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

摘要

We developed a continuous, nonlinear model (FLOG-CN) linking carbon mineralization and nitrogen mineralization-immobilization with respect to time that successfully reproduced the complex CO2-C and SMN dynamics for a collection of 70 paired C and N soil datasets. Application of the model to diverse C and N datasets showed that incorporating latency into the model of C mineralization, and using C to drive N dynamics, allows heterogeneous data from many different soil amendments to be described by the same model. We successfully modeled complex CO2-C and SMN dynamics of widely different shapes and from a variety of soil amendments containing plant and animal residues. The re-interpretation of these datasets with the FLOG-CN models improved the quantitative analysis of C and N dynamics, yielding new insights into how amendment characteristics and experimental conditions influence the timing and quantity of C and N mineralized. Model parameters were responsive to varying soil characteristics (pH, C, N, C:N), amendment N:C, amendment rate, incubation temperature, and N additions. Stepwise regression was used to predict model parameters using metadata available for 56 of these datasets. Significant relationships were developed to estimate model parameters independently using measured system properties or other model parameters that could be independently estimated. Estimates of C and N dynamics both fell along a 1:1 line indicating that the model parameters could be adequately described by the measured properties, but the available metadata was not able to describe C dynamics with high precision. Nitrogen mineralization-immobilization was strongly related to amendment N:C, and switched between the two processes at an amendment N:C between 0.077 and 0.085 (C:N between 11.7 and 12.9). We believe that the modeling approach described here will allow quantitative and objective comparisons of diverse C and N datasets that have been hindered by subjective descriptions of the past. (C) 2016 Elsevier B.V. All rights reserved.