The Effects of Phosphorus Cycle Dynamics on Carbon Sources and Sinks in the Amazon Region: A Modeling Study Using ELM v1

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Abstract

Tropical forests play a crucial role in the global carbon cycle, accounting for one third of the global net primary productivity and containing about 25% of global vegetation biomass and soil carbon. This is particularly true for tropical forests in the Amazon region, as these comprise approximately 50% of the world's tropical forests. It is therefore important for us to understand and represent the processes that determine the fluxes and storage of carbon in these forests. In this study, we show that the implementation of phosphorus (P) cycle and P limitation in the version 1 of the Energy Exascale Earth System Model land model (ELM v1) improves simulated spatial pattern of wood productivity. The P-enabled ELM v1 is able to capture the declining west-to-east gradient of productivity, consistent with field observations. We also show that by improving the representation of mortality processes using soils data, ELMv1 is able to reproduce the observed spatial pattern of above ground biomass. Our model simulations show that the consideration of P availability leads to a smaller carbon sink associated with CO2 fertilization effect and lower carbon emissions due to land use and land cover change. Our simulations suggest P limitation would significantly reduce the carbon sink associated with CO2 fertilization effects through the 21st century. We conclude that P cycle dynamics affect both sources and sinks of carbon in the Amazon region, and the effects of P limitation would become increasingly important as CO2 increases. Therefore, P limitation must be considered for projecting future carbon dynamics in tropical ecosystems.

Original languageEnglish
Pages (from-to)3686-3698
Number of pages13
JournalJournal of Geophysical Research: Biogeosciences
Volume124
Issue number12
DOIs
StatePublished - Dec 1 2019

Funding

This research was supported as part of the E3SM project, funded by the U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research. R. J. Norby was supported as part of the Next Generation Ecosystem Experiments‐Tropics, funded by the U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research. F. M. Hoffman and M. Xu were supported by the Reducing Uncertainties in Biogeochemical Interactions through Synthesis and Computation Scientific Focus Area, which is sponsored by the Regional and Global Model Analysis Program in the Climate and Environmental Sciences Division of the Office of Biological and Environmental Research in the U.S. Department of Energy Office of Science. The source code, input data, and comp set for the simulations are available at https://github.com/E3SM‐Project/E3SM . The model data used in this study can be downloaded at the website https://portal.nersc.gov/project/acme/xyk/datashare_YangEtAl.tar . This research used resources of the Compute and Data Environment for Science at the Oak Ridge National Laboratory, which is supported by the Office of Science of the U.S. Department of Energy under Contract DE‐AC05‐00OR22725. This research was supported as part of the E3SM project, funded by the U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research. R. J. Norby was supported as part of the Next Generation Ecosystem Experiments-Tropics, funded by the U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research. F. M. Hoffman and M. Xu were supported by the Reducing Uncertainties in Biogeochemical Interactions through Synthesis and Computation Scientific Focus Area, which is sponsored by the Regional and Global Model Analysis Program in the Climate and Environmental Sciences Division of the Office of Biological and Environmental Research in the U.S. Department of Energy Office of Science. The source code, input data, and comp set for the simulations are available at https://github.com/E3SM-Project/E3SM. The model data used in this study can be downloaded at the website https://portal.nersc.gov/project/acme/xyk/datashare_YangEtAl.tar. This research used resources of the Compute and Data Environment for Science at the Oak Ridge National Laboratory, which is supported by the Office of Science of the U.S. Department of Energy under Contract DE-AC05-00OR22725.

FundersFunder number
Compute and Data Environment for Science
Office of Biological and Environmental Research
U.S. Department of Energy
Office of ScienceDE‐AC05‐00OR22725
Biological and Environmental Research
Oak Ridge National Laboratory
Savannah River Operations Office, U.S. Department of Energy

    Keywords

    • Amazon
    • Carbon sink
    • Phosphorus

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