Review: Plant Functional Traits With Particular Reference To Tropical Deciduous Forests: A Review

Review
Plant functional traits with particular reference to tropical

deciduous forests: A review
* AS RAGHUBANSHI and
RK CHATURVEDI 1, 2 JS SINGH 1
1 2
Ecosystems Analysis Laboratory, Department of Botany( and Institute of Environment and
Sustainable Development, Banaras Hindu University, Varanasi 221 005, India
*Corresponding author (Fax, 0542 2368174; Email, ravikantchaturvedi10@gmail.com)
Functional traits (FTs) integrate the ecological and evolutionary history of a species, and can potentially be used to
predict its response as well as its influence on ecosystem functioning. Study of inter-specific variation in the FTs of
plants aids in classifying species into plant functional types (PFTs) and provides insights into fundamental patterns
and trade-offs in plant form and functioning and the effect of changing species composition on ecosystem functions.
Specifically, this paper focuses on those FTs that make a species successful in the dry tropical environment.
Following a brief overview, we discuss plant FTs that may be particularly relevant to tropical deciduous forests
(TDFs). We consider the traits under the following categories: leaf traits, stem and root traits, reproductive traits,
and traits particularly relevant to water availability. We compile quantitative information on functional traits of dry
tropical forest species. We also discuss trait-based grouping of plants into PFTs. We recognize that there is
incomplete knowledge about many FTs and their effects on TDFs and point out the need for further research on
PFTs of TDF species, which can enable prediction of the dynamics of these forests in the face of disturbance and
global climate change. Correlations between structural and ecophysiological traits and ecosystem functioning should
also be established which could make it possible to generate predictions of changes in ecosystem services from
changes in functional composition.
[Chaturvedi RK, Raghubanshi AS and Singh JS 2011 Plant functional traits with particular reference to tropical deciduous forests: A review.
J. Biosci. 36 963–981] DOI 10.1007/s12038-011-9159-1
1. Introduction Cabido 2001). In recent years, the possible effects of

terrestrial plant diversity on ecosystem processes and
Plant functional traits (FTs) can be defined as ‘plant services are increasingly being documented (see Díaz et al.
characteristics that respond to the dominant ecosystem 2003; Mooney et al. 2009; Mooney 2010), and ecologists
processes’ (Gitay and Noble 1997). Examples of FTs are are trying to develop functional classifications of species to
leaf size, toughness and longevity, seed size and dispersal comprehend the complex diversity of life on earth
mode, canopy height and structure, ability to resprout (McIntyre et al. 1999; Weiher et al. 1999). Garnier et al.
and capacity for symbiotic fixation of nitrogen (Díaz and (2007) presented a standardized methodology that used FTs
to assess
Keywords. Ecosystem functioning; environmental change; functional traits; leaf traits; moisture stress; tropical deciduous forest
Abbreviations: Aarea, area-based leaf maximum photosynthetic rate; A mass, mass-based leaf maximum photosynthetic rate; ANPP, above
ground net primary production; ATP, adenosine triphosphate; Ca mass, mass-based calcium concentration; CC, leaf construction cost; Chl,
chlorophyll concentration; Cmass, mass-based carbon concentration; DBH, diameter at breast height; E, leaf transpiration rate; FT,
functional trait; gc, leaf stomatal conductance, K mass, mass-based potassium concentration; LA, leaf area; LAI, leaf area index; LDMC,
leaf dry matter content; LL, leaf life-span; LMA, leaf mass per area; LNC, leaf nitrogen concentration; LPC, leaf phosphorus
concentration; LSCmax, maximum leaf specific hydraulic conductivity; LWC, leaf water content; Na mass, mass-based sodium
concentration; Nmass, mass-based nitrogen concentration; PFT, plant functional type; P mass, mass-based phosphorus concentration; Rd area,
area-based dark respiration rate; Rd mass, mass-based dark respiration rate; Rd max, maximum rate of dark respiration; SLA, specific leaf
area; SSD, specific stem density; TDF, tropical deciduous forest; TDMC, twig dry matter content; WUEi, intrinsic water use efficiency
http://www.ias.ac.in/jbiosci J. Biosci. 36(5), December 2011, 963–981, * Indian Academy of Sciences

963
964 RK Chaturvedi, AS Raghubanshi and JS Singh
forests occurring in tropical regions which are characterized
the impacts of land-use changes on vegetation and
by pronounced seasonality in rainfall distribution with
ecosystem functioning. They studied 16 traits describing
several
plant stature, leaf characteristics and reproduction for the
most dominant species at 11 sites representing various types
of land-use changes occurring in marginal agro-ecosystems
across Europe and Israel. According to their results, the
functional traits were able to describe adequately the
functional response of vegetation to land-use changes.
Thus, a consideration of FTs makes it possible to seek
general explanations for differences in functioning of
climatically and edaphically diverse environments
(Pakeman 2004).
Understanding the mechanisms through which species
traits determine community structure is also a priority area
of research (Lavorel et al. 2007). A recent trait based
approach to community assembly helped to integrate
functional ecology and gradient analysis with community
ecology and coexistence theory (Ackerly and Cornwell
2007). Kraft et al. (2008) examined the co-occurrence
patterns of over 1100 tree species in a 25-hectare
Amazonian forest plot in relation to field measured
functional traits and showed that inter-specific differences
in trait-based ecological strategies contribute to the
maintenance of diversity in one of the most diverse tropical
forests in the world.
The complexity and diversity of natural systems makes
grouping of species essential for deriving general principles
of succession and ecosystem recovery following human
impact (Keddy 1992; Grime et al. 1997; Westoby 1998;
Aubin et al. 2009). Traditionally, species have been
grouped into plant functional types (PFTs) on the basis of
their physiological/ecological functions and common
evolutionary history (Noble and Gitay 1996). However,
there has also been a search for the functional description of
vegetation based on FTs that show a common response to
the environment, independent of phylogeny (Rusch et al.
2003). Mouchet et al. (2010) have inferred that in
combination with phylogenetic and taxonomic diversity,
functional diversity will ‘improve our understanding of how
biodiversity interacts with ecosystem processes and
environmental constraints’. In many poorly described plant
communities where taxonomic knowledge is limited, an
FT approach can be used to understand and predict
plant responses to changing management factors and
environment (Díaz et al. 2001). Plant functional groupings
are also potentially useful communication tools for land
managers, who may not necessarily relate to taxonomic
units, particularly when dealing with species-rich
ecosystems (Díaz et al. 2002).
According to Holdridge (1967), tropical forests comprise
about 52% of the global forest cover, and tropical dry
forests comprise 42% of tropical forests. In India, tropical
dry forests account for 38.2% of the total forest cover
(MoEF 1999). Tropical deciduous forests (TDFs) are
J. Biosci. 36(5), December 2011

