A Network-Scale Modeling Framework for Stream Metabolism, Ecosystem Efficiency, and Their Response to Climate Change

Abstract

Climate change and the predicted warmer temperatures and more extreme hydrological regimes could affect freshwater ecosystems and their energy pathways. To appreciate the complex spatial and temporal interactions of carbon cycling in flowing waters, ecosystem metabolism (gross primary production [GPP] and ecosystem respiration [ER]) must be resolved at the scale of an entire river network. Here, we propose a meta-ecosystem framework that couples light and temperature regimes with a reach-scale ecosystem model and integrates network structure, catchment land cover, and the hydrologic regime. The model simulates the distributed functioning of dissolved and particulate organic carbon, autotrophic biomass, and thus ecosystem metabolism, and reproduces fairly well the metabolic regimes observed in 12 reaches of the Ybbs River network, Austria. Results show that the annual network–scale metabolism was heterotrophic, yet with a clear peak of autotrophy in spring. Autochthonous energy sources contributed 43% of the total ER. We further investigated the effect of altered thermal and hydrologic regimes on metabolism and ecosystem efficiency. We predicted that an increase of 2.5°C in average stream water temperature could boost ER and GPP by 31% (24%–57%) and 28% (5%–57%), respectively. The effect of flashier hydrologic regimes is more complex and depends on autotrophic biomass density. The analysis shows the complex interactions between environmental conditions and biota in shaping stream metabolism and highlights the existing knowledge gaps for reliable predictions of the effects of climate change in these ecosystems.