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Effects of climate change on vegetation pattern in Baotou, China

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Abstract

The vegetation system in arid and semi-arid regions is facing severe challenges, so it is urgent to forecast the evolution of vegetation system. Vegetation pattern dynamics can be used to qualitatively analyze and quantitatively describe the formation mechanism and distribution law of vegetation based on dynamic equations and statistical data. Therefore, this paper selects Baotou region, Inner Mongolia which is a typical semi-arid region and applies vegetation-climate dynamics model to study the effect of climate change on vegetation distribution. The last 60 years of carbon dioxide concentration [CO\(_2\)], rainfall and temperature data in this region are collected and the correlation between these climatic factors and vegetation density is analyzed. Besides, vegetation growth over the next 100 years is predicted under different climate scenarios. The results reveal that precipitation makes a critical difference in the growth of vegetation, and the vegetation pattern is the result of the synergistic effect of temperature, precipitation and [CO\(_2\)]. The rate of vegetation desertification is the fastest under current scenario and SSP1-2.6 is the most ideal climate scenario for vegetation growth. Furthermore, we use the optimal control theory to provide a theoretical guidance for the prevention of desertification.

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Data availability

Daily rainfall and temperature data 1960–2019 is from China Meteorological Data Service Center (http://data.cma.cn/). Daily carbon dioxide concentration data is from Global Monitoring Laboratory (http://www.esrl.noaa.gov/gmd/ccgg/trends/). The future climate scenarios data comes from CMIP6 (https://esgfnode.llnl.gov/projects/cmip6/). NDVI data 2000–2020 is from National Ecosystem Science Data Center (http://www.nesdc.org.cn/).

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Acknowledgements

National Natural Science Foundation of China under Grant Nos. 42275034 and 42075029, Fundamental Research Program of Shanxi Province (Grant Nos. 202303021223009, 202203021212327 and 202203021211213), Program for the (Reserved) Discipline Leaders of Taiyuan Institute of Technology, Taiyuan Institute of Technology Scientific Research Initial Funding.

Funding

Funding was provided by National Natural Science Foundation of China (Grant Number 42275034, 42075029).

Author information

Authors and Affiliations

  1. Department of Computer Science and Technology, North University of China, Taiyuan, 030051, China

    Juan Liang & Gui-Quan Sun

  2. Department of Science, Taiyuan Institute of Technology, Taiyuan, 030008, China

    Juan Liang

  3. Department of Mathematics, North University of China, Taiyuan, 030051, China

    Gui-Quan Sun

  4. Complex Systems Research Center, Shanxi University, Taiyuan, 030006, China

    Gui-Quan Sun

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  1. Juan Liang
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Correspondence to Gui-Quan Sun.

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Appendices

Appendix A. Model notation and interpretation

Parameter

Interpretation

Unit

k

The half-saturation constant of water infiltration

\((mmd)^{-1}\)

\(p_c\)

Maximal leaf conductance to CO\(_2\)

\(mod\ m^{-2}d^{-1}\)

A

Rainfall

\((mmd)^{-1}\)

\(D_1\)

Plant dispersal

\(m^2d^{-1}\)

\(D_2\)

Diffusion coefficient for water

\(m^2d^{-1}\)

\(C_a\)

Ambient CO\(_2\) concentration

\(mol\ mol^{-1}\)

\(C_i\)

Intercellular CO\(_2\) concentration (in the leaf)

\(mol\ mol^{-1}\)

\(C_1\)

Conversion coefficient of photosynthesis (mol) into biomass (g)

\(g\ mol^{-1}\)

\(R_b\)

Respiration per unit of biomass

\(d^{-1}\)

T

Temperature

\(^\circ C\)

\(e^*(T)\)

Saturated vapor pressure

kPa

\(R_h\)

Relative humidity \(\frac{e(T)}{e^*(T)}\)

-

R

The water absorption rate by roots

mm/d

L

Evaporation rate of water at the surface

mm/d

P

Vegetation density

\(gm^{-2}\)

W

Water

mm

t

Time

d

Appendix B. Parameter selection

\(R_b=1, Rh=0.4, p_c=10*10^{-3}, M_{10}=1.6, R=2.6*10^{-2}, D_1=1, D_2=200, \gamma =5.55*10^3, C_1=12, \frac{C_i}{C_a}=0.6, k=0.5.\)

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Liang, J., Sun, GQ. Effects of climate change on vegetation pattern in Baotou, China. Nonlinear Dyn 112, 8675–8693 (2024). https://doi.org/10.1007/s11071-024-09500-3

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