Plant functional traits in tropical deciduous forests 965
Functional traits are directly or indirectly linked to plant
months of drought (Mooney et al. 1995). TDFs are population and ecosystem processes (Hillebrand and
typically dominated by deciduous trees where at least
50% of trees present are drought deciduous, the mean Matthiessen 2009). The provides insights into the
annual temperature is >25°C, total annual precipitation correlations between patterns and trade- offs in
ranges between 700 and 2000 mm, and there are 3 or structural and plant form and functioning
more dry months (with precipitation < 100 mm) every ecophysiological traits and (e.g. Poorter and Bergkotte
year (Sánchez-Azofeifa et al. 2005). Pennington et al. ecosystem functioning, 1992; Reich et al. 1992; Von
(2006) use a wider interpretation of TDF which includes including primary Willert et al. 1992; Grime et
vegetation that experiences a minimum dry season period productivity, decomposition al. 1997; Lambers et al.
of 5–6 months, resulting in strongly seasonal ecological and nutrient cycling, and 1998; Craine et al. 2001) and
processes and functions. water availability could reveals the effects of
TDFs have historically supported high human (changing) species
make it possible to predict
population densities because their climatic and edaphic composition on ecosystem
changes in ecosystem
characteristics are attractive for human settlement and functions (e.g. Schulze and
services from changes in
development (Tosi and Voertman 1964; Sánchez-Azofeifa Mooney 1994;
functional composition. MacGillivray et al. 1995;
et al. 2005). Dry forests are more threatened and less Changing species
protected than moist and wet forests (Gerhardt 1993; Wardle et al. 1998; Díaz et
composition can change FT al. 1999).
Powers and Tiffin 2010) and have decreased in area
composition, which in turn Geber and Griffen (2003)
considerably during the past decades. In central India they
affects the ecosystem defined a functional trait as
are threatened by lopping, burning, overgrazing and
functioning that depends any phenotypic character that
clearing for cultivation (Jha and Singh 1990), and as a
result, the forest cover in most regions is being converted, both on the traits of influences an organism’s
over the past several decades, into dry deciduous scrub, species that decline or fitness and reported that the
savanna and grasslands that are progres- sively species- disappear and the traits of influence of FTs on final
poor (Champion and Seth 1968; Sagar and Singh 2003). species that replace them fitness can be complex
These forests are vulnerable to stress during successional (Díaz et al. 2003; Suding et because of the
processes as they experience a severe and less predictable al. 2006; Lavorel et al. interrelationships among
environment (Murphy and Lugo 1986). 2007). FTs. They also argued that
Plant species in TDFs are subjected to water stress There is much variation FTs affect fitness through
during the dry season (Eamus 1999), and the length of dry in plant traits among species performance measures such
season is the controlling factor of vegetation structure and (Wardle et al. 1998; as growth rate, competitive
patterns (Gritti et al. 2010). Due to locational differences Kooyman and Westoby ability, herbivore resistance
in the extent and intensity of seasonal drought, TDFs are 2009) and across groups of to tolerance, attractiveness to
com- posed of a mosaic of different PFTs showing species (Garnier 1991).The pollinators, etc. The
varying adaptations to seasonal drought (Borchert 2000). relative importance of FTs performance measures, in
In the present article, following a brief background, we in determining ecosystem turn, affect fitness
review the literature on plant FTs which are particularly processes changes across components such as age-
relevant to TDFs in order to understand the relationship plant groups (Cornelissen specific rates of survival,
between FTs and functioning of plants in tropical and Thompson 1997; growth, fertility, or mating
deciduous forest ecosystems. We consider the traits under McLaren and Turkington success, and, eventually,
following categories: leaf traits, stem and root traits, 2010). Further, plant effects lifetime fitness. Violle et al.
reproductive traits and traits particularly relevant to water on any ecosystem process (2007) consider functional
availability and discuss their relevance to functioning of can be mediated by multiple traits as morpho-physio-
tropical deciduous forest ecosystems. We also discuss traits, and many of these phenological traits that affect
trait-based grouping of plants into PFTs. Finally, this traits vary independently fitness indirectly through
article compiles information on FTs of TDF species, and from one another (Eviner their effects on growth,
recognizes that there is incomplete knowledge about and Chapin 2003). Specific reproduction and survival.
many FTs and suggests the need for further research on processes could be affected Currently, the
FTs and their effects on TDFs. We suggest that a major by a combination of traits, construction of a large
focus of research should be to evaluate those FTs that while particular key traits database of FTs is gaining
make a species successful in relation to moisture gradient. could simultaneously high priority in the research
control multiple processes agenda of plant ecology
2. Plant functional traits and ecosystem processes (de Bello et al. 2010). A (e.g. Westoby and Wright
consideration of inter- 2006; TraitNet:
specific variation in FTs http://traitnet.ecoinformatics
.org/) because it appears as et al. (2006), the efficiency A high priority goal to
3. Tropical help reduce the measuring
a fundamental step both to of whole-plant nitrogen
deciduous forest effort is
understand and to predict use, uptake and response
functional traits the identification of
the distribution of species increase monotonically
in the present and future relationships between tree
with decreasing soil physiology and tree (or
environments (Grime et al. As mentioned above,
tropical deciduous forests nitrogen and water, and it leaf) morphological and
1988; Keddy 1992; is higher on infertile (dry)
are characterized by phenological traits.
Westoby 1998), and to habitats than on fertile
warm temperatures and a Examples are leaf lifespan
relate the functioning of (wet) habitats.
dry period of 3 or more – photosynthesis or leaf
species to that of
months. Deciduousness is There are a number of conductance relations,
ecosystems (Grime 1997;
a phenological attribute FTs that can influence specific leaf area –
Chapin et al. 2000).
expressing adaptation to ecosystem processes in photosynthesis
seasonality and drought, TDFs. Starting with relationships (e.g. Reich et
resulting in reduced vegetative traits, various al. 1998), and tree height –
activities during the growth forms represent photosynthesis relations
unfavourable season and adaptations in response to (Zhang et al. 2009; Brienen
resumption of growth with et al. 2010). Data are now
grazing by different
variable rates of resource available on tropical
herbivores. Life forms
use during the short deciduous trees with
favourable season (Singh with perennating tissues respect to selected
and Singh 1992). The help in the survival of physiological attributes or
deciduousness of TDF plant species from functional relationships
species is affected by unpredictable such as (i) nitrogen and
rainfall, temperature and disturbances. Plant height water use efficiency
solar radiation and affects is associated with (Sobrado 1991), (ii)
intra- and inter-annual competitive vigour and photosynthetic
pattern of water, carbon whole plant fecundity characteristics and
and energy balance in (Cornelissen et al. 2003). associated traits (Kitajima
TDFs (Bohlman 2010). Clonality, spinescence and et al. 1997; Niinemets and
FTs that enable flammability are also Tenhunen 1997; Niinemets
acquisition of limiting important vegetative traits 1999; Niinemets et al.
nutrients and water are 2009; Posada et al. 2009),
of plant species in TDFs
important for TDF species. (iii) water and trait relations
(Saha and Howe 2003;
Plant water uptake (Olivares and Medina 1992;
Raherison and Grouzis Medina and Francisco
patterns from different 2005). 1994; Franco et al.
soil depths, which often
vary spatially and 2005; Wright et al. 2007; damage (Janzen 1970; Coley
temporally between Gotsch et al. 2010), (iv) and Barone 1996; Coley
different plant functional light- dependent leaf trait 1998; Arnold and Asquith
groups or types, can variations (Rozendaal et al. 2002; Campo and Dirzo
directly influence soil 2006; Markesteijn et al. 2003; Brenes-Arguedas et al.
water dynamics during the 2007), (v) nitrogen fixation 2009) and (viii) leaf flushing
growing season (Ryel et and nitrate/ ammonium and flowering phenology
assimilation capacities (Opler et al. 1980; Seghieri
al. 2008; Schwinning
(Schulze et al. 1991; et al. 2009; Hayden et al.
2010). Apart from water,
Högberg 1992; Högberg and 2010; Fallas-Cedeño et al.
nutrient supply also limits
Alexander 1995; Freitas et 2010). However, despite
growth rates in TDFs al. 2010), (vi) drought rapid progress in the field of
(Hedin et al. 2009) and effects on leaf conductance, dry tropical tree
may determine spatial leaf water status and ecophysiology, most studies
variation in growth of photosynthesis (Eamus (a) do not consider more than
individual species in these 1999; Brodribb et al. 2003; two or three FTs (which
forests (Swaine et al. Brodribb and Holbrook makes a multivariate analysis
1987). According to Yuan 2003a,b), (vii) herbivore of tree character sets

