广西马尾松林植物功能多样性与生产力的关系

doi:10.17520/biods.2018092

摘要/Abstract

摘要：

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

Abstract

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

黄小荣 (2018) 广西马尾松林植物功能多样性与生产力的关系. 生物多样性, 26, 690-700. DOI: 10.17520/biods.2018092.

Xiaorong Huang (2018) Relationship between plant functional diversity and productivity of Pinus massoniana plantations in Guangxi. Biodiversity Science, 26, 690-700. DOI: 10.17520/biods.2018092.

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链接本文: https://www.biodiversity-science.net/CN/10.17520/biods.2018092

https://www.biodiversity-science.net/CN/Y2018/V26/I7/690

图/表 6

参考文献 43

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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	大 Large	12	30	灌木 Shrub	6	25	37	15
2	老虎岭 Laohuling	18	127	7.06	蜜茱萸属 Melicope	大 Large	12	30	灌木 Shrub	6	30	37	8
3	老虎岭 Laohuling	29	161	5.55	松属 Pinus	大 Large	12	7	乔木 Tree	6	49	10	12
4	老虎岭 Laohuling	29	156	5.38	锥属 Castanopsis	大 Large	11	10	乔木 Tree	6	47	16	11
5	老虎岭 Laohuling	29	196	6.76	锥属 Castanopsis	大 Large	11	10	乔木 Tree	5	43	10	11
6	老虎岭 Laohuling	28	125	4.46	柯属 Lithocarpus	大 Large	9.7	20	乔木 Tree	3	21	5	13
7	老虎岭 Laohuling	28	162	5.79	柯属 Lithocarpus	大 Large	9.7	20	乔木 Tree	5	29	6	14
8	老虎岭 Laohuling	28	187	6.68	柯属 Lithocarpus	大 Large	9.7	14.5	乔木 Tree	5	37	11	11
9	老虎岭 Laohuling	28	127	4.54	柯属 Lithocarpus	大 Large	9.7	20	乔木 Tree	4	24	16	6
10	老虎岭Laohuling	28	133	4.75	柯属 Lithocarpus	大 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	大 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	大 Large	9.7	20	乔木 Tree	5	39	13	7
17	三门江 Sanmenjiang	57	214	3.75	松属 Pinus	大 Large	9.7	30	乔木 Tree	4	44	13	13
18	三门江 Sanmenjiang	57	218	3.82	柯属 Lithocarpus	大 Large	9.7	30	乔木 Tree	6	37	24	12
19	三门江 Sanmenjiang	57	249	4.37	柯属 Lithocarpus	大 Large	9.7	30	乔木 Tree	5	40	15	15
23	苍梧 Cangwu	11	96	8.73	松属 Pinus	中 Middle	15	30	灌木 Shrub	6	35	37	22
24	苍梧 Cangwu	11	97	8.82	松属 Pinus	大 Large	11	30	乔木 Tree	6	41	29	28
25	苍梧 Cangwu	11	83	7.55	松属 Pinus	小 Small	11	30	乔木 Tree	6	41	21	32
26	全州 Quanzhou	22	114	5.18	松属 Pinus	中 Middle	12	30	草本 Herb	4	20	15	22
27	全州 Quanzhou	22	76	3.45	松属 Pinus	小 Small	12	30	草本 Herb	5	13	8	26
28	全州 Quanzhou	22	77	3.50	松属 Pinus	小 Small	12	30	草本 Herb	5	13	13	21
29	全州 Quanzhou	22	54	2.45	松属 Pinus	中 Middle	12	30	草本 Herb	5	14	14	20
30	全州 Quanzhou	22	95	4.32	松属 Pinus	中 Middle	12	30	草本 Herb	5	17	20	32
31	老虎岭 Laohuling	22	151	6.86	锥属 Castanopsis	大 Large	12	30	乔木 Tree	5	47	6	7
32	老虎岭 Laohuling	22	124	5.64	松属 Pinus	大 Large	7.5	30	乔木 Tree	6	29	7	10

