Climate Change and the Global Soil Carbon Stocks

2018 ◽  
pp. 419-426
Author(s):  
Rattan Lal
2018 ◽  
pp. 301-322 ◽  
Author(s):  
Tarik Mitran ◽  
Rattan Lal ◽  
Umakant Mishra ◽  
Ram Swaroop Meena ◽  
T. Ravisankar ◽  
...  

2021 ◽  
Author(s):  
David Bysouth ◽  
Merritt Turetsky ◽  
Andrew Spring

<p>Climate change is causing rapid warming at northern high latitudes and disproportionately affecting ecosystem services that northern communities rely upon. In Canada’s Northwest Territories (NWT), climate change is impacting the access and availability of traditional foods that are critical for community health and well-being. With climate change potentially expanding the envelope of suitable agricultural land northward, many communities in the NWT are evaluating including agriculture in their food systems. However, the conversion of boreal forest to agriculture may degrade the carbon rich soils that characterize the region, resulting in large carbon losses to the atmosphere and the depletion of existing ecosystem services associated with the accumulation of soil organic matter. Here, we first summarize the results of 35 publications that address land use change from boreal forest to agriculture, with the goal of understanding the magnitude and drivers of carbon stock changes with time-since-land use change. Results from the literature synthesis show that conversion of boreal forest to agriculture can result in up to ~57% of existing soil carbon stocks being lost 30 years after land use change occurs. In addition, a three-way interaction with soil carbon, pH and time-since-land use change is observed where soils become more basic with increasing time-since-land use change, coinciding with declines in soil carbon stocks. This relationship is important when looking at the types of crops communities are interested in growing and the type of agriculture associated with cultivating these crops. Partnered communities have identified crops such as berry bushes, root vegetables, potatoes and corn as crops they are interested in growing. As berry bushes grow in acidic conditions and the other mentioned crops grow in more neutral conditions, site selection and management practices associated with growing these crops in appropriate pH environments will be important for managing soil carbon in new agricultural systems in the NWT. Secondly, we also present community scale soil data assessing variation in soil carbon stocks in relation to potential soil fertility metrics targeted to community identified crops of interest for two communities in the NWT.  We collected 192 soil cores from two communities to determine carbon stocks along gradients of potential agriculture suitability. Our field soil carbon measurements in collaboration with the partnered NWT communities show that land use conversions associated with agricultural development could translate to carbon losses ranging from 2.7-11.4 kg C/m<sup>2</sup> depending on the type of soil, agricultural suitability class, and type of land use change associated with cultivation. These results highlight the importance of managing soil carbon in northern agricultural systems and can be used to emphasize the need for new community scale data relating to agricultural land use change in boreal soils. Through the collection of this data, we hope to provide northern communities with a more robust, community scale product that will allow them to make informed land use decisions relating to the cultivation of crops and the minimization of soil carbon losses while maintaining the culturally important traditional food system.</p>


2019 ◽  
Vol 22 (6) ◽  
pp. 936-945 ◽  
Author(s):  
T. W. Crowther ◽  
C. Riggs ◽  
E. M. Lind ◽  
E. T. Borer ◽  
E. W. Seabloom ◽  
...  

2013 ◽  
Vol 10 (3) ◽  
pp. 1717-1736 ◽  
Author(s):  
K. E. O. Todd-Brown ◽  
J. T. Randerson ◽  
W. M. Post ◽  
F. M. Hoffman ◽  
C. Tarnocai ◽  
...  

