The value of soil respiration measurements for interpreting and modeling terrestrial carbon cycling

An acceleration of model-data synthesis activities has leveraged many terrestrial carbon datasets, but utilization of soil respiration (R-S) data has not kept pace. We identify three major challenges in interpreting R-S data, and opportunities to utilize it more extensively and creatively: (1) When R-S is compared to ecosystem respiration (R-ECO) measured from EC towers, it is not uncommon to find R-S > R-ECO. We argue this is most likely due to difficulties in calculating R-ECO, which provides an opportunity to utilize R-S for EC quality control. (2) R-S integrates belowground heterotrophic and autotrophic activity, but many models include only an explicit heterotrophic output. Opportunities exist to use the total R-S flux for data assimilation and model benchmarking methods rather than less-certain partitioned fluxes. (3) R-S is generally measured at a very different resolution than that needed for comparison to EC or ecosystem- to global-scale models. Downscaling EC fluxes to match the scale of R-S, and improvement of R-S upscaling techniques will improve resolution challenges. R-S data can bring a range of benefits to model development, particularly with larger databases and improved data sharing protocols to make R-S data more robust and broadly available to the research community.