Chapter 13
13.1 In Search of the Holy Grail
Functional classifications have been seen as a necessary
tool for the simplification of floristic complexity in glo-
bal vegetation models (Neilson et al. 1992; Prentice et al.
1992; Foley et al. 1996; Woodward and Cramer 1996), for
mapping vegetation patterns at key times in the past
(Prentice and Webb 1998; Prentice et al. 2000), and for
monitoring effects of global change or management on
vegetation distribution and ecosystem processes (Díaz
et al. 2002a; Cruz et al. 2002). Plant functional classifica-
tions were first designed by grouping plants a priori based
on knowledge of their function, or based on observed
correlations among their morphological, physiological,
biochemical, reproductive or demographic characteris-
tics (Woodward and Cramer 1996; Smith et al. 1997). It
was assumed that these classifications would allow to
predict changes in ecosystem processes directly from
projected changes in plant species composition in re-
sponse to global change. This idea was challenged by the
recognition that functional effect groups (species with a
similar effect on one or several ecosystem functions; e.g.,
primary productivity, nutrient cycling, Gitay and Noble
1997; Walker et al. 1999) and functional response groups
(groups of species with a similar response to a particu-
lar environmental factor; e.g., resource availability, dis-
turbance or CO2; Gitay and Noble 1997; Lavorel et al. 1997)
do not necessarily coincide. Although there have been
sustained efforts to refine plant functional type (PFT)
concepts and terminology (Gitay and Noble 1997; Lavorel
et al. 1997; Lavorel and Garnier 2002), the search for a
single, functionally comprehensive yet relatively parsi-
monious, plant functional classification has remained an
elusive Holy Grail.
The Holy Grail requires to focus on functional traits
of terrestrial vascular plants that (1) can together repre-
sent the key responses and effects of vegetation at vari-
ous scales from ecosystems to landscapes, biomes, and
continents; (2) are suitable for relatively easy, inexpen-
sive and standardised measurement over the world; and
(3) can hence be used to devise a satisfactory functional
classification for global-scale modeling and mapping of
the biosphere.
A large amount of research has been initiated on plant
furnctional traits and PFTs since the early days of GCTE,
where the Holy Grail was formulated largely by modellers.
In this chapter we first summarise theoretical and em-
pirical progress on the understanding of the response
traits that are relevant to different aspects of environ-
mental change. Recently numerous empirical studies
have made considerable progress in elucidating how plant
traits can be related to plant function in relation to main
environmental constraints (see Sect. 13.2), and how these
same traits are then relevant to the distribution of spe-
cies along gradients of climate, nutrient availability, and
disturbance. Additional theoretical (Ackerly 2003) and
empirical (Ackerly 2004a) work has also analysed the role
of phenotypic plasticity, ecological sorting and natural
selection in determining present patterns of association
between plant traits and environmental gradients. The
correlational approach, which has formed the bulk of that
research, has been quite successful in detecting signifi-
cant associations between particular plant traits and
environmental factors (reviewed in Sect. 13.3). Under-
standing how these traits may then influence biotic in-
teractions, and eventually shape local vegetation
through community assembly has however appeared to
be a non-trivial scaling exercise, and we review current
state of the art in Sect. 13.4. Likewise, scaling from indi-
vidual plant traits that are affected by environmental
changes to ecosystem effects has proved more challeng-
ing than initially anticipated because the traits that de-
termine the response to specific environmental factors
overlap directly, indirecly, or not at all with the traits that
determine ecosystem functions such as biogeochemical
cycling or flammability (Lavorel and Garnier 2002; re-
viewed in Sect. 13.5). Finally, we return to asking how
these results have helped modellers working at larger
scales, and what key challenges remain.
13.2 Individual Plant Structure and Function
Among all possible traits measurable on an individual
plant, those of interest to global syntheses and modeling
must fill four conditions: (i) bear some relationship to
plant function; (ii) be relatively easy to observe and quick
Plant Functional Types: Are We Getting Any Closer to the Holy Grail?
Sandra Lavorel · Sandra Díaz · J. Hans C. Cornelissen · Eric Garnier · Sandy P. Harrison · Sue McIntyre · Juli G. Pausas
Natalia Pérez-Harguindeguy · Catherine Roumet · Carlos Urcelay
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150 CHAPTER 13 · Plant Functional Types: Are We Getting Any Closer to the Holy Grail?
to quantify (‘soft’ traits; Hodgson et al. 1999), (iii) using
measurements that can be standardized across a wide
range of species and growing conditions (Cornelissen
et al. 2003b); (iv) have a consistent ranking – not neces-
sarily constant absolute values – across species when
environmental conditions vary (Garnier et al. 2001;
Cornelissen et al. 2003a; Shipley and Almeida-Cortez
2003). Such traits are called ‘functional traits’ or ‘func-
tional markers’ (Garnier et al. 2004), and can be mor-
phological, ecophysiological, biochemical, demographical
or phenomenological (Fig. 13.1). At this stage, the inter-
est lies in the role of these traits for main plant func-
tions, while their role in ecosystem dynamics is not speci-
fied, and they may turn to be response and/or effect traits.
Information on soft traits is available for large numbers
of species from all types of vegetation (see Díaz et al.
2004; Wright et al. 2004). Over the years, a consensus has
been growing about which soft traits are best related to
key plant functions such as resource economy or recruit-
ment and how these then become response traits to cli-
mate and disturbances (Grime et al. 1997; Westoby et al.
2002; Cornelissen et al. 2003b) (Table 13.1). Comparabil-
ity of data and global coverage must be ensured by using
standardised lists of traits, which are a consensus about
which traits are critical for the ecological challenges ahead
(Table 13.1), and measuring them with standard method-
ologies (McIntyre et al. 1999; Díaz et al. 2002b; Cornelissen
et al. 2003b), now freely available (Cornelissen et al. 2003b1).
