Agro-ecosystem models, such as the DNDC (DeNitrification and DeComposition) model are useful tools when assessing the sustainability of agricultural management. Accuracy in soil temperature estimations is important as it regulates many important soil biogeochemical processes that lead to greenhouse gas emissions (GHG). The objective of this study was to account for the effects of snow cover in terms of the measured snow depth (mm of water), soil texture and crop management in temperate latitudes in order to improve the surface soil temperature mechanism in DNDC and thereby improve GHG predictions. The estimation of soil temperature driven by the thermal conductivity and heat capacity of the soil was improved by considering the soil texture under frozen and unfrozen conditions along with the effects of crop canopy and snow depth. Calibration of the developed model mechanisms was conducted using data from Alfred, ON under two contrasting soil textures (sandy loam vs. clay). Independent validation assessments were conducted using soil temperatures at different depths for contrasting managements for two field sites located in Canada (Guelph, ON and Glenlea, MB). The validation results indicated high model accuracy (R-2 > 0.90, EF >= 0.90, RMSE < 3.00 degrees C) in capturing the effects of management on soil temperature. These developments in soil heat transfer mechanism improved the performance of the model in estimating N2O emissions during spring thaw and provide a foundation for future studies aimed at improving simulations in DNDC for better representations of other biogeochemical processes. Crown Copyright (C) 2017 Published by Elsevier Ltd on behalf of IAgrE. All rights reserved.

\ Northern peatlands have accumulated a large amount of organic carbon (C) in their thick peat profile. Climate change and associated variations in soil environments are expected to have significant impacts on the C balance of these ecosystems, but the magnitude is still highly uncertain. Verifying and understanding the influences of changes in environmental factors on C gas fluxes in biogeochemical models are essential for forecasting feedbacks between C gas fluxes and climate change. In this study, we applied a biogeochemical model, DeNitrification-DeComposition (DNDC), to assess impacts of air temperature (T-A) and water table (WT) on C gas fluxes in an Alaskan peatland. DNDC was validated against field measurements of net ecosystem exchange of CO2 (NEE) and CH4 fluxes under manipulated surface soil temperature and WT conditions in a moderate rich fen. The validation demonstrates that DNDC was able to capture the observed impacts of the manipulations in soil environments on C gas fluxes. To investigate responses of C gas fluxes to changes in T-A and soil water condition, we conducted a series of simulations with varying T-A and WT. The results demonstrate that (1) uptake rates of CO2 at the site were reduced by either too colder or warmer temperatures and generally increased with increasing soil moisture; (2) CH4 emissions showed an increasing trend as T-A increased or WT rose toward the peat surface; and (3) the site could shift from a net greenhouse gas (GHG) sink into a net GHG source under some warm and/or dry conditions. A sensitivity analysis evaluated the relative importance of T-A and WT to C gas fluxes. The results indicate that both T-A and WT played important roles in regulating NEE and CH4 emissions and that within the investigated ranges of the variations in T-A and WT, changes in WT showed a greater impact than changes in T-A on NEE, CH4 fluxes, and net C gas fluxes at the study fen.

Primary succession in deglaciated region is the ideal environment for examining soil respiration (SR). In this study, we measured SR and employed a process-oriented model, Forest-denitrification-decomposition (DNDC), to study responses of SR to climate change in three primary successional stages in deglaciated region on Gongga Mountain, China. Stand types included a hardwood stand (S1), a coniferous and broad-leaved mixed forest stand (S2), and a mature stand of Abies fabri (Mast.) Craib (S3). Four climate scenarios (Baseline, B1, A1B, A2) reported by the Intergovernmental Panel on Climate Change were investigated. According to measured values, there was substantial temporal variation (coefficient of variation ranged from 49.7% in S1 to 61.4% in S3) and spatial variation (annual SR ranged from 2657 +/- 944 kg C ha(1) in S1 to 9228 +/- 1743 kg C ha(1) in S3) in the data. The modeled results showed that climate change affected the different stages to different extent in this region. Climate change will weaken the carbon sink strength of forest ecosystems in deglaciated region. The results have provided a better understanding on patterns of SR, and provided useful information on the magnitude and the response of SR to climate change in deglaciated region.