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Title: Quantifying Soil Phosphorus Dynamics: A Data Assimilation Approach

Journal Article · · Journal of Geophysical Research. Biogeosciences
DOI:https://doi.org/10.1029/2018jg004903· OSTI ID:1610919
ORCiD logo [1]; ORCiD logo [2]; ORCiD logo [3];  [4]; ORCiD logo [3]
  1. Chinese Academy of Sciences, Guangzhou (China). South China Botanical Garden; Northern Arizona Univ., Flagstaff, AZ (United States)
  2. Northern Arizona Univ., Flagstaff, AZ (United States); Sun Yat-Sen Univ., Guangzhou (China)
  3. Northern Arizona Univ., Flagstaff, AZ (United States)
  4. Chinese Academy of Sciences, Guangzhou (China). South China Botanical Garden

The dynamics of soil phosphorus (P) control its bioavailability. Yet it remains a challenge to quantify soil P dynamics. In this work 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.

Research Organization:
Univ. of Florida, Gainesville, FL (United States); Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
Sponsoring Organization:
National Natural Science Foundation of China (NSFC); National Science Foundation (NSF); Natural Science Foundation of Guangdong Province; USDOE Office of Science (SC), Biological and Environmental Research (BER)
Grant/Contract Number:
SC0006982; AC05-00OR22725; SC0014085; DEB 1655499
OSTI ID:
1610919
Alternate ID(s):
OSTI ID: 1543154
Journal Information:
Journal of Geophysical Research. Biogeosciences, Vol. 124, Issue 7; ISSN 2169-8953
Publisher:
American Geophysical UnionCopyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 17 works
Citation information provided by
Web of Science

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Cited By (1)


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