Plant functional traits are considered as reflecting
adaptations to variation in the physical environment and
trade-offs (ecophysiological and/or evolutionary) among
different functions within a plant. Co-varying sets of
traits have been associated to ‘major axes of plant spe-
cialization’, that are consistent across environments, bio-
geographic regions and major plant taxa (Grime 1977;
Chapin et al. 1993; Díaz et al. 2004). More generally, the
analysis of plant functional trait responses to environ-
mental variation, and of their effects on ecosystem func-
tion has been guided by the recognition that plants are
constrained for performing alternative functions simul-
taneously, such as resource capture and conservation
(Grime 1979; Chapin et al. 1993; Poorter and Garnier
1999), acquisition of several different resources (light and
water, Smith and Huston 1989; light and nutrients, Tilman
1988), or growth and reproduction (Silvertown et al. 1993;
Solbrig 1993).
A synthesis of empirical and theoretical studies pro-
posed that at least four axes of plant specialization should
be considered (Westoby et al. 2002). The first and best
understood axis is represented by the specific leaf area
(SLA) – leaf life span trade-off and is associated with
turnover time of plant parts (including through her-
bivory), nutrient residence times and rate of response to
favourable growth conditions. The global relevance of
this axis was confirmed by an analysis across four floras
from different biomes and biogeographic regions (Díaz
et al. 2004). The second axis, representing the trade-off
between fecundity and seed mass addresses establish-
ment opportunities and success in the face of hazards,
respectively. Seed mass and fecundity are negatively cor-
related, even after correcting for plant size. The third axis
represented by potential plant height, carries several
trade-offs and adaptive elements, and captures multiple
constraints such as the density and height of shading
competitors, water economy, and response to disturbance.
The global relevance of plant height was confirmed by
cross-continental analysis (Díaz et al. 2004). Finally, a
fourth axis representing the coupled variation between
twig size and leaf size determines the texture of cano-
pies. Although a decrease in leaf size is common in dry,
high light or cold conditions, the costs and benefits of
small vs. large leaves remain to be formalized. Still, iden-
tifying an axis relevant to temperature variation, and es-
pecially response to extremes, stands as a challenge to
ecophysiologists and ecologists.
However, the previous syntheses focused on above-
ground traits, which are easily accessible. Recent studies
have endeavoured to provide the same kind of informa-
tion belowground, focusing on the functions of root traits,
trade-offs among them, and how they relate to above-
ground traits that could then be used as proxies for be-
lowground function. Suites of correlated traits appear to
also exist in roots, and represent a trade-off between root
longevity and growth rate. Generally, low specific root
length (SRL: ratio between root length and root biom-
ass) is associated with thick, dense roots with low nitro-
gen and high lignin concentrations (Comas and Eissen-
stat 2004; Craine et al. 2002; Craine et al. 2003), a syn-
drome usually found in slow growing species or plants
grown in limiting conditions (Reich et al. 1998a; Ryser
1998; Comas et al. 2002; Comas and Eissenstat 2004).
Available data linking root morphology and plant func-
tioning, and analogies to leaf traits suggest that this suite
of traits reflects root longevity (Eissenstat 1991; Eissenstat
Fig. 13.1. Examples of soft traits and associated functions
1 http://www.publish.csiro.au/nid/65/paper/BT02124.htm.
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151
et al. 2000; Ryser 1996), greater nutrient use efficiency
and resistance to herbivore and physical damage (Craine
et al. 2001). These traits are thought to minimize nutri-
ent losses, allowing plants to grow larger at low nutrient
supply rates. Opposite traits tend to maximize root sur-
face area and length per unit biomass, thereby allowing
quick exploration of soil resources and rapid growth.
However, root traits are definitely not easily measured.
Therefore, there are a number of challenges still to be
resolved: (i) to identify traits that are closely related to
key root functions such as nutrient acquisition, anchor-
ing, rhizospheric activity, decomposition rate; (ii) to nor-
malize root traits measurements for broad comparisons;
(iii) to test relationships between leaf and root traits for
13.2 · Individual Plant Structure and Function
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152 CHAPTER 13 · Plant Functional Types: Are We Getting Any Closer to the Holy Grail?
later use of leaf traits as easier proxies. Close relation-
ships between leaf and root nitrogen concentration have
already been shown at a global scale (Craine and Lee 2003;
Craine et al. 2005).
As recognised by early work (Theophrastus ca. 300 bc;
Raunkiaer 1934), growth forms are one expression of
trade-offs among traits and adaptation to different types
of environments. As such, they provide comprehensive
links between key traits, plant response to their environ-
ment and their effecs on ecosystem function (Chapin
1993), and this is why large scale dynamic models have
used them as the basis for their plant functional classifi-
cations. However, there is also an important range of
variation in trait values and detailed trade-offs among
traits within each life form. For instance, the trade-off
between leaf lifespan (and underlying protective traits)
and traits that promote leaf productivity (e.g., SLA) op-
erates both within and between life forms (Díaz et al.
2004; Wright et al. 2004), but relationships between seed
dispersal syndromes and seed size depend on seed size
(Westoby et al. 1990).
13.3 Traits and Environmental Gradients
The functional meaning of plant traits for response to
environmental variation has been identified through
observations of the variations in trait values across envi-
ronments differing for one or several factors, targeted
experiments and modeling. Most of our knowledge is
derived from the first approach, and therefore directly
applies to spatial variation. Space-for-time substitution
is then used to assume that the same changes in trait val-
ues would be observed following an environmental
change of the same magnitude. Growing numbers of
experiments have confirmed this assumption for re-
sponses to single environmental factors such as nutrient
availability (Dyer et al. 2001) or grazing (Bullock et al.
2001), as do models of community or ecosystem dynam-
ics (Pausas 1999; Colasanti et al. 2001; Ackerly 2003; Boer
and Stafford Smith 2003; Hickler et al. 2004).
This combination of approaches has advanced the
understanding of the adaptive significance of traits, or
combinations of traits, to predict the response of organ-
isms to climate, nutrients and disturbance (Table 13.1).
Globally, response to climate, considered in terms of re-
sponse to extreme low or high temperatures, and to gra-
dients of moisture availability, is associated with varia-
tions in life form, leaf traits, rooting depth and lateral
root spread, and genome size (McGillivray 1995; Díaz and
Cabido 1997; Pavón et al. 2000; Niinemets 2001; Schenk
and Jackson 2002, 2005). Specific leaf area (SLA), leaf
dry matter content (LDMC) and leaf chemical composi-
tion co-vary with soil resource availability (Cunningham
et al. 1999; Poorter 1999) as do specific root length, tissue
density and diameter (Reich et al. 2003; Robinson and
Rorison 1988). Responses to CO2 depend on life cycle,
relative growth rate (RGR), photosynthetic pathway, and
stochiometric relationships (Poorter et al. 1996). Re-
sponse to water availability is associated with variation
in SRL, root diameter and root architecture (Fitter 1991;
Wright and Westoby 1999; Nicotra et al. 2002). RGR, leaf
and root morphology, and seed mass determine response
to shading (Leishman and Westoby 1994; Reich et al.
