不同时间尺度上西藏色季拉山急尖长苞冷杉林下倒木空间格局分析

Spatial pattern analysis of logs in Abies georgei var.smithii forests in the Sajila Mountains of Tibet at different time scales

【目的】分析西藏色季拉山急尖长苞冷杉(Abies georgei var.smithii)原始林下倒木在不同时间尺度上的空间分布格局及其相关性,探讨该森林生态系统内倒木的分布规律。【方法】在研究区内设置100 m×100 m固定样地,采用相邻网格法对样地内倒木进行调查,获取倒木的大小头直径、长度、腐烂程度、植被覆盖状况、坐标等基本信息,用腐烂等级表征倒木的时间尺度,分析倒木在不同时间尺度上的空间分布格局。【结果】倒木总体空间分布格局随空间尺度的增大依次呈现集群分布、随机分布和均匀分布,且以随机分布为主要特征;在各个时间尺度上的倒木均呈现显著的集群分布;不同时间尺度上的倒木在空间分布上虽无显著关联,但时间尺度间隔越近,越趋于正关联,越远则越趋于负关联。【结论】色季拉山急尖长苞冷杉原始林下倒木在空间分布上具有明显的时间特征,这与当地异常气候密切相关。

【Objective】This study aimed to analyze the spatial distribution pattern and correlation of fallen logs in Abies georgei var.smithii virgin forests distributed in the Sejila Mountain of Southeastern Tibet on different time scales and understand the distribution mechanism of fallen logs in Abies georgei var.smithii forest ecosystem.【Method】Within a 100 m×100 m permanent sample plot,the fallen logs(Abies georgei var.smithii)were surveyed according to neighboring grid method.Information including diameter,length,decaying condition of logs,coordinates and plants coverage was gathered.The time scale was estimated by decaying class and the spatial distribution of fallen logs in different time scales was obtained.【Result】Fallen logs exhibited three distribution patterns in accordance with the size of land plots.As the plot size increased,the logs exhibited aggregation distribution,random distribution and uniformly distribution,with random distribution being the most common distribution.All fallen logs across different time scales exhibited apparent aggregation distribution.Although there was no definitive correlation between spatial distribution patterns at different time scales,closer timing more likely showed positive correlation,while farther timing more likely showed negatively correlation.【Conclusion】The spatial distribution of fallen logs of Abies georgei var.smithii virgin forests on the Sejila Mountain strongly exhibited temporal characteristics and this feature was closely associated with the abnormal climate in the Sejila Mountain.