Document Type

Article

Publication Date

12-1-2016

Abstract

Recent studies have found that solar ultraviolet (UV) radiation significantly shifts the mass loss and nitrogen dynamics of plant litter decomposition in semi-arid and arid ecosystems. In this study, we examined the role of photodegradation in litter decomposition by using the DayCent-UV biogeochemical model. DayCent-UV incorporated the following mechanisms related to UV radiation: (1) direct photolysis, (2) facilitation of microbial decomposition via production of labile materials, and (3) microbial inhibition effects. We also allowed maximum photodecay rate of the structural litter pool to vary with litter's initial lignin fraction in the model. We calibrated DayCent-UV with observed ecosystem variables (e.g., volumetric soil water content, live biomass, actual evapotranspiration, and net ecosystem exchange), and validated the optimized model with Long-Term Intersite Decomposition Experiment (LIDET) observations of remaining carbon and nitrogen at three semi-arid sites in Western United States. DayCent-UV better simulated the observed linear carbon loss patterns and the persistent net nitrogen mineralization in the 10-year LIDET experiment at the three sites than the model without UV decomposition. In the DayCent-UV equilibrium model runs, UV decomposition increased aboveground and belowground plant production, surface net nitrogen mineralization, and surface litter nitrogen pool, but decreased surface litter carbon, soil net nitrogen mineralization, and mineral soil carbon and nitrogen. In addition, UV decomposition had minimal impacts on trace gas emissions and biotic decomposition rates. The model results suggest that the most important ecological impact of photodecay of surface litter in dry grasslands is to increase N mineralization from the surface litter (25%), and decay rates of the surface litter (15%) and decrease the organic soil carbon and nitrogen (5%).

Creative Commons License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.

Rights Information

© 2016 Chen et al.

DOI

10.1002/ecs2.1631

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