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Title: A global trait-based approach to estimate leaf nitrogen functional allocation from observations

Nitrogen is one of the most important nutrients for plant growth and a major constituent of proteins that regulate photosynthetic and respiratory processes. However, a comprehensive global analysis of nitrogen allocation in leaves for major processes with respect to different plant functional types is currently lacking. This study integrated observations from global databases with photosynthesis and respiration models to determine plant-functional-type-specific allocation patterns of leaf nitrogen for photosynthesis (Rubisco, electron transport, light absorption) and respiration (growth and maintenance), and by difference from observed total leaf nitrogen, an unexplained “residual” nitrogen pool. Based on our analysis, crops partition the largest fraction of nitrogen to photosynthesis (57%) and respiration (5%) followed by herbaceous plants (44% and 4%). Tropical broadleaf evergreen trees partition the least to photosynthesis (25%) and respiration (2%) followed by needle-leaved evergreen trees (28% and 3%). In trees (especially needle-leaved evergreen and tropical broadleaf evergreen trees) a large fraction (70% and 73% respectively) of nitrogen was not explained by photosynthetic or respiratory functions. Compared to crops and herbaceous plants, this large residual pool is hypothesized to emerge from larger investments in cell wall proteins, lipids, amino acids, nucleic acid, CO2 fixation proteins (other than Rubisco), secondary compounds, and other proteins.more » Our estimates are different from previous studies due to differences in methodology and assumptions used in deriving nitrogen allocation estimates. Unlike previous studies, we integrate and infer nitrogen allocation estimates across multiple plant functional types, and report substantial differences in nitrogen allocation across different plant functional types. Furthermore, the resulting pattern of nitrogen allocation provides insights on mechanisms that operate at a cellular scale within leaves, and can be integrated with ecosystem models to derive emergent properties of ecosystem productivity at local, regional, and global scales.« less
 [1] ;  [1] ;  [1] ;  [2] ;  [3] ;  [4] ;  [5]
  1. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
  2. Max Planck Institute for Biogeochemistry, Jena (Germany); German Centre for Integrative Biodiversity Research (iDiv), Halle-Jena-Leipzig (Germany)
  3. Brookhaven National Lab. (BNL), Upton, NY (United States)
  4. Univ. of Minnesota, St. Paul, MN (United States); Univ. of Western Sydney, Penrith, NSW (Australia)
  5. Macquarie Univ., NSW (Australia)
Publication Date:
Report Number(s):
Journal ID: ISSN 1051-0761; R&D Project: 80888; YN1901000
Grant/Contract Number:
SC00112704; Contract No. DE-AC02-05CH11231
Accepted Manuscript
Journal Name:
Ecological Applications
Additional Journal Information:
Journal Volume: 27; Journal Issue: 5; Journal ID: ISSN 1051-0761
Ecological Society of America
Research Org:
Brookhaven National Laboratory (BNL), Upton, NY (United States)
Sponsoring Org:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23)
Country of Publication:
United States
OSTI Identifier:
Alternate Identifier(s):
OSTI ID: 1401293