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River networks regulate carbon and nutrient exchange between continents, atmosphere, and oceans. However, contributions of riverine processing are poorly constrained at continental scales. Scaling relationships of cumulative biogeochemical function with watershed size (allometric scaling) provide an approach for quantifying the contributions of fluvial networks in the Earth system. Here we show that allometric scaling of cumulative riverine function with watershed area ranges from linear to superlinear, with scaling exponents constrained by network shape, hydrological conditions, and biogeochemical process rates. Allometric scaling is superlinear for processes that are largely independent of substrate concentration (e.g., gross primary production) due to superlinear scaling of river network surface area with watershed area. Allometric scaling for typically substrate-limited processes (e.g., denitrification) is linear in river networks with high biogeochemical activity or low river discharge but becomes increasingly superlinear under lower biogeochemical activity or high discharge, conditions that are widely prevalent in river networks. The frequent occurrence of superlinear scaling indicates that biogeochemical activity in large rivers contributes disproportionately to the function of river networks in the Earth system.

 

Mean annual temperature and mean annual precipitation drive much of the variation in productivity across Earth's terrestrial ecosystems but do not explain variation in gross primary productivity (GPP) or ecosystem respiration (ER) in flowing waters. We document substantial variation in the magnitude and seasonality of GPP and ER across 222 US rivers. In contrast to their terrestrial counterparts, most river ecosystems respire far more carbon than they fix and have less pronounced and consistent seasonality in their metabolic rates. We find that variation in annual solar energy inputs and stability of flows are the primary drivers of GPP and ER across rivers. A classification schema based on these drivers advances river science and informs management. 

To assess the distribution, frequency, and global extent of riverine hypoxia, we compiled 118 million paired dissolved oxygen (DO) and water temperature measurements from 125,158 unique locations in rivers in 93 countries and territories across the globe. The dataset also includes site characteristics derived from StreamCat, the National Hydrography and HydroAtlas datasets and proximal land cover derived from MODIS-based IGBP land cover types compiled using Google Earth Engine (GEE). 

Hypoxia in coastal waters and lakes is widely recognized as a detrimental environmental issue, yet we lack a comparable understanding of hypoxia in rivers. We investigated controls on hypoxia using 118 million paired observations of dissolved oxygen (DO) concentration and water temperature in over 125,000 locations in rivers from 93 countries. We found hypoxia (DO < 2 mg L⁻¹) in 12.6% of all river sites across 53 countries, but no consistent trend in prevalence since 1950. High‐frequency data reveal a 3‐h median duration of hypoxic events which are most likely to initiate at night. River attributes were better predictors of riverine hypoxia occurrence than watershed land cover, topography, and climate characteristics. Hypoxia was more likely to occur in warmer, smaller, and lower‐gradient rivers, particularly those draining urban or wetland land cover. Our findings suggest that riverine hypoxia and the resulting impacts on ecosystems may be more pervasive than previously assumed.

 

High‐resolution data are improving our ability to resolve temporal patterns and controls on river productivity, but we still know little about the emergent patterns of primary production at river‐network scales. Here, we estimate daily and annual river‐network gross primary production (GPP) by applying characteristic temporal patterns of GPP (i.e., regimes) representing distinct river functional types to simulated river networks. A defined envelope of possible productivity regimes emerges at the network‐scale, but the amount and timing of network GPP can vary widely within this range depending on watershed size, productivity in larger rivers, and reach‐scale variation in light within headwater streams. Larger rivers become more influential on network‐scale GPP as watershed size increases, but small streams with relatively low productivity disproportionately influence network GPP due to their large collective surface area. Our initial predictions of network‐scale productivity provide mechanistic understanding of the factors that shape aquatic ecosystem function at broad scales.