Ecol Res (2005) 20: 563–572 DOI 10.1007/s11284-005-0069-2
O R I GI N A L A R T IC L E
Guo-Hong Wang Æ Jian Ni
Responses of plant functional types to an environmental gradient on the Northeast China Transect
Received: 12 November 2004 / Accepted: 28 February 2005 / Published online: 24 May 2005 The Ecological Society of Japan 2005
Abstract The hypothesis that some plant traits such as life form are robust surrogates for plant functional type (PFT) has provoked an ongoing debate. Based on a dataset from the Northeast China Transect (NECT), we attempted to test the hypothesis by comparing an objective PFT identification framework in which large datasets of plant traits were considered with two subjective PFT frameworks in which only a few plant traits were involved. Additionally, we addressed the relations between the relative abundance of PFTs and the environmental gradient represented by actual evapotranspiration (AET) along the NECT. We also discuss the changes in ecosystem functioning associated with the PFT turnover along the environmental gradient. Based on an objective PFT classification, eight PFTs were identified: deciduous trees, shrubs, perennial forbs with lower net photosynthesis, perennial forbs with higher net photosynthesis, perennial bulb-grasses, perennial tillergrasses, annual C4 herbs and evergreen trees. Our results indicated that some plant traits, such as life form and photosynthesis pathway, are robust surrogates for PFTs, implying that subjective approaches to PFT classification are useful. Nonetheless, caution should be used during the classification of PFTs. The framework adopted for PFT classification should depend on the specific scientific issues being dealt with. It is therefore meaningless to pursue a general framework for the identification of PFTs even within given plant commu-
G.-H. Wang (&) Æ J. Ni Laboratory of Quantitative Vegetation Ecology, Institute of Botany, The Chinese Academy of Sciences, 20 Nanxincun Xiangshan, 100093 Beijing, The People’s Republic of China E-mail:
[email protected] J. Ni Max Planck Institute for Biogeochemistry, PO Box 100164, 07701 Jena, Germany
nities. On the other hand, our quantitative classification of PFTs confirmed recurrent patterns with respect to PFT turnover along an environmental gradient. Furthermore, with the turnover in PFT along the NECT from the west to the east, ecosystem properties such as productivity and carbon storage are predicted to decrease, while photosynthesis is predicted to increase, suggesting that PFT turnover would inevitably lead to changes in ecosystem functioning. Key words Life form Æ Plant traits Æ Actual evapotranspiration (AET) Æ Productivity Æ Carbon storage Æ Photosynthesis pathway
Introduction Plant functional types (PFTs) are defined as groups of plants exhibiting either similar responses to an environment or similar effects on major ecosystem processes (Noble and Gitay 1996; Skarpe 1996; Diaz and Cabido 1997; Duckworth et al. 2000; Kleyer 2002; Lavorel and Garnier 2002). PFTs are considered to be a powerful linkage bridging the gap between plant physiology and ecosystem processes (Diaz and Cabido 1997), providing a promising framework for predicting ecosystem response to human-induced global changes (Diaz and Cabido 1997; Craine et al. 2001; Lavorel and Garnier 2002). The Northeast China Transect (NECT), one of the 15 IGBP Terrestrial Transects (Canadell et al. 2002), represents a semi-arid environmental gradient in the midlatitude area (Zhang et al. 1997; Ni and Zhang 2000). In previous studies, PFTs identified on the NECT were basically based on subjective approaches using either plant life form and vegetation type (Jiang et al. 1999; Jiang and Dong 2000; Ni 2003) or photosynthetic pathway (Tang 1999) as the major plant traits. Subjective life form classifications have been repeatedly found to reflect broad ecosystem functions (Aguiar et al.
