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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 Catchments with minimal disturbance usually have low dissolved inorganic nitrogen (DIN) export, but disturbances and anthropogenic inputs result in elevated DIN concentration and export and eutrophication of downstream ecosystems. We studied streams in the southern Appalachian Mountains, USA, an area dominated by hardwood deciduous forest but with areas of valley agriculture and increasing residential development. We collected weekly grab samples and storm samples from nine small catchments and three river sites. Most discharge occurred at baseflow, with baseflow indices ranging from 69% to 95%. We identified three seasonal patterns of baseflow DIN concentration. Streams in mostly forested catchments had low DIN with bimodal peaks, and summer peaks were greater than winter peaks. Streams with more agriculture and development also had bimodal peaks; however, winter peaks were the highest. In streams draining catchments with more residential development, DIN concentration had a single peak, greatest in winter and lowest in summer. Three methods for estimating DIN export produced consistent results. Annual DIN export ranged from less than 200 g ha⁻¹ year⁻¹for the less disturbed catchments to over 2,000 g ha⁻¹ year⁻¹in the catchments with the least forest area. Land cover was a strong predictor of DIN concentration but less significant for predicting DIN export. The two forested reference catchments appeared supply limited, the most residential catchment appeared transport limited, and export for the other catchments was significantly related to discharge. In all streams, baseflow DIN export exceeded stormflow export. Morphological and climatological variation among watersheds created complexities unexplainable by land cover. Nevertheless, regression models developed using land cover data from the small catchments reasonably predicted concentration and export for receiving rivers. Our results illustrate the complexity of mechanisms involved in DIN export in a region with a mosaic of climate, geology, topography, soils, vegetation, and past and present land use. 

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.