Relationship between functional diversity and productivity in meadow and marsh plant communities

doi:10.3724/SP.J.1258.2014.00037

Abstract

Abstract:

Aims There are two hypotheses on the mechanism of functional diversity driving ecosystem processes: one is the mass ratio hypothesis based on dominant species, and the other is the diversity hypothesis based on ecological niche. Both hypotheses have been supported by different studies, but their applicability and universality are still controversial. Our objective was to clarify whether the explanatory ability of these two hypotheses to productivity is influenced by the existence of intensive environmental filtering, which was flooding in this study.
Methods Three meadow communities and three marsh communities were studied over two years in the Momoge National Nature Reserve in western Jilin Province. The aboveground biomass, species diversity (species richness and Shannon-Weaver index), functional diversity (community weighted mean and Rao’s quadratic entropy), and several environmental factors were compared among different communities. The functional diversity was calculated for seven plant traits. The relationship between diversity index and aboveground biomass was explored by simple linear regression analysis and multiple linear regression analysis with stepwise method.
Important findings Both Rao’s quadratic entropy and community weighted mean could explain more variation in community productivity than species diversity. Furthermore, both mass ratio hypothesis and diversity hypothesis supported the diversity-productivity relationship. However, the mass ratio hypothesis may play a relatively greater role than the diversity hypothesis, indicating that the ecosystem function mainly depended on the functional traits of dominant species. Intensive environment filtering in terms of flooding affected the diversity-productivity relationship. The mass ratio hypothesis based on community weighted mean explained more variation of the productivity in meadow communities without flooding filtering, while diversity hypothesis based on Rao’s quadratic entropy explained more variation of the productivity in marsh communities with flooding filtering.

Key words: biodiversity, biomass ratio hypothesis, community weighted mean, diversity hypothesis, plant trait, Rao’s quadratic entropy

LÜ Ting-Ting,WANG Ping,YAN Hong,ZHANG Wen,LIAO Gui-Xiang,JIANG Hai-Bo,ZOU Chang-Lin,SHENG Lian-Xi. Relationship between functional diversity and productivity in meadow and marsh plant communities[J]. Chin J Plant Ecol, 2014, 38(5): 405-416.

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URL: https://www.plant-ecology.com/EN/10.3724/SP.J.1258.2014.00037

https://www.plant-ecology.com/EN/Y2014/V38/I5/405

Figures/Tables 9

Table 1 Distribution and characteristics of the experimental sites (mean ± SE)

生境 Habitat	群落 Community	经纬度 Longitude and latitude	海拔 Altitude (m)	群落高度 Community height (cm)	群落盖度 Community cover (%)
草甸 Meadow	芦苇群落 Phragmites australis community	45.87° N, 123.77° E	134.80	32.98 ± 9.42	50.96 ± 3.79
	虎尾草群落 Chloris virgatas community	46.17° N, 123.55° E	146.40	15.45 ± 2.99	23.89 ± 3.91
	碱蓬群落 Suaeda glauca community	46.67° N, 123.52° E	141.10	7.60 ± 1.34	33.84 ± 5.06
沼泽 Marsh	扁秆藨草群落 Scirpus planiculmis community	45.88° N, 123.70° E	138.90	98.85 ± 17.53	70.94 ± 4.25
	扁秆藨草-芦苇群落 Scirpus planiculmis-Phragmites australis community	46.83° N, 123.67° E	135.30	84.54 ± 20.76	45.50 ± 3.76
	芦苇-荆三棱群落 Phragmites australis-Scirpus fluviatilis community	46.10° N, 123.67° E	140.30	90.34 ± 9.95	35.26 ± 4.88

Table 2 T-test between the meadow and marsh sites, and F-test among communities on soil physical and chemical properties

土壤理化性质 Soil physical and chemical property	t检验 t-test	F检验 F-test
土壤理化性质 Soil physical and chemical property	t检验 t-test	草甸 Meadow	沼泽 Marsh
有机质 Organic matter (g·kg^-1)	-7.00^***	13.86 ± 1.03	40.47 ± 3.26^***
全氮 Total nitrogen (g·kg^-1)	-7.07^***	0.78 ± 0.05^***	1.96 ± 0.19^***
全磷 Total phosphorus (g·kg^-1)	-0.70	0.30 ± 0.02	0.28 ± 0.02^***
电导率 Electrical conductivity (μS·cm^-1)	1.79	794.63 ± 112.89^**	550.58 ± 44.09^***
pH	6.88^***	9.97 ± 0.10^***	9.17 ± 0.19^***
水位 Water lever	-	-	29.17 ± 3.04^***

Fig. 1 Species richness (S) and Shannon-Weaver index (H) in different plant communities in meadow (A) and marsh (B). CV, Chloris virgate community; LA, Phragmites australis community; LS, Phragmites australis-Scirpus fluviatilis community; SG, Suaeda glauca community; SL, Scirpus compactus-Phragmites australis community; SP, Scirpus planiculmis community. Different lower-case letters indicate significant differences among communities (p < 0.05).

