Using the Lund-Potsdam-Jena Model to Understand the  Different Responses of Three Woody Plants to Land Use in China

SUN Guodong; MU Mu

doi:10.1007/s00376-012-2011-1

Impact Factor: 5.8

Volume 30 Issue 2

Mar. 2013

Article Contents

Article > ADVANCES IN ATMOSPHERIC SCIENCES > 2013 > 30(2): 515-524

Using the Lund-Potsdam-Jena Model to Understand the Different Responses of Three Woody Plants to Land Use in China

SUN Guodong,
MU Mu

1.
State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029;Key Laboratory of Ocean Circulation and Wave, Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chine

SUN Guodong,
MU Mu

doi: 10.1007/s00376-012-2011-1

Abstract
References
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Abstract:
In this study, the approach of conditional nonlinear optimal perturbation related to initial perturbation (CNOP-I) was employed to investigate the maximum variations in plant amount for three main woody plants (a temperate broadleaved evergreen, a temperate broadleaved summergreen, and a boreal needleleaved evergreen) in China. The investigation was conducted within a certain range of land use intensity using a state-of-the-art Lund-Potsdam-Jena dynamic global vegetation model (LPJ DGVM). CNOP-I represents a class of deforestation and can be considered a type of land use with respect to the initial perturbation. When deforestation denoted by the CNOP-I has the same intensity for all three plants, the variation in plant amount of the boreal needleleaved evergreen in northern China is greater than the variation in plant amount of both the temperate broadleaved evergreen and temperate broadleaved summergreen in southern China. As deforestation intensity increases, the plant amount variation in the three woody plant functional types carbon changes, in a nonlinear fashion. The impact of land use on plant functional types is minor because the interaction between climate condition and land use is not considered in the LPJ model. Finally, the different impacts of deforestation on net primary production of the three plant functional types were analyzed by modeling gross primary production and autotrophic respiration. Our results suggest that the CNOP-I approach is a useful tool for exploring the nonlinear and different responses of terrestrial ecosystems to land use.
- conditional nonlinear optimal perturbation,
- initial perturbation,
- CNOP-I,
- terrestrial ecosystem,
- land use
References

