基于EALCO模型对中亚热带人工针叶林CO2通量季节变异的模拟

doi:10.17521/cjpe.2007.0140

植物生态学报 ›› 2007, Vol. 31 ›› Issue (6): 1119-1131.DOI: 10.17521/cjpe.2007.0140

所属专题：生态系统碳水能量通量

基于EALCO模型对中亚热带人工针叶林CO₂通量季节变异的模拟

米娜¹^,², 于贵瑞²^,^*(), 王盘兴¹, 温学发², 孙晓敏², 张雷明², 宋霞², 王树森³

1 南京信息工程大学,南京 210044
2 中国科学院地理科学与资源研究所生态系统网络观测与模拟重点实验室,北京 100101
3 加拿大遥感中心,渥太华

收稿日期:2006-10-16 接受日期:2007-02-22 出版日期:2007-10-16 发布日期:2007-11-30
通讯作者: 于贵瑞
作者简介:* E-mail: yugr@igsnrr.ac.cn
基金资助:
国家重点基础研究发展规划项目(C2002CB412501);国家自然科学基金面上项目(30670384);国家自然科学基金重大项目(30590381)

MODELING SEASONAL VARIATION OF CO₂ FLUX IN A SUBTROPICAL CONIFEROUS FOREST USING THE EALCO MODEL

MI Na¹^,², YU Gui-Rui²^,^*(), WANG Pan-Xing¹, WEN Xue-Fa², SUN Xiao-Min², ZHANG Lei-Ming², SONG Xia², WANG Shu-Sen³

¹Nanjing University of Information Science and Technology, Nanjing 210044, China
²Synthesis Research Center of Chinese Ecosystem Research Network, Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
³Canada Centre for Remote Sensing, Ottawa, Canada

Received:2006-10-16 Accepted:2007-02-22 Online:2007-10-16 Published:2007-11-30
Contact: YU Gui-Rui

摘要/Abstract

摘要：

EALCO模型是一个基于生理生态学过程,模拟生态系统下垫面与大气之间水、热和碳通量交换的综合模型。将该模型应用在亚热带常绿针叶林,对其生态系统过程进行了模拟,以深入探讨季节性干旱对生态系统过程的影响。对EALCO模型进行了参数化与初始化并对模型的光合作用时段和落叶机制进行了改进,以更好地模拟亚热带人工针叶林生态系统。千烟洲通量观测站自2002年底开始应用涡度相关技术对中亚热带人工针叶林生态系统进行通量观测,该站点2003年经历了一次较严重的季节性干旱(由高温与少雨综合作用造成),降水量仅为多年平均值的65%,而2004年的年降水量与多年平均值较为接近,利用该站点2003和2004年特殊的气候条件,使用其通量观测数据对模型的模拟效果进行检验。从模拟结果的总体趋势来看,模型能较好地从半小时、日及年尺度上反映两年内土壤-植被-大气之间的碳交换状况。总初级生产力(Gross primary production, GPP)在一年中呈现单峰型变化,遇高温及干旱胁迫GPP值下降。由于受到干旱胁迫的影响,2003年GPP值比2004年偏低12.9%。模拟结果显示,2003年GPP值比2004年偏低11.2%。观测数据与模拟结果均显示,水分胁迫期间净碳交换量(Net ecosystem production, NEP)模拟值与实测值的日变化均呈现一种“偏态",即一天中生态系统碳交换量最大值出现在上午某一时刻,之后逐渐降低。模拟结果显示,水分匮缺对光合能力的影响比对生态系统呼吸作用的影响更为强烈,因而导致了净生态系统生产力的降低。进一步分析表明,水分匮缺期间,晴天正午之前,深层土壤(>20 cm) 水分的匮缺抑制了光合作用能力,正午之后,高温与深层土壤水分匮缺共同削弱光合作用能力,影响各占一半。

关键词: 人工针叶林, 碳通量, EALCO模型, 生态系统过程, 季节性干旱

Abstract:

Aims Seasonal drought frequently occurs in the mid-subtropical region of China and commonly combines with high temperature. Our objectives were to test the sensitivity of carbon exchange to this seasonal drought and discuss the influence of seasonal drought on carbon assimilation.

Methods We used flux measurements obtained from eddy covariance technology since October 2002 over a human-planted forest ecosystem at Qianyanzhou (QYZ) (26°44' N, 115°03' E, 110.8 m als.). The EALCO (ecological assimilation of land and climate observations) model is parameterized to simulate the ecosystem carbon exchange process in the human-planted evergreen forest. Simulation results were validated using half-hourly carbon fluxes and daily and annualGPP (gross primary production), NEP (net ecosystem production) and TER (total ecosystem respiration) estimated from eddy covariance measurements.