Plant functional traits in tropical deciduous forests 967
difficult), (b) refer to tree Three such traits are SLA
saplings instead of adults (specific leaf area, i.e. the the whole plant level species (e.g. CC; Villar and
(which do not reveal the ratio of leaf area to dry (Grime et al. 1997; Poorter Merino 2001), values of
complete picture, because mass), LDMC (leaf dry and Garnier 1999; Lavorel other traits differ between
there are changes in many matter content. i.e. the ratio et al. 2007). the species of these two
biological processes as of leaf dry mass to saturated Data available on leaf habits. In the TDF,
organisms grow and age, fresh mass) and LNC (leaf various leaf traits of tree broad-leaved deciduous
leading to increased nitrogen concentration) species in TDFs are trees are reported to have
structural complexity) and (Cunningham et al. 1999; limited, and summarized greater SLA, LNC and
(c) are related to the Reich et al. 1999; Wilson et in table 1. There are photosynthetic rates as
neotropics, therefore al. 1999; Markesteijn et al. marked inter-specific and compared to broad- leaved
limiting generalizations 2007). Two of these traits inter-regional variations in evergreen trees (see
about the pattern of (SLA and LNC) have the values of most of the references in Powers and
functional trait already been compiled into a traits. Inter-specific Tiffin 2010). The mean
relationships worldwide database (Wright et al. variation in a majority of values of leaf life-span
(Díaz et al. 2004; Wright et 2004). SLA and LNC of cases was larger than the (LL) for desert (14 mo),
al. 2007). In the following component species may have inter-regional variation tropical evergreen (20 mo),
subsections, we review our a significant impact on (table 1). For example, temperate evergreen (44
understanding of functional primary productivity and while mean SLA of TDF mo), temperate deciduous
traits in TDFs. nutrient cycling at the species among six (13 mo) and tundra (7 mo)
ecosystem level (Reich et al. countries varied between species (Reich et al. 1998)
3.1 L 1992; Cornelissen et al. 8.5 mm2 mg−1 (Panama) to are greater than the value (6
e 1999; Aerts and Chapin 20.7 mm2 mg−1 (Bolivia), mo) observed by Prior et
a 2000). This is because a within a region (e.g. al. (2003) for deciduous
f combination of SLA and Argentina) the maximum species of Australia. Thus,
LNC, which are related to value of SLA was more mean LL is shorter and
t leaf lifespan, can predict than six times the LMA is lower in TDF
r accurately the maximum minimum value. The species compared to
a photosynthetic rate of a desert, tropical evergreen, evergreen woody species
i wide range of species (Reich temperate evergreen and (Wright et al. 2004a). In
t et al. 1997). A similar tundra species usually Argentina, the desert
s argument has been made for have lower SLA than the species showed greater
LDMC (Ryser and Urbas TDF species. For example, average leaf thickness (1.9
Leaf habit (i.e. 2000). The above traits are SLA ranged between 6.2 mm) and LWC (80%) as
deciduousness/evergreenne involved in a trade-off and compared to the average
ss) has been traditionally between rapid biomass 4.7 mm2mg−1 in desert leaf thickness (0.3 mm) and
considered as an important production and efficient species (Reich et al. LWC (60%) of deciduous
1998; species (Vendramini et al.
FT for grouping species nutrient conservation at
Vendramini et al. 2002), 2002). Among
into ecologically relevant
PFTs. However, Powers 5.9 and 9.7 mm2 mg−1 in ecophysiological traits, gc
and Tiffin (2010) analysed tropical evergreen of TDF species also varied
the potential of leaf habit as (Vendramini et al. 2002; substantially among the
a trait for defining Santiago 2003), 4.2 and regions and species (table
ecologically meaningful 4.8 mm2 mg−1 in 1). The reported values for
groups of tropical dry temperate evergreen gc from desert (329 mmol
forest species, and (Reich et al. 1995; Reich m−2 s−1; Horton et al.
concluded that leaf habit et al. 1998) and 3.3 and 2001), tropical evergreen
alone has little utility in 7.0 mm2 mg−1 in tundra (90 mmol m−2 s−1; Ishida
distinguishing PFTs in the species (Körner et al. et al. 2006) and temperate
Costa Rican TDFs. It has 1986; Reich et al. 1998) deciduous (190 mmol m−2
been rightly argued that a compared to the TDF s−1; Kubiske and Abrams
database of FTs must range of 8.5 to 18.6 mm2 1993) are lower compared
include all traits that are mg−1 (table 1). While to the values for TDF
relevant to acquisition and some leaf trait values of species (205 to 680 mmol
use of resources (Westoby TDF species are similar to m−2 s−1; table 1). On the
1998; Weiher et al. 1999). those of tropical evergreen contrary, Aarea, Nmass, Pmass
and Cmass exhibited little
variation among regions
and species (table 1).
Generally, deciduous
trees maintain greater
Nmass than evergreen
species and consequently
maintain larger light
saturated assimilation rate
(Eamus 1999). Rdarea of
TDF species (0.6–1.9
μmol m−2 s−1; table 1) is
lower than that of desert
species (2.4 μmol m−2
s−1; Reich et al. 1998)
but is within