1998b). Response to disturbance is associated with varia-
tion in life cycle, plant height, architecture, resprouting
and seed traits (McIntyre and Lavorel 2001; Bond and
Migdley 2001; Pausas et al. 2004; Díaz et al. in press). Fol-
lowing, we summarise recent progress in the identifica-
tion of plant traits associated with response to the two
simple factors that vary most significantly across com-
munities within a landscape: resource availability and
disturbance.
13.3.1 Plant Functional Response
to Mineral Resource Availability
Early syntheses on changes in species traits along nu-
trient gradients (Grime 1977; Chapin 1980) recognised
that species from nutrient-rich habitats tend to be in-
herently fast-growing. This goes along with rapid re-
source capture and fast turn-over of organs leading to
poor internal conservation of resources, while the re-
verse is true for species from nutrient-poor habitats
(Tables 13.1, 13.2). More recently, a series of quantitative
traits has been associated with this fundamental trade-
off in plant functioning (Reich et al. 1992; Grime et al.
1997; Poorter and Garnier 1999; Díaz et al. 2004; Wright
et al. 2004). Fast-growing species from nutrient-rich
habitats usually have a combination of high SLA, high
SRL and relatively more fine roots, high tissue nutrient
(in particular nitrogen) concentration, low tissue den-
sity and cell wall content, high rates of carbon and nu-
trient uptake, and short-lived leaves and roots. Oppo-
site traits characterize species from nutrient-poor habi-
tats, in which the mean residence time of nutrients tends
to be maximized through longer-lived organs and/or
higher resorption of nutrients from senescing organs
(Ryser 1996; Garnier and Aronson 1998; Boot 1989; Aerts
and Chapin 2000; Westoby et al. 2002).
13.3.2 Plant Functional Response to Disturbance
Disturbances are defined here as natural or land use re-
lated events that remove biomass or individuals (Grime
1977). Although disturbances must be considered for rel-
evant plant functional classifications (Lavorel et al. 1997;
Lavorel and Cramer 1999; Pausas et al. 2003), a theoreti-
cal framework comparable to that developed for resource
economy remains elusive. Moving beyond the well-
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153
known ruderal syndrome (Grime 1977) requires better
understanding of regeneration traits. There is good evi-
dence that seed size has a fundamental evolutionary and
ecological significance for post-disturbance colonization,
competitive response and tolerance to abiotic stress
(Venable et al. 1988; Westoby et al. 2002). However the
role of this trait for seed persistence, dispersal or seed-
ling growth and survival is debated (Marañon and Grubb
1993; Thompson et al. 1993; Hughes et al. 1994). Overall,
traits determining population persistence have so far
received limited attention in functional trait analyses
(Eriksson and Ehrlén 2001). In an analysis of the sensi-
tivity of population growth rate to species demographic
parameters, Silvertown et al. (1993) found a correspon-
dence between longevity and resource-rich environ-
ments, survival and resource shortage, and fecundity and
disturbance. These patterns still need to be matched with
variation in soft traits through meta-analyses of large
demographic and trait data bases.
Syntheses targeted at specific disturbances organised
under the banner of GCTE have highlighted recurrent
patterns of plant specialization in relation to soil distur-
bance, grazing and fire, as well as the nuances that need
to be applied to them.
Soil disturbance consistently favours plants with a
suite of traits additional to the ruderal syndrome (Lavorel
and McIntyre 1999c). Plant species tolerant to soil distur-
bance by ploughing or mammal digging are characterised
by: a short and prostrate stature, with either a stolonifer-
ous architecture in perennial grasses, or flat rosettes in
forbs, high fecundity and a small dormant seed pool. In-
tolerant species are typically larger tussock grasses or
dicotyledons, with low fecundity and no seed dormancy
mechanisms, and with low plasticity in their morphol-
ogy. Finally, a group of indifferent species has an archi-
tecture characterised by leafy stems, with high morpho-
logical plasticity, and high seed dormancy (Lavorel et al.
1998, 1999a,b).
There are few empirically tested generalizations about
which plant traits are positively or negatively associated
with ungulate grazing, and the validity of some widely
recognized trait responses to grazing has remained
mostly untested at the global scale. There have been sug-
gestions in the literature, based on pair-wise regional
comparisons (Díaz et al. 2001; Adler et al. 2004, 2005), that
evolutionary history of grazing by ungulates, as well as
habitat productivity, determine what plant traits are
favoured by grazing. Díaz et al. (in press) have asked what
plant traits are consistently associated with grazing at
the global scale, and whether these traits varied with pre-
cipitation (a surrogate for resource availability) and evo-
lutionary history of grazing. A quantitative analysis of
195 studies from all over the world confirmed that over-
all grazing favoured annuals over perennials, short-
statured over tall-statured plants, prostrate over erect
plants, and stoloniferous or rosette over tussock archi-
tecture. This analysis demonstrated for the first time that
some of the response patterns disappeared or were sub-
stantially stronger or weaker under particular combina-
tions of precipitation and evolutionary history of her-
bivory. For example, in dry regions with long evolution-
ary history of ungulate herbivory, grazing did not favor
annual plants over perennial plants.