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1996; Chapin et al. 1996). However, many correlations among traits that hold true over entire floras may not be relevant under less contrasted ranges of conditions (McIntyre et al. 1999). Thus the use of a surrogate (such as life form) may lead to loss of information unique to particular traits, and consequently impose limitations when clarifying the underlying mechanisms that operate in the context of plant response to environmental gradient (Boutin and Keddy 1993; Lavorel and Garnier 2002). In addition, previous studies conducted on the NECT examining PFT–environment relations are restricted to a part of the transect, mainly the Inner Mongolia steppes (Tang 1999; Ni 2003). Although Jiang et al. (1999) and Jiang and Dong (2000) conducted a field observation throughout the entire transect, they mainly focused on the response of plant physiological properties to the environmental gradient. Studies concerning either objective PFT classification or PFT responses to the major environmental gradient along the NECT are absent (Ni and Wang 2004). In this paper, based on data from field surveys across the entire range of the NECT, we attempted to answer three questions: What PFTs will emerge if objective approaches are involved and sets of plant traits are considered? How do PFTs respond to the major envi-
ronmental gradient along the NECT? Would PFT turnover inevitably lead to changes in ecosystem functioning?
Methods The Northeast China Transect The NECT runs parallel to the 43.5N with latitudes ranging from 42–46N and longitudes from 108–132E. The NECT is ca. 1,600 km in length and ca. 300 km in width, and is located in the temperate zone of the mid-latitude area (Zhang et al. 1997). The major environmental gradient is precipitation, ranging from 600– 1,000 mm in the east, to 300–600 mm in the mid-part, to 100–300 mm in the west. Mean annual temperature ranges from 1.8–5.8C (Zhang et al. 1997; Ni and Zhang 2000). Due to the steep rainfall gradient, vegetation along the transect varies gradually from temperate evergreen conifer–deciduous broad-leaved forests dominated by Pinus koraiensis, Abies fabri, Picea jezoensis, and Fraxinus mandshurica; to temperate deciduous broad-leaved forests dominated by Quercus mongolicus and Juglans mandshurica; to meadow steppe and typical
Table 1 Summary of the 27 sites that were surveyed along the Northeast China Transect (NECT) in 2001 Site no.
Latitude (N)
Longitude (E)
Altitude (m)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27
4322¢1100 431¢2300 4313¢1100 4314¢5800 4322¢1900 4354¢0000 4413¢1700 4412¢2500 4333¢5700 4334¢0500 4336¢500 4338¢1100 4349¢5500 4339¢2500 4314¢4300 4318¢5500 4330¢2000 4331¢0200 4338¢3100 4356¢4000 4354¢3200 4353¢5100 4354¢4500 4347¢3500 4345¢5300 4340¢4800 4340¢5600
1318¢3200 13019¢3400 13020¢4900 12838¢3800 12754¢2200 12626¢5000 12557¢2200 12356¢1400 12318¢2400 12159¢4500 12102¢4600 12050¢3600 11911¢3300 11851¢4300 11836¢4700 11704¢4500 11649¢3000 11650¢5000 11642¢0200 11558¢2100 11526¢5600 11520¢5800 11425¢2300 11319¢0200 11308¢2500 11157¢2500 11157¢2400
680 339 510 650 720 260 243 243 160 207 280 315 626 645 664 1,300 1,459 1,448 1,248 1,060 1,182 1,199 1,012 1,033 1,065 993 993
Mean annual temperature (C)
Mean annual precipitation (mm)
AET (mm)
Vegetation type
1.36 3.75 2.62 2.16 1.82 4.23 4.14 4.58 5.75 5.76 5.50 5.33 3.76 3.66 4.19 0.89 (0.11 (0.07 0.97 1.91 1.37 1.30 2.53 2.75 2.64 3.36 3.36
833.04 766.03 784.25 744.18 722.18 562.35 523.46 451.03 450.58 410.76 385.83 383.14 364.17 367.35 382.75 429.51 436.11 434.41 388.56 313.55 316.96 316.86 251.10 221.25 221.78 171.61 171.61
479.6 460.1 460.1 439.4 428.6 408.5 390.1 367.7 377.6 359.7 352.8 346.7 329 324.2 326.9 311.4 303.1 303.1 300.8 288.1 285 284.4 273.6 262.9 262 246 246