Fig. 2 Aboveground biomass of different plant communities in meadow (A) and marsh (B). CV, Chloris virgate community; LA, Phragmites australis community; LS, Phragmites australis-Scirpus fluviatilis community; SG, Suaeda glauca community; SL, Scirpus compactus-Phragmites australis community; SP, Scirpus planiculmis community. Different lower-case letters indicate significant differences among communities (p < 0.05).

Fig. 3 Relationships between aboveground biomass (lg transformed) and species diversity (lg transformed) of communities. The bold solid line represents all communities, the thin solid line represents meadow communities, and the dash line represents marsh communities. *, ** and *** indicate p = 0.05, 0.01 and 0.001, respectively.

Fig. 4 Relationships between aboveground biomass (lg transformed) and Rao’s quadratic entropy of different traits of communities. The bold solid line represents all communities, the thin solid line represents meadow communities, and the dash line represents marsh communities. FDH, FDLDMC (lg transformed), FDLignin (lg transformed), FDLS (lg transformed), indicate Rao’s quadratic entropy of plant height, leaf dry matter content, leaf lignin content and leaf size, respectively. *, ** and *** indicate p = 0.05, 0.01 and 0.001, respectively.

Fig. 5 Relationships between aboveground biomass (lg transformed) and community weighted mean of different traits of communities. The bold solid line represents all communities, the thin solid line represents meadow communities, and the dash line represents marsh communities. CWMH (lg transformed), CWMLCC, CWMLDMC, CWMLNC (lg transformed), CWMLS, CWMSLA (lg transformed) indicate community weighted mean of plant height, leaf carbon content, leaf dry matter content, leaf nitrogen content, leaf size and specific leaf area, respectively. *, ** and *** indicate p = 0.05, 0.01 and 0.001, respectively.

Table 4 Stepwise regression equations of community aboveground biomass and diversity

	回归方程Regression equation	R²	p
草甸 Meadow	lgW = 2.735 + 0.967 (0.785) lgCWM_H -1.378 (0.348) lgCWM_SLA	0.747	<0.001
沼泽 Marsh	lgW = 4.724 + 0.655 (0.546) lgFD_LDMC -0.226 (0.345) pH	0.442	<0.001
全部 Total	lgW = 1.877 + 0.569 (0.582) lgFD_LS + 0.291 (0.242) lgFD_LDMC + 0.891 (0.961) lgCWM_H -0.04 (0.768) CWM_LS -0.212 (0.223) FD_SLA	0.702	<0.002

Table 3 Summary of ANOVA on functional diversity among meadow and marsh plant communities

指标 Item	草甸 Meadow			沼泽 Marsh
指标 Item	自由度 df	F检验 F-test	显著性 Sig.	自由度 df	F检验 F-test	显著性 Sig.
CWM_H	29	23.633	< 0.001	21	0.927	0.411
CWM_LCC	29	8.148	0.002	21	4.903	0.018
CWM_LDMC	29	7.304	0.003	21	10.494	0.001
CWM_Lignin	29	3.841	0.033	21	18.966	< 0.001
CWM_LNC	29	5.162	0.012	21	14.541	< 0.001
CWM_LS	29	71.731	< 0.001	21	1.528	0.240
CWM_SLA	29	8.082	0.002	21	1.161	0.332
FD_H	29	3.179	0.056	21	7.791	0.003
FD_LCC	29	10.642	< 0.001	21	2.717	0.089
FD_LDMC	29	14.909	< 0.001	21	14.043	< 0.001
FD_Lignin	29	11.241	< 0.001	21	19.152	< 0.001
FD_LNC	29	9.414	0.001	21	2.301	0.125
FD_LS	29	29.094	< 0.001	21	50.351	< 0.001
FD_SLA	29	8.701	0.001	21	10.245	0.001