Table 1. List of leaf traits of tree species in tropical deciduous forests
Species/Forest Mean Value Range ±1SE References

2 -1
Dry forest of Panama SLA
8.5 (n= 7) (mm mg
5.0) to 12.5 0.9 Santiago 2003
Deciduous forest of Australia 9.9 (n= 2) 9.0 to 10.7 0.8 Eamus and Prichard 1998
Dry forest of Costa Rica 10.2 (n=87) 5.5 to 23.0 3.6 Powers and Tiffin 2010
Deciduous forest of India 10.9 (n=54) 6.4 to 19.1 0.4 Lal et al. 2001
Deciduous forest of central-western Argentina 11.2 (n=16) 4.2 to 25.4 1.5 Vendramini et al. 2002
Deciduous forest of India 11.7 (n=6) 7.6 to 14.4 1.3 Chaturvedi et al. 2011
Dry forest of Panama 12.6 (n=6) 7.3 to 21.9 1.1 Kitajima et al. 1997
Deciduous forest of India 11.4 (n=7) 8.8 to 16.9 1.0 Pandey et al. 2009
Deciduous forest of central-western Argentina 15.0 (n=23) nk 1.2 Cornelissen et al. 1999
Dry forest of Venezuela 18.6 (n=6) 11.6 to 26.8 2.9 Sobrado 1991
Dry deciduous forest of Bolivia 20.7 (n=12) 11.5 to 26.9 6.0 Markesteijn et al. 2011
LA (cm2)
Dry monsoon forest of Australia 40.0 (n=4) 31.0 to 64.0 8.0 Prior et al. 2004
Dry deciduous forest of Bolivia 45.1 (n=12) 2.5 to 201 13.0 Markesteijn et al. 2011
Deciduous forest of India 75.9 (n=7) 26.4 to 143 17.6 Pandey et al. 2009
Chl (mg g-1)
Deciduous forest of India 0.93 (n=7) 0.72 to 1.26 0.08 Pandey et al. 2009
LDMC (% saturated wt.)
Deciduous forest of central-western Argentina 35.9 (n=13) 13.4 to 47.4 3.6 Vaieretti et al. 2007
Nmass (%)
Savanna of Africa 1.3 (n= 4) 1.2 to 1.6 0.2 Manlay et al. 2002
Dry forest of Brazil 1.8 (n= 3) 1.4 to 2.1 0.3 Geßler et al. 2005
Deciduous forest of Australia 1.8 (n= 27) 0.8 to 4.0 0.3 Roderick et al. 1999
Deciduous forest of India 2.0 (n= 54) 0.9 to 3.2 0.1 Lal et al. 2001
Deciduous forest of Central Ethiopia 2.1 (n= 7) 1.7 to 3.2 0.3 Kindu et al. 2006
Deciduous forest of India 2.2 (n= 6) 1.9 to 2.5 0.1 Chaturvedi et al. 2011
Dry forest of Panama 2.3 (n= 8) nk 0.2 Santiago 2003
Dry forest of Costa Rica 2.3 (n= 87) 1.2 to 3.6 0.7 Powers and Tiffin 2010
Deciduous forest of Australia 2.4 (n= 6) 1.1 to 3.2 0.4 Prior et al. 2003
Dry forest of Panama 2.4 (n= 6) 1.5 to 3.8 0.3 Kitajima et al. 1997
LL (mo)
Dry forest of Venezuela 8.4 (n= 6) 6.0 to 10.0 1.3 Sobrado 1991
Table 1 (continued)
Aarea (μmol m-2s-1)
Lowland forest of Panama 12.9 (n=16) 9.7 to 18.3 0.7 Santiago 2003
Deciduous forest of Australia 13.9 (n=6) 9.6 to 18.7 1.3 Prior et al. 2003
Deciduous forest of Australia 14.8 (n=2) 14.0 to 15.6 0.8 Eamus and Prichard 1998
Amass (nmol g-1s-1)
Dry forest of Panama 122.3 (n=7) 58.1 to 200.4 17.5 Santiago 2003
Rdarea (μmol m-2s-1)
gc (mmol m-2s-1)
Dry forest of Venezuela 204.8 (n=5) 140.7 to 274.8 23.0 Sobrado 1991
Dry forest of Panama 456.6 (n=7) 199.3 to 670.2 91.4 Santiago 2003
WUEi (μmol mol-1)
Savanna of central Venezuela 37.5 (n=3) 30.4 to 46.0 4.6 Medina and Francisco 1994
Tropical dry forest of Venezuela 44.8 (n=6) 36.0 to 53.0 2.7 Sobrado 1991
Pmass (%)
Savanna of Africa 0.07 (n=4) 0.05 to 0.09 0.01 Manlay et al. 2002
Deciduous forest of Central Ethiopia 0.18 (n=7) 0.15 to 0.30 0.03 Kindu et al. 2006
LSCmax (mmol m-1s-1MPa-1)
Lowland forest of Panama 53.8 (n=16) 15.8 to 120.7 6.8 Santiago 2003
Dry tropical forest of Costa Rica 19.3 (n=3) 15.0 to 25.0 11.2 Brodribb and Holbrook 2003a
Table 1 (continued)
E (mmol m-2s-1)
Dry forest of Venezuela 6.5 (n= 4) 5.2 to 7.7 0.5 Sobrado 1991
CC (g glu.g-1)
Dry forest of Charallave, Venezuela 1.5 (n= 7) 1.4 to 1.6 0.02 Villar and Merino 2001
LWC (%)
Deciduous forest of central-western Argentina 60.4 (n=16) 38.0 to 83.0 3.0 Vendramini et al. 2002
Cmass (%)
Savanna of Africa 37.3 (n=4) 35.8 to 39.7 1.3 Manlay et al. 2002
Dry forest of Brazil 43.0 (n=2) 42.7 to 43.3 0.6 Geßler et al. 2005
Deciduous forest of India 46.3 (n=8) 44.8 to 47.4 0.7 Negi et al. 2003
Dry forest of Panama 49.0 (n=8) nk 0.8 Santiago 2003
Deciduous forest of Australia 49.2 (n=27) 0.41 to 57.6 1.4 Roderick et al. 1999
Namass (%)
Deciduous forest of India 0.07 (n=25) nk 0.01 Singh and Singh 1991
Kmass (%)
Camass (%)
Deciduous forest of India 1.2 (n= 8) 0.6 to 2.3 0.3 Negi et al. 2003
Thickness (mm)
Deciduous forest of central-western Argentina 0.4 (n= 16) 0.2 to 0.6 0.03 Vendramini et al. 2002
n=number of species, nk= not known. SLA (specific leaf area); LA (leaf area); Chl (chlorophyll concentration); LDMC (leaf dry matter
content); LSCmax (maximum leaf specific hydraulic conductivity); A area (area-based leaf maximum photosynthetic rate); A mass (mass-
based leaf maximum photosynthetic rate); Rd area (area-based dark respiration rate); E (leaf transpiration rate); g c (leaf stomatal
conductance); WUEi (intrinsic water use efficiency); CC (leaf construction cost); LWC (leaf water content); N mass (mass-based nitrogen
concentration); LL (leaf life-span); P mass (mass-based phosphorus concentration); C mass (mass-based carbon concentration); Na mass (mass-
based sodium concentration); Kmass (mass-based potassium concentration); Camass (mass-based calcium concentration).
the range of 0. 8–1.3 μmol m−2 s−1 observed for tropical
density and leaf thickness. LWC, although not typically
evergreen, temperate evergreen, temperate deciduous and
considered as a plant functional trait, is important for
tundra species (Reich et al. 1998). Santiago (2003)
properties such as flammability and can be quantified
observed greater mean value of LSCmax in evergreen
through remote sensing (Powers and Tiffin 2010). Leaf-
species (83.4 mmol m−1 s−1MPa−1) than the deciduous
area-based maximum photosynthetic rate (Aarea) and stomatal
species (19. 3 mmol m−1 s−1MPa−1) of Costa Rica. conductance are positively correlated with maximum
