基于SCOPE模型的樟子松人工林日光诱导叶绿素荧光及初级生产力模拟与评估

张宇昕; 杨凯捷; 丛巍巍; 陆森; 张劲松; 王锋

doi:10.12356/j.2096-8884.2024-0004

基于SCOPE模型的樟子松人工林日光诱导叶绿素荧光及初级生产力模拟与评估

doi: 10.12356/j.2096-8884.2024-0004

张宇昕^{1, 2, 3,},
杨凯捷^{1, 2, 3},
丛巍巍⁴,
陆森⁵,
张劲松⁵,
王锋^{1, 2, 3, ,}

1.
中国林业科学研究院生态保护与修复研究所，北京 100091
2.
中国林业科学研究院荒漠化研究所，北京 100091
3.
三北工程研究院，内蒙古巴彦淖尔市磴口县 015200
4.
沈阳农业大学农学院，沈阳 110161
5.
中国林业科学研究院林业研究所，北京 100091

基金项目: 中央级公益性科研院所基本科研业务费专项资金项目（CAFYBB2020QD002）；国家自然科学基金项目（32171875）

详细信息

作者简介:
张宇昕：E-mail：zhangyuxin@caf.ac.cn

通讯作者:
E-mail：wangfeng@caf.ac.cn

中图分类号: Q141
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- 文章访问数: 90
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- 被引次数: 0
出版历程
- 收稿日期: 2024-01-10
- 录用日期: 2024-04-21
- 网络出版日期: 2024-06-18

Simulation and Assessment of Sun-induced Chlorophyll Fluorescence and Gross Primary Production in Pinus sylvestris var. mongolica Plantation Based on the SCOPE Model

Yuxin Zhang^{1, 2, 3
,},
Kaijie Yang^{1, 2, 3},
Weiwei Cong⁴,
Sen Lu⁵,
Jinsong Zhang⁵,
Feng Wang^{1, 2, 3
, ,}

1.
Institute of Ecological Conservation and Restoration, Chinese Academy of Forestry, Beijing 100091, China
2.
Institute of Desertification Studies, Chinese Academy of Forestry, Beijing 100091, China
3.
Institute of Great Green Wall, Dengkou, Bayannur, Inner Mongolia 015200, China
4.
College of Agronomy, Shenyang Agricultural University, Shenyang 110161, China
5.
Research Institute of Forestry, Chinese Academy of Forestry, Beijing 100091, China

