Predicting the impact of climate change on the distribution of two relict Liriodendron species by coupling the MaxEnt model and actual physiological indicators in relation to stress tolerance.

Climate change has a crucial impact on the distributions of plants, especially relict species. Hence, predicting the potential impact of climate change on the distributions of relict plants is critical for their future conservation. Liriodendron plants are relict trees, and only two natural species have survived: L. chinense and L. tulipifera. However, the extent of the impact of future climate change on the distributions of these two Liriodendron species remains unclear. Therefore, we predicted the suitable habitat distributions of two Liriodendron species under present and future climate scenarios using MaxEnt modeling. The results showed that the area of suitable habitats for two Liriodendron species would significantly decrease. However, the two relict species presented different habitat shift patterns, with a local contraction of suitable habitat for L. chinense and a northward shift in suitable habitat for L. tulipifera, indicating that changes in environmental factors will affect the distributions of these species. Among the environmental factors assessed, May precipitation induced the largest impact on the L. chinense distribution, while L. tulipifera was significantly affected by precipitation in the driest quarter. Furthermore, to explore the relationship between habitat suitability and Liriodendron stress tolerance, we analyzed six physiological indicators of stress tolerance by sampling twelve provenances of L. chinense and five provenances of L. tulipifera. The composite index of six physiological indicators was significantly negatively correlated with the habitat suitability of the species. The stress tolerance of Liriodendron plants in highly suitable areas was lower than that in areas with moderate or low suitability. Overall, these findings improve our understanding of the ecological impacts of climate change, informing future conservation efforts for Liriodendron species.