Growth potential of a species is an integrated outcome of specific hydraulic conductivity (LSCmax) of leaf (Santiago et
responses of various traits and is particularly determined by al. 2004). Chl is highly correlated with LNC (Marino et al.
its leaf traits. A study in an abandoned grazing land in 2010). According to Loranger and Shipley (2010), thicker
Australia proved SLA as the best predictor of response to leaves have high stomatal density and low Chl. Many
land-use change (Meers et al. 2008). Bertiller et al. (2006) studies have shown that the photochemical part of the
have studied leaf strategies and soil nitrogen across a photosynthetic apparatus increases relative to the
regional humidity gradient in Patagonia and reported that biochemical part at low light to enhance light harvesting
the leaf traits related to carbon fixation and the and provide the energy for carbon fixation (see Kull 2002
decomposition pathway significantly varied with humidity. for a review). This acclimation pattern is expected to lead to
Wright et al. (2004b) identified six leaf traits that together an increased chlorophyll-to- nitrogen ratio in low light
capture many essentials of carbon economy of the leaf: (Hallik et al. 2009). Leaf area (LA), the one-sided projected
LMA, Amass, leaf nitrogen concentration (LNC), leaf surface area of the leaf, is an essential component of plant
phosphorus concentration (LPC), rate of dark respiration growth analysis and evapo- transpirational studies. It also
(Rdmax) and leaf lifespan (LL). LMA measures investment has large influence on transpitation rate (E) (Enoch and
of dry matter per unit of light- intercepting leaf area Hurd 1979). It is useful in the analysis of canopy
deployed. LMA can be calculated as 1/ SLA. High LMA architecture as it allows determination of LAI. It is related
means a thicker leaf blade or denser tissue, or both. Amass is to canopy light interception and photosynthetic efficiency
the photosynthetic assimilation rate measured under high and contributes to the carbohydrate metabolism, dry matter
light, ample soil moisture and ambient CO 2. Stomatal accumulation, yield and RGR (Leith et al. 1986, Williams
conductance and the drawdown of CO2 concentration inside 1987; Centritto et al. 2000). Leaf construction cost (CC) is
the leaf (carboxylation capacity) influence Amass. While considered as the energy invested by plants to synthesize
Amass in deciduous species is zero during the dry period carbon skeletons and nitrogenous compounds (Baruch and
when trees are leafless, the decline in A mass is much less Goldstein 1999). Indirectly CC can also be related to
under low water conditions in mature evergreen tree efficiency of resource utilization (Williams et al. 1987;
species (15–50%) and semi-deciduous species (25–75%) Lambers and Poorter 1992; Griffin 1994).
(Eamus 1999). Leaf nitrogen is integral to the proteins of
According to Chapin (1980), low LNC and LPC are
photosynthetic machinery, especially RuBisCo, which is
characteristics of plants having relatively high nutrient-
responsible for drawdown of CO2 inside the leaf. The
use efficiency. In unproductive habitats, plant species
drawdown of CO2 is also affected by leaf structure.
increase leaf carbon content (C mass) by accumulating
Phosphorus occurs in nucleic acids, lipid membranes and
many carbon-based secondary compounds including
bioenergetic molecules such as ATP. According to
lignin and tannins (Coley et al. 1985; Lambers and
Westoby and Wright (2006), leaf N:P ratio increases with
Poorter 1992), and it has been suggested that leaves of
temperature, and species with lower absolute LNC and LPC
species accumulating these compounds have high CC
tend to have higher N:P ratio, which in turn is associated
(Miller and Stoner 1979). In other studies, concentration
with slow leaf-specific growth rates. The mean N:P ratio of
of nutrients such as nitrogen, phosphorus, sodium,
tree leaves for deciduous woody species is lower than that
potassium and calcium in leaves control retranslocation
for evergreens (Wright et al. 2004a). Leaf dark respiration
of nitrogen and phosphorus from senescing leaves
rate per unit mass (Rdmass) reflects metabolic expenditure of
(Loneragan et al. 1976). Plants having high nutrient
photosynthate, especially protein turnover and phloem-
concentration in leaves retranslocate larger proportions of
loading of photosynthates and is related to LMA (Reich
nitrogen and phosphorus than do plants with low nutrient
et al. 1997). LL describes the average duration of the
status (Miller et al. 1976; Turner and Olson 1976). All the
revenue stream from each leaf constructed. Long LL
above-mentioned traits exhibit plasticity. Plasticity is
requires robust construction in the form of high LMA.
particularly high along moisture gradients, being the least
There are other leaf traits that are either directly or
in the dry forest and greatest in the moist forest tree species
indirectly associated with the above-mentioned traits.
(Markesteijn et al. 2007). Studies also indicate that there is
According to Vendramini et al. (2002), variation in SLA
no substantial change in species ranking for these traits in
depends on changes in leaf tissue density or leaf water
time or across different environments (Jurik 1986;
content (LWC), which is closely correlated with tissue
Thompson et al. 1997; Garnier et al. 2001).
3.2 Stem and root traits major natural or anthropogenic disturbance could prove an
For the maintenance of physiological activity of dry forest

