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

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 1^st 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 m.day⁻¹, respectively, under favorable meteorological conditions of 2015 and 0.05969 m. and 0.00049 ±0.00035 m.day⁻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.day⁻¹ in 2015 and 52.3 ±23.4 kg.C.ha-1.day⁻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.day⁻¹) than under unfavorable (5.17 ±2.19 kg.C.ha⁻¹.day⁻¹) meteorological conditions.