天山天然云杉林小蠹优势种及其空间分布格局OA

[Objective]Severe damage has been observed in the natural Picea schrenkiana forests of eastern Tianshan,Xinjiang,while research on wood-boring pest communities and their distribution patterns in the region remains limited.This study aimed to characterize the community composition and spatial distribution patterns of wood-boring pest in Picea schrenkiana forests and to identify the dominant pest species and their spatial niches,providing a scientific basis for precise monitoring and effective management.[Method]Field surveys,pheromone trapping,and stem analysis were used to assess wood-boring pest communities across stands with different damage severities.A Stand Integrated Damage Index(SI)was developed to quantify stand damage severity,and community composition,dominant species,and spatial niche relationships were analyzed.[Result]Damage severity was higher in the eastern than in the western Tianshan Mountains.SI was strongly and positively correlated with the mean number of individuals captured per trap(rs=0.881,P＜0.01),but was not significantly associated with community diversity.Ips hauseri was the absolute dominant species in the Eastern Tianshan,followed by Pityogenes spessivtsevi,I.hauseri predominantly occupied the lower-middle trunk(4-10 m)and on larger-diameter stems and branches(D＞10 cm),P.spessivtsevi was concentrated in the upper-middle trunk(9-17 m)and on smaller-diameter stems and branches(D≤10 cm).The two species showed low niche overlap,niche similarity,and interspecific competition along both vertical and diameter gradients,indicating pronounced spatial niche differentiation.[Conclusion]At the regional,community and individual-tree scales,damage severity of P.schrenkiana stands in the Tianshan Mountains showed clear spatial differentiation,and the two dominant bark beetles exhibited distinct spatial niche differentiation.The high population density of I.hauseri was a key biotic factor for the damage in the eastern Tianshan Mountains.A multi-scale monitoring system integrating regional risk zonation and dominant-species surveys is recommended to improve early warning and precision management.