species, the minimum seasonal water potential is
ecologically relevant (Bhaskar and Ackerly 2006). Wright
et al. (2006) studied many leaf and stem traits and found
that their coordinated effect is very important for a plant’s
water use efficiency. Therefore, study of stem and root
traits along with leaf traits are important to detect the effect
of water stress on the physiology of dry tropical plant
species. Also, FTs which enable acquisition of limiting
nutrients such as extensive root foraging and/or association
with mycorrhizal fungi may be important for C dynamics
(de Deyn et al. 2008).
Stem FTs include specific stem density (SSD) or wood-
specific gravity, which is directly associated with soil water
availability (Preston et al. 2006), and above-ground wood
productivity along with species maximum height (Baker et
al. 2008). Increasing wood density is associated with
decline in wood water content, and hence its potential for
water storage (Borchert 1994). SSD has been emphasized
for studying the rehydration processes in species showing
variable duration of deciduousness (Eamus and Prior 2001)
– it is a good predictor of resistance to drought-driven
embolism (Sperry 2003). Higher SSD appears to be related
to smaller leaf and twig sizes (Westoby and Wright 2006).
Other stem FTs include twig dry matter content (TDMC)
and bark thickness, which helps plants survive lethally high
temperature associated with fire. Since aboveground and
belowground plant traits involved in C cycling are weakly
coupled, identification of easily measurable, cost-effective,
aboveground traits that may capture belowground C
dynamics is an important area of research (de Deyn et al.
2008).
Among other structural traits, plant stature (herb, shrub,
tree), leaf area index (LAI) or crown depth, bark thickness,
rooting depth, tree/root architecture, tree lifespan, plant
architecture (DBH to height curve), maximum size/height
may be important for the drought tolerance capability in TDF
trees. Other stem and root traits such as nitrogen content
(Nmass), phosphorus content (Pmass), carbon content (Cmass),
sodium content (Namass), potassium content (Kmass) and
calcium content (Camass) are also associated with the
physiology of TDF tree species; however, the work on these
aspects of plant traits in TDF is scarce (tables 2 and 3).
Compared to other traits listed in tables 2 and 3, SSD is
highly variable among regions (0.37–0.73 g cm−3) and among
species (e.g. dry forest of Costa Rica, 0.19–1.20 g cm−3).
Borchert (1994) reported a greater mean value of SSD in
deciduous trees (0.73 g cm−3) compared to evergreen trees
(0.60 g cm−3). The limited data in table 2 indicate about
threefold difference in stem Nmass among TDF species. The
significance of these variations, however, remains to be
examined.
Regenerative traits especially resprouting capacity after
important trait in the TDF facing a high population load
(pers. observation).
3.3 Reproductive traits
A large number of reproductive traits are important for the

