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Effects of soil data and simulation unit resolution on quantifying changes of soil organic carbon at regional scale with a biogeochemical process model.

Zhang L, Yu D, Shi X, Xu S, Xing S, Zhao Y - PLoS ONE (2014)

Bottom Line: Results project that from 1982 to 2000, total SOC change in the top layer (0-30 cm) of the 2.3 M ha of paddy soil in the Tai-Lake region was +1.48 Tg C, -3.99 Tg C and -15.38 Tg C based on P5, C5 and C14 databases, respectively.With the total SOC change as modeled with P5 inputs as the baseline, which is the advantages of using detailed, polygon-based soil dataset, the relative deviation of C5 and C14 were 368% and 1126%, respectively.The results also indicate that improving the framework of DNDC is essential in creating accurate models of the soil carbon cycle.

View Article: PubMed Central - PubMed

Affiliation: College of Resource and Environment, Fujian Agriculture and Forestry University, Fuzhou, China ; State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing, China.

ABSTRACT
Soil organic carbon (SOC) models were often applied to regions with high heterogeneity, but limited spatially differentiated soil information and simulation unit resolution. This study, carried out in the Tai-Lake region of China, defined the uncertainty derived from application of the DeNitrification-DeComposition (DNDC) biogeochemical model in an area with heterogeneous soil properties and different simulation units. Three different resolution soil attribute databases, a polygonal capture of mapping units at 1:50,000 (P5), a county-based database of 1:50,000 (C5) and county-based database of 1:14,000,000 (C14), were used as inputs for regional DNDC simulation. The P5 and C5 databases were combined with the 1:50,000 digital soil map, which is the most detailed soil database for the Tai-Lake region. The C14 database was combined with 1:14,000,000 digital soil map, which is a coarse database and is often used for modeling at a national or regional scale in China. The soil polygons of P5 database and county boundaries of C5 and C14 databases were used as basic simulation units. Results project that from 1982 to 2000, total SOC change in the top layer (0-30 cm) of the 2.3 M ha of paddy soil in the Tai-Lake region was +1.48 Tg C, -3.99 Tg C and -15.38 Tg C based on P5, C5 and C14 databases, respectively. With the total SOC change as modeled with P5 inputs as the baseline, which is the advantages of using detailed, polygon-based soil dataset, the relative deviation of C5 and C14 were 368% and 1126%, respectively. The comparison illustrates that DNDC simulation is strongly influenced by choice of fundamental geographic resolution as well as input soil attribute detail. The results also indicate that improving the framework of DNDC is essential in creating accurate models of the soil carbon cycle.

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Spatial distribution of average annual SOC change modeled with P5, C5 and C14 in the Tai-Lake region, China (a: P5, b: c5, and c:C14).
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pone-0088622-g007: Spatial distribution of average annual SOC change modeled with P5, C5 and C14 in the Tai-Lake region, China (a: P5, b: c5, and c:C14).

Mentions: As Table 3 illustrated, initial SOC content was the most sensitive parameter controlling SOC change among all soil factors in P5 and C5 [20], [22]. The average initial SOC value of P5 and C5 were 15 g kg−1 and 16 g kg−1 for the entire Tai-Lake region, respectively. Furthermore, the average initial SOC content sourced from P5 for 24 counties was lower than that from C5, while the average clay content sourced from P5 for 24 counties was also higher than that from C5. Many previous studies showed that soils with lower initial organic carbon and higher clay content tended to sequester C [20], [22], [35]. The high SOC sequestration rate (34 kg C ha−1 yr −1) was thus associated with P5 (Fig. 7a). Conversely, the high SOC losses rate (-91 kg C ha−1 yr−1) was associated with C5 (Fig. 7b). The SOC losses rate (-349 kg C ha−1 yr−1) in C14 was the highest in the three resolution databases (Fig. 7c). Table 3 demonstrates that pH and initial SOC content are the most sensitive parameters controlling SOC change among all soil factors in C14. The average initial SOC value (22 g kg−1) of C14 was significantly higher than that of P5 (15 g kg−1) and C5 (16 g kg−1) for the entire Tai-Lake region. In addition, the average pH value of C14 for 34 counties was close to neutral (6.5–7.5), and the average initial SOC contents of C14 for 28 counties were higher than 20 g kg−1. Some studies showed that soils with neutral pH value and higher organic carbon content were favorable for CO2 production by providing more substrates and better living environment for microbes [22], [56].


