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\begin{document}

\title{Potential vegetation changes in the permafrost areas over the Tibetan
Plateau under future climate warming}



\author[1]{Rui Chen}%
\author[2]{Jan Nitzbon}%
\author[1]{Schneider von Deimling Thomas}%
\author[1]{Simone Maria Stuenzi}%
\author[1]{Ngai-Ham Chan}%
\author[3]{Julia Boike}%
\author[4]{Moritz Langer}%
\affil[1]{Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research}%
\affil[2]{Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research}%
\affil[3]{Alfred-Wegener Institute}%
\affil[4]{Alfred Wegener Institute}%


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  \date{May 27, 2024}


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\begin{abstract}
Permafrost degradation on the Tibetan Plateau is well-documented and
expected to continue throughout this century. However, the impact of
thawing permafrost on the distribution, composition, and resilience of
vegetation communities in this region is not well understood. In this
study, we combined a transient numerical permafrost model with machine
learning algorithms to project the near-future thermal state of
permafrost and vegetation (represented by the Normalized Difference
Vegetation Index {[}NDVI{]}) changes under two contrasting climate
pathways (Shared Socioeconomic Pathway 1--2.6 {[}SSP1--2.6{]} and
SSP5--8.5). The contribution of climatic and terrestrial variables to
vegetation evolution was quantified using ridge regression. By 2100,
permafrost areas were expected to decrease by 21\selectlanguage{ngerman}±4\%, and 55±2\% under
the SSP1--2.6 and SSP5--8.5 scenarios, respectively, relative to the
baseline period (2000--2018). Under the SSP1--2.6 scenarios, the mean
annual ground temperature and active layer thickness were projected to
fluctuate stably, while under the SSP5--8.5 scenarios, a significant
increasing trend was anticipated. Satellite-based observations indicated
an increasing trend of NDVI within the permafrost areas from 2000 to
2018 (0.01 per decade), mainly attributed to climatic factors. In the
future, vegetation greenness was expected to possibly remain stable
under SSP1--2.6 scenarios, whereas a rising trend was likely noted under
SSP5--8.5 scenarios during 2019--2050, mainly controlled by the surface
air temperature and liquid water content at the root zone during the
growing season. Our modeling work provides a potential approach for
investigating future vegetation changes and offers more possibilities to
improve understanding of the interaction between
soil-vegetation-atmosphere in cold regions.%
\end{abstract}\selectlanguage{ngerman}%



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