Abstract. Stocks of soil organic carbon represent a large component of the carbon cycle that may participate in climate change feedbacks, particularly on decadal and centennial timescales. For Earth system models (ESMs), the ability to accurately represent the global distribution of existing soil carbon stocks is a prerequisite for accurately predicting future carbon–climate feedbacks. We compared soil carbon simulations from 11 model centers to empirical data from the Harmonized World Soil Database (HWSD) and the Northern Circumpolar Soil Carbon Database (NCSCD). Model estimates of global soil carbon stocks ranged from 510 to 3040 Pg C, compared to an estimate of 1260 Pg C (with a 95% confidence interval of 890–1660 Pg C) from the HWSD. Model simulations for the high northern latitudes fell between 60 and 820 Pg C, compared to 500 Pg C (with a 95% confidence interval of 380–620 Pg C) for the NCSCD and 290 Pg C for the HWSD. Global soil carbon varied 5.9 fold across models in response to a 2.6-fold variation in global net primary productivity (NPP) and a 3.6-fold variation in global soil carbon turnover times. Model–data agreement was moderate at the biome level (R2 values ranged from 0.38 to 0.97 with a mean of 0.75); however, the spatial distribution of soil carbon simulated by the ESMs at the 1° scale was not well correlated with the HWSD (Pearson correlation coefficients less than 0.4 and root mean square errors from 9.4 to 20.8 kg C m−2). In northern latitudes where the two data sets overlapped, agreement between the HWSD and the NCSCD was poor (Pearson correlation coefficient 0.33), indicating uncertainty in empirical estimates of soil carbon. We found that a reduced complexity model dependent on NPP and soil temperature explained much of the 1° spatial variation in soil carbon within most ESMs (R2 values between 0.62 and 0.93 for 9 of 11 model centers). However, the same reduced complexity model only explained 10% of the spatial variation in HWSD soil carbon when driven by observations of NPP and temperature, implying that other drivers or processes may be more important in explaining observed soil carbon distributions. The reduced complexity model also showed that differences in simulated soil carbon across ESMs were driven by differences in simulated NPP and the parameterization of soil heterotrophic respiration (inter-model R2 = 0.93), not by structural differences between the models. Overall, our results suggest that despite fair global-scale agreement with observational data and moderate agreement at the biome scale, most ESMs cannot reproduce grid-scale variation in soil carbon and may be missing key processes. Future work should focus on improving the simulation of driving variables for soil carbon stocks and modifying model structures to include additional processes.


2005 ◽  
Vol 11 (1) ◽  
pp. 154-166 ◽  
Author(s):  
Chris Jones ◽  
Claire McConnell ◽  
Kevin Coleman ◽  
Peter Cox ◽  
Peter Falloon ◽  
...  

2012 ◽  
Vol 9 (10) ◽  
pp. 14437-14473 ◽  
Author(s):  
K. E. O. Todd-Brown ◽  
J. T. Randerson ◽  
W. M. Post ◽  
F. M. Hoffman ◽  
C. Tarnocai ◽  
...  

Abstract. Stocks of soil organic carbon represent a large component of the carbon cycle that may participate in climate change feedbacks, particularly on decadal and century scales. For Earth system models (ESMs), the ability to accurately represent the global distribution of existing soil carbon stocks is a prerequisite for predicting future carbon-climate feedbacks. We compared soil carbon predictions from 16 ESMs to empirical data from the Harmonized World Soil Database (HWSD) and Northern Circumpolar Soil Carbon Database (NCSCD). Model estimates of global soil carbon stocks ranged from 510 to 3050 Pg C, compared to an estimate of 890–1660 Pg C from the HWSD. Model predictions for the high latitudes fell between 60 and 800 Pg C, compared to 380–620 Pg C from the NCSCD and 290 Pg C from the HWSD. This 5.3-fold variation in global soil carbon across models compared to a 3.4-fold variation in net primary productivity (NPP) and a 3.8-fold variation in global soil carbon turnover times. The spatial distribution of soil carbon predicted by the ESMs was not well correlated with the HWSD (Pearson's correlations < 0.4, RMSE 9.4 to 22.8 kg C m−2), although model-data agreement generally improved at the biome scale. There was poor agreement between the HWSD and NCSCD datasets in northern latitudes (Pearson's correlation = 0.33), indicating uncertainty in empirical estimates of soil carbon. We found that a reduced complexity model dependent on NPP and soil temperature explained most of the spatial variation in soil carbon predicted by most ESMs (R2 values between 0.73 and 0.93). This result suggests that differences in soil carbon predictions between ESMs are driven primarily by differences in predicted NPP and the parameterization of soil carbon responses to NPP and temperature not by structural differences between the models. Future work should focus on accurately representing these driving variables and modifying model structure to include additional processes.


2018 ◽  
Vol 24 (5) ◽  
pp. 1873-1883 ◽  
Author(s):  
Bertrand Guenet ◽  
Marta Camino-Serrano ◽  
Philippe Ciais ◽  
Marwa Tifafi ◽  
Fabienne Maignan ◽  
...  

Author(s):  
M.V. Marek ◽  
I. Marková ◽  
M. Pavelka ◽  
K. Havránková ◽  
J. Macků ◽  
...  

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