Important findings In general, the model can effectively simulate the two years' carbon fluxes among soil-plant-atmosphere on hourly, daily and annual scales. Both simulations and observations showed strong impact of drought on GPP in 2003. Compared with 2004, the annual GPP in 2003 was 12.9% lower according to observations (1 610 vs. 1 865 g C·m^-2) and 11.2% lower according to model results (1 637 vs. 1 844 g C·m^-2). The diurnal variations of NEP from both observations and simulations during the period of soil water deficit showed asymmetric format, i.e., the peak value of carbon exchange accrued at a certain time in the morning and then decreased with time. Modeling results indicated that water stress has more influence on photosynthesis than TER, which led to the decrease of NEP. Further analysis suggested that deep soil water content controls canopy photosynthesis in sunny days before noon during soil water stress. Afternoon, both high temperature and deep soil water content eliminate the GPP, and their elimination percents are equal. On cloudy days, radiation and deep soil water content primarily determine the photosynthesis, and temperature becomes a generally minor controlling factor.

Key words: coniferous plantation, carbon flux, EALCO model, ecosystem processes, seasonal drought

米娜, 于贵瑞, 王盘兴, 温学发, 孙晓敏, 张雷明, 宋霞, 王树森. 基于EALCO模型对中亚热带人工针叶林CO₂通量季节变异的模拟. 植物生态学报, 2007, 31(6): 1119-1131. DOI: 10.17521/cjpe.2007.0140

MI Na, YU Gui-Rui, WANG Pan-Xing, WEN Xue-Fa, SUN Xiao-Min, ZHANG Lei-Ming, SONG Xia, WANG Shu-Sen. MODELING SEASONAL VARIATION OF CO₂ FLUX IN A SUBTROPICAL CONIFEROUS FOREST USING THE EALCO MODEL. Chinese Journal of Plant Ecology, 2007, 31(6): 1119-1131. DOI: 10.17521/cjpe.2007.0140

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链接本文: https://www.plant-ecology.com/CN/10.17521/cjpe.2007.0140

https://www.plant-ecology.com/CN/Y2007/V31/I6/1119

图/表 12

附表A 模型中使用的参数及其取值

Appendix A Parameters in the model

符号 Symbol	描述 Description	取值 Value	单位 Unit	来源 Source
φ_c,min	式(3)	-200	m H₂O	Larcher, 1995; Kimmins, 1997
φ_c,max	式(3)	0	m H₂O	Larcher, 1995; Kimmins, 1997
m	式(6)	7		Ball et al., 1987
b	式(6)	0.008	mol·m^-2·s^-1	Ball et al., 1987
r_m,F	式(10), 叶 Leaf	4.8×10^-8	Kg C·kg C^-1·S^-1	Amthor, 1989
r_m,S	式(10), 茎 Stem	1.6×10^-8	Kg C·kg C^-1·S^-1	Amthor, 1989
r_m,S	式(10), 根 Root	2.4×10^-8	Kg C·kg C^-1·S^-1	Amthor, 1989
A	式(11)	8.8(16.9^*)
S	式(11)	710(710^*)	J·K^-1·mol^-1
H_a	式(11)	36 000(57 500^*)	J·mol^-1
H_dh	式(11)	220 000(226 000^*)	J·mol^-1
H_dl	式(11)	175 000(192 000^*)	J·mol^-1
r_g,X	式(12)	0.42		Amthor, 1989
V_cmax	最大羧化能力 Maximum catalytic activity of Rubisco	35	μmol·m^-2·s^-1	Farquhar et al., 1980
J_max	最大电子传递速 Potential rate of whole-chain electron transport	87	μmol·m^-2·s^-1	Farquhar et al., 1980
TreeDesi	树的密度Density of tree	0.199 1	trees·m^-2	宋霞等, 2004
SLA	比叶面积Specific leaf area	12	m²·kg^-1	李轩然等, 2007
ζ	决定凋落量的系数 Coefficient	0.000 2	(DOY210~250)	本研究 This study
		0.000 65	(DOY250~365)
Clay	粘土百分含量 Percent of clay	18	%	CERN数据 CERN tada
Sand	沙土百分含量 Percent of sand	20	%	CERN数据 CERN tada
SOM	有机物质含量 Content of soil organic matter	3	%	周志田等, 2002
SOILC	土壤碳含量 Content of soil carbon	8.76(6.80^**)	Kg C·m^-2	自运行后2003年1月1日的值 Data simulated from January 1, 2003
SOILN	土壤氮含量 Content of soil nitrogen	0.87	Kg N·m^-2	自运行后2003年1月1日的值 Data simulated from January 1, 2003

