生物多样性 ›› 2018, Vol. 26 ›› Issue (7): 690-700.doi: 10.17520/biods.2018092

所属专题: 生物多样性与生态系统功能

• 研究报告 • 上一篇    下一篇

广西马尾松林植物功能多样性与生产力的关系

黄小荣*()   

  1. 广西壮族自治区林业科学研究院, 南宁 530002
  • 收稿日期:2018-03-27 接受日期:2018-06-03 出版日期:2018-07-20
  • 通讯作者: 黄小荣 E-mail:huangxr2004@sina.com
  • 作者简介:# 共同第一作者
  • 基金项目:
    国家林业局生物安全与遗传资源管理(KJZXSA2018012)、广西科技厅项目(桂科攻14124004-3-11)和国家林业公益性行业科研专项(201204512)

Relationship between plant functional diversity and productivity of Pinus massoniana plantations in Guangxi

Xiaorong Huang*()   

  1. Guangxi Zhuang Autonomous Region Forestry Research Institute, Nanning 530002
  • Received:2018-03-27 Accepted:2018-06-03 Online:2018-07-20
  • Contact: Huang Xiaorong E-mail:huangxr2004@sina.com
  • About author:# Co-first authors

探索植物多样性与生产力的关系可为森林经营与管理提供科学基础。本研究以广西4个地区的马尾松(Pinus massoniana)人工林群落为研究对象, 通过计算物种多样性、功能多样性和功能优势值, 运用相关分析、自动线性建模和方差划分等方法, 分析了多样性与生产力的关系。研究发现, 生产力与物种丰富度、Shannon指数、功能丰富度、功能均匀度极显著正相关(P < 0.01), 与物种均匀度、功能多样性、功能离散度、功能团个数、坡向显著正相关(P < 0.05), 与林龄极显著负相关(P < 0.01), 4个功能多样性参数和4个物种多样性参数两两之间皆为显著正相关; 未发现初始生物量制约生产力的提高; 方差划分最优模型中, 功能多样性参数效应、功能优势值效应和林龄效应分别解释生产力方差的56%、43%和33%, 功能多样性参数效应和功能优势值效应重叠部分高达27%; 生态位互补效应主要由功能丰富度和功能均匀度产生, 选择效应主要由生长型优势值产生; 生长型优势值为灌木的样地生产力较高, 次优种或过渡种对生态系统功能也有重要作用。以生产力为响应变量的自动线性建模最佳子集包括重要性由大到小的5个因素: 林龄、生长型优势值、功能丰富度、功能均匀度、功能团个数。建议维护森林功能多样性, 加强林下叶层植物保护, 用好功能重要的物种, 通过林下叶层的补偿性光合作用和生长竞争, 有效地提高生产力和生物多样性。

关键词: 功能多样性, 功能优势值, 生产力, 林龄, 功能团个数

Understanding the relationship between plant diversity and productivity can provide essential information for forest management. We surveyed plant communities in Pinus massoniana dominated plantations from four regions of Guangxi. Using correlation analysis, automatic linear modeling and variance partitioning, we assessed the effect of species diversity, functional diversity, and functional dominance on productivity. We found that productivity was extremely positively correlated with species richness, Shannon index, functional richness and functional evenness (P < 0.01). Species evenness, RaoQ, functional dispersion, functional group richness and aspect were also positively correlated with productivity (P < 0.05), while forest age was negatively correlated with productivity (P < 0.01). Four functional diversity parameters positively correlated with four species-diversity indices. No evidence of negative density-dependence was found. In the best variance partitioning model, functional diversity parameters, functional dominance and forest age explained 56%, 43% and 33% of variance in productivity respectively; and the overlap between functional diversity parameters and functional dominance was up to 27%. Functional richness and functional evenness were major contributors of complementary effects while community weighted mean (CWM) of growth form contributed to selection effects. Plots identified as dominantly shrub had higher productivity than plots identified as dominantly herbs or trees, suggesting that subordinates and transients may have important effects on ecosystem functions. The best-fit subset model built by automatic linear modeling included forest age, growth form CWM, functional richness, functional evenness and functional group richness (FGR) indescending order. We recommend that to maintain diversity and forest function, protection of understory plant species should be strengthened. Further, to enhance productivity and biodiversity we recommend planting functionally important species through compensatory photosynthesis and growth competition in understorey layers.