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	大 Large	12	30	灌木 Shrub	6	25	37	15
2	老虎岭 Laohuling	18	127	7.06	蜜茱萸属 Melicope	大 Large	12	30	灌木 Shrub	6	30	37	8
3	老虎岭 Laohuling	29	161	5.55	松属 Pinus	大 Large	12	7	乔木 Tree	6	49	10	12
4	老虎岭 Laohuling	29	156	5.38	锥属 Castanopsis	大 Large	11	10	乔木 Tree	6	47	16	11
5	老虎岭 Laohuling	29	196	6.76	锥属 Castanopsis	大 Large	11	10	乔木 Tree	5	43	10	11
6	老虎岭 Laohuling	28	125	4.46	柯属 Lithocarpus	大 Large	9.7	20	乔木 Tree	3	21	5	13
7	老虎岭 Laohuling	28	162	5.79	柯属 Lithocarpus	大 Large	9.7	20	乔木 Tree	5	29	6	14
8	老虎岭 Laohuling	28	187	6.68	柯属 Lithocarpus	大 Large	9.7	14.5	乔木 Tree	5	37	11	11
9	老虎岭 Laohuling	28	127	4.54	柯属 Lithocarpus	大 Large	9.7	20	乔木 Tree	4	24	16	6
10	老虎岭Laohuling	28	133	4.75	柯属 Lithocarpus	大 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	大 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	大 Large	9.7	20	乔木 Tree	5	39	13	7
17	三门江 Sanmenjiang	57	214	3.75	松属 Pinus	大 Large	9.7	30	乔木 Tree	4	44	13	13
18	三门江 Sanmenjiang	57	218	3.82	柯属 Lithocarpus	大 Large	9.7	30	乔木 Tree	6	37	24	12
19	三门江 Sanmenjiang	57	249	4.37	柯属 Lithocarpus	大 Large	9.7	30	乔木 Tree	5	40	15	15
23	苍梧 Cangwu	11	96	8.73	松属 Pinus	中 Middle	15	30	灌木 Shrub	6	35	37	22
24	苍梧 Cangwu	11	97	8.82	松属 Pinus	大 Large	11	30	乔木 Tree	6	41	29	28
25	苍梧 Cangwu	11	83	7.55	松属 Pinus	小 Small	11	30	乔木 Tree	6	41	21	32
26	全州 Quanzhou	22	114	5.18	松属 Pinus	中 Middle	12	30	草本 Herb	4	20	15	22
27	全州 Quanzhou	22	76	3.45	松属 Pinus	小 Small	12	30	草本 Herb	5	13	8	26
28	全州 Quanzhou	22	77	3.50	松属 Pinus	小 Small	12	30	草本 Herb	5	13	13	21
29	全州 Quanzhou	22	54	2.45	松属 Pinus	中 Middle	12	30	草本 Herb	5	14	14	20
30	全州 Quanzhou	22	95	4.32	松属 Pinus	中 Middle	12	30	草本 Herb	5	17	20	32
31	老虎岭 Laohuling	22	151	6.86	锥属 Castanopsis	大 Large	12	30	乔木 Tree	5	47	6	7
32	老虎岭 Laohuling	22	124	5.64	松属 Pinus	大 Large	7.5	30	乔木 Tree	6	29	7	10

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p_i是物种i的多度, trait_i为物种i的性状值, n为物种个数。 In formula, p_i is the abundance of species i and trait_i 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a_j为物种j的多度, z_j为物种j到加权质心的距离。 Here a_j is the abundance of species j, z_j 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; EW_l为加权均匀度; dist (i, j)是物种i和物种j的欧氏距离; PEW_l为偏加权均匀度; S是物种数。 Feve is functional evenness; EW_l 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 w_i is the relative abundance of species i; PEW_l 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)	$FG{{R}_{i}}=Grou{{p}_{present\,in\,plot\,i}}$	FGR_i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。 FGR_i 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d_ij为物种i和j的距离, p_i为物种i的多度, n为研究的性状总数, u_ij为物种i和j性状值不同的性状数量。 Here d_ij is the difference between the i-th and j-th species, and p_i is abundance of species i; n = total number of traits considered, u_ij= number of traits with different values in species i and j.	Botta-Dukát, 2005

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p_i是物种i的多度, trait_i为物种i的性状值, n为物种个数。 In formula, p_i is the abundance of species i and trait_i 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a_j为物种j的多度, z_j为物种j到加权质心的距离。 Here a_j is the abundance of species j, z_j 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; EW_l为加权均匀度; dist (i, j)是物种i和物种j的欧氏距离; PEW_l为偏加权均匀度; S是物种数。 Feve is functional evenness; EW_l 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 w_i is the relative abundance of species i; PEW_l 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)	$FG{{R}_{i}}=Grou{{p}_{present\,in\,plot\,i}}$	FGR_i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。 FGR_i 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d_ij为物种i和j的距离, p_i为物种i的多度, n为研究的性状总数, u_ij为物种i和j性状值不同的性状数量。 Here d_ij is the difference between the i-th and j-th species, and p_i is abundance of species i; n = total number of traits considered, u_ij= number of traits with different values in species i and j.	Botta-Dukát, 2005

	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^**