[1]	SUN Guodong, MU Mu, ZHANG Yale, 2010: Algorithm Studies on How to Obtain a Conditional Nonlinear Optimal Perturbation (CNOP), ADVANCES IN ATMOSPHERIC SCIENCES, 27, 1311-1321. doi: 10.1007/s00376-010-9088-1
[2]	SUN Guodong, MU Mu, 2012: Inducing Unstable Grassland Equilibrium States Due to Nonlinear Optimal Patterns of Initial and Parameter Perturbations: Theoretical Models, ADVANCES IN ATMOSPHERIC SCIENCES, 29, 79-90. doi: 10.1007/s00376-011-0226-1
[3]	Zhenhua HUO, Wansuo DUAN, Feifan ZHOU, 2019: Ensemble Forecasts of Tropical Cyclone Track with Orthogonal Conditional Nonlinear Optimal Perturbations, ADVANCES IN ATMOSPHERIC SCIENCES, 36, 231-247. doi: 10.1007/s00376-018-8001-1
[4]	JIANG Zhina, 2006: Applications of Conditional Nonlinear Optimal Perturbation to the Study of the Stability and Sensitivity of the Jovian Atmosphere, ADVANCES IN ATMOSPHERIC SCIENCES, 23, 775-783. doi: 10.1007/s00376-006-0775-x
[5]	WANG Qiang, MU Mu, Henk A. DIJKSTRA, 2012: Application of the Conditional Nonlinear Optimal Perturbation Method to the Predictability Study of the Kuroshio Large Meander, ADVANCES IN ATMOSPHERIC SCIENCES, 29, 118-134. doi: 10.1007/s00376-011-0199-0
[6]	Xin LIU, Jing CHEN, Yongzhu LIU, Zhenhua HUO, Zhizhen XU, Fajing CHEN, Jing WANG, Yanan MA, Yumeng HAN, 2024: An Initial Perturbation Method for the Multiscale Singular Vector in Global Ensemble Prediction, ADVANCES IN ATMOSPHERIC SCIENCES, 41, 545-563. doi: 10.1007/s00376-023-3035-4
[7]	ZHENG Qin, SHA Jianxin, SHU Hang, and LU Xiaoqing, 2014: A Variant Constrained Genetic Algorithm for Solving Conditional Nonlinear Optimal Perturbations, ADVANCES IN ATMOSPHERIC SCIENCES, 31, 219-229. doi: 10.1007/s00376-013-2253-6*
[8]	ZHU Benlu, LIN Wantao, ZHANG Yun, 2010: Analysis Study on Perturbation Energy and Predictability of Heavy Precipitation in South China, ADVANCES IN ATMOSPHERIC SCIENCES, 27, 382-392. doi: 10.1007/s00376-009-8164-x
[9]	QIN Xiaohao, MU Mu, 2014: Can Adaptive Observations Improve Tropical Cyclone Intensity Forecasts?, ADVANCES IN ATMOSPHERIC SCIENCES, 31, 252-262. doi: 10.1007/s00376-013-3008-0
[10]	Junhua YANG, Zhenming JI, Deliang CHEN, Shichang KANG, Congshen FU, Keqin DUAN, Miaogen SHEN, 2018: Improved Land Use and Leaf Area Index Enhances WRF-3DVAR Satellite Radiance Assimilation: A Case Study Focusing on Rainfall Simulation in the Shule River Basin during July 2013, ADVANCES IN ATMOSPHERIC SCIENCES, 35, 628-644. doi: 10.1007/s00376-017-7120-4
[11]	SUN Guodong, MU Mu, 2011: Response of a Grassland Ecosystem to Climate Change in a Theoretical Model, ADVANCES IN ATMOSPHERIC SCIENCES, 28, 1266-1278. doi: 10.1007/s00376-011-0169-6
[12]	CHEN Boyu, MU Mu, 2012: The Roles of Spatial Locations and Patterns of Initial Errors in the Uncertainties of Tropical Cyclone Forecasts, ADVANCES IN ATMOSPHERIC SCIENCES, 29, 63-78. doi: 10.1007/s00376-011-0201-x
[13]	Bin MU, Juhui REN, Shijin YUAN, Rong-Hua ZHANG, Lei CHEN, Chuan GAO, 2019: The Optimal Precursors for ENSO Events Depicted Using the Gradient-definition-based Method in an Intermediate Coupled Model, ADVANCES IN ATMOSPHERIC SCIENCES, 36, 1381-1392. doi: 10.1007/s00376-019-9040-y
[14]	Li Yinpeng, Ji Jinjun, 2001: Model Estimates of Global Carbon Flux between Vegetation and the Atmosphere, ADVANCES IN ATMOSPHERIC SCIENCES, 18, 807-818.
[15]	WANG Bo, and HUO Zhenhua, 2013: Extended application of the conditional nonlinear optimal parameter perturbation method in the Common Land Model, ADVANCES IN ATMOSPHERIC SCIENCES, 30, 1213-1223. doi: 10.1007/s00376-012-2025-8
[16]	Xing ZHANG, Mu MU, Qiang WANG, Stefano PIERINI, 2017: Optimal Precursors Triggering the Kuroshio Extension State Transition Obtained by the Conditional Nonlinear Optimal Perturbation Approach, ADVANCES IN ATMOSPHERIC SCIENCES, 34, 685-699. doi: 10.1007/s00376-017-6263-7
[17]	JIANG Zhina, WANG Xin, WANG Donghai, 2015: Exploring the Phase-Strength Asymmetry of the North Atlantic Oscillation Using Conditional Nonlinear Optimal Perturbation, ADVANCES IN ATMOSPHERIC SCIENCES, 32, 671-679. doi: 10.1007/s00376-014-4094-3
[18]	MU Mu, DUAN Wansuo, XU Hui, WANG Bo, 2006: Applications of Conditional Nonlinear Optimal Perturbation in Predictability Study and Sensitivity Analysis of Weather and Climate, ADVANCES IN ATMOSPHERIC SCIENCES, 23, 992-1002. doi: 10.1007/s00376-006-0992-3
[19]	SHI Xiaoying, MAO Jiafu, WANG Yingping, DAI Yongjiu, TANG Xuli, 2011: Coupling a Terrestrial Biogeochemical Model to the Common Land Model, ADVANCES IN ATMOSPHERIC SCIENCES, 28, 1129-1142. doi: 10.1007/s00376-010-0131-z
[20]	XU Yongfu, HUANG Yao, LI Yangchun, 2012: Summary of Recent Climate Change Studies on the Carbon and Nitrogen Cycles in the Terrestrial Ecosystem and Ocean in China, ADVANCES IN ATMOSPHERIC SCIENCES, 29, 1027-1047. doi: 10.1007/s00376-012-1206-9

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Manuscript History

Manuscript received: 10 March 2013

Manuscript revised: 10 March 2013

通讯作者: 陈斌, bchen63@163.com

1.
沈阳化工大学材料科学与工程学院沈阳 110142

Using the Lund-Potsdam-Jena Model to Understand the Different Responses of Three Woody Plants to Land Use in China

SUN Guodong,
MU Mu

1. State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029;Key Laboratory of Ocean Circulation and Wave, Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chine

Manuscript received: 2013-03-10
Manuscript revised: 2013-03-10

Abstract: In this study, the approach of conditional nonlinear optimal perturbation related to initial perturbation (CNOP-I) was employed to investigate the maximum variations in plant amount for three main woody plants (a temperate broadleaved evergreen, a temperate broadleaved summergreen, and a boreal needleleaved evergreen) in China. The investigation was conducted within a certain range of land use intensity using a state-of-the-art Lund-Potsdam-Jena dynamic global vegetation model (LPJ DGVM). CNOP-I represents a class of deforestation and can be considered a type of land use with respect to the initial perturbation. When deforestation denoted by the CNOP-I has the same intensity for all three plants, the variation in plant amount of the boreal needleleaved evergreen in northern China is greater than the variation in plant amount of both the temperate broadleaved evergreen and temperate broadleaved summergreen in southern China. As deforestation intensity increases, the plant amount variation in the three woody plant functional types carbon changes, in a nonlinear fashion. The impact of land use on plant functional types is minor because the interaction between climate condition and land use is not considered in the LPJ model. Finally, the different impacts of deforestation on net primary production of the three plant functional types were analyzed by modeling gross primary production and autotrophic respiration. Our results suggest that the CNOP-I approach is a useful tool for exploring the nonlinear and different responses of terrestrial ecosystems to land use.

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