Seasonality and Spatial Pattern of Leaf Area Index of a Spruce-Fir Forest at the Valley in Xiaoxing＇an Mountains | 小兴安岭谷地云冷杉林叶面积指数的季节动态及空间格局

Китайский. 应用半球摄影技术对小兴安岭谷地云冷杉林落叶季节（7-11月）的有效叶面积指数进行动态监测.为准确估测谷地云冷杉林的叶面积指数（LAI）,对叶凋落末期（11月初）的有效叶面积指数（LAIe）进行木质部分及集聚效应（包括冠层水平集聚和针簇内集聚效应）的合理校正,以校正值作为该时期常绿树种的真实叶面积指数（LAIt）,结合凋落物法,反推得到LAIt的季节动态并分析LAIt最大时期（7月）和最小时期（11月）的空间格局特征.结果表明：谷地云冷杉林11月初木质部分所占比例（α）均值为0.10±0.06,冠层水平集聚指数（ΩE）均值为0.90±0.04,常绿针叶树种的针簇内集聚指数（针簇比,γE）为红松（1.77）＞云杉（1.28）＞冷杉（1.10）;LAIt随季节变化呈递减趋势,7月达到峰值（3.97）,11月值最小（2.71）;相对而言,光学仪器法测定的LAIe各调查期的低估范围为28.81％ ～43.24％,平均低估值为32.98％;变异函数分析表明,LAIt大的月份其空间异质性程度也大,7和11月LAIt的空间异质性主要由空间自相关引起,其引起的空间异质性分别占总空间异质性的99.8％,66.9％.

Английский. Leaf area index （LAI） is one of the most frequently used parameters for analysis of canopy structure.We monitored the seasonality of effective leaf area index （LAIe） for a Spruce-fir forest at the valley in Xiaoxing＇an Mountains by using Digital Hemispherical Photography （DHP） during deciduous season （from July to November）.In order to estimate LAI more accurate for the stand,the optically-based effective leaf area index （LAIe） values of early November were adjusted to eliminate wood elements and clumping effects （including both beyond and within shoots）.The adjusted value was regarded as true leaf area index （LAIt） of evergreen species.The seasonal dynamics of LAIt were obtained by incorporation of litterfall data for each observation,and we analyzed spatial pattern of LAIt during the maximum and minimum LAIt period.Results showed that the mean woody-to-total area ratio （α） was 0.10 ± 0.06 and the mean clumping effect （ΩE） was 0.90 ± 0.04 in early November for Spruce-fir forest at the valley,and the order of mean needle-to-shoot area ratio （γE） for evergreen coniferous species was Pinus koraiensis （1.77） ＞ Picea spp.（1.28） ＞ Abies nephrolepis （1.10）.LAIt decreased with season from July to November,and LAIt was highest with a value of 3.97 in July,and lowest in November with a value of 2.71.In comparison with LAIt,LAIe was underestimated by 32.98％ （from 28.81％ to 43.24％）; The spatial heterogeneity of the LAIt was greater with the higher LAIt,and the spatial heterogeneity of LAIt for July and November resulted mainly from the spatial autocorrelation that accounted for 99.8％ and 66.9％ of the total space heterogeneity,respectively.