A study over 33 years shows that carbon and nitrogen stocks in a subtropical soil are increasing under native vegetation in a changing climate

Shining a Light on How Soil Organic Carbon Behaves at Fine Scales under Long-Term Elevated CO2: An 8 Year Free-Air Carbon Dioxide Enrichment Study

Building and protecting soil organic carbon (SOC) are critical to agricultural productivity, soil health, and climate change mitigation. We aim to understand how mechanisms at the organo-mineral interfaces influence SOC persistence in three contrasting soils (Luvisol, Vertisol, and Calcisol) under long-term free air CO2 enrichment conditions. A continuous wheat-field pea-canola rotation was maintained. For the first time, we provided evidence to a novel notion that persistent SOC is molecularly simple even under elevated CO2 conditions. We found that the elevated CO2 condition did not change the total SOC content or C forms compared with the soils under ambient CO2 as identified by synchrotron-based soft X-ray analyses. Furthermore, synchrotron-based infrared microspectroscopy confirmed a two-dimensional microscale distribution of similar and less diverse C forms in intact microaggregates under long-term elevated CO2 conditions. Strong correlations between the distribution of C forms and O-H groups of clays can explain the steady state of the total SOC content. However, the correlations between C forms and clay minerals were weakened in the coarse-textured Calcisol under long-term elevated CO2. Our findings suggested that we should emphasize identifying management practices that increase the physical protection of SOC instead of increasing complexity of C. Such information is valuable in developing more accurate C prediction models under elevated CO2 conditions and shift our thinking in developing management practices for maintaining and building SOC for better soil fertility and future environmental sustainability.

Prediction of Soc in Calcic Chernozem in the Steppe Zone of Ukraine Using Brightness and Colour Indicators

Soil organic carbon (SOC) is an important component of any soil which determines many of its properties. Nowadays, more and more attention is being paid to the SOC content determination in soils by not using the conventional, time-consuming and expensive technique, but by using colour image processing of soil samples. In this case, even the camera of modern smartphones can be used as an image source, making this technique very convenient and practical. However, it is important to maintain certain standardised conditions (light intensity, light incidence angle, etc.) when capturing the images of soil samples. In our opinion, it is best to use a regular scanner for this purpose, with subsequent image processing by graphic programs (e.g., Adobe Photoshop). To increase the reliability of the colour information obtained in this way, it is desired (if possible) to use a spectrograph or a monochromator in the subsequent calculation of reflection or brightness ratios. It is these two approaches that we have implemented in our work. As a result of the experiment, the values of brightness ratios (at 480, 650 and 750 nm wavelengths and integral brightness ratio), colour indicators (the hue, saturation and value [HSV], red, green and blue [RGB], CIE L*a*b* and cyan, magenta, yellow and key [CMYK] systems) and SOC content in Calcic Chernozem samples of the steppe zone of Ukraine were obtained. Using correlation analysis of the dataset, the existence of direct (r = 0.88–0.90) and inverse close relationships (r = −0.75–0.90) between SOC, values of brightness ratios and colour indicators of the soil samples were established. This allows us to develop predictive models. Statistical analysis showed that the models were significant when they were based on the values of brightness ratios at 650 nm wavelength, integral brightness ratio, V indicator in HSV system, R, G and B indicators in RGB system, C, M and K indicators in CMYK system and L* and b* indicators in L*a*b* system. The subsequent calculation of variation coefficients showed that the largest variability was observed in SOC indicators (CV = 0.72) and slightly less variability in the K index of CMYK system and brightness ratio values at 650 nm wavelength (CV = 0.67 and 0.53, respectively). Based on this, we believe that the models y = 0.0188 + 0.0535*x (x is the value of the K index in CMYK system) and y = 5.0716 – 3.2255*log10(x) (x is the value of brightness ratio at 650 nm wavelength) were the most statistically significant and promising parameters for determining SOC content (y in these equations) in Calcic Chernozem samples of the steppe zone of Ukraine.

Climate Change Decreased Net Ecosystem Productivity in the Arid Region of Central Asia

Numerous studies have confirmed that climate change leads to a decrease in the net ecosystem productivity (NEP) of terrestrial ecosystems and alters regional carbon source/sink patterns. However, the response mechanism of NEP to climate change in the arid regions of Central Asia remains unclear. Therefore, this study combined the Carnegie–Ames–Stanford approach (CASA) and empirical models to estimate the NEP in Central Asia and quantitatively evaluate the sensitivity of the NEP to climate factors. The results show that although the net primary productivity (NPP) in Central Asia exhibits an increasing trend, it is not significant. Soil heterotrophic respiration (RH) has increased significantly, while the NEP has decreased at a rate of 6.1 g C·m−2·10 a−1. Spatially, the regional distribution of the significant increase in RH is consistent with that of the significant decrease in the NEP, which is concentrated in western and southern Central Asia. Specifically, the NPP is more sensitive to precipitation than temperature, whereas RH and NEP are more sensitive to temperature than precipitation. The annual contribution rates of temperature and precipitation to the NEP are 28.79% and 23.23%, respectively. Additionally, drought has an important impact on the carbon source/sink in Central Asia. Drought intensified from 2001 to 2008, leading to a significant expansion of the carbon source area in Central Asia. Therefore, since the start of the 21st century, climate change has damaged the NEP of the Central Asian ecosystem. Varying degrees of warming under different climate scenarios will further aggravate the expansion of carbon source areas in Central Asia. An improved understanding of climate change impacts in Central Asia is critically required for sustainable development of the regional economy and protection of its natural environment. Our results provide a scientific reference for the construction of the Silk Road Economic Belt and global emissions reduction.