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Title: Assessing Impacts of Plant Stoichiometric Traits on Terrestrial Ecosystem Carbon Accumulation Using the E3SM Land Model

Abstract

Carbon (C) enters into the terrestrial ecosystems via photosynthesis and cycles through the system together with other essential nutrients (i.e., nitrogen [N] and phosphorus [P]). Such a strong coupling of C, N, and P leads to the theoretical prediction that limited nutrient availability will limit photosynthesis rate, plant growth, and future terrestrial C dynamics. However, the lack of reliable information about plant tissue stoichiometric constraints remains a challenge for quantifying nutrient limitations on projected global C cycling. In this study, we harmonized observed plant tissue C:N:P stoichiometry from more than 6,000 plant species with the commonly used plant functional type framework in global land models. Using observed C:N:P stoichiometry and the flexibility of these ratios as emergent plant traits, we show that observationally constrained fixed plant stoichiometry does not improve model estimates of present-day C dynamics compared with unconstrained stoichiometry. However, adopting stoichiometric flexibility significantly improves model predictions of C fluxes and stocks. The 21st century simulations with RCP8.5 CO2 concentrations show that stoichiometric flexibility, rather than baseline stoichiometric ratios, is the dominant controller of plant productivity and ecosystem C accumulation in modeled responses to CO2 fertilization. The enhanced nutrient limitations and plant P use efficiency mainly explain this result. Thismore » study is consistent with the previous consensus that nutrient availability will limit xfuture land carbon sequestration but challenges the idea that imbalances between C and nutrient supplies and fixed stoichiometry limit future land C sinks. We show here that it is necessary to represent nutrient stoichiometric flexibility in models to accurately project future terrestrial ecosystem carbon sequestration.« less

Authors:
ORCiD logo [1]; ORCiD logo [1]; ORCiD logo [2];  [3]
  1. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
  2. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
  3. Max Planck Inst. for Biogeochemistry, Jena (Germany)
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER)
OSTI Identifier:
1615221
Grant/Contract Number:  
AC05-00OR22725; AC02-05CH11231
Resource Type:
Accepted Manuscript
Journal Name:
Journal of Advances in Modeling Earth Systems
Additional Journal Information:
Journal Volume: 12; Journal Issue: 4; Journal ID: ISSN 1942-2466
Publisher:
American Geophysical Union (AGU)
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; carbon‐nutrient interactions; earth system land model (E3SM); future ecosystem carbon accumulation

Citation Formats

Zhu, Qing, Riley, William J., Iversen, Colleen M., and Kattge, Jens. Assessing Impacts of Plant Stoichiometric Traits on Terrestrial Ecosystem Carbon Accumulation Using the E3SM Land Model. United States: N. p., 2020. Web. doi:10.1029/2019MS001841.
Zhu, Qing, Riley, William J., Iversen, Colleen M., & Kattge, Jens. Assessing Impacts of Plant Stoichiometric Traits on Terrestrial Ecosystem Carbon Accumulation Using the E3SM Land Model. United States. doi:https://doi.org/10.1029/2019MS001841
Zhu, Qing, Riley, William J., Iversen, Colleen M., and Kattge, Jens. Fri . "Assessing Impacts of Plant Stoichiometric Traits on Terrestrial Ecosystem Carbon Accumulation Using the E3SM Land Model". United States. doi:https://doi.org/10.1029/2019MS001841. https://www.osti.gov/servlets/purl/1615221.
@article{osti_1615221,
title = {Assessing Impacts of Plant Stoichiometric Traits on Terrestrial Ecosystem Carbon Accumulation Using the E3SM Land Model},
author = {Zhu, Qing and Riley, William J. and Iversen, Colleen M. and Kattge, Jens},
abstractNote = {Carbon (C) enters into the terrestrial ecosystems via photosynthesis and cycles through the system together with other essential nutrients (i.e., nitrogen [N] and phosphorus [P]). Such a strong coupling of C, N, and P leads to the theoretical prediction that limited nutrient availability will limit photosynthesis rate, plant growth, and future terrestrial C dynamics. However, the lack of reliable information about plant tissue stoichiometric constraints remains a challenge for quantifying nutrient limitations on projected global C cycling. In this study, we harmonized observed plant tissue C:N:P stoichiometry from more than 6,000 plant species with the commonly used plant functional type framework in global land models. Using observed C:N:P stoichiometry and the flexibility of these ratios as emergent plant traits, we show that observationally constrained fixed plant stoichiometry does not improve model estimates of present-day C dynamics compared with unconstrained stoichiometry. However, adopting stoichiometric flexibility significantly improves model predictions of C fluxes and stocks. The 21st century simulations with RCP8.5 CO2 concentrations show that stoichiometric flexibility, rather than baseline stoichiometric ratios, is the dominant controller of plant productivity and ecosystem C accumulation in modeled responses to CO2 fertilization. The enhanced nutrient limitations and plant P use efficiency mainly explain this result. This study is consistent with the previous consensus that nutrient availability will limit xfuture land carbon sequestration but challenges the idea that imbalances between C and nutrient supplies and fixed stoichiometry limit future land C sinks. We show here that it is necessary to represent nutrient stoichiometric flexibility in models to accurately project future terrestrial ecosystem carbon sequestration.},
doi = {10.1029/2019MS001841},
journal = {Journal of Advances in Modeling Earth Systems},
number = 4,
volume = 12,
place = {United States},
year = {2020},
month = {3}
}

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