Pausas et al. (2004) analysed regeneration strategies
worldwide for woody plant species from ecosystems that
are subject to stand-replacement (crown) fires. It is com-
monly assumed that the main traits allowing persistence
after stand-replacement fires are resprouting capacity
and the ability to retain a persistent seed bank (termed
‘propagule persistence capacity’). Different combinations
of these two traits have been preferentially selected in
floras with different evolutionary histories. Although all
four possible binary combinations appear in most fire-
prone ecosystems, the relative proportions of each type
(and the dominant type) differ. In Australian heathlands,
the proportion of resprouters and non-resprouters is rela-
13.3 · Traits and Environmental Gradients
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154 CHAPTER 13 · Plant Functional Types: Are We Getting Any Closer to the Holy Grail?
tively even, compared with other fire-prone ecosystems,
though post-fire obligate resprouters (resprouters with-
out a seed bank) are almost absent. In the Mediterra-
nean basin, most resprouters are obligate, while in Cali-
fornia shrubs resprouters are evenly segregated among
those having propagules that persist after fire (faculta-
tive species) and those without propagule persistence
capacity (obligate resprouters). Species with neither per-
sistence mechanism are rare in most fire-prone shrublands.
Although data was limited, the review also highlighted
some clear trade-offs with other traits (e.g., height), as
well as the importance of considering the phylogenetic
relatedness for a proper understanding of functional
traits and trade-offs. For instance, in the Mediterranean
basin flora, most resprouters have fleshy fruits and most
non-resprouters have dry fruits. However, this pattern is
not due to an ecological trade-off, but to a common lin-
eage, as demonstrated by a phylogenetically controlled
analysis (Pausas and Verdú 2005).
The data syntheses relating response traits to fire and
grazing have still only dealt with individual disturbances.
A further challenge lies in the understanding of distur-
bance regimes. For example, in many grasslands of the
world disturbance regimes combine fire, grazing and/or
mowing, fertilization and soil disturbance. Because re-
gimes represent fixed combinations of disturbances that
recur on the landscape, they can mask the interactions
between the individual disturbances within that struc-
ture plant communities (Collins 1987). Woodlands and
savannas are often shaped by the combination of graz-
ing by wild and domestic herbivores, together with in-
tentional or unintentional fire (Bond et al. 2003). Addi-
tional disturbances associated with farming and forestry
can co-occur with grazing and fire to structure wood-
lands and forests (McIntyre and Martin 2001; McIntyre
et al. 2002; Dale et al. 2001). Grazing tolerance of a num-
ber of species from Australian subtropical grasslands was
found to covary with other disturbances (McIntyre et al.
2003), with the grazing tolerance of native species tend-
ing to decline in the presence of soil disturbance or wa-
ter enrichment. Novel combinations of human-induced
and natural disturbances are already widespread and are
expected to be features of the future. Their effects can
range from changes in dominance of different PFTs to
dramatic shifts associated to plant invasions (D’Antonio
and Vitousek 1992).
Pausas and Lavorel (2003) proposed a unifying frame-
work that may apply to a variety of disturbance types.
This framework is based on the recognition that plants
can have persistence strategies at different levels of
organisation and provides an understanding of the or-
der in which different mechanisms act on plant persis-
tence in disturbed systems. The main parameters to de-
termine persistence in chronically disturbed ecosystems
are those related to: Individual-persistence capacity,
Propagule-persistence capacity (persistence at the popu-
lation level), Competitive capacity (persistence at the
community level) and Dispersal capacity (persistence at
the landscape level). The approach by Pausas et al. (2004)
is a special case of this approach. Much remains to be
done to identify traits relevant to different levels of re-
sponse, and how these may vary depending on context.
Nevertheless, sixteen possible functional types could be
obtained by assuming a simple binary classification of
the four levels of persistence.
13.3.3 Projecting Changes in Plant Functional Traits
in Response to Global Change
Natural gradients usually combine variations in climate,
resource availability, and disturbance regimes. These
underlying simple gradients may be explicit for analyses
of plant response to altitude (Pavón et al. 2000) or agri-
cultural disturbance (Kleyer 1999), though again these
combinations are likely to not be stable in the future. In
many other instances however, the nature and amount
of environmental variation underlying complex gradi-
ents (sensu Austin and Smith 1989) along which traits
are studied has not been quantified or formalized. For
instance, this is the case of successional gradients (Bazzaz
1996; Prach et al. 1997; Garnier et al. 2004; Richardson
et al. 2005) or ecotones (Dodd et al. 2002) which are prime
opportunities to obtain time series of plant functional
traits.
Interpretation and projections of plant distributions
along complex gradients are problematic because traits
associated with different factors, such as water and nu-
trient stress, can overlap (Díaz et al. 2004) or be inde-
pendent (Cunningham et al. 1999; Dyer et al. 2001). Non-
overlapping trait responses are commonly observed
when one environmental factor involves adult traits (e.g.,
nutrient availability) and other regeneration traits (e.g.,
disturbance) (Shipley et al. 1989; Leishman and Westoby
1992; Thompson et al. 1996; Lavorel et al. 1999b). In ad-
dition, the role of genetically-based plasticity of traits in
response to environmental changes has largely been ig-
nored from analyses, though it may contribute to popu-
lation persistence (Strand and Weisner 2004; Stanton
et al. 2000). Attempts to understand linkages, trade-offs
and dependency among traits based on basic ecophysi-
ological and evolutionary mechanisms, as reviewed in
Sect. 13.2, are the way forward to address these complex
responses (Ackerly et al. 2000; Westoby et al. 2002). In
the context of global change, our ability to generate reli-
able projections of future vegetation is further limited
by the fact that different combinations of climatic fac-
tors could occur in the future, as they have in the past
(Jackson and Williams 2004), as will novel combinations
of atmospheric CO2 concentration, climate and distur-
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155
bance regimes. Our ability to apply plant functional re-
sponses to generate future vegetation projections must
therefore rely on more experimental and modeling work.
One remaining challenge for modeling, however, lies in
the construction of PFTs from analyses of continuous
plant traits. This methodological challenge can be solved
with statistical approaches (Pillar and Sosinsky 2003;
Nygaard and Erjnaes 2004), but is also a more funda-
mental issue because of the assumption that future re-
sponses to multiple factors will be stable within groups.
