. J. Andrews ExperimentalForest (Cascade Mountains, Oregon, USA) in summer 2016 during low-dischargeconditions. Extensive characterization of 62 sites including surface water,hyporheic water, and streambed sediment was conducted spanning 1st- through5th-order reaches in the river network. The objective of the sample designand data acquisition was to generate a novel data set to support scaling ofriver corridor processes across varying flows and morphologic forms presentin a river network. The data are available at https://doi.org/10.4211/hs.f4484e0703f743c696c2e1f209abb842 (Ward, 2019). 

Abstract. Although most field and modeling studies of river corridorexchange have been conducted at scales ranging from tens to hundreds of meters,results of these studies are used to predict their ecological andhydrological influences at the scale of river networks. Further complicatingprediction, exchanges are expected to vary with hydrologic forcing and thelocal geomorphic setting. While we desire predictive power, we lack acomplete spatiotemporal relationship relating discharge to the variation ingeologic setting and hydrologic forcing that is expected across a riverbasin. Indeed, the conceptual model of Wondzell (2011) predicts systematicvariation in river corridor exchange as a function of (1) variation inbaseflow over time at a fixed location, (2) variation in discharge withlocation in the river network, and (3) local geomorphic setting. To testthis conceptual model we conducted more than 60 solute tracer studiesincluding a synoptic campaign in the 5th-order river network of the H. J. Andrews Experimental Forest (Oregon, USA) and replicate-in-time experimentsin four watersheds. We interpret the data using a series of metricsdescribing river corridor exchange and solute transport, testing forconsistent direction and magnitude of relationships relating these metricsto discharge and local geomorphic setting. We confirmed systematic decreasein river corridor exchange space through the river networks, from headwatersto the larger main stem. However, we did not find systematic variation withchanges in discharge through time or with local geomorphic setting. Whileinterpretation of our results is complicated by problems with the analyticalmethods, the results are sufficiently robust for us to conclude that space-for-timeand time-for-space substitutions are not appropriate in our study system.Finally, we suggest two strategies that will improve the interpretability oftracer test results and help the hyporheic community develop robust datasets that will enable comparisons across multiple sites and/or dischargeconditions. 

River ecosystems receive and process vast quantities of terrestrial organic carbon, the fate of which depends strongly on microbial activity. Variation in and controls of processing rates, however, are poorly characterized at the global scale. In response, we used a peer-sourced research network and a highly standardized carbon processing assay to conduct a global-scale field experiment in greater than 1000 river and riparian sites. We found that Earth’s biomes have distinct carbon processing signatures. Slow processing is evident across latitudes, whereas rapid rates are restricted to lower latitudes. Both the mean rate and variability decline with latitude, suggesting temperature constraints toward the poles and greater roles for other environmental drivers (e.g., nutrient loading) toward the equator. These results and data set the stage for unprecedented “next-generation biomonitoring” by establishing baselines to help quantify environmental impacts to the functioning of ecosystems at a global scale.