Chin J Plant Ecol ›› 2018, Vol. 42 ›› Issue (12): 1131-1144.doi: 10.17521/cjpe.2018.0231

• Research Articles •     Next Articles

Testing parameter sensitivities and uncertainty analysis of Biome-BGC model in simulating carbon and water fluxes in broadleaved-Korean pine forests

LI Xu-Hua,SUN Osbert Jianxin()   

  1. College of Forestry, Beijing Forestry University, Beijing 100083, China
  • Received:2018-09-18 Revised:2018-12-06 Online:2019-04-04 Published:2018-12-20
  • Contact: Osbert Jianxin SUN E-mail:jshe@pku.edu.cn
  • Supported by:
    Supported by the Forestry Research for the Public Benefits of Ministry of Finance of China(201404201)

Abstract:

Aims The emergence and application of ecosystem process models have provided useful tools for studying carbon and water balances of terrestrial ecosystems at large spatiotemporal scales, but the accuracy of model simulations is affected by the parameterization of key variables among many factors. Sensitivity analysis is commonly used to screen the critical parameters that have predominant influences on model simulations. The objective of this study was to identify the critical ecophysiological parameters in Biome-BGC model in simulating annual net primary productivity (NPP) and evapotranspiration (ET) of broadleaved-Korean pine forests in Northeast China.

Methods We simulated carbon and water fluxes of broadleaved-Korean pine forests with the Biome-BGC (version 4.2) at a daily time step based on site- and species-specific parameters. Daily meteorological data for the period 1958-2015 was obtained from the China Meteorological Administration. Initialization parameters such as geographical position, soil depth, and soil texture of the site were obtained from field measurements. Among the 43 ecophysiological parameters represented in the model, 30 were derived either from field measurements or from published data for the study sites in literature, and the default values were used for 13 of the parameters. The modeled forest NPP was compared with the tree-ring width index to test the model’s ability to simulate the inter-annual variations in forest productivity. The modeled NPP and ET were also compared with existing remote sensing products for the period 2000-2014 for validation purpose. Sensitivity analysis was conducted using a variance-based sensitivity analysis method—Extended Fourier Amplitude Sensitivity Test (EFAST) to acquire the first order and total order sensitivity index of the parameters.

Important findings Our locally parameterized Biome-BGC model well simulated the carbon and water fluxes of the broadleaved-Korean pine forests. The uncertainty of simulated NPP is higher for Korean pine trees than for broad-leaved trees, while that of ET was small for both tree types. Both NPP and ET of broad-leaved trees were generally less sensitive to ecophysiological parameters than Korean pine. Leaf carbon to nitrogen ratio, fine root carbon to nitrogen ratio, specific leaf area (SLA), and water interception coef?cient were among the highly sensitive parameters affecting the modeled NPP; while fine root carbon to new leaf carbon allocation, new stem carbon to new leaf carbon allocation and SLA were the highly sensitive parameters influencing ET. In addition, fraction of leaf N in Rubisco, leaf and fine root turnover, ratio of all sided to projected leaf area are also critical parameters affecting the output of Biome-BGC simulations. The degree of sensitivity of the critical parameters varied with species and sites, highlighting the need to adopt local parametrization of Biome-BGC model in simulating regional forest carbon and water fluxes. For other non-sensitive parameters, model default value can be readily used.

Key words: sensitivity analysis, extended fourier amplitude sensitivity test method, net primary production, evapotranspiration, Biome-BGC model

Table 1

Parameterization for Korean pine (PK) and broadleaved species (DB) ecophysiological parameters"

