Data-driven ENZYme (DENZY) model represents soil organic carbon dynamics in forests impacted by nitrogen deposition

被引:10
作者
Chen, Yizhao [1 ,2 ,3 ]
Chen, Ji [4 ]
Luo, Yiqi [2 ,3 ,5 ,6 ]
机构
[1] Nanjing Forestry Univ, Joint Innovat Ctr Modern Forestry Studies, Coll Biol & Environm, Nanjing 210037, Jiangsu, Peoples R China
[2] Tsinghua Univ, Minist Educ, Key Lab Earth Syst Modeling, Beijing 100084, Peoples R China
[3] Tsinghua Univ, Dept Earth Syst Sci, Beijing 100084, Peoples R China
[4] Aarhus Univ, Dept Agroecol, Ctr Circular Bioecon, DK-8830 Tjele, Denmark
[5] No Arizona Univ, Ctr Ecosyst Sci & Soc, Flagstaff, AZ 86011 USA
[6] No Arizona Univ, Dept Biol Sci, Flagstaff, AZ 86011 USA
基金
国家重点研发计划; 中国博士后科学基金; 中国国家自然科学基金;
关键词
Soil organic carbon modelling; Meta-analysis; TECO; Ligninase activity; N deposition; Data driven modelling; TERRESTRIAL ECOSYSTEM MODEL; LITTER DECOMPOSITION; BACTERIAL-POPULATIONS; MICROBIAL MODELS; RESPONSES; CO2; STOICHIOMETRY; MATTER; SEQUESTRATION; TEMPERATURE;
D O I
10.1016/j.soilbio.2019.107575
中图分类号
S15 [土壤学];
学科分类号
0903 ; 090301 ;
摘要
Soil microorganisms participate in almost all soil organic carbon (SOC) transformations, but they are not represented explicitly in the current generation of earth system models. This study used a data-driven approach to incorporate extracellular enzyme activity into the Terrestrial ECOsystem (TECO) model, and the updated version was named the Data-driven ENZYme (DENZY) model. DENZY is based on results from an extensive data synthesis, which show that the CN ratio is positively correlated with ligninase activity (R-2 = 0.50). The latter is inversely correlated to soil organic carbon storage. The DENZY model was parameterized using the revise database to information from a recent meta-analysis and tested for its ability to simulate SOC dynamics at Duke Forest (North Carolina, USA) from 1996 to 2007. DENZY can well simulate the observed negative relationship between ligninase activity and SOC under N deposition conditions (R-2 ranges from 0.61 to 0.89). Moreover, outputs from DENZY better matched the observed SOC than its prototype model with the same parameterization. This study provides a simple and straightforward approach to effectively use real-world observations to improve SOC projections in terrestrial biogeochemical models.
引用
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页数:9
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