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\begin{document}

\title{Predicting the distribution of plant associations under climate change:
A case study on \emph{Larix gmelinii} in China}



\author[1]{Chen Chen}%
\author[1]{Xijuan Zhang}%
\author[2]{Jizhong Wan}%
\author[1]{Feifei Gao}%
\author[1]{Shusheng Yuan}%
\author[1]{Tiantian  Sun}%
\author[1]{Zhendong Ni}%
\author[1]{Jinghua Yu}%
\affil[1]{Institute of Applied Ecology Chinese Academy of Sciences}%
\affil[2]{Qinghai University State Key Laboratory of Plateau Ecology and Agriculture}%


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  \date{May 25, 2024}


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\begin{abstract}
Association is the basic unit of plant community classification.
Exploring the distribution of plant associations can help improve the
understanding of biodiversity conservation. Different associations
depend on different habitats. Studying the association level is
significant for ecological restoration, regional ecological protection,
regulating the ecological balance, and maintaining biodiversity.
However, previous studies have focused only on the suitable distribution
areas of species and not on the distribution of plant associations.
Larix gmelinii is a sensitive and abundant species spread in the
southern margin of Eurasian boreal forests, and its distribution is
closely related to permafrost. In this study, 420 original plots of L.
gmelinii forests were investigated. We used Maxent model and ArcGIS
software to project the potential geographical distribution of L.
gmelinii associations in the future (by 2050 and 2070) according to the
climate scenarios RCP 2.6, RCP 4.5, and RCP 8.5. The causes for the
changes in spatial distribution were analyzed using multinomial logistic
regression analysis. The results revealed that temperature is the most
important factor affecting the distribution of L. gmelinii forests and
most of its associations under different climate scenarios. Further, the
suitable areas for each association type are shrinking by varying
degrees, especially due to habitat loss at high altitudes in special
terrains. For different L. gmelinii associations, management measures
should also be different based on the different site conditions,
composition structure, growth, development, and renewal succession
trends. Furthermore, subsequent research should consider data on
biological factors to obtain more accurate prediction results.%
\end{abstract}%



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\verb`Distribution_prediction_of_plant_associations_.docx`  available at \url{https://authorea.com/users/467467/articles/561519-predicting-the-distribution-of-plant-associations-under-climate-change-a-case-study-on-larix-gmelinii-in-china}

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