Observation-based global soil heterotrophic respiration indicates underestimated turnover and sequestration of soil carbon by terrestrial ecosystem models

Abstract

Soil heterotrophic respiration (R_h ) refers to the flux of CO₂ released from soil to atmosphere as a result of organic matter decomposition by soil microbes and fauna. As one of the major fluxes in the global carbon cycle, large uncertainties still exist in the estimation of global R_h , which further limits our current understanding of carbon accumulation in soils. Here, we applied a Random Forest algorithm to create a global data set of soil R_h , by linking 761 field observations with both abiotic and biotic predictors. We estimated that global R_h was 48.8 ± 0.9 Pg C year^-1 for 1982-2018, which was 16% less than the ensemble mean (58.6 ± 9.9 Pg C year^-1 ) of 16 terrestrial ecosystem models. By integrating our observational R_h with independent soil carbon stock data sets, we obtained a global mean soil carbon turnover time of 38.3 ± 11 year. Using observation-based turnover times as a constraint, we found that terrestrial ecosystem models simulated faster carbon turnovers, leading to a 30% (74 Pg C) underestimation of terrestrial ecosystem carbon accumulation for the past century, which was especially pronounced at high latitudes. This underestimation is equivalent to 45% of the total carbon emissions (164 Pg C) caused by global land-use change at the same time. Our analyses highlight the need to constrain ecosystem models using observation-based and locally adapted R_h values to obtain reliable projections of the carbon sink capacity of terrestrial ecosystems.

Keywords: carbon cycling; carbon turnover time; random forest; soil heterotrophic respiration; terrestrial carbon sink; terrestrial ecosystem models.