Microbe-iron interactions control lignin decomposition in soil
Microbe-iron interactions control lignin decomposition in soil
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DOI:
10.1016/j.soilbio.2022.108803
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发表时间:
2022-08
影响因子:
9.7
通讯作者:
Cuijuan Liao;Wenjuan Huang;Jon Wells;Ruiying Zhao;K. Allen;E. Hou;Xin Huang;Han Qiu;F. Ta
中科院分区:
文献类型:
--
作者:
Cuijuan Liao;Wenjuan Huang;Jon Wells;Ruiying Zhao;K. Allen;E. Hou;Xin Huang;Han Qiu;F. Ta
Lignin decomposition is critically linked to terrestrial carbon (C) cycle due to the enormous C mass of lignin and its importance in controlling overall rates of litter decomposition. Interactions between lignin and iron (Fe) minerals have been increasingly recognized as key mediators of lignin decomposition in experimental studies. However, we still lack a quantitative understanding of how Fe minerals interact with microbes to control lignin decomposition. Here, we leveraged experimental results from an incubation of Fe-rich soil, in which lignin decomposition rates were measured at aerobic conditions after four levels of pre-treated O2availability, to examine microbe-Fe (MiFe) interactions in lignin decomposition with a MiFe model. We quantified how Fe redox cycling interacted with microbial activities to control lignin decomposition via data-model integration. Our results showed that the MiFe model with time-dependent growth and mortality functions better represented CO2release from lignin decomposition (R2ranging from 0.96 to 0.97) than models assuming either first-order or Michaelis-Menten kinetics. Reduction of Fe(III) to Fe(II) after pre-treatments with lower O2availability stimulated the Fenton reaction to break down macro-molecular lignin into small molecules available to microbes. The small molecules of lignin and necromass bounded with oxidized Fe and were protected from decomposition. After 1-year incubation, the model implied that most of C stabilized with Fe minerals was derived from small molecular lignin C. Our quantitative analysis of microbe-Fe interactions sheds new light on lignin decomposition and preservation and helps improve model prediction of soil C persistence under global change.