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Towards improved modeling of SOC decomposition: soil water potential beyond the wilting point.

Junyi LiangKangli Chennull SiqintanaTianci HuoYaowen ZhangJingying JingWenting Feng
Published in: Global change biology (2022)
Soils are important carbon (C) reservoirs and play a critical role in regulating the global C cycle. Soil water potential (SWP) measures the energy with which water is retained in the soil and is one of the most vital factors that constrain the decomposition of soil organic C (SOC). The measurements for soil water retention curve (SWRC), on which the estimation of SWP depends, are usually carried out above -1.5 MPa (i.e., the wilting point for many plants). However, the average moisture threshold at which soil microbial activity ceases is usually below -10 MPa in mineral soils. Beyond the measurement range, the SWP estimation has to be derived from extrapolating the SWRC, which violates the statistical principle, resulting in possibly inaccurate SWP estimations. To date, it is unclear to what extent the extrapolated SWP estimation deviates from the "true value" and how it impacts the modeling of SOC decomposition. This study combined SWRC measurements down to -43.7 MPa, a 72-day soil incubation experiment with four moisture levels, and an SOC decomposition model. In addition to the complete SWRC (SWRC all ), we fitted two more SWRCs by using measurements above -0.5 MPa (SWRC 0.5 ) and -1.7 MPa (SWRC 1.7 ), respectively, to quantify the deviations of extrapolated SWPs from the complete SWRC. Results showed that extrapolating the SWRC beyond its measurement range significantly underestimated the SWP. Incorporating the extrapolated SWP in the model significantly underestimated the SOC decomposition under relatively dry conditions. With the extrapolated SWP, the model predicted no SOC decomposition in the driest treatment, while the experiment observed a significant CO 2 emission. The results emphasize that accurate SWP estimations beyond the wilting point are critically needed to improve the modeling of SOC decomposition.
Keyphrases
  • plant growth
  • heavy metals
  • human health
  • microbial community
  • high resolution
  • climate change