Effects of Soil Temperature and Moisture on the Development and Survival of Grasshopper Eggs in Inner Mongolian Grasslands

Grasshopper eggs overwinter in soil for almost half a year. Changes in soil temperature and moisture have a substantial effect on grasshopper eggs, especially temperature and moisture extremes. However, the combinatorial effect of temperature and moisture on the development and survival of grasshopper eggs has not been well studied. Here, we examined the effects of different soil moistures (2, 5, 8, 11, 14% water content) at 26°C and combinations of extreme soil moisture and soil temperature on the egg development and survival of three dominant species of grasshopper (Dasyhippus barbipes, Oedaleus asiaticus, and Chorthippus fallax) in Inner Mongolian grasslands. Our data indicated that the egg water content of the three grasshopper species was positively correlated with soil moisture but negatively correlated with hatching time. The relationship between hatching rate and soil moisture was unimodal. Averaged across 2 and 11% soil moisture, a soil temperature of 35oCsignificantly advanced the egg hatching time of D. barbipes, O. asiaticus, and C. fallax by 5.63, 4.75, and 2.63 days and reduced the egg hatching rate of D. barbipes by 18%. Averaged across 26 and 35°C, 2% soil moisture significantly delayed the egg hatching time of D. barbipes, O. asiaticus, and C. fallax by 0.69, 11.01, and 0.31 days, respectively, and decreased the egg hatching rate of D. barbipes by 10%. The hatching time was prolonged as drought exposure duration increased, and the egg hatching rate was negatively correlated with drought exposure duration, except for O. asiaticus. Overall, the combination of high soil temperature and low soil moisture had a significantly negative effect on egg development, survival, and egg hatching. Generally, the response of grasshopper eggs to soil temperature and moisture provides important information on the population dynamics of grasshoppers and their ability to respond to future climate change.

Comparison of N2O Emissions From Cold Waterlogged and Normal Paddy Fields

Paddy fields are major sources of atmospheric N2O. Soil temperature and moisture strongly affect N2O emissions from rice fields. However, N2O emissions from cold-waterlogged paddy fields (CW), an important kind of paddy soil in China, are not well studied so far. It is unclear whether the N2O emissions from cold-waterlogged paddy fields are the same as normal paddy fields (NW). We investigated the N2O emission characteristics from the CW and NW paddy fields under with (R1) and without (R0) rice in Tuku Village, Baisha Town, Yangxin County (YX site, monitoring in 2013) and Huandiqiao Town, Daye City (DY site, monitoring in 2014); compared the difference and influencing factors between the CW and NW paddy fields at two sites in South China. The results showed that the N2O emissions from NWR0 were 13.4 times higher than from CWR0, and from NWR1 were 10.3 times higher than from CWR1 in the YX site. The N2O emissions from NWR0 were 2.4 times higher than from CWR0, and from NWR1 were 17.3 times higher than from CWR1 in the DY site. The structural equation models (SEMs) showed that the N2O emissions are mainly driven by rice planting and soil moisture in the NW fields at the annual scale, while soil temperature in the CW fields. Overall, N2O emissions from cold waterlogged paddy fields are significantly lower than those of normal paddy fields due to the low temperature and higher water content; however, there are dinitrogen emissions from cold waterlogged paddy fields denitrification should be further examined.

Do ARMA Models Provide Better Gap Filling in Time Series of Soil Temperature and Soil Moisture? The Case of Arable Land in the Kulunda Steppe, Russia

The adoption of climate-smart agriculture requires the comprehensive development of environmental monitoring tools, including online observation of climate and soil settings. They are often designed to measure soil properties automatically at different depths at hour or minute intervals. It is essential to have a complete dataset to use statistical models for the prediction of soil properties and to make short-term decisions regarding soil tillage operations and irrigation during a vegetation period. This is also important in applied hydrological studies. Nevertheless, the time series of soil hydrological measurements often have data gaps for different reasons. The study focused on solving a problem of gap-filling in hourly time series of soil temperature and moisture, measured at the 30 cm depth using a weighted gravitation lysimeter station while meteorological data were recorded simultaneously by a weather station. The equipment was installed in the Kulunda Steppe in the Altai Krai, Russia. Considering that climate conditions affect soil temperature and moisture content directly, we did a comparative analysis of the gap-filling performance using the three imputation methods—linear interpolation, multiple linear regression, and extended ARMA (p,q) models with exogenous climatic variables. The results showed that, according to the minimum of the mean absolute error, ARMA (p,q) models with optimally selected order parameters, and an adaptive window, had some advantages compared to other single-imputation methods. The ARMA (p,q) model produced a good quality of gap-filling in time series with the mean absolute error of 0.19 °C and 0.08 Vol. % for soil temperature and moisture content, respectively. The findings supplemented the methodology of hydrological data processing and the development of digital tools for the online monitoring of climate and soil properties in agriculture.

Separating autotrophic and heterotrophic soil CO₂ effluxes in afforested peatlands

Peatlands are a significant global carbon (C) store, which can be compromised by drainage and afforestation. Quantifying the rate of C loss from peat soils under forestry is challenging, as soil CO2 efflux includes both CO2 produced from heterotrophic peat decomposition and CO2 produced by tree roots and associated fungal networks (autotrophic respiration). We experimentally terminated autotrophic belowground respiration in replicated forest plots by cutting through all living tree roots (trenching), and measured soil surface CO2 flux, litter input, litter decay rate and soil temperature and moisture over two years. Annual peat decomposition (heterotrophic CO2 flux) was 115 ± 16 g C m−2 y−1, representing c. 40 % of total soil respiration. Decomposition of needle litter is accelerated in the presence of an active rhizosphere, indicating a priming effects by labile C inputs from roots. This suggests that our estimates of peat mineralization in our trenched plots are conservative, and underestimate overall rates of peat C loss. Considering also input of litter from trees, our results indicate that the soils in these 30 year-old drained and afforested peatlands are a net sink for C, since substantially more C enters the soil as organic matter, than is decomposed heterotrophically. However, the C balance for these soils should be taken over the lifespan of the trees, in order to determine if the soils under these drained and afforested peatlands are a sustained sink of C, or become a net source over longer periods of forestry.