Litter quality assessed by solid state 13C NMR spectroscopy predicts decay rate better than C/N and Lignin/N ratios - Bonanomi, Giuliano; Incerti, Guido; Giannino, Francesco; Mingo, Antonio; Lanzotti, Virginia; Mazzoleni, Stefano (Soil Biology and Biochemistry, 2013)
Predictions of litter decomposition rates are critical for modelling biogeochemical cycling in terrestrial ecosystems and forecasting organic carbon and nutrient stock balances. Litter quality, besides climatic conditions, is recognized as a main factor affecting decay rates and it has been traditionally assessed by the C/N and lignin/N ratios of undecomposed materials. Here, solid state 13 C NMR spectroscopy and proximate chemical analysis have been used to characterize litter organic C in a litterbag experiment with 64 different litter types decomposing under controlled conditions of temperature and water content. A statistical comparative analysis provided evidence that C/N and lignin/N ratios, showing different trends of correlation with decay rates at different decomposition stages, can be used to describe the quality of undecomposed litter, but are unable to predict mass loss of already decomposed materials. A principal component regression (PCR) model based on 13 C NMR spectra, ﬁtted and cross-validated by using either two randomly selected sets of litter types, showed highly ﬁtting predictions of observed decay rates throughout the decomposition process. The simple ratio 70e75/52e57 corresponding to Oalkyl C of carbohydrates and methoxyl C of lignin, respectively, showed the highest correlation with decay rate among different tested parameters. These ﬁndings enhance our understanding of litter quality, and improve our ability to predict decomposition dynamics. The 13 C NMR-based 70e75/52e57 ratio is proposed as an alternative to C/N and lignin/N ratios for application in experimental and modelling work
The following values have no corresponding Zotero field: publisher: Elsevier Ltd
Keywords: C stocks; C-cycle; decomposition; litter quality; litterbag; Principal component regression; Proximate cellulose and lignin