TCBMF TDBF TCBMF TCBMF TCBMF TCBMF Saline-alkali meadow Meadow steppe Sandy woodland Meadow steppe Meadow steppe Meadow steppe Typical steppe Typical steppe Typical steppe Typical steppe Typical steppe Typical steppe Sandy woodland Desert steppe Desert steppe Desert steppe Desert steppe Desert steppe Desert steppe Desert steppe Desert steppe
Data for locations (latitude, longitude and altitude) were measured by GPS. Data for mean annual temperature, mean annual precipitation and Penman’s arid index were estimated using multiple regression models (Ni et al. 1999) TCBMF Temperate conifer–deciduous broad-leaved mixed forests, TDBF temperate deciduous broad-leaved forests, AET actual evapotranspiration
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steppe in the mid-part of the transect with Leymus chinensis and Stipa baicalensis as the dominants; to desert steppe in the west dominated by Stipa glareosa, Stipa gobica, Salsola passerina and Caragana stenophylla (Anon. 1980; Zhang et al. 1997; Jiang et al. 1999; Ni and Zhang 2000). Owing to the steep environmental gradient and the diverse vegetation types, the NECT is obviously a suitable area to test hypotheses regarding the response of vegetation to changing environments.
More detailed descriptions on the calculation of AET are available in the literature (Monteith 1995; Haxeltine and Prentice 1996). A total of 2,831 grid cells with AET data values at 10¢ latitude · 10¢ longitude resolution (ca. 13.3·18.3 km grid) existed within the study area. AET for each sampling site was obtained from the grid cell that covers the site. Selection of plant traits
Field sampling A total of 27 sites were sampled along the NECT (Table 1). The sites were located approximately at the same locations where previous field sampling has been conducted (Jiang et al. 1999). The sites averaged ca. 50 km apart from each other. In total, 46 plots were surveyed at the 27 sites. Among them, 8 plots were for canopy trees, 12 plots for shrubs and 27 plots for herbaceous plants. Tree plots consisted of 20 points, sampled along a 200-m-long sampling line on a contour line with 10-m intervals between adjacent points. At each sampling point, four directions (east, south, west and north) were identified and an individual tree nearest to the point at each direction was selected for observation and measurement of plant traits. Each shrubland plot consisted of four quadrats of 4·4 m2 each. For each quadrat, all individuals were sorted into species. Herbaceous plots consisted of 5 quadrats of 1·1 m each, along a sample line at 10-m intervals. In each herb quadrat, all individuals were sorted to species. In each plot, a reasonable degree of homogeneity in topography was ensured. A total of 249 vascular species belonging to 172 genera and 60 families were recorded in the 27 sites. Field work resulted in a plot · species (P·S) matrix. Environmental data Geographical positions (longitude, latitude and altitude) for each site were measured with the Global Positioning System (GPS). We chose actual evapotranspiration (AET) as a surrogate for the site’s environmental factor. As a function of precipitation, temperature, solar radiation and soil water storage, actual AET is considered to be a prominent parameter characterizing a site’s water balance (Haxeltine and Prentice 1996). Actual AET was calculated by the global process-based equilibrium terrestrial biosphere model BIOME3 (Haxeltine and Prentice 1996), which has been used in Chinese vegetation modeling (Ni et al. 2000). Model inputs are monthly climate data [temperature, precipitation and sunshine, and absolute minimum temperature from 841 standard weather stations between 1951 and 2000 in China, as well as soil texture based on textural information digitized from Xiong and Li (1987)]. Climate data were interpolated to a 10¢ latitude · 10¢ longitude resolution by the smoothing spline method of Hutchinson (1989).
