In order to explore the characteristics of vegetation regeneration in the early stage of the burnt land of Yunnan pine forest.

This study focused on the aftermath of the “4·11” forest fire that occurred in Yuxi City, Yunnan Province in 2023. A total of 54 plots measuring 10 m×10 m were established to represent varying levels of fire intensity. Plant surveys and soil analyses were conducted for understory shrub and tree sapling regeneration, and redundancy analysis was employed to explore the relationship between understory plant recovery characteristics and environmental factors.

The results showed that 162 species of plants of 133 genera and 58 families were identified in the study area. Species diversity indices showed an overall trend of decreasing and then increasing with increasing fire intensity. The Margalef richness index (R) and diversity threshold (E) were positively correlated with fire intensity, and the difference was significant (P<0.05). Redundancy analysis showed that TN, fire intensity, forest stand, elevation and slope aspect are the main explanatory factors affecting species diversity. while the importance value of shrub layer was greatly affected by altitude and forest stand. The regeneration coverage of understory vegetation was 67% for unburned areas, 43% for lightly burned areas, and 32% for severely burned areas. The density of tree seedings was in the order of Low fire intensity > High fire intensity > unburned areas, The regeneration density of the uphill slope was higher than that of the downhill slope in the high fire intensity area. There was a significant negative correlation between tree seedings density and understory vegetation regeneration coverage (P<0.05).

Fire increased the diversity of understory vegetation to a certain extent, low fire intensity was most beneficial to the regeneration of P. yunnanensis seedlings. On severely burned sites, the density of seedings and the regeneration coverage are low, with the risk of soil erosion. The results were of great significance for predicting the structural and functional changes of forest ecosystem and scientific management after fire.