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Predicting the changes in suitable habitats for six common woody species in Central Asia

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Abstract

Climate change over the past decades has significantly altered global hydrothermal conditions and caused an evident shift in species distribution. Predicting species distribution patterns and identifying their influencing factors will be essential in developing coping strategies to prevent species extirpation and extinction. Yet, environmental factors affecting the distribution of woody species in Central Asia remain largely unknown. Here, I used the MaxEnt model to predict the current distributions and future distribution under three SSP-RCP scenarios of six common woody species in Central Asia. The results indicated a good performance of the MaxEnt model. Precipitation of driest month and annual mean temperature were the dominant factors affecting species distribution. For the species with wide ecological niches, i.e., Acer negundo and Rosa chinensis, the suitable areas showed an evident expansion trend under future scenarios. In addition, a trend toward higher elevation was found for the species that grew at high altitudes (1600–3200 m). However, the average elevation of suitable area for A. negundo and R. chinensis firstly increased but then decreased under future scenarios. Even though the areas with high species diversity increased from 0.59% under the current situation to 0.82% and 0.81% under ssp245 in 2021–2040 and 2041–2060, respectively, species diversity showed an apparent loss in parts of the northwest and southeast areas under ssp370 and ssp585. This study can guide susceptible habitat protections under climate change.

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Funding

This work was funded by National Key R&D Program of China (Grant No. 2018YFA0606102), National Natural Science Foundation of China (Grant No. 41901014), and Strategic Priority Research Program of Chinese Academy of Sciences (Grant No. XDA20020202).

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Correspondence to Zexing Tao.

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Tao, Z. Predicting the changes in suitable habitats for six common woody species in Central Asia. Int J Biometeorol 67, 107–119 (2023). https://doi.org/10.1007/s00484-022-02389-w

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  • DOI: https://doi.org/10.1007/s00484-022-02389-w

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