Outgassing of carbon dioxide (CO2) from rivers and streams to the atmosphere is a major loss term in the coupled terrestrial‐aquatic carbon cycle of major low‐gradient river systems (the term “river system” encompasses the rivers and streams of all sizes that compose the drainage network in a river basin). However, the magnitude and controls on this important carbon flux are not well quantified. We measured carbon dioxide flux rates (FCO2), gas transfer velocity (k), and partial pressures (pCO2) in rivers and streams of the Amazon and Mekong river systems in South America and Southeast Asia, respectively. FCO2 and k values were significantly higher in small rivers and streams (channels <100 m wide) than in large rivers (channels >100 m wide). Small rivers and streams also had substantially higher variability in k values than large rivers. Observed FCO2 and k values suggest that previous estimates of basinwide CO2 evasion from tropical rivers and wetlands have been conservative and are likely to be revised upward substantially in the future. Data from the present study combined with data compiled from the literature collectively suggest that the physical control of gas exchange velocities and fluxes in low‐gradient river systems makes a transition from the dominance of wind control at the largest spatial scales (in estuaries and river mainstems) toward increasing importance of water current velocity and depth at progressively smaller channel dimensions upstream. These results highlight the importance of incorporating scale‐appropriate k values into basinwide models of whole ecosystem carbon balance.

We present a Bayesian statistical model of diel oxygen dynamics in aquatic ecosystems to simultaneously estimate gross primary production, ecosystem respiration, and oxygen exchange with the atmosphere (and their uncertainties) on the basis of changes in dissolved oxygen concentration, water temperature, irradiance, and, if desired, the 18 O to 16 O ratio (d 18 O-O 2 ). We test this model using simulated data with realistic measurement errors to demonstrate that it accurately estimates the model parameters and that parameter uncertainties correctly scale with error in the observations and number of data points. Application of the model to field data from two productive stream ecosystems with substantial daily dissolved oxygen variation quantified the underlying physical and biological factors that control oxygen dynamics in these ecosystems and provided empirical support for a light saturation model of the photosynthesis-irradiance relationships at the ecosystem scale. Although inclusion of d 18 O-O 2 provides a second oxygen budget, analysis of field data shows that metabolic and reaeration parameters can be accurately estimated by modeling the transient dynamics of dissolved oxygen concentration alone in relation to daily changes in water temperature and light regime. This model is particularly suited to lowgas exchange, high-productivity systems, which have thus far proved challenging to measure ecosystem metabolism accurately. The modeling framework is applicable to single-station, open-system experimental designs and provides a rigorous and generalizable framework for estimating ecosystem metabolism in aquatic ecosystems.

Understanding the biogeochemical processes regulating carbon cycling is central to mitigating atmospheric CO 2 emissions. The role of living organisms has been accounted for, but the focus has traditionally been on contributions of plants and microbes. We develop the case that fully "animating" the carbon cycle requires broader consideration of the functional role of animals in mediating biogeochemical processes and quantification of their effects on carbon storage and exchange among terrestrial and aquatic reservoirs and the atmosphere. To encourage more hypothesis-driven experimental research that quantifies animal effects we discuss the mechanisms by which animals may affect carbon exchanges and storage within and among ecosystems and the atmosphere. We illustrate how those mechanisms lead to multiplier effects whose magnitudes may rival those of more traditional carbon storage and exchange rate estimates currently used in the carbon budget. Many animal species are already directly managed. Thus improved quantitative understanding of their influence on carbon budgets may create opportunity for management and policy to identify and implement new options for mitigating CO 2 release at regional scales.

Rivers provide unrivaled opportunity for clean energy via hydropower, but little is known about the potential impact of dam-building on the food security these rivers provide. In tropical rivers, rainfall drives a periodic flood pulse fueling fish production and delivering nutrition to more than 150 million people worldwide. Hydropower will modulate this flood pulse, thereby threatening food security. We identified variance components of the Mekong River flood pulse that predict yield in one of the largest freshwater fisheries in the world. We used these variance components to design an algorithm for a managed hydrograph to explore future yields. This algorithm mimics attributes of discharge variance that drive fishery yield: prolonged low flows followed by a short flood pulse. Designed flows increased yield by a factor of 3.7 relative to historical hydrology. Managing desired components of discharge variance will lead to greater efficiency in the Lower Mekong Basin food system.