13.4 Scaling from Individual Plants to Communities:
from Response Traits to Community Assembly
Having learned how populations of individual species
respond to environmental variation across landscapes,
understanding how communities assemble remains a sig-
nificant challenge (Weiher and Keddy 1999; Ackerly 2003;
Suding et al. 2003). This challenge is particularly signifi-
cant when novel environmental conditions and landscape
fragmentation by land use may lead to entirely new as-
semblages, as have different environmental conditions
in the past (Jackson and Williams 2004). Effects of
changes in climate or land use might be modeled as
changes in the strength of different abiotic (climatic, at-
mospheric CO2 concentration, resource availability, distur-
bance) and biotic (competition, predation, mutualisms)
filters that successively constrain which species and traits,
from a regionally available pool, can persist at a site
(Woodward and Diament 1991; Díaz et al. 1999; Naeem
and Wright 2003; see also Díaz et al. 2007, Chap. 7 of this
volume). We should then be able to predict the trait com-
position of communities by combining knowledge
of (1) the regional species pool, (2) the nature and
strength of different filters, (3) the response traits asso-
ciated with each filter and (4) the rules that shape as-
sembly (Campbell et al. 1999).
Attempts to predict interspecific competition from
plant traits have had mixed success (Keddy et al. 1998;
Wardle et al. 1998), in particular because species com-
petitive rankings are sensitive to nutrient availability
(Keddy et al. 2000), disturbance (Suding and Goldberg
2001), and to mycorrhizal associations (van der Heijden
et al. 1998; Wardle et al. 1998). A reasonable consensus
has been reached regarding tolerance of competition by
neighbours (competitive response) where plant height
and seed mass are positively associated with greater tol-
erance (Goldberg 1991). However, the attributes that de-
termine competitive effects of plants upon their
neighbours, and how these may vary with resources and
disturbance, remain to be elucidated. Grime’s competi-
tive syndrome (1977, 2001) includes attributes such as tall
stature, wide spread, nutrient monopolization and abun-
dant litter production. Tilman (1988) also emphasised
the importance of height in productive conditions, but
in nutrient-poor environments leaf and root attributes
associated with nutrient uptake are those expected to
confer competitive effects (Craine et al. 2001, 2005). Fur-
ther, Goldberg and Novoplansky (1997) proposed that
competitive effects of species may depend on whether
nutrients or water is most limiting. Relating this idea to
the strategy model by Ackerly (2004b) in the case of nu-
trient limitation, a ‘conservative competitor’ strategy, with
leaf traits promoting resource conservation, such as a low
SLA, high tissue density and long life span, is expected.
Otherwise an ‘exploitative competitor’ strategy, with op-
posite leaf traits, is expected (Michalet 2001; Liancourt
et al. 2005). In addition, other types of plant-plant inter-
actions such as facilitation and allelopathy may gain im-
portance in either resource-poor and physically stress-
ful, or resource-rich and physically benign environments
(Bertness and Callaway 1994; Pellissier 1998; Bruno et al.
2003). Which plant traits are conducive to these other
mechanisms remains to be elucidated, but are most likely
related to the nutrient and water acquisition vs. conser-
vation syndromes (Liancourt et al. 2005), including their
effects on herbivory.
Another fundamental interaction structuring commu-
nities is herbivory (Crawley 1992). There is good evidence
that structural and chemical traits known to be associ-
ated with nutrient or climatic gradients influence pat-
terns of herbivory by generalist invertebrates (Grime et al.
1996; Wardle et al. 1998; Cornelissen et al. 1999; Pérez-
Harguindeguy et al. 2003) and vertebrates (McKey et al.
1978; Bryant et al. 1991). Nutrient and/or water limita-
tion tends to select for conservative strategies which re-
sult in low attractiveness to these herbivores due for ex-
ample, to leaf high tensile strength (toughness) and low
nutritive value (e.g., high C/N ratio) (Bryant et al. 1983;
Coley et al. 1985; Cebrían 1998; Díaz et al. 2004). The op-
posite applies to resource-rich environments. How
antiherbivore defences may then feedback to ecosystem
productivity via the soil is discussed in Sect. 13.5.
Finally, the strength of interactions among plants is
also expected to co-vary with other key traits along en-
vironmental gradients. This is because the nature and
the quantity of the production of secondary biochemi-
cal compounds involved in anti-herbivore defense, litter
decomposition, or allelopathy (Pellissier and Souto 1999)
can also be affected by microclimate and resource avail-
ability (Herms and Mattson 1992; Hartley and Jones 1997).
Other types of trophic interactions that influence com-
munity structure and ecosystem processes are associa-
tions with soil microbes, for instance mycorrhizae (van
der Heijden et al. 1998; Klironomos et al. 2000; Langley
and Hungate 2003; Read et al. 2004; Rillig 2004).
Cornelissen et al. (2001) revealed consistent large and
significant differences in inherent relative growth rate
(RGR), foliar chemistry and leaf litter decomposability
13.4 · Scaling from Individual Plants to Communities: from Response Traits to Community Assembly
In: Canadell JG, Pataki D, Pitelka L (eds) (2007) Terrestrial Ecosystems in a Changing World.
The IGBP Series, Springer-Verlag, Berlin Heidelberg

156 CHAPTER 13 · Plant Functional Types: Are We Getting Any Closer to the Holy Grail?
among plants with mycorrhizal association strategies.
This results in slow carbon cycling in ericoid and
ectomycorrhizal plant species from temperate ecosystems
with low pH, vs. low nitrogen availability and fast car-
bon cycling in arbuscular and non-mycorrhizal species,
found in more nitrogen-rich ecosystems with higher pH.
The relative abundance of dependent and non-depen-
dent species in a community will determine the impor-
tance of this plant-fungus interaction (Urcelay and Díaz
2003). All together, these findings support Read’s (1991)
hypothesis that mycorrhizal type is an important com-
ponent of a plant’s strategy in the context of nutrient
availability. However, at a global scale we still know little
about links between plant-associated microbes and plant
traits, or about belowground plant traits in general. Re-
cent efforts in this field are promising (Jackson et al. 1996;
Ryser 1996; Craine et al. 2003; Craine and Lee 2003;
Wardle 2002).
In order to better capture the complexities of com-
munity assembly, and how these may link to individual
plant traits, Suding et al. (2003) proposed that trade-offs
among species traits (e.g., ability to capture and cycle
resources quickly vs. leaf toughness) determine commu-
nity structure through the nature and intensity of com-
petition and other interspecific interactions depending
on environmental conditions. Our current knowledge,
as summarised above, highlights a number of these link-
ages. For instance, we expect that nutrient-poor environ-
ments will select for species with leaf traits promoting
resource conservation, such as low SLA, high tissue den-
sity and long life span. As a consequence of these pri-
mary traits, predominant plants in such environments
will compete with their neighbours by sequestering nu-
trients – possibly with the help of mycorrhizal associa-
tions, by accumulating poorly degradable litter (Berendse
1994), and sometimes through allelopathy or nutrient
immobilization (Michelsen et al. 1995; Hättenschwiller
and Vitousek 2000); while also facilitating subordinates
by herbivore protection. The converse would be expected
in nutrient-rich environments (Table 13.2).
