scholarly journals The Role of Arbuscular Mycorrhiza Fungi in the Decomposition of Fresh Residue and Soil Organic Carbon: A Mini-Review

2019 ◽  
Vol 83 (3) ◽  
pp. 511-517 ◽  
Author(s):  
Lili Wei ◽  
Miroslav Vosátka ◽  
Bangping Cai ◽  
Jing Ding ◽  
Changyi Lu ◽  
...  
CATENA ◽  
2013 ◽  
Vol 109 ◽  
pp. 186-194 ◽  
Author(s):  
Chao Wang ◽  
Fuchun Li ◽  
Huanzhi Shi ◽  
Zhangdong Jin ◽  
Xuhui Sun ◽  
...  

2015 ◽  
Vol 114 (1) ◽  
pp. 22-32
Author(s):  
Jason K. Keller ◽  
Tyler Anthony ◽  
Dustin Clark ◽  
Kristin Gabriel ◽  
Dewmini Gamalath ◽  
...  

2021 ◽  
Author(s):  
Katerina Georgiou ◽  
Avni Malhotra ◽  
William R. Wieder ◽  
Jacqueline H. Ennis ◽  
Melannie D. Hartman ◽  
...  

AbstractThe storage and cycling of soil organic carbon (SOC) are governed by multiple co-varying factors, including climate, plant productivity, edaphic properties, and disturbance history. Yet, it remains unclear which of these factors are the dominant predictors of observed SOC stocks, globally and within biomes, and how the role of these predictors varies between observations and process-based models. Here we use global observations and an ensemble of soil biogeochemical models to quantify the emergent importance of key state factors – namely, mean annual temperature, net primary productivity, and soil mineralogy – in explaining biome- to global-scale variation in SOC stocks. We use a machine-learning approach to disentangle the role of covariates and elucidate individual relationships with SOC, without imposing expected relationships a priori. While we observe qualitatively similar relationships between SOC and covariates in observations and models, the magnitude and degree of non-linearity vary substantially among the models and observations. Models appear to overemphasize the importance of temperature and primary productivity (especially in forests and herbaceous biomes, respectively), while observations suggest a greater relative importance of soil minerals. This mismatch is also evident globally. However, we observe agreement between observations and model outputs in select individual biomes – namely, temperate deciduous forests and grasslands, which both show stronger relationships of SOC stocks with temperature and productivity, respectively. This approach highlights biomes with the largest uncertainty and mismatch with observations for targeted model improvements. Understanding the role of dominant SOC controls, and the discrepancies between models and observations, globally and across biomes, is essential for improving and validating process representations in soil and ecosystem models for projections under novel future conditions.


2020 ◽  
Author(s):  
Zhongkui Luo ◽  
Raphael Viscarra-Rossel

Abstract. Soil organic carbon (SOC) accounts for two-thirds of terrestrial carbon. Yet, the role of soil physiochemical properties in regulating SOC stocks is unclear, inhibiting reliable SOC predictions under land use and climatic changes. Using legacy observations from 141,584 soil profiles worldwide, we disentangle the effects of biotic, climatic and edaphic factors (a total of 30 variables) on the global spatial distribution of SOC stocks in four sequential soil layers down to 2 m. The results indicate that the 30 variables can explain 70–80 % of the global variance of SOC in the four layers, to which edaphic properties contribute ~ 60 %. Soil lower limit is the most important individual soil properties, positively associated with SOC in all layers, while climatic variables are secondary. This dominant effect of soil properties challenges current climate-driven framework of SOC dynamics, and need to be considered to reliably project SOC changes for effective carbon management and climate change mitigation.


Sign in / Sign up

Export Citation Format

Share Document