Key words: functional diversity, functional dominance, productivity, forest age, functional group richness

表1

样地基本概况和功能优势值"

编号
No.
地区
Site
林龄
Age (yr)
地上生物量 Above-
ground biomass (t·ha-1)
生产力
Produc-
tivity
(t·ha-1·yr-1)
属名优势值
CWM_
genus
叶面积
优势值
CWM_
leafsize
比叶面积优势值 CWM_ sla (mm2·mg-1) 高度优势值
CWM_
height
(m)
生长型
优势值
CWM_
form
功能团
个数Functional group richness (FGR)
乔木多度加和值
Sum of tree abundance
灌木多度加和值
Sum of shrub abundance
草本多度加和值
Sum of herb abundance
1 老虎岭 Laohuling 18 128 7.11 木姜子属 Litsea
Large
12 30 灌木 Shrub 6 25 37 15
2 老虎岭 Laohuling 18 127 7.06 蜜茱萸属 Melicope
Large
12 30 灌木 Shrub 6 30 37 8
3 老虎岭 Laohuling 29 161 5.55 松属
Pinus

Large
12 7 乔木
Tree
6 49 10 12
4 老虎岭 Laohuling 29 156 5.38 锥属
Castanopsis

Large
11 10 乔木
Tree
6 47 16 11
5 老虎岭 Laohuling 29 196 6.76 锥属
Castanopsis

Large
11 10 乔木
Tree
5 43 10 11
6 老虎岭 Laohuling 28 125 4.46 柯属
Lithocarpus

Large
9.7 20 乔木
Tree
3 21 5 13
7 老虎岭 Laohuling 28 162 5.79 柯属
Lithocarpus

Large
9.7 20 乔木
Tree
5 29 6 14
8 老虎岭 Laohuling 28 187 6.68 柯属
Lithocarpus

Large
9.7 14.5 乔木
Tree
5 37 11 11
9 老虎岭 Laohuling 28 127 4.54 柯属
Lithocarpus

Large
9.7 20 乔木
Tree
4 24 16 6
10 老虎岭Laohuling 28 133 4.75 柯属
Lithocarpus

Large
9.7 20 乔木
Tree
6 29 9 11
15 三门江 Sanmenjiang 57 253 4.44 紫金牛属 Ardisia
Large
9.7 20 乔木
Tree
4 35 14 7
16 三门江 Sanmenjiang 57 126 2.21 紫金牛属 Ardisia
Large
9.7 20 乔木
Tree
5 39 13 7
17 三门江 Sanmenjiang 57 214 3.75 松属
Pinus

Large
9.7 30 乔木
Tree
4 44 13 13
18 三门江 Sanmenjiang 57 218 3.82 柯属
Lithocarpus

Large
9.7 30 乔木
Tree
6 37 24 12
19 三门江 Sanmenjiang 57 249 4.37 柯属
Lithocarpus

Large
9.7 30 乔木
Tree
5 40 15 15
23 苍梧 Cangwu 11 96 8.73 松属
Pinus

Middle
15 30 灌木 Shrub 6 35 37 22
24 苍梧 Cangwu 11 97 8.82 松属
Pinus

Large
11 30 乔木
Tree
6 41 29 28
25 苍梧 Cangwu 11 83 7.55 松属
Pinus

Small
11 30 乔木
Tree
6 41 21 32
26 全州
Quanzhou
22 114 5.18 松属
Pinus

Middle
12 30 草本 Herb 4 20 15 22
27 全州
Quanzhou
22 76 3.45 松属
Pinus

Small
12 30 草本 Herb 5 13 8 26
28 全州
Quanzhou
22 77 3.50 松属
Pinus

Small
12 30 草本 Herb 5 13 13 21
29 全州
Quanzhou
22 54 2.45 松属
Pinus

Middle
12 30 草本 Herb 5 14 14 20
30 全州
Quanzhou
22 95 4.32 松属
Pinus

Middle
12 30 草本 Herb 5 17 20 32
31 老虎岭 Laohuling 22 151 6.86 锥属
Castanopsis

Large
12 30 乔木
Tree
5 47 6 7
32 老虎岭 Laohuling 22 124 5.64 松属
Pinus

Large
7.5 30 乔木
Tree
6 29 7 10

表2

功能参数计算方法"