摘要

摘要: 目的检验SCOPE（Soil Canopy Observation of Photosynthesis and Energy fluxes）模型用于模拟樟子松人工林的日光诱导叶绿素荧光（sun-induced chlorophyll fluorescence, SIF）和植被总初级生产力（gross primary productivity, GPP）动态变化的可能性。方法对科尔沁沙地南缘樟子松人工林，基于样地SIF、GPP及气象协同观测数据，利用SCOPE模型模拟SIF与GPP的日变化与季节变化，评估了SCOPE模型在典型晴天、典型多云日、整个观测期的模拟效果。结果结果显示，利用气象观测数据及冠层参数（入射短波辐射、气温、大气实际水汽压、CO₂浓度及叶面积指数），可驱动SCOPE模型模拟樟子松人工林的SIF与GPP。典型晴天日与多云日的SIF模拟值和实测值的R²分别为0.42与0.52，RMSE分别为0.19与0.18 W·m⁻²·μm⁻¹·sr⁻¹；GPP模拟值和观测值的R²分别为0.78与0.89，RMSE分别为1.87与2.57 μmol·m⁻²·s⁻¹。在季节尺度上，SIF和GPP模拟值和观测值的R²分别为0.50、0.72，RMSE分别为0.19 W·m⁻²·μm⁻¹·sr⁻¹和2.64 μmol·m⁻²·s⁻¹。在整个观测期，多云日的SIF（R²=0.31, RMSE=0.22 W·m⁻²·μm⁻¹·sr⁻¹）与 GPP（R²=0.80, RMSE =2.42 μmol·m⁻²·s⁻¹）的模拟效果优于晴天日（SIF：R²=0.30，RMSE=0.26 W·m⁻²·μm⁻¹·sr⁻¹，GPP：R²=0.64，RMSE=3.64 μmol·m⁻²·s⁻¹）。SIF模拟值总体高于观测值，当SIF强度较低时易对SIF高估，反之则易低估。GPP的模拟精度较高，模型对较低与较高GPP有所低估，对中间值有所高估。结论 SCOPE模型可用于日尺度与季节尺度的SIF与GPP模拟，且多云日的模拟精度更高。SCOPE模型对樟子松人工林的GPP模拟结果优于SIF，推测SIF模拟精度较低的原因可能是模型对SIF的模拟是基于阔叶植物的辐射传输过程。未来应发展针对针叶植物的SIF辐射传输模型，为针叶林的辐射传输与荧光遥感监测提供模型基础。
- 日光诱导叶绿素荧光 /
- 总初级生产力 /
- 樟子松 /
- SCOPE模型
Abstract: Objective To investigate the possibility of using SCOPE (Soil Canopy Observation of Photosynthesis and Energy fluxes) model to simulate the dynamic changes of sun-induced chlorophyll fluorescence (SIF) and gross primary productivity (GPP) in Pinus sylvestris var. mongolica plantation. Methods This study focused on a P. sylvestris var. mongolica plantation on the southern edge of the Horqin Sandy Land. Using coordinated observations SIF, GPP, and meteorological data, we simulated the diurnal and seasonal variations of SIF and GPP in the P. sylvestris var. mongolica plantation based on the SCOPE model. The model's performance was evaluated for a typical sunny day, a typical cloudy day, and the entire observation period. Results The results showed that using meteorological observation data and canopy parameters (incoming shortwave radiation, air temperature, atmospheric vapor pressure, CO₂ concentration, and leaf area index), the SCOPE model can be driven to simulate the SIF and GPP in the P. sylvestris var. mongolica plantation. The R² values for SIF simulations on a typical sunny and cloudy day were 0.42 and 0.52, with RMSE values of 0.19 and 0.18 W·m⁻²·μm⁻¹·sr⁻¹, respectively. The R² values for GPP simulations on these days were 0.78 and 0.89, with RMSE values of 1.87 and 2.57 μmol·m⁻²·s⁻¹, respectively. At the seasonal scale, the R² values for SIF and GPP were 0.50 and 0.72, with RMSE values of 0.19 W·m⁻²·μm⁻¹·sr⁻¹ and 2.64 μmol·m⁻²·s⁻¹, respectively. Throughout the observation period, the simulations of SIF (R²=0.31, RMSE=0.22 W·m⁻²·μm⁻¹·sr⁻¹) and GPP (R²=0.80, RMSE=2.42 μmol·m⁻²·s⁻¹) on cloudy days were better than those on sunny days (SIF: R²=0.30, RMSE=0.26 W·m⁻²·μm⁻¹·sr⁻¹; GPP: R²=0.64, RMSE=3.64 μmol·m⁻²·s⁻¹). Overall, the simulated SIF values were higher than the observed values, and the model tended to overestimate SIF at low intensities and underestimate it at high intensities. While GPP simulations demonstrated high accuracy, with slight underestimation for both low and high GPP and slight overestimation for intermediate values. Conclusion The SCOPE model is suitable for simulating daily and seasonal variations of SIF and GPP, with higher accuracy in simulations on cloudy days. The model's performance in simulating GPP in the P. sylvestris var. mongolica plantation is better than its performance in simulating SIF. The lower accuracy of SIF simulations is speculated to be due to the model being based on the radiation transfer process of broadleaf plants. Future efforts should focus on developing SIF radiative transfer models specifically for needle forests to establish a modeling foundation for the radiative transfer and fluorescence remote sensing monitoring of needle forests.
- sun-induced chlorophyll fluorescence /
- gross primary production /
- Pinus sylvestris var. mongolica /
- SCOPE model

HTML全文

图 1 科尔沁沙地南缘辽宁省建平县樟子松人工林观测点（41°58'169″ N，119°25'104″ E）及荧光通量与气象协同观测设备

Figure 1. Observation site of the Pinus sylvestris var. mongolica plantation in Jianping, Liaoning Province, on the southern edge of the Horqin Sandy Land (41°58'169″ N, 119°25'104″ E), and the fluorescence, flux and meteorological co-observation equipment

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图 2 樟子松人工林日光诱导叶绿素荧光（SIF）与植被总初级生产力（GPP）典型晴天和典型多云日变化

注：典型晴天日（8月22日），典型多云日（8月29日）。Typical sunny day (August 22), typical cloudy day (August 29).

