Linking short-term soil carbon and nitrogen dynamics: Environmental and stoichiometric controls on fresh organic matter decomposition in agroecosystems

Abstract

21A continuous, nonlinear model (FLOG-CN) linking carbon mineralization and nitrogen 22 mineralization-immobilization with respect to time was developed that successfully reproduced 23 the complex CO 2 -C and SMN dynamics for a collection of 70 paired C and N soil datasets. 24 Application of the model to diverse C and N datasets showed that incorporating latency into the 25 model of C mineralization, and using C to drive N dynamics, allows heterogeneous data from 26 many different soil amendments to be described by the same model. We successfully modelled 27 complex CO 2 -C and SMN dynamics of widely different shapes and from a variety of soil 28 amendments containing plant and animal residues. The re-interpretation of these datasets with 29 the FLOG-CN models improved the quantitative analysis of C and N dynamics, yielding new 30 insights into how amendment characteristics and experimental conditions influence the timing 31 and quantity of C and N mineralized. Model parameters were responsive to varying soil 32 characteristics (pH, C, N, C:N), amendment N:C, amendment rate, incubation temperature, and 33 N additions. Stepwise regression was used to predict model parameters using metadata available 34 for 56 of these datasets. Significant relationships were developed to estimate model parameters 35 independently using measured system properties or other model parameters that could be 36 independently estimated. Estimates of C and N dynamics both fell along a 1:1 line indicating that 37 the model parameters could be adequately described by the measured properties, but the 38 available metadata was not able to describe C dynamics with high precision. Nitrogen 39 mineralization-immobilization was strongly related to amendment N:C, and switched between 40 the two processes at an amendment N:C between 0.077 to 0.085 (C:N between 11.7 to 12.9). We 41 believe that the modelling approach described here will allow quantitative and objective 42 3 comparisons of diverse C and N datasets that have been hindered by subjective descriptions of 43 the past. 44 decomposition or mineralized in excess of microbial requirements, is expressed as SMN labile =

Dominant effects of organic carbon chemistry on decomposition dynamics of crop residues in a Mollisol

“…Nonetheless, Parton et al (2007) observed net N release when litter mass loss arrived at 60% and the average C/N ratio was lower than 40 in a 10-year field decomposition experiment. These inconsistent findings about C/N threshold for net N mineralization could be attributed to the differences in experimental conditions and duration, and also to the residue C and N characteristics (Abiven et al, 2005;Jensen et al, 2005;Gillis and Price, 2016). Trinsoutrot et al (2000b) reported that the quantity of N released from roots, stems, and pod walls of Brassica napus L. were closely related to the initial N content.…”

Sensitivity analysis of C and N modules in biogeochemical crop and grassland models following manure addition to soil

“…To overcome this limitation, alternative methods can be used to define manure pools kinetically. They assign C and N contents to model pools that optimize the simulation of experimental dynamics (Gillis & Price, ; Mondini et al, ; Noirot‐Cosson et al, ; Petersen et al, ) and assume implicitly that fast‐ and slow‐decay pools are chemically heterogeneous mixtures of molecules.…”

“…Previous aerobic incubation studies (Bechini & Marino, ; Morvan, Nicolardot, & Péan, ; Thomsen & Olesen, ) have shown the complexity of responses related to C respiration and N immobilization in manure‐amended soils. The suitability of simulation models to reproduce, through adequate model parameterization, C and N decomposition dynamics after manure incorporation has also been shown to be difficult (Cavalli & Bechini, ; Gillis & Price, ; Petersen et al, ; Probert et al, ).…”

“…In conventional practice, sensitivity analysis carried out before calibration reduces the number of parameters subject to calibration. In this way, optimized sets of parameters can be identified better, either specifically for soil and substrate‐type (Cavalli & Bechini, ; Gillis & Price, ; Petersen et al, ) or common to all soils (Petersen, Berntsen, Hansen & Jensen, ).…”

Soil carbon and nitrogen stocks and fractions for improving soil quality and mitigating climate change

“…The dynamics of C and N are largely linked via the chemical composition and stoichiometry of biomolecules (Gillis and Price, 2016). The unique relationship between the total N and the total OC implies that both reveal similar general trends of accumulation, degradation and subsurface transport, and hence, always follows similar patterns (Wong et al, 2008 andSharma et al, 2017).…”