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Title: Root traits explain observed tundra vegetation nitrogen uptake patterns: Implications for trait-based land models

Abstract

Ongoing climate warming will likely perturb vertical distributions of nitrogen availability in tundra soils through enhancing nitrogen mineralization and releasing previously inaccessible nitrogen from frozen permafrost soil. But, arctic tundra responses to such changes are uncertain, because of a lack of vertically explicit nitrogen tracer experiments and untested hypotheses of root nitrogen uptake under the stress of microbial competition implemented in land models. We conducted a vertically explicit 15N tracer experiment for three dominant tundra species to quantify plant N uptake profiles. Then we applied a nutrient competition model (N-COM), which is being integrated into the ACME Land Model, to explain the observations. Observations using an 15N tracer showed that plant N uptake profiles were not consistently related to root biomass density profiles, which challenges the prevailing hypothesis that root density always exerts first-order control on N uptake. By considering essential root traits (e.g., biomass distribution and nutrient uptake kinetics) with an appropriate plant-microbe nutrient competition framework, our model reasonably reproduced the observed patterns of plant N uptake. Additionally, we show that previously applied nutrient competition hypotheses in Earth System Land Models fail to explain the diverse plant N uptake profiles we observed. These results cast doubt on current climate-scalemore » model predictions of arctic plant responses to elevated nitrogen supply under a changing climate and highlight the importance of considering essential root traits in large-scale land models. Finally, we provided suggestions and a short synthesis of data availability for future trait-based land model development.« less

Authors:
ORCiD logo [1]; ORCiD logo [2]; ORCiD logo [1]; ORCiD logo [3]; ORCiD logo [2]
  1. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Climate Sciences Dept.
  2. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Climate Change Science Inst. and Environmental Sciences Division
  3. Colorado State Univ., Fort Collins, CO (United States). Ecology and Dept. of Biology
Publication Date:
Research Org.:
Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States); Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER)
OSTI Identifier:
1474984
Alternate Identifier(s):
OSTI ID: 1362201; OSTI ID: 1402246
Grant/Contract Number:  
AC02-05CH11231; AC05-00OR22725
Resource Type:
Accepted Manuscript
Journal Name:
Journal of Geophysical Research. Biogeosciences
Additional Journal Information:
Journal Volume: 121; Journal Issue: 12; Journal ID: ISSN 2169-8953
Publisher:
American Geophysical Union
Country of Publication:
United States
Language:
English
Subject:
58 GEOSCIENCES; 15N tracer; Carex aquatilis; Eriophorum angustifolium; plant-soil competition; root nitrogen uptake; Salix rotundifolia; trait-based modeling; tundra

Citation Formats

Zhu, Qing, Iversen, Colleen M., Riley, William J., Slette, Ingrid J., and Vander Stel, Holly M. Root traits explain observed tundra vegetation nitrogen uptake patterns: Implications for trait-based land models. United States: N. p., 2016. Web. doi:10.1002/2016JG003554.
Zhu, Qing, Iversen, Colleen M., Riley, William J., Slette, Ingrid J., & Vander Stel, Holly M. Root traits explain observed tundra vegetation nitrogen uptake patterns: Implications for trait-based land models. United States. https://doi.org/10.1002/2016JG003554
Zhu, Qing, Iversen, Colleen M., Riley, William J., Slette, Ingrid J., and Vander Stel, Holly M. Fri . "Root traits explain observed tundra vegetation nitrogen uptake patterns: Implications for trait-based land models". United States. https://doi.org/10.1002/2016JG003554. https://www.osti.gov/servlets/purl/1474984.
@article{osti_1474984,
title = {Root traits explain observed tundra vegetation nitrogen uptake patterns: Implications for trait-based land models},
author = {Zhu, Qing and Iversen, Colleen M. and Riley, William J. and Slette, Ingrid J. and Vander Stel, Holly M.},
abstractNote = {Ongoing climate warming will likely perturb vertical distributions of nitrogen availability in tundra soils through enhancing nitrogen mineralization and releasing previously inaccessible nitrogen from frozen permafrost soil. But, arctic tundra responses to such changes are uncertain, because of a lack of vertically explicit nitrogen tracer experiments and untested hypotheses of root nitrogen uptake under the stress of microbial competition implemented in land models. We conducted a vertically explicit 15N tracer experiment for three dominant tundra species to quantify plant N uptake profiles. Then we applied a nutrient competition model (N-COM), which is being integrated into the ACME Land Model, to explain the observations. Observations using an 15N tracer showed that plant N uptake profiles were not consistently related to root biomass density profiles, which challenges the prevailing hypothesis that root density always exerts first-order control on N uptake. By considering essential root traits (e.g., biomass distribution and nutrient uptake kinetics) with an appropriate plant-microbe nutrient competition framework, our model reasonably reproduced the observed patterns of plant N uptake. Additionally, we show that previously applied nutrient competition hypotheses in Earth System Land Models fail to explain the diverse plant N uptake profiles we observed. These results cast doubt on current climate-scale model predictions of arctic plant responses to elevated nitrogen supply under a changing climate and highlight the importance of considering essential root traits in large-scale land models. Finally, we provided suggestions and a short synthesis of data availability for future trait-based land model development.},
doi = {10.1002/2016JG003554},
journal = {Journal of Geophysical Research. Biogeosciences},
number = 12,
volume = 121,
place = {United States},
year = {Fri Dec 23 00:00:00 EST 2016},
month = {Fri Dec 23 00:00:00 EST 2016}
}

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