Components of Soil Respiration and Its Temperature Sensitivity in Four Reconstructed Soils

seasonal changes characteristics in the respiration of four reconstructed soils Abstract: seasonal changes characteristics in the respiration of four reconstructed soil masses 9 in a barren gravel land were monitored using soil carbon flux measurement system. The 10 results showed that (1) The seasonal changes in soil respiration and heterotrophic respiration 11 of four reconstructed soils of meteorite, shale, sand and soft rock were the same as the 12 seasonal change in soil temperature. Soil respiration and heterotrophic respiration increased 13 with soil temperature. It was gradually increasing, reaching the maximum in summer and 14 decreasing to the minimum in winter. Among the four reconstructed soils, the average annual 15 soil respiration of reconstructed soil with sand was 4.87 μmol•m –2 •s –1 , which was 16 significantly higher than the other reconstructed soils (p<0.05).(2) The autotrophic respiration 17 of four reconstructed soils showed obvious seasonal dynamic changes. The maximum and 18 minimum values appeared in August 2018 and January 2018, respectively. In the whole year, 19 The variation range of the annual average soil autotrophic respiration in the total respiration 20 of the reconstituted soil with addtion of meteorite, shale, sand and soft rock were 12.5-38.0%, 21 9.5-42.0%, 7.7-41.2%, and 5.0-39.3%, respectively.(3) Soil temperature was the main factor 22 affecting soil respiration. The four reconstructed respiration had a very significant correlation 23 with soil temperature (p<0.01). The relationship between reconstructed soils respiration and 24 soil temperature can be indexed function characterization. The 90% to 93% changes in soil 25 respiration of reconstructed soils were caused by soil temperature. The order of Q 10 in soils 26 respiration of four reconstructed was as follows: Sand> shale> soft rock > meteorite.

Impact of temperature and water availability on microwave-derived gross primary production

Vegetation optical depth (VOD) from microwave satellite observations has received much attention in global vegetation studies in recent years due to its relationship to vegetation water content and biomass. We recently have shown that VOD is related to plant productivity, i.e., gross primary production (GPP). Based on this relationship between VOD and GPP, we developed a theory-based machine learning model to estimate global patterns of GPP from passive microwave VOD retrievals. The VOD-GPP model generally showed good agreement with site observations and other global data sets in temporal dynamic but tended to overestimate annual GPP across all latitudes. We hypothesized that the reason for the overestimation is the missing effect of temperature on autotrophic respiration in the theory-based machine learning model. Here we aim to further assess and enhance the robustness of the VOD-GPP model by including the effect of temperature on autotrophic respiration within the machine learning approach and by assessing the interannual variability of the model results with respect to water availability. We used X-band VOD from the VOD Climate Archive (VODCA) data set for estimating GPP and used global state-of-the-art GPP data sets from FLUXCOM and MODIS to assess residuals of the VOD-GPP model with respect to drought conditions as quantified by the Standardized Precipitation and Evaporation Index (SPEI). Our results reveal an improvement in model performance for correlation when including the temperature dependency of autotrophic respiration (average correlation increase of 0.18). This improvement in temporal dynamic is larger for temperate and cold regions than for the tropics. For unbiased root-mean-square error (ubRMSE) and bias, the results are regionally diverse and are compensated in the global average. Improvements are observed in temperate and cold regions, while decreases in performance are obtained mainly in the tropics. The overall improvement when adding temperature was less than expected and thus may only partly explain previously observed differences between the global GPP data sets. On interannual timescales, estimates of the VOD-GPP model agree well with GPP from FLUXCOM and MODIS. We further find that the residuals between VOD-based GPP estimates and the other data sets do not significantly correlate with SPEI, which demonstrates that the VOD-GPP model can capture responses of GPP to water availability even without including additional information on precipitation, soil moisture or evapotranspiration. Exceptions from this rule were found in some regions: significant negative correlations between VOD-GPP residuals and SPEI were observed in the US corn belt, Argentina, eastern Europe, Russia and China, while significant positive correlations were obtained in South America, Africa and Australia. In these regions, the significant correlations may indicate different plant strategies for dealing with variations in water availability. Overall, our findings support the robustness of global microwave-derived estimates of gross primary production for large-scale studies on climate–vegetation interactions.