We selected plant traits for each species from a range of attributes within several broad categories: vegetative traits, regenerative traits, phenological traits and physiological traits in terms of photosynthetic ability and pathway (Leishman and Westoby 1992; Boutin and Keddy 1993; Lavorel et al. 1997; Mabry et al. 2000). As suggested by Diaz and Cabido (1997) and Weiher et al. (1999), most traits we selected have distinctive functional implications. Vegetative traits included life form, a measure of plant response to climate and effect on ecosystem properties, such as carbon storage and rate of biomass turnover (McGillivray and Grime 1995; Diaz and Cabido 1997; Pavo´n et al. 2000; Niinemets 2001) and leaf trait including leaf hairiness, leaf type, ratio of leaf length to width, leaf margin and phyllotaxy; most of these are considered relevant to leaf gas exchange and plant response to drought and carbon fixation (Lavorel et al. 1997; Lavorel and Garnier 2002). Phenology traits included flowering time, fruit dispersal time and leaf phenology, which are relevant to plant response to climate; maximum leafiness during the period most favorable to high rate of photosynthesis was also measured (Lavorel and Garnier 2002). Regenerative traits included the method of reproduction, such as clonal vs non-clonal, which is relevant to a plant’s ability to capture resources, and the types of regenerative organ (Leishman and Westoby 1994; Reich et al. 1998; Bond and Midgley 2001; McIntyre and Lavorel 2001). Physiological traits included net photosynthesis and C3 or C4 pathway, two direct measurements for plant carbon fixation capability (Lavorel and Garnier 2002). A total of 22 plant traits within the four categories were identified, each trait included 2–14 possible attributes. As a result, 22 traits were expanded into 81 attributes among the 249 vascular species, and each attribute was marked with different numbers (Table 2). Plant traits selected in this paper were either measured in the field or derived from the literature (Jiang et al. 1999; Tang 1999; Jiang and Dong 2000; Fu et al. 2001). Based on the availability of data, three ecosystem processes were considered: productivity, carbon storage and photosynthesis. Data on productivity were taken from a published dataset (Ni et al. 1999). Along the NECT, productivity in terms of NPP (t ha1 year1) for different plant life forms ranged from 2–9 (Ni et al. 1999). We identified four productivity ranks: very low (short grass and annuals, NPP 2–3), low (high grass and perennial forbs, NPP 3–4), intermediate (shrubs, NPP
566 Table 2 Plant traits identified among the 249 plant species along the NECT Plant traitsa
Attributes
1 Life history2 2 Root type1,2 3 Hairiness1,2 4 Leaf structure1,2 5 Length/width of leaves1,2 6 Leaf margin1,2 7 Leaf moisture1,2 8 Phyllotaxy1,2 9 Clone/none-clone2 10 Clone organ2
1=trees; 2=shrubs; 3=perennial; 4=annual 1=taproot; 2=fiber 1=hair variable with age; 2=no hair; 3=some hair; 4=very hairy 1=leafless; 2=simple; 3=compound 1 ratio‡3; 2 ratio £ 3 1=lobed/dissected; 2=entire; 3=serrate 1=non-succulent; 2=succulent 1=alternate; 2=whorled; 3=opposite 1=clone; 2=non-clone 1=radical bud; 2=sprouting; 3=rhizome; 4=subterranean bud; 5=tuberous root; 6=bulb; 7=tiller 1=unisexual and perfect; 2=perfect; 3=unisexual 1=panicles; 2=racemes; 3=umbels; 4=borne singly; 5=cymes; 6=spica; 7=capitulum; 8=catkin 1=insect; 2=wind; 1=berry; 2=silique; 3=samara; 4=spore; 5=follicle; 6=pome; 7=achene; 8=utricle; 9=nut; 10=caryopsis; 11=capsule; 12=legume; 13=drupe; 14=cone 1=dry; 2=fleshy 1=dehiscent; 2=indehiscent 1=no appendage; 2=appendage 1=summer fruit dispersal; 2=autumn fruit dispersal; 3=spring fruit 1=summer flowering; 2=spring flowering; 3=autumn flowering 1=deciduous; 2=evergreen 1=0–5; 2=5–10; 3=10–15; 4=15–20; 5‡20 1=C3; 2=C4