success of a tree species in dry tropical environment.
Some of these are fruit number, fruit mass, seed weight,
seed viability, time period for seed germination (table 4),
number of seeds, dispersal distance, specialized
pollination/dispersal, maturity age/size, seed production and
reproductive phenology. Dispersal ability is strongly
influenced by the seed size of a species (Khurana et al.
2006). Smaller seeds have greater dispersal ability as
compared to heavier and larger seeds but the seedlings
produced by heavier, larger seeds have greater competitive
ability, enabling them to establish and survive under various
stresses such as competition, moisture, shading,
disturbances, defoliation and herbivory (Khurana et al.
2006). The above advantages of the seed size cause the
structure of the TDF to be largely determined by the
medium- to large-seeded species (Khurana et al. 2006).
3.4 Functional traits syndrome for maintaining

growth in seasonally dry environments
The total amount of rainfall sets limits to distribution of

forests in the tropics (Holdridge 1967; Walter 1979; White
1983; Woodward 1987; Portillo-Quintero and Sánchez-
Azofeifa 2010). Research indicates that spatial and
temporal variation in soil water availability determines
intra- and inter-annual patterns of growth, productivity
and survival within seasonal forests (Baker et al. 2003a;
Baker et al. 2003b; Urbeita et al. 2008; Sánchez-
Coronado et al. 2007; Namirembe et al. 2008). The
annual girth increment of deciduous species correlates
positively with rainfall during the middle of the wet
season (Bullock 1997) and also with total rainfall during
the previous 2 years (Whigham et al. 1990). This
observation is also verified by tree ring studies in
seasonal forests of Panama (Devall et al. 1995).
It is evident that TDF species maintain a set of FTs
which leads to their survival in seasonally dry
environments by conserving water. They may achieve this
by reducing their LL and modulating leaf FTs in such a
way that a higher rate of photosynthesis is maintained
during the brief period of water availability favourable for
the physiological processes essential for the plant growth
during that period. However, there is incomplete
knowledge about many FTs involved and further research
efforts are needed to study these and to develop a database
of FTs of TDF species. Our review of FTs indicates that
TDF species generally have a higher SLA, LNC, Nmass, gc
and light saturated photosynthetic rate and a
Table 2. List of stem traits of tree species in tropical deciduous forests
Dry deciduous forest of Bolivia cm-3to

0.37 (n= 12) SSD (g0.19 ) 0.52 0.11 Markesteijn et al. 2011
Dry forest of Costa Rica 0.40 (n= 18) 0.16 to 0.78 0.04 Wiemann and Williamson 1989
Deciduous forest of Panama 0.51 (n= 16) 0.35 to 0.70 0.02 Santiago 2003
Deciduous forest of India 0.58 (n= 7) 0.37 to 0.75 0.04 Chaturvedi et al. 2010
Dry forest of Costa Rica 0.72 (n= 26) 0.19 to 1.20 0.05 Borchert 1994
Deciduous forest of Mexico 0.73 (n= 21) 0.27 to 1.39 0.09 Huante et al. 1995
Nmass (%)
Pmass (%)
Cmass (%)
Namass (%)
Deciduous forest of India 0.08 (n= 25) nk 0.03 Singh and Singh 1991
Kmass (%)
Camass (%)
Bark Cmass (%)
Bark Camass (%)
n=number of species, nk=not known. SSD (stem specific density); N mass (mass-based nitrogen concentration); Pmass (mass-based
phosphorus concentration); Cmass (mass-based carbon concentration); Na mass (mass-based sodium concentration); K mass (mass-based
potassium concentration); Camass (mass-based calcium concentration).
Table 3. List of root traits of tree species in tropical deciduous forests
Nmass (%)
Pmass (%)
Cmass (%)
Namass (%)
Kmass (%)
Camass (%)
n=number of species, nk= not known. N mass (mass-based nitrogen concentration); P mass (mass-based phosphorus concentration); C mass
(mass-based carbon concentration); Namass (mass-based sodium concentration); K mass (mass-based potassium concentration); Ca mass (mass-
based calcium concentration).
lower LMA, LL and LSCmax compared to the tree species of as high cavitation resistance, strong stomatal control or the
other biomes. SLA and LNC relates positively to LL and, in maintenance of tissue turgor pressure at low leaf water
combination, accurately predicts the maximum photosynthetic potentials. Other studies also support these observations. For
rate across the species (Reich et al. 1997). Therefore, a trait example, Li et al. (2009) studied adaptation responses to
set of high SLA, LNC and Nmass is expected to lead to high different water conditions and the drought tolerance of
light saturated photosynthetic rates. Observations in four Sophora davidii seedlings in a greenhouse experiment and
lowland Panamanian forests also indicate that nitrogen content found that water stress decreased leaf relative water content,
per unit mass and light- and CO2-saturated photosynthetic SLA, leaf area ratio and WUE, whereas it increased the
rate per unit mass of upper canopy leaves decreases with biomass allocation to roots, which resulted in a higher root:
annual precipitation, while leaf thickness increases and SLA stem mass ratio under drought.
decreases (Santiago et al. 2004). Similarly, relatively high gc
(205–680 mmol m−2 s−1), together with relatively short LL 4. Plant functional types
(6–8 mo) and LSCmax (19–54 mmol m−1 s−1MPa−1) are
expected to confer a selective advantage in seasonally dry It is being increasingly realized that, in order to understand the
environments. Because gc plays an important role in plant– interaction of plants and ecosystem processes and their
atmosphere water exchange by relating positively to the rate potential response to global environmental changes, groups of
of photosynthesis, high gc may be essential in the deciduous species with shared characteristics, known as plant functional
species with short LL to optimally utilize resources in a types (PFTs), need to be identified. Groupings of plant
limited duration of favourable soil moisture. Markesteijn et species on the basis of FTs can yield information on the
al. (2010) have also reviewed literature to show that tolerance relative contribution of each PFT to total ecosystem plant
to water stress by plants is codetermined by a suite of FTs biomass (Hoorens et al. 2010). Inter-specific variation in
such FTs can help in the
Table 4. List of reproductive traits of tree species in tropical deciduous forests
Fruit no. per tree