参数
Parameter
符号
Symbol
红松基
准值
Basic value of Korean pine
阔叶树
基准值
Basic value of broadleaf species
单位
Unit
来源
Source
转移生长占生长季的比例 Transfer growth period Tt 0.3 0.2 - Biome-BGC V4.2
凋落过程占生长季的比例 Litterfall period LFG 0.3 0.2 - Biome-BGC V4.2
叶片与细根周转率 Annual leaf and fine root turnover fraction LFRT 0.32 1.0 a-1 Liu et al., 2014
活立木周转率 Annual live wood turnover fraction LWT 0.7 0.7 a-1 Biome-BGC V4.2
整株植物死亡率 Annual whole-plant mortality fraction WPM 0.009 0 0.021 3 a-1 Sang & Li, 1998
火灾死亡率 Annual fire mortality fraction FM 0 0 a-1 Set by us
细根与叶片碳分配比 New fine root C: leaf C FRC:LC 1.2 0.9 - Yao et al., 1986; Mei, 2006
新茎与新叶碳分配比 New stem C: leaf C SC:LC 1.4 2.4 - Li, 1984
活立木与所有木质组织碳分配比 New live wood C: total wood C LWC:TWC 0.379 0.1 - Wu et al., 2017
粗根与新茎碳分配比 New coarse root C: stem C CRC:SC 0.29 0.23 - White et al., 2000
当前生长比例 Current growth proportion CGP 0.5 0.5 - Biome-BGC V4.2
叶片碳氮比 C:N of leaves C:Nleaf 34.30 17.55 kg·kg-1 Measured by us
叶片凋落物碳氮比 C:N of falling leaf litter C:Nlitter 96.5 41.1 kg·kg-1 Li et al., 2008; Mao et al., 2016; Li et al., 2017
细根碳氮比 C:N of ?ne roots C:Nfr 56.4 47.4 kg·kg-1 Liang et al., 2018
活立木碳氮比 C:N of live wood C:Nlw 97.4 97.05 kg·kg-1 Wu et al., 2017
死立木碳氮比 C:N of dead wood C:Ndw 398 212 kg·kg-1 Zhang & Wang, 2010
叶片凋落物易分解物质所占比 Leaf litter labile proportion Llab 0.45 0.53 - Jiang, 2013
叶片凋落物纤维素所占比 Leaf litter cellulose proportion Lcel 0.25 0.22 - Jiang, 2013
叶片凋落物木质素所占比 Leaf litter lignin proportion Llig 0.30 0.25 - Jiang, 2013
细根中易分解物质所占比 Fine root labile proportion FRlab 0.34 0.30 - Biome-BGC V4.2
细根中纤维素所占比 Fine root cellulose proportion FRcel 0.44 0.45 - Biome-BGC V4.2
细根中木质素所占比 Fine root lignin proportion FRlig 0.22 0.25 - Biome-BGC V4.2
死立木中纤维素所占比 Dead wood cellulose proportion DWcel 0.73 0.76 - Zhu, 2013
死立木中木质素所占比 Dead wood lignin proportion DWlig 0.27 0.24 - Zhu, 2013
冠层截留系数 Water interception coef?cient Wint 0.045 0.033 LAI-1·d-1 Wu et al., 2017
冠层消光系数 Light extinction coef?cient k 0.50 0.58 - Zhou et al., 2008
所有叶面积与投影叶面积之比 Ratio of all sided to projected leaf area LAIall:proj 2.6 2.0 - White et al., 2000
冠层平均比叶面积 Average speci?c leaf area SLA 16.4 54.2 m2·kg-1 Measured by us
阴叶与阳叶比叶面积比 Ratio of shade SLA : sunlit SLA SLAshd:sun 2 2 - White et al., 2000
Rubisco酶中叶氮含量 Fraction of leaf N in Rubisco FLNR 0.080 0.075 - Su et al., 2015
最大气孔导度 Maximum stomatal conductance Gsmax 0.006 0 0.006 5 m·s-1 Su et al., 2015
表皮导度 Cuticular conductance Gcut 0.000 06 0.000 01 m·s-1 Su et al., 2015
边界层导度 Boundary layer conductance Gbl 0.09 0.01 m·s-1 White et al., 2000
气孔开始减小时叶片水势 Leaf water potential : start of gs reduction LWPi -0.65 -0.34 MPa White et al., 2000
气孔停止减小时叶片水势 Leaf water potential : completion of gs reduction LWPf -2.5 -2.2 MPa White et al., 2000
气孔开始减小时饱和水汽压差 Vapor pressure deficit : start of gs reduction VPDi 610 1 100 Pa White et al., 2000
气孔停止减小时饱和水汽压差
Vapor pressure deficit : completion of gs reduction
VPDf 3 100 3 600 Pa White et al., 2000

Table 2

Value range of the crucial ecophysiological parameters of Korean pine and broadleaved species used in sensitivity analysis"

参数符号
Parameter
symbol
红松取值范围
Value range of
Korean pine
阔叶树取值范围
Value range of
broadleaved species
单位
Unit
LFRT [0.256, 0.384] a-1
LWT [0.56, 0.84] [0.56, 0.84] a-1
WPM [0.0072, 0.0108] [0.017, 0.0256] a-1
FRC:LC [0.96, 1.44] [0.72, 1.08] -
SC:LC [1.12, 1.68] [1.92, 2.88] -
LWC:TWC [0.303, 0.455] [0.08, 0.12] -
CRC:SC [0.232, 0.348] [0.184, 0.276] -
CGP [0.4, 0.6] [0.4, 0.6] -
C:Nleaf [27.44, 41.16] [14.04, 21.06] kg·kg-1
C:Nlitter [77.2, 115.8] [32.88, 49.32] kg·kg-1
C:Nfr [45.12, 67.68] [37.92, 56.88] kg·kg-1
C:Nlw [77.92, 116.88] [77.64, 116.46] kg·kg-1
C:Ndw [318.4, 477.6] [169.6, 254.4] kg·kg-1
Lcel [0.2, 0.3] [0.176, 0.264] -
Llig [0.24, 0.36] [0.2, 0.3] -
FRcel [0.352, 0.528] [0.36, 0.54] -
FRlig [0.176, 0.264] [0.2, 0.3] -
DWlig [0.216, 0.324] [0.192, 0.288] -
Wint [0.036, 0.054] [0.0264, 0.0396] LAI-1·d-1
k [0.4, 0.6] [0.464, 0.696] -
LAIall:proj [2.08, 3.12] [1.6, 2.4] -
SLA [13.12, 19.68] [43.36, 65.04] m2·kg-1
SLAshd:sun [1.6, 2.4] [1.6, 2.4] -
FLNR [0.064, 0.096] [0.06, 0.09] -
Gsmax [0.0048, 0.0072] [0.0052, 0.0078] m·s-1
Gcut [0.000048, 0.000072] [0.000008, 0.000012] m·s-1
Gbl [0.072, 0.108] [0.008, 0.012] m·s-1
LWPi [-0.78, -0.52] [-0.408, -0.272] MPa
LWPf [-3, -2] [-2.64, -1.76] MPa
VPDi [488, 732] [880, 1320] Pa
VPDf [2480, 3720] [2880, 4320] Pa

