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Influences of stand, soil and space factors on spatial heterogeneity of leaf area index in a spruce-fir valley forest in Xiao Hinggan Ling, China
YANG Huan-Ying, SONG Jian-Da, ZHOU Tao, JIN Guang-Ze, JIANG Feng, LIU Zhi-Li
Chin J Plant Ecol    2019, 43 (4): 342-351.   DOI: 10.17521/cjpe.2018.0310
Abstract   (1230 HTML76 PDF(pc) (2590KB)(691)  

AimsSpatial heterogeneity of leaf area index (LAI) is very important for exploring the growth and spatial distributions of plants, as well as response strategy of plants to climate changes. Many previous studies have shown that biotic and abiotic factors had significant influences on spatial heterogeneity of LAI. However, few studies have been conducted to show the relative contributions of different influencing factors to the total variations of LAI. Our aim was to quantify the relative contributions of stand, soil and space factors to the total spatial variations of LAI in a spruce-fir valley forest in northeast China.
MethodsWe relied on a 9.12 hm 2 (380 m × 240 m) spruce-fir valley forest plot in Xiao Hinggan Ling, China, which was divided into 228 subplots (20 m × 20 m). First, we measured LAI for each subplot by using the LAI-2200 plant canopy analyzer and then analyzed the spatial heterogeneity of LAI using geo-statistic methods (semivariogram and Kriging interpolation). Second, we measured 28 stand factors and 10 soil factors for each subplot, and quantified space factors using principal coordinates of neighbor matrices (PCNM). Finally, we quantified the relative contributions of stand, soil and space factors to the total spatial variations of LAI using the variance partitioning method.
Important findings The results showed that strong spatial autocorrelations of LAI values within 37 m distances in the spruce-fir valley forest, and the LAI presented different spatial patterns along distinct directions. The stand, soil and space factors totally explained 50.4% of the total spatial variations of LAI in the forest plot. The space factors explained greater spatial variations of LAI in relative to stand and soil factors, and solely explained 25.5% of the total spatial variations. The density of middle tree group (5 cm < diameter at breast height ≤ 10 cm) and basal area of major tree groups (including Abies nephrolepis and Picea spp.) were both significantly and positively correlated with LAI; and soil mass moisture content was significantly and negatively correlated with LAI. These results generally suggest that the spatial autocorrelation is more important than stand factor and soil factor for determining spatial heterogeneity of LAI of the spruce-fir valley forest in Xiao Hinggan Ling, China.


理论模型
Theory model
块金值
Nugget (C0)
基台值
Sill (C0 + C)
空间结构比
Spatial structure ratio C0/(C0 + C)
变程
Range (A, m)
决定系数
R2
高斯模型 Gaussian 0.204 1.751 0.117 37 0.887
指数模型 Exponential 0.251 2.541 0.099 53 0.859
球状模型 Spherical 0.079 2.519 0.031 43 0.880
Table 1 Theory semivariogram theoretical models and fitted parameters for leaf area index (LAI) values in a spruce-fir valley forest in Xiao Hinggan Ling, China
Extracts from the Article
小兴安岭谷地云冷杉林LAI在样地内呈正态分布, LAI值为4-5的样方约占总样方数的25%; 且LAI具有中等强度变异性, 变异系数(CV)为32% (图1)。LAI变异函数的最优理论模型为高斯模型, R2值为0.887 (表1)。由随机因素产生的变异占LAI总变异的11.7%, 即空间结构比为0.117, LAI在37 m尺度内具有很强的空间自相关(表1)。此外, 谷地云冷杉林的LAI呈斑块状分布, 样地边缘的LAI主要分布在4-5之间(图2)。
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