References 43

[1]	Aarssen LW (1997). High productivity in grassland ecosystems: effected by species diversity or productive species? Oikos, 80, 183-184. DOI URL
[2]	Bao SD (2005). Soil Agrochemical Analysis. Chinese Agriculture Press, Beijing. 30-34. (in Chinese)
	[ 鲍士旦 (2005). 土壤农化分析. 中国农业出版社, 北京. 30-34.]
[3]	Cadotte MW, Cavender-Bares J, Tilman D, Oakley TH (2009). Using phylogenetic, functional and trait diversity to understand patterns of plant community productivity. PLoS ONE, 4, e5695. DOI URL PMID
[4]	Callaway JC, Sullivan G, Zedler JB (2003). Species-rich plantings increase biomass and nitrogen accumulation in a wetland restoration experiment. Ecology Application, 13, 1626-1639.
[5]	Chanteloup P, Bonis A (2013). Functional diversity in root and above-ground traits in a fertile grassland shows a detrimental effect on productivity. Basic and Applied Ecology, 14, 208-216.
[6]	Cornelissen JHC, Kavorel S, Garnier E, Díaz S, Buchmann N, Gurvich DE, Reich PB, ter Steege H, Morgan HD, van der Heijden MGA, Pausas JG, Poorter H (2003). A handbook of protocols for standardized and easy measurements of plant functional traits worldwide. Annals of Botany, 51, 335-380.
[7]	de Bello F, Lepš J, Sebastià MT (2006). Variations in species and functional plant diversity along climatic and grazing gradients. Ecography, 29, 801-810.
[8]	Díaz S, Cabido M (2001). Vive la difference: plant functional diversity matters to ecosystem processes. Trends in Ecology & Evolution, 16, 646-655.
[9]	Dukat B (2005). Rao’s quadratic entropy as a measure of functional diversity based on multiple traits. Journal of Vegetation Science, 16, 533-540.
[10]	Dukes JS (2001). Productivity and complementarity in grassland microcosms of varying diversity. Oikos, 94, 468-480.
[11]	Garnier E, Cortez J, Billès G, Navas M, Roumet C, Debussche M, Laurent G, Blanchard A, Aubry D, Bellmann A, Neill C, Toussaint JP (2004). Plant functional markers capture ecosystem properties during secondary succession. Ecology, 85, 2630-2637.
[12]	Grime JP (1997). Biodiversity and ecosystem function: the debate deepens. Science, 277, 1260-1261.
[13]	Grime JP (1998). Benefits of plant diversity to ecosystems: immediate, filter and founder effects. Journal of Ecology, 86, 902-910.
[14]	Hector A, Beale AJ, Minns A, Otway SJ, Lawton JH (2000). Consequences of the reduction of plant diversity for litter decomposition: effects through litter quality and microenvironment. Oikos, 90, 357-371.
[15]	Hector A, Schmid B, Beierkuhnlein C, Caldeira MC, Diemer M, Dimitrakopoulos PG, Finn JA, Freitas H, Giller PS, Good J, Harris R, Högberg P, Huss-Danell K, Joshi J, Jumpponen A, Körner C, Leadley PW, Loreau M, Minns A, Mulder CPH, Donovan GO, Otway SJ, Pereira JS, Prinz A, Read DJ, Scherer-Lorenzen M, Schulze ED, Siamantziouras ASD, Spehn EM, Terry AC, Troumbis AY, Woodward FI, Yachi S, Lawton JH (1999). Plant diversity and productivity experiments in European grasslands. Science, 286, 1123-1127.
[16]	Hooper DU (1998). The role of complementarity and competition in ecosystem responses to variation in plant diversity. Ecology, 79, 704-719.
[17]	Hooper DU, Solan M, Symstad AJ, Díaz S, Gessner MO, Buchmann N, Degrande V, Grime JP, Hulot FD, Mermillod- Blondin F, Roy J, Spehn EM, van Peer L (2002). Species Diversity, Functional Diversity, and Ecosystem Functioning. Oxford University Press, Oxford.
[18]	Hooper DU, Vitousek PM (1997). The effects of plant composition and diversity on ecosystem processes. Science, 277, 1302-1305.
[19]	Hooper DU, Vitousek PM (1998). Effects of plant composition and diversity on nutrient cycling. Ecology Monograph, 68, 121-149.
[20]	Huston MA (1997). Hidden treatments in ecological experiments: re-evaluating the ecosystem function of biodiversity. Oecologia, 110, 449-460. DOI URL PMID
[21]	Iiyama K, Wallis AFA (1990). Determination of lignin in herbaceous plants by an improved acetyl bromide procedure. Journal of the Science of Food and Agriculture, 51, 145-161.
[22]	Jiang XL, Zhang WG, Wang G (2007). Effects of different components of diversity on productivity in artificial plant communities. Ecological Research, 22, 629-634.