Spatial variability of carbon allocation to soil autotrophic respiration in global forest ecosystems

&lt;p&gt;Belowground or &amp;#8216;soil&amp;#8217; autotrophic respiration (RAsoil) depends on carbohydrates from photosynthesis flowing to roots and rhizospheres, and is one of the most important but uncertain components in forest carbon cycling. Carbon allocation plays an important role in forest carbon cycling and reflects forest adaptation to changing environmental conditions. However, carbon allocation to RAsoil is rarely measured directly and has not been fully examined at the global scale. To fill this knowledge gap, the spatio-temporal patterns of RAsoil with a spatial resolution of half degree from 1981 to 2017 were predicted by Random Forest (RF) algorithm using the most updated Global Soil Respiration Database (v5) with global environmental variables; carbon allocation from photosynthesis to RAsoil (CAsoil), was calculated as the ratio of RAsoil to gross primary production (GPP); and its temporal and spatial patterns were assessed in global forest ecosystems. We found strong temporal and spatial variabilities of RAsoil with an increasing trend from boreal forests to tropical forests. Globally, mean RAsoil from forests was 8.9 &amp;#177; 0.08 Pg C yr&lt;sup&gt;-1&lt;/sup&gt; (mean &amp;#177; standard deviation) from 1981 to 2017 increasing at a rate of 0.0059 Pg C yr&lt;sup&gt;-2&lt;/sup&gt;, paralleling broader soil respiration changes and indicating an increasing carbon loss respired by roots. Mean CAsoil was 0.243 &amp;#177; 0.016 and showed a decreasing trend over time, although there were interannual variabilities, indicating that CAsoil was sensitive to environmental changes. The temporal trend of CAsoil varied greatly in space, reflecting uneven responses of CAsoil to environmental changes. The spatio-temporal variability of carbon allocation should be considered in global biogeochemical models to accurately predict belowground carbon cycling in an era of ongoing climate change.&amp;#160;&lt;/p&gt;

Autotrophic and heterotrophic contributions to soil respiration in a subtropical camphor tree forest

Understanding the contributions of autotrophic respiration (Ra) and heterotrophic respiration (Rh) to total soil respiration (Rs) is necessary for accurate prediction of global carbon balance and net ecosystem production under environmental change. In this research, annual Rs and Rh and estimated were investigated by using a root trenching experiment in a Camphor tree (Cinnamomum camphora) forest in subtropical China for two years to qualify the relative contribution of Ra and Rh components to Rs, and to determine the environmental factors that control the seasonal changes in Ra, Rh and Rs. The results showed that annual mean Rs was 405 ± 219 gC m-2 year-1 in the studied forests, of which Rh and Ra were 240 ± 120 gC m-2 year-1 and 164 ±102 gC m-2 year-1, respectively. The contribution of Rh to Rs averaged 58.1%, ranging from 45 to 81%. The seasonal changes in Rs and Rh were highly correlated with soil temperature, but not to soil water content. Our results suggest microbial community and activity make a primary contribution to carbon flux released from soil to atmosphere in the studied forest ecosystems.

Respiration characteristics and its responses to hydrothermal seasonal changes in reconstructed soils

Seasonal changes in respiration and the components of four reconstructed soils (gravel + meteorite + lou; gravel + shale + lou; gravel + sand + lou; and gravel + soft rock + lou) in barren gravel land were monitored using the soil carbon flux measurement system. The results showed that (1) the monthly average respiration rate and the rates of the components in the four reconstructed soils were the highest in summer and lowest in winter. In winter, the monthly average respiration rates of the four reconstructed soils were not different (p > 0.05). In summer, the monthly average respiration rate of the sand or meteorite reconstructed soil was different from that of the other three (p < 0.05). (2) The heterotrophic and autotrophic respiration rates were different between the four reconstructed soils (p < 0.05). The contribution of heterotrophic respiration to total respiration in the four reconstructed soils was greater than that of autotrophic respiration throughout the year. In winter, autotrophic respiration accounts for the smallest proportion of total respiration. As the temperature rises, the proportion of autotrophic respiration to total respiration gradually increases and peaks in summer. In summer, the proportion of heterotrophic respiration in the total respiration is the smallest. With the decrease in temperature, the proportion of heterotrophic respiration in total respiration gradually increases and peaks in winter. (3) The maximum and minimum values of the monthly average respiration rate of the four reconstructed soils coincided with the months of maximum and minimum soil temperature. The soil volumetric water content changed with the amount of precipitation. The correlation between soil respiration and temperature was greater than that between soil respiration and volumetric water content. (4) The correlation in seasonal variation between respiration of the four remodelled soils and hydrothermal factors in the study area can be characterised by an exponential function and power-exponential function.