scholarly journals Improving Estimations of Spatial Distribution of Soil Respiration Using the Bayesian Maximum Entropy Algorithm and Soil Temperature as Auxiliary Data

PLoS ONE ◽  
2016 ◽  
Vol 11 (1) ◽  
pp. e0146589 ◽  
Author(s):  
Junguo Hu ◽  
Jian Zhou ◽  
Guomo Zhou ◽  
Yiqi Luo ◽  
Xiaojun Xu ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Soil Respiration ◽  
Soil Temperature ◽  
Maximum Entropy ◽  
Bayesian Maximum Entropy ◽  
Auxiliary Data

scholarly journals Improvement of Soil Respiration Parameterization in a Dynamic Global Vegetation Model and Its Impact on the Simulation of Terrestrial Carbon Fluxes

2018 ◽  
Vol 32 (1) ◽  
pp. 127-143 ◽  
Author(s):  
Dongmin Kim ◽  
Myong-In Lee ◽  
Eunkyo Seo
Keyword(s):  
Spatial Distribution ◽  
Soil Respiration ◽  
Soil Temperature ◽  
Vegetation Type ◽  
Carbon Fluxes ◽  
Decomposition Process ◽  
Spatial And Temporal Variation ◽  
In Situ Observation ◽  
Terrestrial Carbon ◽  
Soil Temperature And Moisture

Abstract The Q10 value represents the soil respiration sensitivity to temperature often used for the parameterization of the soil decomposition process has been assumed to be a constant in conventional numerical models, whereas it exhibits significant spatial and temporal variation in the observations. This study develops a new parameterization method for determining Q10 by considering the soil respiration dependence on soil temperature and moisture obtained by multiple regression for each vegetation type. This study further investigates the impacts of the new parameterization on the global terrestrial carbon flux. Our results show that a nonuniform spatial distribution of Q10 tends to better represent the dependence of the soil respiration process on heterogeneous surface vegetation type compared with the control simulation using a uniform Q10. Moreover, it tends to improve the simulation of the relationship between soil respiration and soil temperature and moisture, particularly over cold and dry regions. The modification has an impact on the soil respiration and carbon decomposition process, which changes gross primary production (GPP) through controlling nutrient assimilation from soil to vegetation. It leads to a realistic spatial distribution of GPP, particularly over high latitudes where the original model has a significant underestimation bias. Improvement in the spatial distribution of GPP leads to a substantial reduction of global mean GPP bias compared with the in situ observation-based reference data. The results highlight that the enhanced sensitivity of soil respiration to the subsurface soil temperature and moisture introduced by the nonuniform spatial distribution of Q10 has contributed to improving the simulation of the terrestrial carbon fluxes and the global carbon cycle.

scholarly journals Improvement of Soil Respiration Parameterization in a Dynamic Global Vegetation Model and Its Impact on the Simulation of Terrestrial Carbon Fluxes

2017 ◽  
Author(s):  
Dongmin Kim ◽  
Myong-In Lee ◽  
Eunkyo Seo
Keyword(s):  
Spatial Distribution ◽  
Soil Respiration ◽  
Soil Temperature ◽  
Numerical Models ◽  
Gross Primary Production ◽  
Substantial Reduction ◽  
Observation Data ◽  
Terrestrial Carbon ◽  
Dynamic Global Vegetation Model ◽  
Soil Temperature And Moisture

Abstract. Soil decomposition is one of the critical processes for maintaining a terrestrial ecosystem and the global carbon cycle. The sensitivity of soil respiration (Rs) to temperature, the so-called Q10 value, is required for parameterizing the soil decomposition process and is assumed to be a constant in conventional numerical models, while realistically it is not in cases of spatiotemporal heterogeneity. This study develops a new parameterization method for determining Q10 by considering the soil respiration dependence on soil temperature and moisture obtained by multiple regression. This study further investigates the impacts of the new parameterization on the global terrestrial carbon flux. Our results show that non-uniform spatial distribution of Q10 tends to represent the dependence of the soil respiration process on heterogeneous surface vegetation type compared with the control simulation using a uniform Q10. Moreover, it tends to improve the simulation of the observed relationship between soil respiration and soil temperature and moisture, particularly over cold and dry regions. The new parameterization improves the simulation of gross primary production (GPP). It leads to a more realistic spatial distribution of GPP, particularly over high latitudes (60–80 N) where the original model has a significant underestimation bias. In addition, overestimation bias of GPP in the tropics and the midlatitudes is significantly reduced. Improvement in the spatial distribution of GPP leads to a substantial reduction of global mean bias of GPP from +9.11 to +1.68 GtC yr−1 compared with the FLUXNET-MTE observation data.