名称 Name R代码Argument 公式 Formula 说明 Note 参考文献Reference
功能优势值Community-level weighted means functcomp (X, comm) $CWM $CWM=\sum\limits_{i=1}^{n}{{{p}_{i}}}\times trai{{t}_{i}}$ 式中pi是物种i的多度, traiti为物种i的性状值, n为物种个数。
In formula, pi is the abundance of species i and traiti is the trait value of species i.
Lavorel
et al, 2008
功能离散度Functional dispersion dbFD (X, comm)
$FDis
$Fdis=\frac{\sum{{{a}_{j}}{{z}_{j}}}}{\sum{{{a}_{j}}}}$ 式中aj为物种j的多度, zj为物种j到加权质心的距离。
Here aj is the abundance of species j, zj is the distance of species j to the centroid.
Laliberté & Legendre, 2010
功能均匀度Functional evenness dbFD (X, comm) $FEve $E{{W}_{l}}=\frac{dist\,(i,j)}{{{w}_{i}}+{{w}_{j}}}$
$PE{{W}_{l}}=\frac{E{{W}_{l}}}{\sum\limits_{l=1}^{S-1}{E{{W}_{l}}}}$
$Feve=\frac{\sum\limits_{l=1}^{S-1}{\min \left( PE{{W}_{l}},\frac{1}{S-1} \right)-\frac{1}{S-1}}}{1-\frac{1}{S-1}}$
Feve为功能均匀度; EWl为加权均匀度; dist (i, j)是物种i和物种j的欧氏距离; PEWl为偏加权均匀度; S是物种数。
Feve is functional evenness; EWl is weighted evenness, dist (i, j) is the Euclidean distance between species i and j, the species involved is branch l in minimum spanning tree, and wi is the relative abundance of species i; PEWl is the partial weighted evenness of branch l; S is species in the community.
Villéger
et al, 2008
功能团个数 A posteriori functional group richness dbFD (X, comm, calc.FGR = TRUE) $FG{{R}_{i}}=Grou{{p}_{present\,in\,plot\,i}}$ FGRi是样地i包含的功能团个数; 本研究指定按功能团总数为6个来分组; dbFD函数默认不计算FGR, 需指定calc.FGR = TRUE。
FGRi is the number of groups present in plot i; and in this study, total functional group was designated as 6. Default dbFD function has set FGR = FALSE and addition is needed in the argument.
Petchey & Gaston, 2006
功能丰富度Functional richness dbFD (X, comm)
$FRic
$\begin{align} & Fri{{c}_{i}}=\text{Number}\,\text{of}\,\text{unique} \\ & \text{trait}\,\text{combination}\,\text{in}\,\text{plot} \\ \end{align}$ 纯数值性状情况下默认使用凸壳体算法计算功能丰富度。如果有一个性状为类型变量, 则全部性状都作为类型变量, 样地i的功能丰富度为其包含的独特性状组合的个数。
The default convex hull volume algorithm for quantitative data is suppressed as categorical traits present in ‘X’. Fric is measured as the number of unique trait combinations in this study.
Villéger
et al, 2008
功能多样性Rao’s quadratic entropy dbFD (X, comm)
$RaoQ
$RaoQ=\sum\limits_{i=1}^{S-1}{\sum\limits_{j=i+1}^{S}{{{d}_{ij}}{{p}_{i}}{{p}_{i}}}}$${{d}_{ij}}=\frac{{{u}_{ij}}}{n}$ 式中dij为物种i和j的距离, pi为物种i的多度, n为研究的性状总数, uij为物种i和j性状值不同的性状数量。
Here dij is the difference between the i-th and j-th species, and pi is abundance of species i; n = total number of traits considered, uij= number of traits with different values in species i and j.
Botta-Dukát, 2005

表3

生产力与多样性参数、林龄、坡向的相关分析"

生产力Produc-
tivity
林龄
Age
坡向
Aspect
功能丰富度 Functional richness (Fric) 功能均匀度 Functional evenness (Feve) 功能离散度 Functional dispersion (Fdis) 功能多样性 Rao’s quadratic entropy (RaoQ) 功能团个数 Functional group richness (FGR) Shannon指数
Shannon index (H)
Simpson指数Simpson index (D) 物种丰富度
Species richness (S)
Age -0.601**
Aspect 0.505* -0.691**
Fric 0.761** -0.342 0.333
Feve 0.577** -0.360 0.277 0.426*
Fdis 0.442* -0.367 0.422* 0.723** 0.544**
RaoQ 0.459* -0.340 0.404* 0.750** 0.545** 0.997**
FGR 0.449* -0.336 0.177 0.615** 0.231 0.597** 0.611**
H 0.608** -0.442* 0.536** 0.814** 0.626** 0.899** 0.900** 0.529**
D 0.395 -0.359 0.504* 0.614** 0.603** 0.863** 0.849** 0.389 0.948**
S 0.722** -0.388 0.371 0.974** 0.433* 0.806** 0.828** 0.654** 0.856** 0.670**
均匀度Evenness 0.441* -0.408* 0.568** 0.596** 0.659** 0.830** 0.815** 0.348 0.943** 0.990** 0.644**

图1

林龄对生物量、生产力、功能丰富度的效应(平均值与95%置信区间, 不同字母表示差异显著)"

图2

生长型性状优势值与生产力、功能丰富度和功能团个数的关系(平均值与95%置信区间, 不同字母表示差异显著)"

表4

生产力方差划分最优模型的归因结果"

全块分量
Full
fractions
解释率
Adjusted R2
单块分量
Individual fractions
解释率
Adjusted
R2
偏分量
Controlling
1 matrix
解释率
Adjusted R2
X1 0.33 X1|X2+X3 0.22 X1|X3 0.12
X2 0.43 X2|X1+X3 0.14 X1|X2 0.31
X3 0.56 X3|X1+X2 0.08 X2|X3 0.04
X1+X2 0.74 X1*X2 -0.10 X2|X1 0.41
X1+X3 0.68 X2*X3 0.27 X3|X1 0.35
X2+X3 0.60 X3*X1 0.09 X3|X2 0.17
X1+X2+X3 0.83 X1*X2*X3 0.12
残差Residual 0.17
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