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Zusammenfassung:
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 (PFTs) is currently lacking. This study integrated observations
from global databases with photosynthesis and respiration models to determine plantfunctional-
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. 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 PFTs, and report
substantial differences in nitrogen allocation across different PFTs. 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.