New Techniques and Data for Understanding the Global Soil Respiration Flux

Abstract Soil respiration ( R s ; the soil surface‐to‐atmosphere CO 2 flux) has been measured in the field for decades, but only recently have we begun to assemble and leverage these small‐scale but extensive data. Recently, Zhao et al. (2017, https://doi.org/10.1002/2016ef000480 ) applied a novel artificial neural network model to the problem of estimating the global R s flux and understanding its variations between regions and biomes. Their results point to a convergence in estimates of global R s , and the power of leveraging the long record of observed R s in global ecosystems, but also to uncertainties about soils' response to climate change. It will take a combination of long‐term studies, data syntheses, modeling intercomparisons, and probably a new generation of sampling networks and experiments to fully resolve these questions.