植物生态学报 ›› 2012, Vol. 36 ›› Issue (4): 269-280.DOI: 10.3724/SP.J.1258.2012.00269
• 研究论文 • 下一篇
黄运峰1,丁易1,臧润国1,*(),李小成2,邹正冲2,韩文涛2
收稿日期:
2011-10-29
接受日期:
2012-01-12
出版日期:
2012-10-29
发布日期:
2012-03-28
通讯作者:
臧润国
HUANG Yun-Feng1,DING Yi1,ZANG Run-Guo1,*(),LI Xiao-Cheng2,ZOU Zheng-Chong2,HAN Wen-Tao2
Received:
2011-10-29
Accepted:
2012-01-12
Online:
2012-10-29
Published:
2012-03-28
Contact:
ZANG Run-Guo
摘要:
树木空间格局及其形成过程是物种共存及生物多样性维持机制研究的一个重要方面。该文以海南岛两个1 hm 2的典型热带低地雨林老龄林森林动态样地为基础, 通过4个点格局模型(均质Poisson过程、异质Poisson过程、均质Thomas过程和异质Thomas过程)模拟扩散限制和生境异质性作用对树木空间分布格局的影响, 并分析不同空间尺度下(< 2 m, 2-5 m, 5-10 m, 10-15 m, 15-20 m和20-25 m)不同作用的相对重要性。结果表明: 热带低地雨林的所有树木总体上呈现聚集分布的空间格局, 随着尺度的增大, 聚集强度逐渐减小。树种在模拟空间分布格局最优模型中的比例由高到低分别是: 均质Thomas过程, 均质Poisson过程、异质Thomas过程和异质Poisson过程。扩散限制作用是形成热带低地雨林树木空间分布格局最重要的生态过程, 其次是完全随机作用以及生境异质性和扩散限制的联合作用, 而生境异质性的作用最小。不同空间尺度上模拟各树种空间分布格局的最优模型比例差异显著, 扩散限制作用能够在多数空间尺度上模拟多个树种的空间分布格局, 其次为随机作用; 生境异质性和扩散限制的联合作用主要在小尺度(0-5 m)影响树种分布, 而生境异质性在较大尺度(15-25 m)上影响树种的空间分布格局。
黄运峰,丁易,臧润国,李小成,邹正冲,韩文涛. 海南岛霸王岭热带低地雨林树木的空间格局. 植物生态学报, 2012, 36(4): 269-280. DOI: 10.3724/SP.J.1258.2012.00269
HUANG Yun-Feng,DING Yi,ZANG Run-Guo,LI Xiao-Cheng,ZOU Zheng-Chong,HAN Wen-Tao. Spatial pattern of trees in tropical lowland rain forest in Bawangling of Hainan Island, China. Chinese Journal of Plant Ecology, 2012, 36(4): 269-280. DOI: 10.3724/SP.J.1258.2012.00269
图1 两个样地(LOG1和LOG2)中胸径(DBH) ≥ 1 cm植株的种多度累积曲线、种多度等级分布曲线(多度进行对数转换)、径级结构和树高分布结构。LOG1和LOG2是面积均为1 hm2的森林动态样地。
Fig. 1 The species-abundance accumulation curve, species rank-abundance distribution curve (log-abundances), and distribution structure of DBH class, and height class of trees (DBH ≥ 1 cm) in LOG1 and LOG2 plots. DBH, diameter at breast height. LOG1 and LOG2 are forest dynamic plots with 1-hm2 area.
图2 基于样地水平的个体空间格局及其对应的L函数值和配对关联函数值。灰色线表示在α = 0.01水平由均质Poisson模型拟合的置信区间; 灰色最小点表示胸径DBH < 10 cm的个体; 黑色圆圈大小表示对应的径级大小。X, 东西方向; Y, 南北方向; LOG1和LOG2是面积均为1 hm2的森林动态样地。L(r)表示Ripley’s K函数值; g(r)表示配对关联函数值。
Fig. 2 Plot-level patterns of stems and their corresponding L-functions and pair correlation functions (PCFs). Confidence envelopes (gray lines) estimated at the α = 0.01 level using a homogeneous Poisson model. In the maps of two plots, smallest dots represent trees < 10 cm in diameter at breast height (DBH), and the circle sizes are proportional to the DBH classes. X, west-east direction; Y, south-north direction; LOG1 and LOG2 are forest dynamic plots with 1-hm2 area. L(r) represent the value of Ripley’s K function; g(r) represent the value of pair correlation function.