图1 千烟洲2003和2004年逐日降水(柱形图)和各层土壤水分百分含量

Fig.1 Daily precipitation and soil water content of each layer in 2003 and 2004 at Qianyanzhou site

图2 温度对光合能力的影响函数

Fig.2 Temperature function effects on photosynthesis

图3 2003和2004年DOY203~209 NEP的模拟值(线)与观测值(点)

Fig.3 Modeling results (line) and observation (dot) of NEP from DOY203 to DOY209 in 2003 and 2004 at Qianyanzhou site

图4 2003和2004年DOY203~209的GPP和TER模拟值 GPP: 总初级生产力 Gross primary production TER: 总生态系统呼吸 Total ecosystem respiration

Fig.4 Modeling results of GPP and TER from DOY203 to DOY209 in 2003 and 2004 at Qianyanzhou site

表1 半小时尺度CO2通量(NEP) (μmol C·m-2·s-1)观测值(x)与模拟值(y)的回归统计

Table 1 Statistics from the regression of simulated (as y) on observed (as x) half-hourly net ecosystem CO2 fluxes (μmol C·m-2·s-1)

变量 Item	年 Year	斜率 Slope	截距 Intercept	R²	标准差 Standard deviation	记录数 Observations
净CO₂交换量	2003	0.91	-0.34	0.68	3.66	12 849
Net CO₂ flux (NEP)	2004	0.91	-0.02	0.67	4.17	13 141
	2003~2004	0.91	-0.18	0.68	3.93	25 990

图5 2003与2004年辐射与温度状况(DOY203~209)

Fig.5 Radiation and temperature conditions from DOY203 to DOY209 in 2003 and 2004 at Qianyanzhou site

图6 2003与2004年降水与空气饱和水汽压差(VPD)状况(DOY203~209)

Fig.6 Precipitation and vapor pressure deficit (VPD) conditions from DOY203 to DOY209 in 2003 and 2004 at Qianyanzhou site

图7 光合能力下降的百分数(圆点)与冠层温度影响所占的百分数(三角点), Tc代表模型模拟的冠层温度,PG和PT的含义见式(17)和(18)

Fig.7 Decline percent of photosynthesis capacity in 2003 compared to the same time in 2004 and influence percent of temperature on canopy photosynthesis. Tc represents the simulated canopy temperature. The calculation equation of PG and PT refer to equation (17) and (18)

图8 2003~2004年日总初级生产力(GPP)与总生态系统呼吸(TER)的模拟值(线)与“实测值"(点) 年观测值(x)与模拟值(y)的回归统计结果 Regression results between observation data (x) and modeling results (y) GPP: y=1.18x-0.76, R2=0.76 (2003);y=1.15x-0.81, R2=0.88 (2004) TER: y=1.25x-0.84, R2=0.82 (2003);y=1.05x-0.78, R2=0.94 (2004) GPP、TER: See Fig. 4

Fig.8 Modeling results (line) and observations (dot) of daily GPP and TER in 2003 and 2004 at Qianyanzhou site

图9 2003~2004年日净CO2交换量(NEP)的模拟值(线)与“实测值"(点) NEP: 见表2 See Table 2

Fig.9 Modeling results (line) and observations (dot) of daily NEP in 2003 and 2004 at Qianyanzhou site

表2 碳循环组分模拟值与基于观测的估算值的比较

Table 2 Simulated annual carbon balance components vs. some observation-based estimations at Qianyanzhou site (g C·m-2·a-1)

变量 Variable	2003		2004
变量 Variable	模拟值 Simulation	估算值 Estimated¹⁾	模拟值 Simulation	估算值 Estimated¹⁾
GPP	1 637.5	1 610.4	1 844.1	1 865.8
NPP	546.8	-	728.9	-
NEP	404.4	387.2	582.1	423.8
R_above	-765.8	-	-768.3	-
R_soil	-467.3	-	-493.7	-536.5
TER	-1 233.1	-1 223.3	-1 262.0	-1 442.0

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基于EALCO模型对中亚热带人工针叶林CO₂通量季节变异的模拟

MODELING SEASONAL VARIATION OF CO₂ FLUX IN A SUBTROPICAL CONIFEROUS FOREST USING THE EALCO MODEL

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