Figure 2. Diurnal variations of sun-induced chlorophyll fluorescence (SIF) and gross primary productivity (GPP) of Pinus sylvestris var. mongolica plantation on a typical sunny day and a typical cloudy day

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图 3 不同天气状况下樟子松人工林SIF与GPP的日散点图

注：典型晴天日（8月22日），典型多云日（8月22日）。Typical sunny day (August 22), typical cloudy day (August 29).

Figure 3. Scatter plots of daily SIF and GPP in the Pinus sylvestris var. mongolica plantation under different weather conditions

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图 4 樟子松人工林日光诱导叶绿素荧光（SIF）与植被总初级生产力（GPP）全观测期模拟值与实测值评估（2022年8月至12月）

Figure 4. Evaluation of simulated and measured sun-induced chlorophyll fluorescence (SIF) and gross primary productivity (GPP) of Pinus sylvestris var. mongolica plantation throughout the observation period (August to December, 2022)

下载: 全尺寸图片幻灯片

图 5 樟子松人工林日光诱导叶绿素荧光（SIF）与植被总初级生产力（GPP）全观测期变化（2022年8月至12月）

Figure 5. Variations of sun-induced chlorophyll fluorescence (SIF) and gross primary productivity (GPP) of Pinus sylvestris var. mongolica plantation throughout the observation period (August to December 2022)

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图 6 基于SCOPE模型的晴天和多云天气条件下樟子松人工林日光诱导叶绿素荧光（SIF）与植被总初级生产力（GPP）全观测期模拟值与实测值评估

Figure 6. Evaluation of simulated and measured sun-induced chlorophyll fluorescence (SIF) and gross primary productivity (GPP) of Pinus sylvestris var. mongolica plantation throughout the observation period under clear and cloudy weather conditions based on the SCOPE model

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表 1 SCOPE模型主要参数

Table 1. Key Parameters in SCOPE Model

类型 Types	定义 Definition	取值 Value	单位 Unit	来源 Source
叶片生化参数 Leaf biochemical parameters	25 ℃时最大羧化速率（V_cmax25） Maximum carboxylation rate at 25 ℃ (V_cmax25)	62.5	μmol·m⁻²·s⁻¹	Cui et al., 2020
叶片生化参数 Leaf biochemical parameters	Ball-Berry气孔导度模型斜率（m） Slope of Ball-Berry stomatal conductance model (m)	观测并计算	—	观测并计算

冠层结构参数 Canopy structure parameters	叶面积指数（LAI） Leaf area index (LAI)	0.88	m²·m⁻²	观测
	叶倾角分布参数a（LIDF_a） Leaf angle distribution parameter a (LIDF_a)	0	—	Verhoef, 1985
	叶倾角分布参数b（LIDF_b） Leaf angle distribution parameter b (LIDF_b)	1	—	Verhoef, 1985

叶片辐射传输模型参数 Leaf radiative transfer model parameters	叶绿素含量（C_ab） Chlorophyll content (C_ab)	20	μg·m⁻²	Croft et al., 2020
	衰老系数（C_s） Senescent material fraction (C_s)	0	—	Cui et al., 2020
	叶片厚度参数（N） Leaf thickness parameters (N)	2	—	Cui et al., 2020
	光系统荧光量子产额（FQE） Fluorescence quantum yield efficiency at photosystem level (FQE)	0.01	—	Croft et al., 2020

气象参数 Meteorological parameters	入射短波辐射（R_in） Incoming shortwave radiation (R_in)	观测	W·m⁻²	观测
	气温（T_a） Air temperature (T_a)	观测	℃	观测
	大气实际水汽压（e_a） Atmospheric vapor pressure (e_a)	观测并计算	hPa	观测并计算
	CO₂ 浓度（C_a） CO₂ concentration (C_a)	观测	mg·m⁻³	观测

下载: 导出CSV

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