The impact of climate change on the distribution of rare and endangered tree Firmiana kwangsiensis using the Maxent modeling

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Abstract

The upsurge in anthropogenic climate change has accelerated the habitat loss and fragmentation of wild animals and plants. The rare and endangered plants are important biodiversity elements. However, the lack of comprehensive and reliable information on the spatial distribution of these organisms has hampered holistic and efficient conservation management measures. We explored the consequences of climate change on the geographical distribution of Firmiana kwangsiensis (Malvaceae), an endangered species, to provide a reference for conservation, introduction, and cultivation of this species in new ecological zones. Modeling of the potential distribution of F. kwangsiensis under the current and two future climate scenarios in maximum entropy was performed based on 30 occurrence records and 27 environmental variables of the plant. We found that precipitation-associated and temperature-associated variables limited the potentially suitable habitats for F. kwangsiensis. Our model predicted 259,504 km2 of F. kwangsiensis habitat based on 25 percentile thresholds. However, the high suitable habitat for F. kwangsiensis is only about 41,027 km2. F. kwangsiensis is most distributed in Guangxi's protected areas. However, the existing reserves are only 2.7% of the total suitable habitat and 4.2% of the high suitable habitat for the plant, lower than the average protection area in Guangxi (7.2%). This means the current protected areas network is insufficient, underlining the need for alternative conservation mechanisms to protect the plant habitat. Our findings will help identify additional F. kwangsiensis localities and potential habitats and inform the development and implementation of conservation, management, and cultivation practices of such rare tree species.

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Gao, X., Liu, J., & Huang, Z. (2022). The impact of climate change on the distribution of rare and endangered tree Firmiana kwangsiensis using the Maxent modeling. Ecology and Evolution, 12(8). https://doi.org/10.1002/ece3.9165

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