Fig. 1

Comparison of modeled net primary productivity (NPP) with tree-ring width index (RWI) during the period 1958-2015. A, Time series of modeled NPP and RWI. B, Correlations between modeled NPP and RWI."

Fig. 2

Comparisons of modeled net primary productivity (NPP) and evapotranspiration (ET) with that of MODIS NPP and ET (mean + SD), respectively. A, NPP. B, ET. Different lowercase letters indicate significant difference between modeled values and MODIS values."

Table 3

Summary statistics of the uncertainty analysis in simulated net primary productivity (NPP) and evapotranspiration (ET)"

红松 Korean pine 阔叶树 Broadleaved species
NPP
(g C·m-2·a-1)
ET
(mm·a-1)
NPP
(g C·m-2·a-1)
ET
(mm·a-1)
平均值
Mean
498.4 677.6 656.1 678.0
标准差
SD
76.9 0.013 63.5 0.19
变异系数
CV
15.4 0.002 9.7 0.03

Fig. 3

Uncertainty analysis of modeled net primary productivity (NPP) of Korean pine (A) and broadleaved species (B)."

Fig. 4

Uncertainty analysis of modeled evapotranspiration (ET) of Korean pine (A) and broadleaved species (B)."

Fig. 5

Sensitivity analysis of the ecophysiological parameters of Korean pine to annual net primary productivity (NPP)(A) and evapotranspiration (ET)(B). See Table 1 for ecophysiologcal parameter symbols."

Fig. 6

Sensitivity analysis of the ecophysiological parameters of broadleaved trees to annual net primary productivity (NPP)(A) and evapotranspiration (ET)(B). See Table 1 for ecophysiologcal parameter symbols."

Table 4

The path coefficients of sensitive parameters on net primary productivity (NPP) and evapotranspiration (ET) of Korean pine"

参数符号
Parameter
symbol
NPP 决定系数R2
Determination coefficient
参数符号
Parameter
symbol
ET 决定系数R2
Determination coefficient
简单相关系数
Correlation coeffficient
直接通径系数
Direct path coefficient
间接通径系数
Indirect path coefficient
简单相关系数Correlation coeffficient 直接通径系数
Direct path
coefficient
间接通径系数Indirect path coefficient
LAIall:proj -0.459 -0.474 0.015 0.901 SLA 0.210 0.168 0.041 0.481
C:Nfr 0.252 0.204 0.047 FRC:LC -0.113 -0.117 0.004
Wint -0.513 -0.476 -0.038 SC:LC -0.051 0.029 -0.080
LFRT 0.422 0.493 -0.071 C:Nleaf -0.018 -0.086 0.069
FLNR 0.117 0.065 0.052 Gcut 0.141 0.204 -0.063
SLA -0.389 -0.446 0.057 Gsmax -0.370 -0.359 -0.011
C:Nleaf 0.035 -0.039 0.074 k 0.429 0.421 0.009
WPM 0.008 -0.045 0.052
C:Nfr 0.308 0.229 0.078
Gbl -0.128 -0.064 -0.064
C:Nlitter 0.114 0.103 0.011

Table 5

The path coefficients of sensitive parameters on net primary productivity (NPP) and evapotranspiration (ET) of broadleaved trees"

参数符号
Parameter
symbol
NPP 决定系数R2
Determination coefficient
参数符号
Parameter
symbol
ET 决定系数R2
Determination coefficient
简单相关系数
Correlation coeffficient
直接通径系数
Direct path coefficient
间接通径系数
Indirect path coefficient
简单相关系数
Correlation coeffficient
直接通径系数
Direct path
coefficient
间接通径系数
Indirect path coefficient
C:Nleaf -0.385 -0.436 0.052 0.749 CGP -0.367 -0.300 -0.067 0.706
SLA -0.526 -0.483 -0.043 SLA 0.416 0.409 0.007
Gsmax -0.334 -0.259 -0.075 FRC:LC -0.288 -0.202 -0.086
C:Nlitter 0.362 0.306 0.055 SC:LC -0.409 -0.321 -0.087
C:Nfr -0.175 -0.117 -0.058 Gbl 0.388 0.329 0.059
SC:LC 0.215 0.195 0.020 FLNR 0.215 0.179 0.036
Wint -0.333 -0.203 -0.130 LWPf -0.271 -0.257 -0.014
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