Zhang & Niu, 2018

Talk/Poster

A microbial-based soil organic carbon decomposition model coupled with Noah-MP: development and test in semiarid grassland

Zhang, X., Niu, G.-Y. (2018)
Abstract B23A-07 presented at 2018 AGU Fall Meeting, Washington, D.C., 10-14 Dec  
  • Guo-Yue Niu

    Catalina-Jemez, INVESTIGATOR, COLLABORATOR

Abstract

Explicit representation of soil microbial growth and respiration for use in climate models has received increasing attention. However, these representations are inadequate to represent hydrological control on the microbial activities. Here, we show a stepwise development of microbial-based soil carbon decomposition models for reproducing respiratory pulses in response to pulsed rainfall (known as “Birch effect”) observed at a semiarid savanna site. We first revised a four-carbon pool (4C-pool) microbial-based model with soil moisture control on SOC degradation and microbial uptake of DOC and incorporated it into a land surface model to substitute for a soil first-order decay model typically used in climate models. We found land surface model with the 4C-pool model and a first-order decay model failed to simulate the observed Birch effect. We then revised the 4C-pool model into a six carbon (6C) pool model by respectively splitting the DOC and ENZ pools into two sub-pools, one in the dry zone and the other in the wet zone of the soil pore space. During dry periods, microbial enzymes in the dry zone remain active to degrade SOC, and in turn labile carbon accumulates in the dry zone for not being accessible to microbes. The labile carbon accumulated during dry periods becomes immediately dissolved for microbial use in response to rainstorms, and thus the 6C-pool model successfully reproduced the observed respiration pulses of various sizes, thereby improving the simulation of net ecosystem exchange.

 

Citation

Zhang, X., Niu, G.-Y. (2018): A microbial-based soil organic carbon decomposition model coupled with Noah-MP: development and test in semiarid grassland. Abstract B23A-07 presented at 2018 AGU Fall Meeting, Washington, D.C., 10-14 Dec.