植被光合呼吸模型在千烟洲亚热带常绿针叶林的优化及验证

doi:10.17521/cjpe.2015.0038

植物生态学报 ›› 2015, Vol. 39 ›› Issue (4): 388-397.DOI: 10.17521/cjpe.2015.0038

所属专题：生态系统碳水能量通量

植被光合呼吸模型在千烟洲亚热带常绿针叶林的优化及验证

刘诚^1,^*(), 黄建平^1,^**(), 刁一伟¹, 温学发², 肖薇¹, 张弥¹, 李旭辉¹, 刘寿东¹

¹南京信息工程大学大气环境中心, 南京 210044
²中国科学院地理科学与资源研究所, 北京 100101

收稿日期:2014-09-04 接受日期:2015-01-10 出版日期:2015-04-01 发布日期:2015-04-21
通讯作者: 刘诚,黄建平
作者简介:
*作者简介:E-mail:chengliu6542@gmail.com
基金资助:
国家自然科学基金(31100359和31200377)、教育部“长江学者与创新团队发展计划”(PCSIRT)和江苏省高校优势学科建设工程项目(PAPD)

Optimization and evaluation of vegetation photosynthesis and respiration model using the measurements collected from the forest site of subtropical coniferous-evergreen

LIU Cheng^1,^*(), HUANG Jian-Ping^1,^**(), DIAO Yi-Wei¹, WEN Xue-Fa², XIAO Wei¹, ZHANG Mi¹, LEE Xu-Hui¹, LIU Shou-Dong¹

¹Yale-NUIST Center on Atmospheric Environment, Nanjing University of Information Science & Technology, Nanjing 210044, China
²Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101,China

Received:2014-09-04 Accepted:2015-01-10 Online:2015-04-01 Published:2015-04-21
Contact: Cheng LIU,Jian-Ping HUANG
About author:
# Co-first authors

摘要/Abstract

摘要：

碳循环模型参数的确定和优化对生态系统净CO₂交换(NEE)的模型计算至关重要。该文利用2010-2012年ChinaFLUX千烟洲站点的通量观测资料, 对植被光合呼吸模型(VPRM)的参数进行了优化。通过比较两种不同的拟合方案, 发现利用传统光响应方程得到的参数不适用于VPRM, 而利用模型自身反演方案拟合得到的参数最大光量子效率(λ)达0.203, 大于C₃植物平均值, 但与其他相关研究结果吻合。采用VPRM模型反演方案优化得到的参数后, VPRM能较准确地模拟千烟洲站不同季节的NEE。其对全年半小时NEE模拟的平均误差为-0.86 μmol·m^-2·s^-1, 相关系数为0.72。模型可准确地模拟生长旺季NEE平均日变化, 但低估了非生长旺季白天吸收峰值约52%。通过个例分析发现, VPRM模型可以准确模拟晴天条件下NEE的时间变化, 但对阴雨天条件下NEE的模拟还存在较大的不确定性。该研究将有助于进一步改进CO₂通量及浓度的区域数值模拟。

关键词: 生态系统净交换, 参数优化, 千烟洲, 植被光合呼吸模型

Abstract: Aims

Determination of carbon cycling model parameters is critical to simulate the net ecosystem CO₂ exchange (NEE). The objectives of this study were to determine the parameters of vegetation photosynthesis and respiration model (VPRM) and improve the calculation of NEE to benefit regional modeling of CO₂.

Methods

Two schemes are examined in optimization of the parameters in VPRM. Two years CO₂ flux and meteorological observational data in 2010-2011 at the Qianyanzhou (QYZ) eddy tower site are used to determine the parameters in VPRM and another full year flux observational data in 2012 are used to evaluate the model performance. Several statistics metrics are calculated to evaluate the model performance on NEE simulations.

