Assessing the Impacts of Climate Change-induced Variations in Air Temperature and Precipitation on Plant Physiological and Soil Microbial Processes with DNDC Model


Authors: Eugene V. Balashov, Alexey V. Dobrokhotov and Lyudmila V. Kozyreva

Volume/Issue: Volume 27: Issue 1

Published online: 23 Apr 2024

Pages: 1 - 5



The DNDC (DeNitrification-DeComposition) model (version 9.5) was applied to predict the differences in transpiration and photosynthesis rates of perennial grasses (red clover and timothy), and autotrophic respiration of a sandy Spodosol. The input parameters for two growing seasons (from 1st of May to 31st of August in 2010 and 2015) contrasting in meteorological conditions were used in the modeling experiment. In 2010, the mean air temperature of the period was 14.1 ±3.3 °C and the total precipitation – 0.1796 m, while in 2015 the mean air temperature was 16.8 ±5.5 °C and the total precipitation – 0.538 m. These meteorological parameters were unfavorable for plants in 2010 and favorable in 2015. The results have shown that the DNDC model adequately predicted the weather-induced differences in total and mean transpiration rates of perennial grasses: 0.12204 m. and 0.00099 ±0.00040−1, respectively, under favorable meteorological conditions of 2015 and 0.05969 m. and 0.00049 ±0.00035−1, respectively, under unfavorable meteorological conditions of 2010. Dynamics of daily transpiration rates of plants was significantly (r = 0.34 p <0.001) correlated with soil water content only under unfavorable meteorological conditions. Mean values of simulated photosynthesis rates were equal to 84.4 ±27.9 kg.C.ha−−1 in 2015 and 52.3 ±23.4−1 in 2010. There were significant differences (p <0.001) in the mean values of photosynthesis rates between the two weather scenarios. The results of one-way analysis of variance (ANOVA) have shown that the rates of autotrophic respiration were significantly (p <0.001) higher under favorable (8.14 ±2.25 kg.C.ha−−1) than under unfavorable (5.17 ±2.19 kg.C.ha−−1) meteorological conditions.

Keywords: DNDC model, air temperature, precipitation, transpiration, photosynthesis, autotrophic respiration



Abdalla, M., Kumar, S., Jones, M., Burke, J., & Williams, M. (2011). Testing DNDC model for simulating soil respiration and assessing the effects of climate change on the CO2 gas flux from Irish agriculture. Global and Planetary Change, 78(3–4), 106–115.

Balashov, E., Buchkina, N., Rizhiya, E., & Farkas, C. (2014). Field validation of DNDC and SWAP models for temperature and water content of loamy and sandy loam Spodosols. International Agrophysics, 28(2).

Balogh, J., Papp, M., Pintér, K., Fóti, S., Posta, K., Eugster, W., & Nagy, Z. (2016). Autotrophic component of soil respiration is repressed by drought more than the heterotrophic one in dry grasslands. Biogeosciences, 13(18), 5171–5182.

Barneze, A. S., Abdalla, M., Whitaker, J., McNamara, N. P., & Ostle, N. J. (2022). Predicted Soil Greenhouse Gas Emissions from Climate× Management Interactions in Temperate Grassland. Agronomy, 12(12), 3055.

Beheydt, D., Boeckx, P., Sleutel, S., Li, C., & Van Cleemput, O. (2007). Validation of DNDC for 22 long-term N2O field emission measurements. Atmospheric Environment, 41(29), 6196–6211.

De Kimpe, C. R., & Warkentin, B. P. (1998). Soil functions and the future of natural resources. Soil functions and the future of natural resources, (31), 3–10.

De Winter, J. C., Gosling, S. D., & Potter, J. (2016). Comparing the Pearson and Spearman correlation coefficients across distributions and sample sizes: A tutorial using simulations and empirical data. Psychological methods, 21(3), 273.

D‘Ottavio, P., Francioni, M., Toderi, M., & Trozzo, L. (2023). Monthly mowing frequency does not affect soil CO2 emissions of fertilized Bromus erectus‐dominated grasslands. Grassland Science, 69(2), 103–112.

Evangelista, S. J., Field, D. J., McBratney, A. B., Minasny, B., Ng, W., Padarian, J., Dobarco, M. R., & Wadoux, A. M. C. (2023). A proposal for the assessment of soil security: Soil functions, soil services and threats to soil. Soil Security, 10, 100086.

Gong, W., Wang, Z., Zhang, Q., & Yue, T. (2023). A review and outlook on the development and application of the DNDC model. Authorea Preprints.

Hopple, A. M., Pennington, S. C., Megonigal, J. P., Bailey, V., & Bond‐Lamberty, B. (2023). Root and Microbial Soil CO2 and CH4 Fluxes Respond Differently to Seasonal and Episodic Environmental Changes in a Temperate Forest. Journal of Geophysical Research: Biogeosciences, 128(8), e2022JG007233.

Li, C. S. (2000). Modeling trace gas emissions from agricultural ecosystems. Methane emissions from major rice ecosystems in Asia (pp. 259–276).

Li, C., Farahbakhshazad, N., Jaynes, D. B., Dinnes, D. L., Salas, W., & McLaughlin, D. (2006). Modeling nitrate leaching with a biogeochemical model modified based on observations in a row-crop field in Iowa. Ecological Modelling, 196(1–2), 116–130.

Liu, Z., Huang, F., Wang, B., Li, Z., Zhao, C., Ding, R., Yang, B., Zhang, P., & Jia, Z. (2023). Soil respiration in response to biotic and abiotic factors under different mulching measures on rain-fed farmland. Soil and Tillage Research, 232, 105749.

Liu, H., Zhang, L., & Liu, Y. (2021). Stomatal conductivity, canopy temperature and evapotranspiration of maize (Zea mays L.) to water stress in Northeast China. International Journal of Agricultural and Biological Engineering, 14(2), 112–119.

Mann, H. B., & Whitney, D. R. (1947). On a test of whether one of two random variables is stochastically larger than the other. The annals of mathematical statistics, 50–60.

Shapiro, S. S., & Wilk, M. B. (1965). An analysis of variance test for normality (complete samples). Biometrika, 52(3/4), 591–611.

Spearman, C. (1904). General Intelligence“ Objectively Determined and Measured. American Journal of Psychology,15(2), 201–293.

Tonitto, C., Li, C., Seidel, R., & Drinkwater, L. (2010). Application of the DNDC model to the Rodale Institute Farming Systems Trial: challenges for the validation of drainage and nitrate leaching in agroecosystem models. Nutrient Cycling in Agroecosystems, 87, 483–494.

Wang, X., Liu, L., Piao, S., Janssens, I. A., Tang, J., Liu, W., Chi, Y., Wang, J., & Xu, S. (2014). Soil respiration under climate warming: differential response of heterotrophic and autotrophic respiration. Global Change Biology, 20(10), 3229–3237.