13.5 Scaling from Communities to Ecosystems:
from Response Traits to Effect Traits
The ‘Holy Grail’ hypothesis states that environmental
changes will lead to changes in community composition
and thus in plant traits, and these in turn will affect eco-
system functioning. This hypothesis was first approached
by matching lists of response attributes with known ef-
fects of some of these attributes (or their correlates) on
ecosystem processes (Díaz et al. 1999; Walker et al. 1999;
Eviner and Chapin 2003; see also Díaz et al. 2007, Chap. 7
of this volume; see Tables 13.1 and 13.2 and Table 1 in
Lavorel and Garnier 2002). Inspections of these lists have
revealed that the resource axis has maximum overlap
between response and effect traits, whereas overlaps are
few in the case of disturbance. One essential step to un-
derstanding the causes of these differing degrees of over-
lap has been the analysis of the specific functions of the
traits involved in either response or effect (Lavorel and
Garnier 2002; see Table 13.1). For the resource axis it showed
that responses to resource availability and effects on bio-
geochemistry are jointly constrained by the trade-off
between acquisition and conservation strategies, and
their characteristic traits (Chapin et al. 1993; Grime 2001).
For example, plants growing in adverse environments
have low specific leaf area, high C/N ratio, and high ten-
sile strength. These traits make them less palatable to
generalist herbivores (see above), and persist in litter,
thereby strongly influencing decomposition (Wardle et al.
1998; Cornelissen et al. 1999; Pérez Harguindeguy et al.
2000). This way, herbivore-induced changes in the bal-
ance of palatable and unpalatable species lead to changes
in the net litter quality and therefore in decomposer ac-
tivity (Wardle et al. 1998; Cebrían et al. 1998; Wardle 2002).
Association with N2 fixing bacteria is another trait that
provides feedback on ecosystem productivity via N-rich
litter. This mechanism is in particular a recurrent one
underlying the impacts of invasive species on nutrient
cycling (D’Antonio and Corbin 2003). On the other hand,
regeneration and demographic traits associated with re-
sponse to disturbance (e.g., fire, grazing) are known to
have little direct relation with adult ecophysiological
traits, and would therefore be of little relevance to bio-
geochemistry.
The ultimate goal of response-effect analyses should
be the formulation of parsimonious quantitative re-
lationships expressing the different components of each
ecosystem function in relation to particular traits
(Lavorel and Garnier 2002; Eviner and Chapin 2003).
These relationships would make it possible to use traits
to scale from individual plants and the communities they
form to the ecosystem level (Dawson and Chapin 1993).
Such formulations have been proposed for aboveground
primary productivity (Chapin 1993 and further modi-
fications by Lavorel and Garnier 2002 and Garnier
et al. 2004). Specific annual net primary productivity
(SANPP; “ecosystem efficiency”, Reich et al. 1997) ex-
presses ANPP per gram of green biomass, and can be
written as:
where pi is the relative contribution of species i to the
biomass of the community, RGRi and (tf–to)i are the
aboveground relative growth rate and period of active
growth of species i, respectively, and ∆T is the period
over which SANPP is assessed. Garnier et al. (2004)
In: Canadell JG, Pataki D, Pitelka L (eds) (2007) Terrestrial Ecosystems in a Changing World.
The IGBP Series, Springer-Verlag, Berlin Heidelberg

157
tested this relationship against independent measure-
ments of leaf traits and productivity and showed that
specific leaf area, LDMC, and leaf nitrogen concentra-
tion are indeed correlated with SANPP due to the well-
established links between these traits and RGR (Reich
et al. 1992; Poorter and Garnier 1999). In this equation,
contributions of individual species to ecosystem func-
tion are proportional to their abundance in the com-
munity. Díaz et al. (this volume) further discuss the role
of dominant species in functional diversity – ecosystem
function relationships.
Correlations have also been established between rates
of litter decomposition and leaf traits (SLA, LDMC and
leaf tensile strength) of individual species (Cornelissen
et al. 1999) and over communities (Garnier et al. 2004).
However, in contrast to the case of ANPP there is no
mechanistic model available. Empirical relationships
between response and effects have been proposed for
several other environmental factors and ecosystem func-
tions (Chapin 2003; Eviner and Chapin 2003; Diaz et al.
2007, Chap. 7 of this volume), but developing formal
models must be the next step.
Our understanding remains even more limited when
attempting to link disturbance response and effect traits.
Lavorel and Garnier (2002) showed that the list of traits
relevant to ecosystem flammability has in fact minimal
direct overlap with traits relating to fire response. When
functional linkages between traits promoting fire toler-
ance and those involved in ecosystem flammability exist
(Bond and Midgley 1995), even once phylogeny has been
accounted for (Schwilk and Ackerly 2001), they result
from associations or trade-offs between fire response
traits and the actual traits that determine flammability,
and are therefore indirect. For instance, a high growth
rate is required to increase the success of seed regenera-
tion after fire, and is also often associated with canopy
architectures with many thin stems and high surface/
volume ratios, which promote fire. Large underground
structures allow resprouting, which increases fire sur-
vival, and drought tolerance, which allows low water po-
tential and hence increases flammability. Closer investi-
gations using phylogenetically independent analyses
across floras evolved in high vs. low fire regimes, or sites
with high vs. low resources, are needed to explore this is-
sue further. Further knowledge will also be gained by ana-
lysing trait and ecosystem processes for cases of invasions
that trigger positive fire feedback loops (D’Antonio 2000;
Grigulis et al. 2005). Likewise, formal analyses and models
linking grazing response strategies and palatability along
resource gradients are still needed to build on the abun-
dant but dispersed grazing literature (Landsberg et al. 1999;
Adler et al. 2004). Pasture agronomists have shown that
patterns of pastoral value (i.e., biomass quantity and
quality over the growing season) along gradients of nu-
trient availability can be related to response traits such
as LDMC (Cruz et al. 2002; Duru et al. 2004).