Important findings

The results indicate, traditional method with Michaelis-Menten equation is not suitable to determine the parameters of VPRM, whereas the method with parameters retrieved from the VPRM calculation equation provides much more reasonable results. The parameter of maximum light use efficiency (λ) is critical for the VPRM calculation of NEE. Our result is larger than the typical value of C₃ plant (1/6), but consistent with the other studies. Using the optimized parameters, VPRM is able to capture NEE variations for different seasons. The statistics calculation with one-year NEE simulation shows that, the mean bias is -0.86 μmol·m^-2·s^-1 and correlation coefficient is 0.72. Overall, the VPRM performs much better in growing season than the non-growing season when the peak value of NEE is underestimated by 52%. The VPRM simulated NEE shows better agreement with observations on sunny days than rainy or cloudy days.

Key words: net ecosystems exchange (NEE), parameter optimization, Qianyanzhou, vegetation photosynthesis and respiration model

刘诚, 黄建平, 刁一伟, 温学发, 肖薇, 张弥, 李旭辉, 刘寿东. 植被光合呼吸模型在千烟洲亚热带常绿针叶林的优化及验证. 植物生态学报, 2015, 39(4): 388-397. DOI: 10.17521/cjpe.2015.0038

LIU Cheng,HUANG Jian-Ping,DIAO Yi-Wei,WEN Xue-Fa,XIAO Wei,ZHANG Mi,LEE Xu-Hui,LIU Shou-Dong. Optimization and evaluation of vegetation photosynthesis and respiration model using the measurements collected from the forest site of subtropical coniferous-evergreen. Chinese Journal of Plant Ecology, 2015, 39(4): 388-397. DOI: 10.17521/cjpe.2015.0038

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链接本文: https://www.plant-ecology.com/CN/10.17521/cjpe.2015.0038

https://www.plant-ecology.com/CN/Y2015/V39/I4/388

图/表 9

图1 VPRM模型结构示意图。EVI, 增强型植被指数; GEE, 总生态系统CO2交换; LSWI, 地表水分指数; NEE, 净生态系统CO2交换; PAR, 光合有效辐射; R, 生态系统呼吸; T, 温度。

Fig. 1 Schematic diagram of the vegetation photosynthesis respiration model (VPRM). EVI, enhanced vegetation index; GEE, gross ecosystem CO2 exchange; LSWI, land surface water index; NEE, net ecosystem CO2 exchange; PAR, photosynthetically active radiation; R, respiration; T, temperature.

表1 采用2010-2011年千烟洲观测资料两种不同方案得到的参数对比

Table 1 A comparison of the parameters derived from two schemes at Qianyanzhou site

方案 Scheme	λ	PAR₀ (μmol·m^-2·s^-1)	α (μmol CO₂·m^-2·s^-1·℃^-1)	β (μmol CO₂·m^-2·s^-1)
1	0.048	514	0.164	0.906
2	0.203	345	0.164	0.906

图2 千烟洲2012年全年VPRM模拟的生态系统净CO2交换(NEE-VPRM)与观测值(NEE-Obs)的对比。+, 方案一参数模拟的NEE; ·, 方案二参数模拟的NEE; 黑色实线代表1:1线。

Fig. 2 A comparison of VPRM-simulated net ecosystem CO2 exchange (NEE-VPRM) with observed NEE (NEE-Obs) for year 2012 at Qianyanzhou site. +, simulated NEE with optimized parameters of scheme 1; ·, simulated NEE with optimized parameters of scheme 2; Solid black line, 1:1 line.

表2 VPRM模拟生态系统净CO2交换(NEE)与观测值之间统计分析

Table 2 Statistical analysis between simulated net ecosystem CO2 exchange (NEE) and observed NEE

	2012年 Year 2012	斜率 Slope	截距 Intercept (μmol·m^-2·s^-1)	R平方值 R square	均方根误差 Root mean squared error (μmol·m^-2·s^-1)	平均误差 Mean bias (μmol·m^-2·s^-1)	有效数据 Valid data
方案一 Scheme 1	全年0.5 h NEE All year 0.5 h NEE	0.17	2.44	0.51	9.58	6.68	5 909
	生长旺季时刻平均 Mean diurnal variation during the peak growing season	0.27	3.49	0.97	8.01	5.63	48
	非生长旺季时刻平均 Mean diurnal variation during the non-peak growing season	0.06	1.78	0.61	4.12	2.24	48
方案二 Scheme 2	全年0.5 h NEE All year 0.5 h NEE	0.73	-2.23	0.52	6.23	-0.86	5 909
	生长旺季时刻平均 Mean diurnal variation during the peak growing season	0.92	0.65	0.96	1.72	0.87	48
	非生长旺季时刻平均 Mean diurnal variation during the non-peak growing season	0.50	0.66	0.89	2.15	0.91	48