11 Flower type2 12 Inflorescence1,2 13 Pollination2 14 Fruit type2 15 16 17 18 19 20 21 22 1 2
Fleshy or dry fruit2 Fruit open or close2 Appendage of fruit or seed2 Dispersal phenology2 Flowering phenology2 Leaf phenology1,2 Net photosynthesis3 (ummol m2 s1) C3/C4 pathway3,4
Plant traits were identified based on field observations Fu et al. 2001
3.5–4.5) and high (trees, NPP 6–9). Carbon storage was considered to be strongly associated with plant life form (van Cleve et al. 1983; Diaz and Cabido 1997; Grime 2001), namely, evergreen trees > deciduous trees > shrubs > perennial herbs with underground storage organs > perennial herbs without underground storage organs > annual herbs. The rank of photosynthesis capacity was identified based on data from previous studies (Jiang et al. 1999). Five ranks for photosynthesis were identified: very low (Pn 0–5), low (Pn 5–10),
Fig. 1 Plant functional types identified by TWINSPAN. Values listed at each splitting level are the eigenvalue
3 4
Jiang et al. 1999 Tang 1999
intermediate (Pn 10–15), high (Pn 15–20), very high (Pn ( 20). A species · trait (S·T) matrix was elaborated based on the methods mentioned above. For a given trait within a species in the S·T matrix, category data were used (Table 2). Data analysis The S·T matrix was subjected to two-way indicator species analysis (TWINSPAN). TWINSPAN can result in classifications of both species and plant traits. Thus, results of TWINSPAN would allow us to know what PFTs will emerge. We identified PFTs at the third splitting level of TWINSPAN because further splitting led to too many groups each consisting of only a few species. The same dataset was subjected to detrended correspondence analysis (DCA) for either verifying the results of TWINSPAN or further disclosing PFT turnover along the environmental gradient. All species were positioned in the DCA-defined space based on their scores for the first two axes. The relationship between actual AET and the relative abundance of PFTs (proportion of the abundance of given PFTs to the total abundance of all PFTs in a site) was presented to understand how PFTs respond to the environmental gradient. Here, we set actual AET as the predicting variable to predict the relative abundance of PFTs. The CANOCO program (version 3.10, ter Braak 1990) was used to perform DCA. All TWINSPAN and DCA analyses followed the default settings.
567 Table 3 Summary of characteristics of the main plant functional types (PFTs) produced by TWINSPAN and DCA for the set of 249 species along the NECT, China (no. of species in each PFT indicated in parentheses) PFTs
PFT-1 (21)
PFT-2 (23)
Plant traits Vegetative traits
Regenerative traits
Deciduous trees; simple or compound leaves, but all broad-leaved (L/W3; leaf entire or serrate, opposite or alternate; dicotyledon and ferns; C3 pathway, most Pn>5
PFT-4 (51)
Perennial forbs; most compound leaves with L/W>3; leaf entire or serrate, opposite or alternate; dicotyledon; C3 or C4 pathway, Pn 15–20
PFT-5 (22)
Most are perennial grasses; simple leaves with L/W>3; leaf entire; monocotyledon; most C3 pathway, with lower net photosynthesis (Pn 0–5)
PFT-6 (18)