模型 Model | LOG1 | LOG2 |
---|---|---|
均质Poisson过程 Homogenous Poisson process | 26% (18) | 33% (20) |
异质Poisson过程 Inhomogenous Poisson process | 13% (9) | 10% (6) |
均质Thomas过程 Homogenous Thomas process | 38% (26) | 43% (26) |
异质Thomas过程 Inhomogenous Thomas process | 23% (16) | 15% (9) |
表1 各样地内最优拟合模型树种所占的比例
Table 1 Proportion of the best-fit models for tree species in each plot
模型 Model | LOG1 | LOG2 |
---|---|---|
均质Poisson过程 Homogenous Poisson process | 26% (18) | 33% (20) |
异质Poisson过程 Inhomogenous Poisson process | 13% (9) | 10% (6) |
均质Thomas过程 Homogenous Thomas process | 38% (26) | 43% (26) |
异质Thomas过程 Inhomogenous Thomas process | 23% (16) | 15% (9) |
图3 不同样地内物种的个体多度与对应的最优拟合模型的Box-and-whisker图。HP, 均质Poisson过程; IP, 异质Poisson过程; ITH, 异质Thomas过程; TH, 均质Thomas过程。虚线表示最低和最大观测值, 图框表示下四分位值和上四分位值, 黑点表示中值, 圆圈表示异常值。LOG1和LOG2是面积均为1 hm2的森林动态样地。
Fig. 3 Box-and-whisker plot of species abundance classified by the best-fit model of each species in each plot. HP, homogenous Poisson process; IP, inhomogenous Poisson process; ITH, inhomogenous Thomas process; TH, homogenous Thomas process. Dashed lines represent the smallest observation and the largest observation, the hinges of box represent lower quartile and upper quartile, black dots represent median, and circles represent outliers. LOG1 and LOG2 are forest dynamic plots with 1-hm2 area.
图4 LOG1和LOG2样地内物种的分布图。黑点分别表示芳槁润楠(LOG1)和白茶(LOG2)。X, 东西方向; Y, 南北方向; LOG1和LOG2是面积均为1 hm2的森林动态样地。
Fig. 4 Distribution map of plant species in LOG1 and LOG2 plots. Black dots represent Machilus suaveolens (LOG1) and Koilodepas hainanense (LOG2), respectively. X, west-east direction; Y, south-north direction; LOG1 and LOG2 are forest dynamic plots with 1-hm2 area.
图5 由4个空间格局模型拟合物种空间分布的典型例子。LOG1和LOG2是面积均为1 hm2的森林动态样地。LOG1中芳槁润楠能被均质Thomas过程拟合; LOG2中白茶能被异质Thomas过程拟合。实线L(r)值表示实测观察值, 虚线为由蒙特卡罗模拟产生的95%置信区间的上限和下限, r表示距离。HP, 均质Poisson过程; IP, 异质Poisson过程; ITH, 异质Thomas过程; TH, 均质Thomas过程。
Fig. 5 Typical example of spatial distribution of species fit by each of the four spatial pattern models. LOG1 and LOG2 are forest dynamic plots with 1-hm2 area. The Thomas process provides the best fit to Machilus suaveolens at LOG1, and the inhomogeneous Thomas process provides the best fit to Koilodepas hainanense at LOG2. The observed L(r) values are expressed as solid lines and the dashed lines represent the upper and lower limits of the 95% confidence intervals of L(r) generated by Monte Carlo simulation, where r represents the distance. HP, homogenous Poisson process; IP, inhomogenous Poisson process; ITH, inhomogenous Thomas process; TH, homogenous Thomas process.
图6 各样地中不同空间尺度下最优拟合模型物种所占的比例。LOG1和LOG2是面积均为1 hm2的森林动态样地。白色条形表示均质Poisson过程; 灰色条形表示异质Poisson过程; 深灰色条形表示均质Thomas过程; 黑色条形表示异质Thomas过程。罗马字母代表不同的尺度范围, I: <2 m; II: 2-5 m; III: 5-10 m; IV: 10-15 m; V: 15-20 m; VI: 20-25 m。
Fig. 6 Proportion of the best-fit models for tree species in each plot at varying spatial scales. LOG1 and LOG2 are forest dynamic plots with 1-hm2 area. White bars represent homogenous Poisson process; grey bars represent inhomogenous Poisson process; dark grey represent homogenous Thomas process; black bars represent inhomogenous Thomas process. Roman letters represent different scales, I: <2 m; II: 2-5 m; III: 5-10 m; IV: 10-15 m; V: 15-20 m; VI: 20-25 m.
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