Effects of soil data and simulation unit resolution on quantifying changes of soil organic carbon at regional scale with a biogeochemical process model.

Zhang L, Yu D, Shi X, Xu S, Xing S, Zhao Y - PLoS ONE (2014)

Spatial distribution of average annual SOC change modeled with P5, C5 and C14 in the Tai-Lake region, China (a: P5, b: c5, and c:C14).
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3921222&req=5

pone-0088622-g007: Spatial distribution of average annual SOC change modeled with P5, C5 and C14 in the Tai-Lake region, China (a: P5, b: c5, and c:C14).
Mentions: As Table 3 illustrated, initial SOC content was the most sensitive parameter controlling SOC change among all soil factors in P5 and C5 [20], [22]. The average initial SOC value of P5 and C5 were 15 g kg−1 and 16 g kg−1 for the entire Tai-Lake region, respectively. Furthermore, the average initial SOC content sourced from P5 for 24 counties was lower than that from C5, while the average clay content sourced from P5 for 24 counties was also higher than that from C5. Many previous studies showed that soils with lower initial organic carbon and higher clay content tended to sequester C [20], [22], [35]. The high SOC sequestration rate (34 kg C ha−1 yr −1) was thus associated with P5 (Fig. 7a). Conversely, the high SOC losses rate (-91 kg C ha−1 yr−1) was associated with C5 (Fig. 7b). The SOC losses rate (-349 kg C ha−1 yr−1) in C14 was the highest in the three resolution databases (Fig. 7c). Table 3 demonstrates that pH and initial SOC content are the most sensitive parameters controlling SOC change among all soil factors in C14. The average initial SOC value (22 g kg−1) of C14 was significantly higher than that of P5 (15 g kg−1) and C5 (16 g kg−1) for the entire Tai-Lake region. In addition, the average pH value of C14 for 34 counties was close to neutral (6.5–7.5), and the average initial SOC contents of C14 for 28 counties were higher than 20 g kg−1. Some studies showed that soils with neutral pH value and higher organic carbon content were favorable for CO2 production by providing more substrates and better living environment for microbes [22], [56].

Bottom Line: Results project that from 1982 to 2000, total SOC change in the top layer (0-30 cm) of the 2.3 M ha of paddy soil in the Tai-Lake region was +1.48 Tg C, -3.99 Tg C and -15.38 Tg C based on P5, C5 and C14 databases, respectively.With the total SOC change as modeled with P5 inputs as the baseline, which is the advantages of using detailed, polygon-based soil dataset, the relative deviation of C5 and C14 were 368% and 1126%, respectively.The results also indicate that improving the framework of DNDC is essential in creating accurate models of the soil carbon cycle.

View Article: PubMed Central - PubMed

Affiliation: College of Resource and Environment, Fujian Agriculture and Forestry University, Fuzhou, China ; State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing, China.

ABSTRACT
Soil organic carbon (SOC) models were often applied to regions with high heterogeneity, but limited spatially differentiated soil information and simulation unit resolution. This study, carried out in the Tai-Lake region of China, defined the uncertainty derived from application of the DeNitrification-DeComposition (DNDC) biogeochemical model in an area with heterogeneous soil properties and different simulation units. Three different resolution soil attribute databases, a polygonal capture of mapping units at 1:50,000 (P5), a county-based database of 1:50,000 (C5) and county-based database of 1:14,000,000 (C14), were used as inputs for regional DNDC simulation. The P5 and C5 databases were combined with the 1:50,000 digital soil map, which is the most detailed soil database for the Tai-Lake region. The C14 database was combined with 1:14,000,000 digital soil map, which is a coarse database and is often used for modeling at a national or regional scale in China. The soil polygons of P5 database and county boundaries of C5 and C14 databases were used as basic simulation units. Results project that from 1982 to 2000, total SOC change in the top layer (0-30 cm) of the 2.3 M ha of paddy soil in the Tai-Lake region was +1.48 Tg C, -3.99 Tg C and -15.38 Tg C based on P5, C5 and C14 databases, respectively. With the total SOC change as modeled with P5 inputs as the baseline, which is the advantages of using detailed, polygon-based soil dataset, the relative deviation of C5 and C14 were 368% and 1126%, respectively. The comparison illustrates that DNDC simulation is strongly influenced by choice of fundamental geographic resolution as well as input soil attribute detail. The results also indicate that improving the framework of DNDC is essential in creating accurate models of the soil carbon cycle.

Show MeSH
Related in: MedlinePlus