13.6 So, Are We Getting Closer to the Holy Grail?
Scaling beyond Ecosystems
13.6.1 Plant Functional Traits
and Landscape Dynamics
Plant functional types have been for a long time ‘build-
ing blocks’ of models of patch and landscape dynamics.
At the landscape scale their most widespread use has been
in models that couple successional dynamics as repre-
sented by applications of the Vital Attributes (VA) model
(Noble and Slatyer 1980) with sub-models of lateral pro-
cesses such as seed dispersal and disturbance propaga-
tion. These applications have been particularly success-
ful in the case of ‘Landscape Fire Succession Models’
(sensu Keane et al. 2007, Chap. 12 of this volume), prob-
ably because the VA scheme was first designed to cap-
ture plant response to fire, and represents an intermedi-
ate level of complexity that is amenable to sophisitication
by addition of new processes. Examples include applica-
tions to Australian wet sclerophyllous forest (Noble and
Gitay 1996), Mediterranean shrublands (Pausas 2003) and
of coniferous-dominated forests of northwestern
America (Roberts and Betz 1997).
More complex versions of VA, such as the FATE model
(Moore and Noble 1990) have been adapted to model
landscape-fire interactions (LAMOS, Grigulis et al. 2005;
FATELAND, Pausas and Ramos 2005) and responses to
other disturbances such as grazing (Cousins et al. 2003)
by including a series of semi-quantitative traits (e.g., for
shade tolerance, recruitment). The latest developments
of VA-based landscape models can take into account con-
tinuous traits and processes e.g., for biomass production
and the dispersal phase (Grigulis et al. 2005). Current
challenges lie in including biogeochemical processes, as
captured by plant effect traits into the current models
that simulate responses to changing soil resources, dis-
turbances and their modifications by climate. Such mod-
els will make it possible to better capture important non-
linearities associated with landscape dynamics (Reynolds
et al. 1997; Boer and Stafford Smith 2003).
13.6.2 Regional to Global Models –
Revisiting the Early Functional Classifications
Dynamic Global Vegetation Models (DGVMs: Foley et al.
1996; Friend et al. 1997; Woodward et al. 1998; Potter and
Klooster 1999; Sitch et al. 2003; Gerten et al. 2004) simu-
late natural vegetation distribution and terrestrial car-
bon cycling in response to atmospheric and soil envi-
ronment, disturbance and their interactions. The prop-
erties of the vegetation system arise out of competition
between a limited number of PFTs whose behavior is, in
turn, determined by basic physiological constraints.
13.6 · So, Are We Getting Closer to the Holy Grail? Scaling beyond Ecosystems
In: Canadell JG, Pataki D, Pitelka L (eds) (2007) Terrestrial Ecosystems in a Changing World.
The IGBP Series, Springer-Verlag, Berlin Heidelberg

158 CHAPTER 13 · Plant Functional Types: Are We Getting Any Closer to the Holy Grail?
DGVMs can be used with some confidence to predict the
broad-scale behavior of terrestrial vegetation in response
to observed climate changes in the recent past, and have
been used to explore the consequences of past climate
changes and future climate scenarios for the function-
ing of terrestrial ecosystems (Cramer et al. 2001; Prentice
et al. 2007, Chap. 15 of this volume). Plant functional clas-
sification is central to all current approaches to model-
ing the response of vegetation to a changing environ-
ment at regional to global scales. However, even state-of-
the-art DGVMs only use a relatively small number (<10)
of PFTs. While the bioclimatic limits of these PFTs are
explicit, their characterization in terms of observable
traits are sketchy, or at best defined from a small set of
postulated characteristics (based on life form or leaf
form) and descriptions of function (phenology, photo-
synthetic pathway, life cycle, bioclimatic tolerance).
Two approaches to improving the representation of
biospheric complexity in DGVMs have been advocated.
The first approach is simply to increase the number of
PFTs, perhaps by incorporating functional types that have
been identified as important for some specific ecologi-
cal function or are responsive to specific aspects of cli-
mate. There are more complex PFT classification schemes
(Box 1981) that would be candidates for such a model
expansion. Increasing the number of PFTs could improve
modeling of the response to both disturbance and of
migration. The IPCD approach (see Sect. 13.3) could pro-
vide a generic framework for modeling vegetation dy-
namics in chronically disturbed systems. Ongoing analy-
ses of how long distance dispersal is distributed across
life forms and in relation to other traits may inform the
development of new classifications (Higgins et al. unpub-
lished, Midgley et al. 2007, Chap. 11 of this volume). In-
creasingly detailed classifications (recognising up to
100 different PFTs) have been devised. However, it re-
mains to be examined whether and how these ‘top-down’
schemes can be matched with ‘bottom-up’ classifications
obtained from empirical work, and the degree to which
they are useful for predicting changes in community com-
position and ecosystem functioning in response to sce-
narios of changes in multiple environmental drivers. In
addition, to be able to simulate the behavior of a given
PFT, it is necessary to provide quantitative values for a
number of parameters relating to plant physiology, phe-
nology, allocation strategy and response to disturbance
(Prentice et al. 2007, Chap. 15 of this volume). Thus, data
availability is a key limitation on the number of PFTs that
could usefully be included in DGVMs. The statistical
analysis of field measurements of trait abundance along
climatic, nutrient and/or disturbance gradients (see
Sect. 13.3), and resulting data bases, may go some way to
providing these quantitative estimates but does not pro-
vide information on absolute physiological limits. Addi-
tional work in comparative ecophysiology and model-
ing is required to establish robust relationships between
‘soft’ traits that are routinely measured over a diversity
of ecosystems, and the ‘hard’ traits used by models (see
e.g., Arora and Boer 2005).
