Abstract
Flow regimes of river ecosystems worldwide have undergone substantial changes because of water resource development, altering the way in which organic matter is generated and cycled throughout entire river catchments. Flow-ecology studies have focused on structural variables measured at small spatial scales. This creates a challenging mismatch when applying adaptive flow management for ecosystem functioning at a catchment or regional scale. Here, we sought to inform flow management by evaluating the drivers of ecosystem metabolism in a regulated river and assessing our ability to predict metabolism at unmonitored locations. We estimated rates of ecosystem metabolism from high-frequency monitoring of dissolved oxygen concentration at eight sites on the Lachlan River of Australia's Murray-Darling Basin. We then applied a spatio-temporal stream network model to predict metabolism at unmonitored locations using only remotely sensed and gauging station predictor variables. Gross primary productivity (GPP) was higher at sites with lower mean annual discharge, and strong seasonal patterns in rates of productivity tended to be disrupted by rising flows. Similarly, ecosystem respiration (ER) was higher at sites with lower mean annual discharge and lower annual flow variation, but increased slightly in response to higher daily flows. Predictions at validation sites were generally accurate, albeit with substantial site-to-site variation. Our results suggest that flow changes may have altered metabolic rates from conditions prior to water abstraction and dam construction. These findings will assist in managing flows for ecosystem function outcomes and support extrapolation from monitored sites to the broad scales required for evaluating catchment-scale outcomes of river management.