Most are perennial grasses; all simple leaves with L/W>3; leaf entire; monocotyledon; C3 or C4 pathway, with higher net photosynthesis (Pn 10–15) Annual herbs; often taproot; simple leaves; leaf entire or serrate; leaf alternate; dicotyledon or monocotyledon; most C4 pathway, with highest net photosynthesis (Pn>15) Evergreen trees; needle leaves; leaf often whorled; gymnosperm; C3 pathway, with lower net photosynthesis (Pn 0–5, 5–10)
PFT-7 (17)
PFT-8 (4)
Ecosystem functioning
PRO=4; CAR=5; PHO=1
PRO=4; CAR=4; PHO=1
PRO=3; CAR=2; PHO=1
PRO=3; CAR=2; PHO=4
PRO=3; CAR=3; PHO=1
PRO=2; CAR=2; PHO=3
PRO=1; CAR=1; PHO=5
PRO=4;CAR=6; PHO=2
Preferential attributes within each PFT have been listed. See Table 2 for further explanations of plant traits and the definition of scales of measurement. List of species within each PFT available upon request PRO Productivity, CAR carbon storage in plants, PHO photosynthesis capacity. Rank: 1 very low, 2 low, 3 intermediate, 4 high, 5 very high, 6 the highest
Results PFTs identified by TWINSPAN and DCA At the third splitting level, eight PFTs were identified based on the TWINSPAN classification (Fig. 1, Table 3). PFT-1 was a pure group of deciduous trees with high productivity, very high carbon storage and very low photosynthesis. Species from PFT-1 are all dominant components in the boreal forests in northeastern China, such as Acer ginnala, A. ukurunduense, Fraxinus rhynchophylla, Phellodendron amurense. PFT-1, along with PFT-2 (deciduous shrubs) and PFT-8 (evergreen conifers) were mainly distributed in the eastern part of the NECT where actual AET is much higher than the rest of the NECT. These three PFTs were located at the
bottom left in the DCA ordination plane (Fig. 2). PFT2 is a combination of shrubs with high productivity and carbon storage and very low photosynthesis. The boundary between PFT-1 and PFT-2 as well as between PFT-2 and PFT-3 overlapped quite a bit, suggesting that shrubs (PFT-2) are a transitional component linking forests and steppes along the NECT. PFT-3 and PFT-4 are perennial forbs at the center of the DCA plane (Fig. 2). Although these two PFT groups share a similar life form with intermediate productivity and low carbon storage, the differences between them are quite prominent. Species from PFT-3 mainly occupy shady understory habitats in forests with very low photosynthesis, while species from PFT-4 basically occur in steppes as subdominant species with high photosynthesis. PFT-5 is a combination of perennial bulb-grasses with intermediate productivity and carbon storage and very low net
568 Fig. 2 Dispersal pattern of plant functional types in the space defined by the DCA axes 1 and 2. AET Actual evapotranspiration
photosynthesis, while PFT-6 consists of perennial tillergrasses with low productivity and carbon storage and intermediate photosynthesis. Although PFT-5 and PFT6 are all monocotyledons, the boundary between these two PFTs is quite clear in the DCA plane (Fig. 2). Species from PFT-5 are dominants in the meadow steppe, such as Carex ssp. or other average species in a typical steppe, while most species from PFT-6 are dominants in the typical steppe, such as Stipa spp., Leymus chinensis, etc. PFT-7 is a combination of C4 annual herbs with high investment in above-ground biomass for supporting photosynthesis and proliferation, with little allocation to carbon storage. This group occupies heavily disturbed habitats such as degraded steppes or farmland. PFT-8 is a combination of evergreen trees with high productivity, the highest carbon storage and low photosynthesis. They are all gymnosperms, and their cones and seeds often have appendages. Due to its specific structure and functional attributes, PFT-8 is set prominently apart from the other PFTs in the DCA plane (Fig. 2).