图3 千烟洲2012年生长旺季(4-9月)模拟的生态系统净CO2交换(NEE)与观测值的平均日变化。NEE-Obs, NEE观测值; NEE-Mod, 方案二得到的VPRM模拟NEE。

Fig. 3 A comparison between the observed and modeled mean diurnal variation of net ecosystem CO2 exchange (NEE) during the peak growing season (April to September) of 2012 at Qianyanzhou site. NEE-Obs, observed NEE; NEE-Mod, simulated NEE with optimized parameters of scheme 2.

图4 千烟洲2012年生长旺季(4-9月)生态系统净CO2交换的VPRM模拟值(NEE-VPRM)与观测值(NEE-Obs)的平均日变化回归分析。黑色圆圈代表方案二得到的VPRM模型模拟NEE; 虚线为1:1线。

Fig. 4 Regression analyses between the VPRM modeled net ecosystem CO2 exchange (NEE-VPRM) and observed NEE (NEE-Obs) during growing season (April to September) in year 2012 at Qianyanzhou site. Black circle: simulated NEE with optimized parameters of scheme 2; dotted line: 1:1 line.

图5 千烟洲2012年非生长旺季模拟的生态系统净CO2交换(NEE)与观测值的平均日变化。NEE-Obs, NEE观测值; NEE-Mod, 方案二得到的VPRM模拟NEE。

Fig. 5 A comparison between the observed and modeled mean diurnal variation of net ecosystem CO2 exchange (NEE) during the non-peak growing season of 2012 at Qianyanzhou site. NEE-Obs, observed NEE; NEE-Mod, simulated NEE with optimized parameters of scheme 2.

图6 千烟洲2012年DOY184-190 (晴天)的生态系统净CO2交换(NEE)模拟值与观测值对比。NEE-Obs, NEE观测值; NEE-Mod, 方案二得到的VPRM模拟NEE; GEE-Mod, 方案二得到的VPRM模拟总生态系统CO2交换量; R-Mod, 方案二得到的VPRM模拟生态系统呼吸。

Fig. 6 A comparison of simulated net ecosystem CO2 exchange (NEE) with observations at Qianyanzhou site during the day 184-190 of 2012 (sunny). NEE-Obs, observed NEE; NEE-Mod, simulated NEE with optimized parameters of scheme 2; GEE-Mod, simulated gross ecosystem CO2 exchange with optimized parameters of scheme 2; R-Mod,simulated respiration with optimized parameters of scheme 2.

图7 千烟洲2012年DOY152-158 (阴天)的生态系统净CO2交换(NEE)模拟值与观测值对比。NEE-Obs, NEE观测值; NEE-Mod, 方案二得到的VPRM模拟NEE; GEE-Mod, 方案二得到的VPRM模拟总生态系统CO2交换量; R-Mod, 方案二得到的VPRM模拟生态系统呼吸。

Fig. 7 A comparison of simulated net ecosystem CO2 exchange (NEE) with observations at Qianyanzhou site during the day 152-158 of 2012 (cloudy). NEE-Obs, observed NEE; NEE-Mod, simulated NEE with optimized parameters of scheme 2; GEE-Mod, simulated gross ecosystem CO2 exchange with optimized parameters of scheme 2; R-Mod,simulated respiration with optimized parameters of scheme 2.

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植被光合呼吸模型在千烟洲亚热带常绿针叶林的优化及验证

Optimization and evaluation of vegetation photosynthesis and respiration model using the measurements collected from the forest site of subtropical coniferous-evergreen

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