An alternative approach to increasing biotic complex-
ity in models is to simulate traits explicitly. This avoids
the classification problems inherent in defining discrete
plant functional types from trait assemblages, but still
raises the need for explicit, quantitative information for
each trait. It also requires a fundamental rearrangement
in the structure of current models. Some continental-
scale models are using continuous traits rather than a
discrete classification. For example, Berry and Roderick
(2002a,b) used two fundamental leaf traits, leaf surface
area to volume ratio and leaf thickness, to capture the
combined response to water and mineral resource avail-
ability and CO2. This classification was sufficient to de-
scribe current distribution of vegetation types on the
Australian continent and to investigate historical and
palaeoenvironmental changes. This plant functional
scheme is also a functional effects scheme, and can be
applied to modeling the carbon cycle at continental scale
(Berry and Roderick 2004). Continuous response traits
may also be used to capture other land-atmosphere feed-
backs, such as effects on climate (Chapin 2003; Díaz et al.
2007, Chap. 7 of this volume).
13.6.3 Validation: the Contribution of Paleo-Data
Palaeoecology provides insights into how vegetation has
responded to global changes in the past (Overpeck et al.
2003). Although the causes of these changes are not iden-
tical to the causes of expected future changes, our confi-
dence in the ability of models (of climate and/or ecosys-
tems) to make future projections can only be assured by
demonstrating that these models are capable of repro-
ducing the range of conditions that are documented from
different periods during the recent geological period
(Harrison and Foley 1995; Grassl 2000; Joussaume and
Taylor 2000). The ability to test models under past con-
ditions depends, in part, on palaeodata being represented
in a form compatible with global model outputs (Prentice
and Webb 1998; Kohfeld and Harrison 2000; Prentice et al.
2000). The desire for such a representation motivated
the GAIM/GCTE-sponsored Palaeovegetation Mapping
Project (BIOME 6000: Prentice and Webb, 1998 ; Prentice
et al. 2000), which used pollen and plant macrofossil data
to produce vegetation maps for the last glacial maximum
and the mid-Holocene. To reduce the taxonomic diver-
sity of the fossil data to a manageable level, BIOME 6000
adopted a method that relied on the allocation of pollen
and plant macrofossil taxa from different floras to a com-
mon global suite of PFTs. Recent regional reconstruc-
tions (Harrison et al. 2001; Bigelow et al. 2003) have con-
verged on a scheme which recognises a suite of 99 cli-
matically-diagnostic PFTs based on combination of traits
In: Canadell JG, Pataki D, Pitelka L (eds) (2007) Terrestrial Ecosystems in a Changing World.
The IGBP Series, Springer-Verlag, Berlin Heidelberg

159
describing life form, leaf morphology, phenology and
bioclimatic tolerances (principally related to cold toler-
ance mechanisms in woody plants). Together, the
BIOME 6000 data set (Prentice et al. 2000) along with
more recent updates (Harrison et al. 2001 ; Harrison and
Prentice 2003 ; Bigelow et al. 2003; Pickett et al. 2004), and
the global PFT-scheme which underlies it suggest one
route for continuing improvement of the representation
of PFTs in DGVMs.
13.7 Summary and Conclusions
Plant functional type research has soared for over ten
years under the impetus of GCTE. The requirement from
large scale ecosystem models to group plants according
to similarity in response to changes in their environment
and effects on ecosystem structure and processes has
proved to be the ‘Holy Grail’ of plant functional type re-
search.
One first achievement has been the production of
standardised lists of the most significant and easily mea-
surable and well understood traits. Based on these and
large data bases, and on large efforts to synthesise the
literature, it has been possible to identify and explain
plant functional response traits associated with response
to resource gradients (esp. nutrients) and widespread
disturbances such as grazing and fire. Current research
is focusing on the links between these and effects on bio-
geochemistry, confirming the relevance of fundamental
trade-offs that constrain the way plants manage their
resources (Grime 2001). This progress and the remain-
ing challenges for ecosystem level plant functional re-
search can be summarised in a series of confirmed or
hypothetical linkages between individual plant traits and
processes at different levels of organisation (Table 13.2).
Significant remaining challenges not only concern fur-
ther understanding the significance of particular traits,
fundamental trade-offs among them, or how short a mini-
mal trait list can be. First, understanding the mechanisms
through which species traits, as determined by environ-
mental factors, determine community structure is a pri-
ority that will require theoretical, experimental and mod-
eling approaches. Second, our understanding of how
these response traits also determine (or not) effects on
ecosystems, remains very preliminary. Significant chal-
lenges to be addressed regard effects of plant disturbance
response on biogeochemical cycles and on disturbance
regimes. For this, and also to further resolve the effects
of plant resource response on biogeochemistry, it is es-
sential to recognize that simultaneous effects on multiple,
linked ecosystem processes are involved (Chapin 2003).
Progress in this area will call upon multi-factorial ma-
nipulations (see Norby et al. 2007, Chap. 3 of this volume),
biodiversity experiments (Hooper et al. 2005; Naeem et al.
2003 and the further development of ecosystem models
that directly use those plant traits that can be easily mea-
sured for large numbers of species.
Current approaches to defining PFTs that emphasize
the importance of classifying plants according to well-
defined, readily observable and usually continuous plant
traits with known responses to particular environmen-
tal factors (CO2 concentration, soil resources, climate, and
different types of disturbances) should encourage the
development of a new generation of DGVMs that explic-
itly represent key features of this global classification.
Model development, however, needs to be paralleled by
the global collection of trait data following unified pro-
tocols, and by the development of an internally-consis-
tent modern (actual) vegetation map explicitly based on
plant functional properties (Nemani and Running 1996).
“The same happens to all of us. One hears about the
Grail and one thinks one is the only one who will find it”
(U. Eco, Baudolino). Rather, the last decade of plant func-
tional research has taught us that, if “There is much to be
done. There is also a real hope that we may be getting
somewhere” (Westoby et al. 2002), getting somewhere will
require continued collaboration across those multiple
fields that span from ecophysiology to global modeling.
Acknowledgments
We thank the members and Task leaders of the GCTE
PFT network for their continued contribution to the de-
velopment of the ideas presented here, and the relentless
efforts in data collection around the world. Special Ac-
knowledgments are made for initial ideas and contin-
ued support over the years to: Terry Chapin, Wolfgang
Cramer, Phil Grime, Ian Noble, Colin Prentice and Will
Steffen. Sandra Lavorel is supported by the CNRS ATIP
project and group members ‘Functional traits and dy-
namics of alpine ecosystems’.
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