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Ecosystem Traits—Linking Functional Traits to Macroecology
He Nianpeng 1,2,*, Liu Congcong 1,2, Piao Shilong 3, Lawren Sack 4, Xu Li1, Luo Yiqi 5, He Jinsheng3, Han
Xingguo6, Zhou Guangsheng 7, Zhou Xuhui 8, Lin Yi 9, Yu Qiang 10, Liu Shirong11, Sun Wei12, Niu Shuli 1,
Li Shenggong 1, Zhang Jiahui1, Yu Guirui 1,2*
1 Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences
and Natural Resources Research, Chinese Academy of Sciences, Beijing, China2 College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, China3 Department of Ecology, College of Urban and Environmental Science, and Key Laboratory for Earth
Surface Processes of the Ministry of Education, Peking University, Beijing, China4 Department of Ecology and Evolutionary Biology, University of California, Los Angeles, CA, USA5 Department of Microbiology & Plant Biology, University of Oklahoma, Norman, OK, USA
6 State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese
Academy of Sciences, Beijing, China7 Chinese Academy of Meteorological Sciences, Haidian District, Beijing, China8 School of Ecological and Environmental Science, East China Normal University, Shanghai, China9 Institute of Remote Sensing and GIS, School of Earth and Space Sciences, Peking University,
Beijing, China10 National Hulunber Grassland Ecosystem Observation and Research Station, Institute of Agricultural
Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing, China11 Key Laboratory of Forest Ecology and Environment, China’s State Forestry Administration, Institute
of Forest Ecology, Environment and Protection, Chinese Academy of Forestry Beijing, China12 Key Laboratory of Vegetation Ecology, Ministry of Education, Northeast Normal University,
Changchun, China
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Table S1 Examples of ecosystem traits and scaling-up method
Components Specific traits Methods or Instruments Measured levelScaling-up method
(Ecosystem)
Plant traits Leaf Morphology (leaf size, leaf thickness, leaf dry mass, and leaf specific
area)
Balance, Scanner, Photoshop Organ Community weighted method
Stomata (stomatal size, stomatal density, and stomatal area fraction) Scanning electron microscope Organ Community weighted method
Anatomy (Adaxial and abaxial epidermis thickness, leaf thickness, and
spongy tissue thickness)
Electron microscope, MIPS software Organ Community weighted method
Elemental composition (C†, N, P, K, Ca, Mg, S, Al, Mn, Fe, Na, Zn,
Cu, and others)
Elemental Analyzer, Organ Community weighted method
Branch Elemental composition (C, N, P, K, Ca, Mg, S, and others) As above Organ Community weighted method
Trunk Elemental composition (C, N, P, K, Ca, Mg, S, and others) As above Organ Community weighted method
Root Morphology (root diameter, root length, and root volume) Root order method
WinRHIZO software
Organ Community weighted method
Elemental composition (C, N, P, K, Ca, Mg, S, and others) As above Organ Community weighted method
Soil traits Physical property Soil particle size (Sand, silt, and clay) Malvern laser particle size analyzer Ecosystem None
Soil moisture content Oven drying method Ecosystem None
Chemical property Elemental composition (C, N, P, K, Ca, Mg, S, and others) As above Ecosystem None
Soil pH Potentiometric method Ecosystem None
SOC composition Soil organic C As above-mentioned Ecosystem None
Easy-oxidized organic C Potassium permanganate method Ecosystem None
Humic acid C Extraction method Ecosystem None
Humin C Extraction method Ecosystem None
Soil microbe traits Microbe Microbial quantity Phospholipid fatty acid Ecosystem None
Microbial biomass Chloroform fumigation Ecosystem None
Enzyme Soil enzyme activity Enzymatic analyzer Ecosystem None
Metabolic activity Biolog micro-plate technique Ecosystem None
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† C, carbon; N, nitrogen; P, phosphorus; K, potassium; Ca, calcium; Mg, magnesium; S, sulfur; SOC, soil organic carbon
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Figure S1 Some traits can be scaled-up from the leaf to the community level
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Figure S2 Ecosystem traits can be calculated separately from plants, animals (including
insects) and soil microbes at community level and related to environmental factors on
consistent land area
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Plants
Standard, continuous, and consistent in scale
Animals
Insects
Litter
Soil microbe
Soil properties
Ecosystem traits on land areaSo
ilA
tmos
pher
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At t
he c
omm
unity
lev
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Figure S3 Relationship between chlorophyll content at the tree (ChlT, panel A) and the
community (ChlC, B) levels and gross primary productivity (GPP).
ChlT values were calculated as the means of Chl for all tree species in a specific forest
community. ChlC values were calculated based on Chl data at the species level with reference
to leaf specific area and community structure in each forest (Primary data were derived from
Li et al., 2018, Ecological indicator, 85, 383-389).
The GPP data represent 10-year mean values for the nine selected forest types obtained from
Moderate Resolution Imaging Spectroradiometer (MODIS) at a resolution of 1 km × 1 km
(https://modis.gsfc.nasa.gov/data/dataprod/mod17.php).
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Chl-commun (g m-2)
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0 2 4 6 8 10 12
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0 2 4 6 8 10 12ChlT(g m–2)
y = 0.12x + 0.44R² = 0.32**
**
y = 0.13x + 0.47R² = 0.31 **
GPP (kg
C m–
2yr–1)
Chlc(g m–2)
GPP (kg
C m–
2yr–1)
A
B
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Figure S4 Theoretical framework of leaf chlorophyll concentration as a proxy of the
photosynthetic capacity of natural forests.
PSC: photosynthetic capacity; Chl: leaf chlorophyll content; Vcmax: the maximum rate of
carboxylation.
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