Response of Leaf Traits and Photosynthetic Fluorescence Characteristics of Fraxinus malacophylla Seedlings to Rainfall Patterns During Dry and Rainy Seasons in Southwestern China

Global climate change has led to a shift in rainfall patterns. And as water is an essential ingredient for plant photosynthesis, shifts in rainfall patterns will inevitably affect plant growth. This study was conducted in Kunming, southwest China. In this study, the response of leaf traits and photosynthetic fluorescence properties of Fraxinus malacophylla seedlings to rainfall patterns during the dry and rainy seasons was investigated using a natural rainfall interval of 5 days (T) and an extended rainfall interval of 10 days (T₊) as rainfall interval treatments and a monthly average rainfall as a control (W), with the corresponding rainfall treatments of a 40% increase in rainfall (W₊) and a 40% decrease in rainfall (W_-). The results showed that Pn, Gs, and Tr basically all tended to increase and then decrease with increasing rainfall in the dry season and generally reached the highest under the W treatment; Pn, Gs, Ci, and Tr mostly remained high at 5 days relative to 10 days; PI was overall higher under the W treatment throughout the dry season. Extending the rainfall interval at the beginning of the rainy season significantly reduced Fm; throughout the rainy season, Gs, Ci, and Tr basically showed a decreasing trend with increasing rainfall, reaching the highest under the W-treatment and mostly higher at 5 days than at 10 days. These results suggest that natural rainfall intervals and natural rainfall amounts are more favorable to the growth of Fraxinus malacophylla seedlings in the dry season; reduced rainfall and multiple rainfalls in the rainy season tend to promote photosynthesis in Fraxinus malacophylla. This study reflects the different survival strategies of Fraxinus malacophylla under different rainfall patterns, as well as provides a theoretical basis for understanding how Fraxinus malacophylla can grow better under rainfall variability and for future management.