where AET is less than 390 mm, such as in the desert steppe or in the heavily degraded typical steppe. Forbs with lower photosynthesis (PFT-3) and tiller-grass (PFT-6) decreased linearly and significantly with increasing AET. Forbs with higher photosynthesis (PFT-4) and C4 annuals (PFT-7) showed a significant and unimodal trend with increasing AET. Bulb-grass (PFT-5) linearly increased with increasing AET at marginally significant level (P=0.06, Fig. 3, Table 4). Based on the dispersal pattern of PFTs in the DCAdefined space as well as the relations between the relative abundance of PFTs and AET, the environmental gradient in terms of AET represented by the first two DCA axes can thus be defined. AET decreases along axis 1 from the left to the right and along axis 2 from the bottom to the top (Fig. 2). In response to this environmental gradient, PFT turnover showed a fairly distinctive sequence from the bottom left to the top right of the DCA plane: deciduous trees (PFT-1), shrubs (PFT-2), evergreen trees (PFT-8), forbs with lower photosynthesis (PFT-3), forbs with higher photosynthesis (PFT-4), bulb-grass (PFT-5), tiller-grass (PFT-6) and C4 annuals (PFT-7).
Response of PFTs to the environmental gradients and PFT turnover In terms of relative abundance, deciduous trees (PFT-1) and evergreen trees (PFT-8) showed similar responses to increasing AET (Fig. 3, Table 4); both mainly occur in the areas where AET is more than 390 mm. Shrubs (PFT-2) showed no significant response to AET (Fig. 3, Table 4). Shrubs mainly occur in the area where AET is more than 390 mm, only a few are found in the area
Changes in ecosystem properties with the turnover of PFTs Given the functional properties represented by different PFTs (Table 2), an indirect prediction with respect to the changes in ecosystem properties is available. Namely, carbon storage and productivity are predicted to decrease while photosynthesis is predicted to increase
569 Fig. 3 Relationships of the relative abundance of PFTs with actual AET
with the turnover of PFTs associated with the decreasing AET gradient (Fig. 2).
Discussion PFTs subjectively recognized by Chinese ecologists provided a preliminary framework for predicting vegetation responses to the environmental gradient along the NECT. For example, Jiang et al. (1999) identified eight PFTs: forest trees, forest shrubs, forest grasses, steppe shrubs, meadow steppe grasses, typical steppe grasses, desert shrubs and desert grasses. This PFT classification scheme is basically a combination of vegetation types (forest, meadow steppe, typical steppe and desert) and life forms (tree, shrub and grass). Using data from
temperate grasslands on the NECT and in southeastern Mongolia, Ni (2003) subjectively identified six PFTs: C3 species, C4 species, grasses, shrubs, forbs and succulents. In this classification scheme, photosynthesis pathway (C3, C4), life form (shrub, grass), and number of cotyledons (forb, grass) are the major traits in distinguishing PFTs. When comparing the subjective PFT classification in previous studies with the objective framework presented in this paper, it can be seen that to some extent they share similarities in terms of some major plant traits. For example, both the objective framework (a large number of plant traits were considered) and the subjective classification (only a few plant traits were considered) take life form as the major plant trait in the context of PFT classification, suggesting that life form is one of the most robust surrogates for PFT. The results confirmed the recurrent pattern found in other studies
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tative PFT classification, suggesting that subjective PFT classification is useful only if key plant traits are considered. The following analysis shows how the subjective approaches act as an important complement to the objective framework. Along the transect from the western end to the eastern end, AET shows an increasing trend from 246 to 479.6 mm (Table 1). Thus the relationship between the relative abundance of PFTs and AET actually reflects the dispersal pattern of PFTs along the transect. In a climatic scenario conducted on the NECT, Gao and Zhang (1997) predicted that, with doubled CO2 concentration, precipitation will increase by 20% and temperature will increase by 4C, and hence AET will increase. Under this AET scenario, one should expect