TY - JOUR
T1 - Quantifying Soil Phosphorus Dynamics
T2 - A Data Assimilation Approach
AU - Hou, Enqing
AU - Lu, Xingjie
AU - Jiang, Lifen
AU - Wen, Dazhi
AU - Luo, Yiqi
N1 - Funding Information:
We thank F. Guo and her colleagues for their data sets used in the present study, Shuang Ma and Zhenggang Du for their discussion, and the Editors and the two anonymous reviewers for their insightful comments that helped to improve this work. This study was financially supported by the National Natural Science Foundation of China (31870464, 31570483, and 41401326), the U.S. Department of Energy (DE-SC00114085), National Science Foundation grant DEB 1655499, U.S. Department of Energy, Terrestrial Ecosystem Sciences grant DE-SC0006982, the subcontracts 4000158404 and 4000161830 from Oak Ridge National Laboratory (ORNL) to the Northern Arizona University, and the Natural Science Foundation of Guangdong Province (2015A030311029). ORNL's work was supported by the U.S. Department of Energy (DOE), Office of Science, Office of Biological and Environmental Research. ORNL is managed by UT-Battelle, LLC, for the U.S. Department of Energy under contract DE-AC05-00OR22725. Data and code used in this study are available at https://figshare.com/articles/A_soil_phosphorus_dynamics_SPD_model/8273816. The authors declare no competing interests. Enqing Hou and Xingjie Lu contributed equally to this work.
Publisher Copyright:
©2019. American Geophysical Union. All Rights Reserved.
PY - 2019
Y1 - 2019
N2 - The dynamics of soil phosphorus (P) control its bioavailability. Yet it remains a challenge to quantify soil P dynamics. Here we developed a soil P dynamics (SPD) model. We then assimilated eight data sets of 426-day changes in Hedley P fractions into the SPD model, to quantify the dynamics of six major P pools in eight soil samples that are representative of a wide type of soils. The performance of our SPD model was better for labile P, secondary mineral P, and occluded P than for nonoccluded organic P (Po) and primary mineral P. All parameters describing soil P dynamics were approximately constrained by the data sets. The average turnover rates were labile P 0.040 g g−1 day−1, nonoccluded Po 0.051 g g−1 day−1, secondary mineral P 0.023 g g−1 day−1, primary mineral P 0.00088 g g−1 day−1, occluded Po 0.0066 g g−1 day−1, and occluded inorganic P 0.0065 g g−1 day−1, in the greenhouse environment studied. Labile P was transferred on average more to nonoccluded Po (transfer coefficient of 0.42) and secondary mineral P (0.38) than to plants (0.20). Soil pH and organic C concentration were the key soil properties regulating the competition for P between plants and soil secondary minerals. The turnover rate of labile P was positively correlated with that of nonoccluded Po and secondary mineral P. The pool size of labile P was most sensitive to its turnover rate. Overall, we suggest data assimilation can contribute significantly to an improved understanding of soil P dynamics.
AB - The dynamics of soil phosphorus (P) control its bioavailability. Yet it remains a challenge to quantify soil P dynamics. Here we developed a soil P dynamics (SPD) model. We then assimilated eight data sets of 426-day changes in Hedley P fractions into the SPD model, to quantify the dynamics of six major P pools in eight soil samples that are representative of a wide type of soils. The performance of our SPD model was better for labile P, secondary mineral P, and occluded P than for nonoccluded organic P (Po) and primary mineral P. All parameters describing soil P dynamics were approximately constrained by the data sets. The average turnover rates were labile P 0.040 g g−1 day−1, nonoccluded Po 0.051 g g−1 day−1, secondary mineral P 0.023 g g−1 day−1, primary mineral P 0.00088 g g−1 day−1, occluded Po 0.0066 g g−1 day−1, and occluded inorganic P 0.0065 g g−1 day−1, in the greenhouse environment studied. Labile P was transferred on average more to nonoccluded Po (transfer coefficient of 0.42) and secondary mineral P (0.38) than to plants (0.20). Soil pH and organic C concentration were the key soil properties regulating the competition for P between plants and soil secondary minerals. The turnover rate of labile P was positively correlated with that of nonoccluded Po and secondary mineral P. The pool size of labile P was most sensitive to its turnover rate. Overall, we suggest data assimilation can contribute significantly to an improved understanding of soil P dynamics.
KW - data assimilation
KW - phosphorus fractionation
KW - soil phosphorus availability
KW - soil phosphorus dynamics
KW - turnover rate
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U2 - 10.1029/2018JG004903
DO - 10.1029/2018JG004903
M3 - Article
AN - SCOPUS:85069724883
SN - 2169-8953
VL - 124
SP - 2159
EP - 2173
JO - Journal of Geophysical Research: Biogeosciences
JF - Journal of Geophysical Research: Biogeosciences
IS - 7
ER -