[23]	Jones RM, Hargreaves JNG (1979). Improvements to the dry-weight-rank method for measuring botanical composition. Grass and Forage Science, 34, 181-189.
[24]	Lepš J, de Bello F, Lavorel S, Berman S (2006). Quantifying and interpreting functional diversity of natural communities: practical considerations matter. Preslia, 78, 481-501.
[25]	Li XG, Zhu ZH, Zhou XS, Yuan FR, Fan RJ, Xu ML (2011). Effects of clipping, fertilizing and watering on the relationship between species diversity, functional diversity and primary productivity in alpine meadow of China. Chinese Journal of Plant Ecology, 35, 1136-1147. (in Chinese with English abstract)
	[ 李晓刚, 朱志红, 周晓松, 袁芙蓉, 樊瑞俭, 许曼丽 (2011). 刈割、施肥和浇水对高寒草甸物种多样性、功能多样性与初级生产力关系的影响. 植物生态学报, 35, 1136-1147.]
[26]	Loreau M, Naeem S, Inchausti P, Bengtsson J, Grime JP, Hector A, Hooper DU, Huston MA, Raffaelli D, Schmid B, Tilman D, Wardle DA (2001). Biodiversity and ecosystem functioning: current knowledge and future challenges. Science, 294, 804-808. DOI URL PMID
[27]	Mannetje L, Haydock KP (1963). The dry-weight-rank method for the botanical analysis of pasture. Journal of the British Grassland Society, 18, 268-275.
[28]	Meng TT, Ni J, Wang GH (2007). Plant functional traits, environment and ecosystem functioning. Journal of Plant Ecology (Chinese Version), 31, 150-165. (in Chinese with English abstract)
	[ 孟婷婷, 倪健, 王国宏 (2007). 植物功能性状与环境和生态系统功能. 植物生态学报, 31, 150-165.]
[29]	Mittelbach GG, Steiner CF, Scheiner SM, Gross KL, Reynoldes HL, Waide RB, Willig MR, Dodson SI, Gough L (2001). What is the observed relationship between species richness and productivity? Ecology, 82, 2381-2396.
[30]	Mokany K, Ash J, Rxburgh S (2008). Functional identity is more important than diversity in influencing ecosystem processes in a temperate native grassland. Journal of Ecology, 96, 884-893.
[31]	Petchey OL, Gaston KJ (2002). Functional diversity (FD), species richness, and community composition. Ecology Letters, 5, 402-411.
[32]	Petchey OL, Hector A, Gaston KJ (2004). How do different measures of functional diversity perform? Ecology, 85, 847-857.
[33]	Roscher C, Schumacher J, Gubsch M, Lipowsky A, Weigelt A, Buchmann N, Schmid B, Schulze ED (2012). Using plant functional traits to explain diversity-productivity relationships. PLoS ONE, 7, e36760. URL PMID
[34]	Roscher C, Temperton VM, Scherer-Lorenzen M, Schmitz M, Schumacher J, Schmid B, Buchmann N, Weisser WW, Ernst-Detlef S (2005). Overyielding in experimental grassland communities irrespective of species pool or spatial scale. Ecology Letters, 8, 419-429.
[35]	Schellberg J, Pontes L da S (2012). Plant functional traits and nutrient gradients on grassland. Grass and Forage Science, 67, 305-319.
[36]	Schulze ED, Mooney HA (1994). Biodiversity and Ecosystem Function. Springer, New York.
[37]	Shannon CE, Weaver W (1971). The Mathematical Theory of Communication. University of Illinois Press, Urbana.
[38]	Tilman D (1997). Distinguishing between the effects of species diversity and species composition. Oikos, 80, 185.
[39]	Tilman D (2001). Functional diversity. Encyclopedia of Biodiversity, 3, 109-120.
[40]	Wacker L, Baudois O, Eichenberger-Glinz S, Schmid B (2009). Diversity effects in early- and mid-successional species pools along a nitrogen gradient. Ecology, 90, 637-648. DOI URL PMID
[41]	Walker B, Kinzig A, Langridge J (1999). Plant attribute diversity, resilience, and ecosystem function: the nature and significance of dominant and minor species. Ecosystems, 2, 95-113.
[42]	Xiao Y, Xie GD, An K, Lu CX (2012). A research framework of ecosystem services based on functional traits. Chinese Journal of Plant Ecology, 36, 353-362. (in Chinese with English abstract) DOI URL
	[ 肖玉, 谢高地, 安凯, 鲁春霞 (2012). 基于功能性状的生态系统服务研究框架. 植物生态学报, 36, 353-362.] DOI URL
[43]	Zang YM, Zhu ZH, Li YN, Wang WJ, Xi B (2009). Effects of species diversity and functional diversity on primary productivity of alpine meadow. Chinese Journal of Ecology, 28, 999-1005. (in Chinese with English abstract)
	[ 臧岳铭, 朱志红, 李英年, 王文娟, 席博 (2009). 高寒矮嵩草草甸物种多样性与功能多样性对初级生产力的影响. 生态学杂志, 28, 999-1005.]