shifts in the relative abundance of PFTs because of local extinction and migration across the landscape (Huntley 1991) and therefore alterations of the predominant plant traits and ecosystem functions along regional gradients (Diaz and Cabido 1997). Based on the different responses of PFTs to changing AET, the western margin of the distribution ranges of deciduous trees and evergreen trees is predicted to migrate westward, while the eastern margin of forbs with higher photosynthesis and C4 annuals is predicted to retreat. In addition, tillergrass is predicted to be replaced by bulb-grass. The unimodal response of forbs with lower photosynthesis to increasing AET suggests that its relative abundance is favored neither by increased nor by decreased AET but by moderate levels of AET. Therefore, the distribution range of forbs with lower photosynthesis may migrate westward. Given the non-significant response of shrubs to AET, it is impossible to predict the dynamics of the relative abundance of shrubs within the AET scenario. Naturally, shrubs on the NECT occur both in forests where AET is more than 390 mm (meso-shrubs) and in desert steppes where AET is less than 290 mm (xero-shrubs). In a more precise framework, if shrubs were further classified into two sub-PFTs, namely xero-shrubs and meso-shrubs, we would predict an expansion of mesoshrubs and a retreat of xero-shrubs in the face of increased AET. It should be noted that the colonization of shrubs is also associated with disturbance dynamics. For
(Friedel et al. 1988; Leishman and Westoby 1992; Chapin et al. 1996; Diaz and Cabido 1997; Mabry et al. 2000). Nonetheless, there are some profound differences between these two classification frameworks. Deciduous woody plants are considered to differ from evergreen trees in several aspects, namely, shorter season of photosynthetic capability, greater resource requirements for supporting high leaf turnover, and higher palatability to herbivores (Chapin et al. 1996). This profound differentiation between evergreen trees and deciduous trees was explicitly identified in the objective classification but was totally neglected in the subjective classification (Jiang et al. 1999). In this paper, trees with different leaf phenology (evergreen and deciduous) were identified as different PFTs (PFT-1 and PFT-8). On the other hand, shrubs in different habitats (understory, degraded steppes and deserts) were grouped into a single PFT (PFT-2), rather than three PFTs as identified by Jiang et al. (1999), due to the strong similarity shared by shrub plants (life form, phenology and carbon storage, and all C3 with low photosynthesis). Ni (2003) identified perennial forbs and grasses as two independent PFTs, while each was further divided into two alternatives in our objective classification. In detail, PFT-3 and PFT-4 (all forbs) were quite similar in vegetative traits and some regenerative traits (clone, flower type, pollination mode, etc.), but quite different in dispersal potential as well as in net photosynthesis. PFT-5 and PFT-6 (all grasses) differed from each other in two aspects, namely, their dominant regeneration organs (bulb vs. tiller) and photosynthetic capability, and hence their capacity for such ecosystem functions as carbon storage and leaf canopy expansion differs (Grime 2001). PFT-7 was characterized by its annual growth form, C4 pathway and the highest photosynthetic ability. However, it was totally missing in the subjective classification schemes (Jiang et al. 1999; Ni 2003). The divergences between these two PFT classification frameworks (subjective or objective) do not mean that the subjective approaches are useless. Results from our objective PFT classification indicated that life form, photosynthesis pathway, and underground organs (bulb vs. tiller) play major roles in the context of the quanti-
Table 4 Summary of regression analyses examining the relationship between plant functional types and actual AET in plant communities along the NECT in China Variable
Model
Dependent
b0
b1
B2
R2
F
P
AET
Quadratic* Quadratic Linear* Quadratic* Linear Linear* Quadratic* Quadratic*
PFT-1 PFT-2 PFT-3 PFT-4 PFT-5 PFT-6 PFT-7 PFT-8
1.04 1.04 0.029 1.47 0.28 0.44 0.97 0.084
0.007 0.006 0.0008 0.009 0.0005 0.0009 0.007 0.0006
1.13e005 8.85e006 0 1.38e005 0 0 1.12e005 1.19e006
0.89 0.17 0.15 0.27 0.13 0.47 0.27 0.69
95.73 2.53 4.38 4.37 3.84 21.75 4.36 27.15