scholarly journals Soil CO2 efflux in central Amazonia: environmental and methodological effects

2012 ◽  
Vol 42 (2) ◽  
pp. 173-184 ◽  
Author(s):  
Fabrício B. Zanchi ◽  
Maarten J. Waterloo ◽  
Bart Kruijt ◽  
Jürgen Kesselmeier ◽  
Flávio J. Luizão ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Soil Respiration ◽  
Soil Temperature ◽  
Bare Soil ◽  
Control Factor ◽  
Co2 Efflux ◽  
Good Tool ◽  
Shuttle Radar Topographic Mission ◽  
Heath Forest ◽  
Total Average

Soil respiration plays a significant role in the carbon cycle of Amazonian rainforests. Measurements of soil respiration have only been carried out in few places in the Amazon. This study investigated the effects of the method of ring insertion in the soil as well as of rainfall and spatial distribution on CO2 emission in the central Amazon region. The ring insertion effect increased the soil emission about 13-20% for sandy and loamy soils during the firsts 4-7 hours, respectively. After rainfall events below 2 mm, the soil respiration did not change, but for rainfall greater than 3 mm, after 2 hours there was a decrease in soil temperature and respiration of about 10-34% for the loamy and sand soils, with emissions returning to normal after around 15-18 hours. The size of the measurement areas and the spatial distribution of soil respiration were better estimated using the Shuttle Radar Topographic Mission (SRTM) data. The Campina reserve is a mosaic of bare soil, stunted heath forest-SHF and tall heath forest-THF. The estimated total average CO2 emissions from the area was 3.08±0.8 µmol CO2 m-2 s-1. The Cuieiras reserve is another mosaic of plateau, slope, Campinarana and riparian forests and the total average emission from the area was 3.82±0.76 µmol CO2 m-2 s-1. We also found that the main control factor of the soil respiration was soil temperature, with 90% explained by regression analysis. Automated soil respiration datasets are a good tool to improve the technique and increase the reliability of measurements to allow a better understanding of all possible factors driven by soil respiration processes.

scholarly journals Dynamics of the soil respiration response to soil reclamation in a coastal wetland

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Xiliang Song ◽  
Yihao Zhu ◽  
Weifeng Chen
Keyword(s):  
Soil Respiration ◽  
Soil Temperature ◽  
Soil Carbon ◽  
Water Content ◽  
Coastal Wetlands ◽  
Positive Relationship ◽  
Soil Reclamation ◽  
Diurnal Changes ◽  
Seasonal Scale ◽  
Study Sites

AbstractThe soil carbon (C) pools in coastal wetlands are known as “blue C” and have been damaged extensively owing to climate change and land reclamation. Because soil respiration (RS) is the primary mechanism through which soil carbon is released into the atmosphere at a global scale, investigating the dynamic characteristics of the soil respiration rate in reclaimed coastal wetlands is necessary to understand its important role in maintaining the global C cycle. In the present study, seasonal and diurnal changes in soil respiration were monitored in one bare wetland (CK) and two reclaimed wetlands (CT, a cotton monoculture pattern, and WM, a wheat–maize continuous cropping pattern) in the Yellow River Delta. At the diurnal scale, the RS at the three study sites displayed single-peak curves, with the lowest values occurring at midnight (00:00 a.m.) and the highest values occurring at midday (12:00 a.m.). At the seasonal scale, the mean diurnal RS of the CK, CT and WM in April was 0.24, 0.26 and 0.79 μmol CO2 m−2 s−1, and it increased to a peak in August for these areas. Bare wetland conversion to croplands significantly elevated the soil organic carbon (SOC) pool. The magnitude of the RS was significantly different at the three sites, and the yearly total amounts of CO2 efflux were 375, 513 and 944 g CO2·m−2 for the CK, CT and WM, respectively. At the three study sites, the surface soil temperature had a significant and positive relationship to the RS at both the diurnal and seasonal scales, and it accounted for 20–52% of the seasonal variation in the daytime RS. The soil water content showed a significant but negative relationship to the RS on diurnal scale only at the CK site, while it significantly increased with the RS on seasonal scale at all study sites. Although the RS showed a noticeable relationship to the combination of soil temperature and water content, the synergic effects of these two environment factors were not much higher than the individual effects. In addition, the correlation analysis showed that the RS was also influenced by the soil physico-chemical properties and that the soil total nitrogen had a closer positive relationship to the RS than the other nutrients, indicating that the soil nitrogen content plays a more important role in promoting carbon loss.

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