Simulation of forest net primary production and the effects of fire disturbance in Northeast China

doi:10.17521/cjpe.2015.0031

Abstract

Abstract: Aims

Forest net primary production (NPP) is an important parameter on measuring the terrestrial carbon source/sink. More accurately estimating NPP of forest ecosystems is the focus of carbon cycle. Our objective was to explore how to use remote sensing process model to simulate NPP of the northeast forest more accurately, and what impacts of forest fire disturbance have on NPP.

Methods

In this study, based on remote sensing data and meteorological data, Boreal Ecosystem Productivity Simulator (BEPS) model was used to simulate NPP of the northeast forest in 2003; The result of BEPS model acted as the reference year data of Integrated Terrestrial Ecosystem C-budget (InTEC) model to simulate NPP from 1901 to 2008 of the northeast forest. Then forest fire disturbance data was incorporated in the InTEC model to simulate NPP from 1966 to 2008 of Daxing’an Mountain.

Important findings

The average value of NPP of the northeast forest was only 278.8 g C·m^-2·a^-1 in 1901. In 1950, average NPP had reached to 338.5 g C·m^-2·a^-1. The average NPP of the northeast forest in 2008 was 378.4 g C·m^-2·a^-1; Substantial increase was evidenced for Daxing’an Mountain, Xiaoxing’an Mountain and Changbai Mountain with 200 g C·m^-2·a^-1to 300 g C·m^-2·a^-1 increase for Changbai Mountain. The average and total value of NPP of Liaoning in 2008 was relatively low, but was still 70 percent higher than that in 1901. Moderate and large fires did not drastically reduce NPP, with less than 10 percent reduction during the year of fire occurrence. In the following years, NPP recovered quickly and maintained at a high level. NPP reduced substantially in each of the four years with burned area exceeding 100000 hm² in Daxing’an Mountain.

Key words: Boreal Ecosystem Productivity Simulator model, carbon cycle, Daxing’an Mountain, forest fire disturbance, Integrated Terrestrial Ecosystem C-budget model, net primary productivity, northeast forest

LI Ming-Ze,WANG Bin,FAN Wen-Yi,ZHAO Dan-Dan. Simulation of forest net primary production and the effects of fire disturbance in Northeast China[J]. Chin J Plan Ecolo, 2015, 39(4): 322-332.

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URL: https://www.plant-ecology.com/EN/10.17521/cjpe.2015.0031

https://www.plant-ecology.com/EN/Y2015/V39/I4/322

Figures/Tables 14

Table 1 Boreal Ecosystem Productivity Simulator (BEPS) model parameters

符号 Symbol	单位 Unit	含义 Description	针叶 Conifers	阔叶 Boreal	针阔混交 Deciduous species	唯一值 Unique value	获取方法 Acquisition Method
Ω	μmol·m^-2·s^-1	叶片聚集度指数 Foliage clumping	0.5	0.7	0.9	-	实测 Measure
V_m,25	μmol·m^-2·s^-1	25 ℃时最大羧化速率 Maximum carboxylation rate at 25 ℃	25	50	50	-	迭代 Iteration
M_leaf	kg C·m^-2	叶片含碳量 Leaf carbon content	-	-	-	0.1	实测 Measure
M_stem	kg C·m^-2	干中含碳量 Stem carbon content	-	-	-	5.00	实测 Measure
M_root	kg C·m^-2	根中含碳量 Root carbon content	-	-	-	1.5	实测 Measure

Table 2 Integrated Terrestrial Ecosystem C-budget (InTEC ) model parameters

符号 Symbol	单位 Unit	含义 Description	针叶 Conifers	阔叶 Boreal	针阔混交 Deciduous species	唯一值 Unique value	获取方法 Acquisition Method
SLA	m²·m^-2	比叶面积参数 Parameter of specific leaf area	70.0	31.5	53.3	-	迭代 Iteration
V_cmax	μmol·m^-2·s^-1	最大羧化速率 Maximum carboxylation rate	33	60	40	-	迭代 Iteration
QN_fix	-	氮固化速率对温度的敏感度 Sensitivity of N fixation rate on temperature	-	-	-	2.3	迭代 Iteration
a_jm	-	电子传输对温度的敏感度 Sensitivity of electron transport on temperature	-	-	-	1.8	实测 Measure
a_vm	-	酶活性对温度的敏感度 Sensitivity of rubisco activity on temperature	-	-	-	2.4	实测 Measure
N_l	g N·m^-2	真实叶片氮含量 Actual leaf nitrogen content	-	-	-	1.2	实测 Measure

Fig. 1 Comparison of the average leaf area index (LAI) values before smooth with after smooth.

Fig. 2 Northeast forest cover type map. A, Betula platyphylla and Populus nigra; B, Betula platyphylla; C, Coniferous forest; D, Mixed forest; E, Broadleaved forest; F, Tilia amurensis; G, Populus nigra; H, Pinus koraiensis and Quercus mongolica; I, Pinus koraiensis and Tilia amurensis; J, Quercus mongolica; K, Larix gmelinii; L, Quercus mongolica and Betula platyphylla; M, Populus davidiana; N, Larix gmelinii and Betula platyphylla; O, Larix gmelinii and Quercus mongolica; P, Pinus sylvestris; Q, Betula platyphylla and Populus davidiana.

Fig. 3 Northeast forest age distribution map.

Fig. 4 Spatial distribution of net primary production (NPP) in 2003 simulated by Boreal Ecosystem Productivity Simulator (BEPS).

Table 3 Net primary production (NPP) and total NPP for different forest types in 2003

森林类型 Forest types	NPP平均值 Average value of NPP (g C·m^-2·a^-1)	NPP总量 Total NPP (g C·a^-1)
针叶林 Coniferous forest	413.1	1.8 × 10¹³
阔叶林 Broadleaved forest	382.8	3.3 × 10¹³
针阔混交林 Mixed forest	380.7	1.7 × 10¹³

Fig. 5 Average value of net primary production (NPP) simulated by Integrated Terrestrial Ecosystem C-budget (InTEC) model from 1901 to 2008.

Fig. 6 Spatial distribution of net primary production (NPP) in Northeastern China. A, 1901. B, 1950. C, 2008.

Fig. 7 Average value of net primary production (NPP) from1966 to 2008.

Fig. 8 Correlation between net primary production (NPP) calculated by plot measurement and NPP simulated by Boreal Ecosystem Productivity Simulator (BEPS) model and calculated by plots.

Fig. 9 Relationship between net primary production (NPP) from Moderate Resolution Imaging Spectroradiometer (MODIS) and NPP simulated by Boreal Ecosystem Productivity Simulator (BEPS) model.

Fig. 10 Comparison of net primary production (NPP) estimated by Integrated Terrestrial Ecosystem C-budget (InTEC) model and NPP simulated by Boreal Ecosystem Productivity Simulator (BEPS) model.

Fig. 11 Comparison of net primary production (NPP) estimated by Integrated Terrestrial Ecosystem C-budget (InTEC ) model with NPP calculated by plots.

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