Dry forest of Costa Rica 271 (n= 7) 4 to 1182 219 Rockwood 1973
Fruit wt. (g)
Dry forest of Costa Rica 108 (n= 7) 1.3 to 385 88.2 Rockwood 1973
Seed wt. (mg)
Deciduous forest of Mexico 184 (n= 22) 0.66 to 1622 116 Huante et al. 1995
Deciduous forest of India 316 (n= 37) 0.10 to 2224 84.6 Khurana et al. 2006
Deciduous forest of India 1229 (n= 99) 1.0 to 20000 670 Murali 1997
Seed viability (days)
Deciduous forest of India 256 (n=99) 5 to 720 38.1 Murali 1997
Period for seed germination (days)
Deciduous forest of India 16.9 (n=98) 8 to 45 1.4 Murali 1997
n=number of species.
classification of plant species into PFTs (Von Willert et al. seasonal variation in their leaf traits. The seasonal pattern in
1990, 1992; Díaz and Cabido 1997; Lavorel et al. 1997; leaf traits, in general, was an early season peak in SLA, LNC
Westoby 1998; Gitay et al. 1999; Semenova and van der and LPC, and a midseason peak in stomatal conductance and
Maarel 2000; Powers and Tiffin 2010). These groupings of Amass, which was associated with increase in soil moisture.
plant species on the basis of common biological parameters
Annual forbs generally exhibited highest leaf trait values and
reduce a wide diversity of species to small number of
the perennial grasses the lowest.
functional groups, which enables the identification of general
Several PFTs, based on leaf phenology and wood
principles for the functioning of organisms which can be used
density, have been recognized in the dry forests of Costa
for making predictions (Duru et al. 2009). The identification Rica by Borchert (1994), ranging from deciduous hardwood
of tree PFTs through either deductive or inductive approaches and water-storing light wood trees in dry upland forest to
(Gitay and Noble 1997) is primarily limited by our restricted evergreen light soft-wood trees confined to moist lowland
knowledge of plant physiological attributes. This is particular- sites. Since plant growth rate integrates several traits
ly true for TDFs. Because the extent and intensity of seasonal underlying trade-offs among resource acquisition strategies,
drought in TDF may vary with geographical location, there defence against natural enemies and allocation to reproduc-
can be a mosaic of different PFTs showing varying tion, Baker et al. (2003a) classified plant species of the
adaptations to seasonal drought (Borchert 2000). With the semi-deciduous forest of Ghana into dry forest pioneers and
development of modern ecopysiological techniques, the wet forest pioneers on the basis of variations in their growth
definition of plant PFTs has shifted from primarily morpho- rates under different soil moisture conditions. Saldaña-
logical classifications (e.g. Raunkiaer 1907; Box 1981) to Acosta et al. (2008) classified 33 tree species of Mexican
function based groupings (e.g. Díaz and Cabido 1997; Lavorel cloud forest into two functional groups on the basis of SLA,
et al. 1997; Reich et al. 1998; Walker et al. 1999; Pausas and height at maturity, wood density and seed mass.
Lavorel 2003; Suding et al. 2008). Nevertheless, growth-form Sagar and Singh (2003) categorized trees of Indian TDF on
categories continue to attract attention. Dubey et al. (2011) the basis of leaf size, leaf texture, deciduousness and bark
grouped TDF herbs into annual grasses, perennial grasses, texture and found that both the percent of species and
annual forbs and perennial forbs, and studied the intra- importance values were larger for medium or low deciduous
categories than for highly deciduous trait, representing a trade-
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MS received 24 May 2010; accepted 26 September 2011
ePublication: 12 November 2011
Corresponding editor: R GEETA

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Plant functional traits with particular reference to tropical

*Corresponding author (Fax, 0542 2368174; Email, ravikantchaturvedi10@gmail.com)

1. Introduction Cabido 2001). In recent years, the possible effects of

http://www.ias.ac.in/jbiosci J. Biosci. 36(5), December 2011, 963–981, * Indian Academy of Sciences

J. Biosci. 36(5), December 2011

J. Biosci. 36(5), December 2011

J. Biosci. 36(5), December 2011

Species/Forest Mean Value Range ±1SE References

Chl (mg g-1)

LDMC (% saturated wt.)

Species/Forest Mean Value Range ±1SE References

Aarea (μmol m-2s-1)

Amass (nmol g-1s-1)

Rdarea (μmol m-2s-1)

WUEi (μmol mol-1)

LSCmax (mmol m-1s-1MPa-1)

Species/Forest Mean Value Range ±1SE References

For the maintenance of physiological activity of dry forest

3.3 Reproductive traits

A large number of reproductive traits are important for the

3.4 Functional traits syndrome for maintaining

The total amount of rainfall sets limits to distribution of

Species/Forest Mean Value Range ±1SE References

Dry deciduous forest of Bolivia cm-3to

Bark Cmass (%)

Bark Camass (%)

Species/Forest Mean Value Range ±1SE References

Species/Forest Mean Value Range ±1SE References

Fruit no. per tree

Fruit wt. (g)

Seed wt. (mg)

Seed viability (days)

Deciduous forest of India 256 (n=99) 5 to 720 38.1 Murali 1997

Period for seed germination (days)

Deciduous forest of India 16.9 (n=98) 8 to 45 1.4 Murali 1997

MS received 24 May 2010; accepted 26 September 2011

ePublication: 12 November 2011

Corresponding editor: R GEETA

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