growth of tree seedlings in a tropical dry forest in relation to soil moisture and leaf traits

13 Pages·2013·1.56 MB·English

Journal of growth of tree seedlings in a
Plant Ecology
VolumE 6, NumbEr 2, tropical dry forest in relation to soil
PagEs 158–170
aPril 2013
moisture and leaf traits
doi:10.1093/jpe/rts025
advance access publication
28 august 2012
R. K. Chaturvedi1,*, A. S. Raghubanshi1 and J. S. Singh2
available online at
www.jpe.oxfordjournals.org
1 Institute of Environment and Sustainable Development, Banaras Hindu University, Varanasi 221005, India
2 Ecosystems Analysis laboratory, Department of Botany, Banaras Hindu University, Varanasi 221005, India
*Correspondence address: Institute of Environment and Sustainable Development, Banaras Hindu D
University, Varanasi 221005, India. Tel: [phone]; Fax: [phone]; o
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E-mail: [email protected] n
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Abstract d
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Aims Important Findings ://a
The growth of plant species in tropical dry forest (TDF) is expected all the traits and physiological rates were interrelated and showed c
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to be largely governed by the availability of soil moisture. in this significant positive relationship with rgr except for the correlation e
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study we attempt to identify mechanisms by which seedlings of dry of lDmC with rgr which was not significant. Further, relationships ic
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tropical trees cope with water stress by adjusting their leaf charac- of smC with all leaf traits, physiological rates and rgr were sig- u
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teristics to water availability and micro environments, and address nificant, except for that between smC and sla for B. lanzan and D. .c
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following questions: How are leaf traits and relative growth rate melanoxylon. The slope of seedling trait:smC relationship, a meas- /jp
(rgr) of the dominant seedling species of TDF affected by seasonal ure of phenotypic plasticity in response to soil moisture gradient, e
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changes in soil moisture content (smC)? What is the relationship of varied among species. among the four species, T. tomentosa was rtic
functional traits with each other? Can leaf traits singly or in com- the most plastic and S. robusta the least. le
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bination predict the growth rate of seedling species of TDF? The in conclusion, leaf traits and physiological processes were bs
study was conducted in situ on four sites (viz., Hathinala, gaighat, strongly related to soil water availability on the one hand and seed- tra
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Harnakachar and ranitali, listed in order of decreasing smC) within ling growth on the other. gs is the most important variable which t/6
net /2
the tropical dry deciduous forest in northern india. accounted for the greatest amount of variability (62%) in rgr, /1
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emphasizing the role of stomatal conductance in shaping growth 8
Methods /9
patterns across spatial and temporal gradients of soil water avail- 20
Five leaf traits viz., specific leaf area (sla), leaf dry matter content 6
ability. gs and smC together explained 64% variability in rgr, 7
(lDmC), concentrations of leaf nitrogen (leaf N), phosphorus (leaf P) indicating ntehtat other traits/factors, not studied by us are also impor- 5 by
and chlorophyll (Chl) and two physiological processes, viz., stoma- g
tant in modulating the growth of tropical tree seedlings. u
tal conductance (gs ) and photosynthetic rate (A ), and rgr, of e
net net s
four dominant tree seedling species of a TDF (viz., Buchanania lan- t o
Keywords: dry deciduous forest • phenotypic plasticity n
zan, Diospyros melanoxylon, Shorea robusta and Terminalia tomen- 0
tosa) on four sites were analysed for species, site and season effects • photosynthetic rate • relative growth rate • stomatal 3 A
over a 2-year period. step-wise multiple regression was performed conductance • soil moisture content pril 2
to predict rgr from mean values of smC, leaf traits and physiologi- received: 1 october 2011 revised: 22 June 2012 accepted: 10 01
9
cal processes. Principal component analysis (PCa) was performed July 2012
to observe the extent of intra- vs. inter-specific variability in the leaf
traits and physiological rates.
et al. 2010). To cope with the seasonality of climatic factors
iNTroDuCTioN
plants adapt traits of ecological importance (Westoby et al.
Seasonality in the phenology of tropical deciduous tree spe- 2002) allowing them to better acclimate to the changing
cies is mainly determined by the duration and intensity of conditions. Species responses to environmental changes are
seasonal drought (Mooney et al. 1995; Reich 1995; Kushwaha supposed to be influenced and modulated by intra-specific
© The Author 2012. Published by Oxford University Press on behalf of the Institute of Botany, Chinese Academy of Sciences and the Botanical Society of China.
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Chaturvedi et al. | growth of tree seedlings in relation to soil moisture and leaf traits 159
variability in traits (Albert et al. 2010). Jung et al. (2010) pro- 2003). Photosynthetic capacity varies considerably with leaf
vided evidence for a strong role of intra-specific trait variability nitrogen content (Meir et al. 2002, 2007; Kattge et al. 2009).
in community assembly and suggested that intra-specific trait Leaf nitrogen and phosphorus contents scale positively with
variability promotes species coexistence, by enabling species to one another and show similar relationships with A (Wright
net
pass through both abiotic and biotic filters. The changes in trait et al. 2001). According to Schulze et al. (1994), Gs is linearly
net
values, in most cases, constitute the basis of homeostasis at the related to leaf N for broad categories of vegetation types with
individual level (Chambel et al. 2005), and can express pheno- variable leaf longevity. Species in dry habitats have lower net
typic plasticity which can be defined as ‘the capacity of a given photosynthetic capacity at a given leaf nitrogen or phosphorus,
genotype to render different phenotypic values for a given higher mass-based leaf respiration at a given SLA or mass-based
trait under different environmental conditions’ (Valladares photosynthetic rate and lower stomatal conductance at a given
et al. 2006). It is understood as a way of adapting to variable area-based photosynthetic rate (Reich et al. 2003).
environments (Callaway et al. 2003; Valladares et al. 2005). The growth of plant species in tropical dry forest (TDF)
Marked seasonal variation in photosynthetic rate per unit is expected to be largely governed by the availability of soil D
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leaf area could result in seasonal stem growth rates (Prior et al. moisture (Lugo et al. 1978; Ray and Brown 1995; Gerhardt w
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2004). Prior et al. (2004) correlated a variety of leaf traits with 1996a, 1996b; Khurana and Singh 2001; Chaturvedi et al. lo
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increments in diameter at breast height and cross-sectional 2011a). In tropical forests, soils are nearly saturated during de
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area and found that the relative growth rates (RGRs) of most the wet season, while, soil water potential decreases and con- fro
deciduous tree species of the Australian savannah were highly sequently drought stress increases in the dry season (Comita m
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seasonal in all habitats and confined predominantly to the wet and Engelbrecht 2009). Chaturvedi et al. (2011a) studied leaf ttp
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season. Plants often have some physiological or morphological traits and relative growth rate of the tree species in a TDF ://a
traits that prevent excessive water loss (e.g. smaller leaf size and inferred that the soil moisture content (SMC) determines c
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and increased trichome density) that allow them to survive the RGR of tropical trees, whereas the response of different e
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in arid environments (Nobel 1999). Plants may also respond tree species is modulated by alterations in key functional ic
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to water stress by altering characteristics of above-ground traits such as SLA, leaf N and Chl. According to Cao (2000), u
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(shoots and leaves) and/or below-ground (roots) organs the small, shallow root systems of seedlings cannot tap into .c
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throughout the growing season (plasticity; Picotte et al. 2009). deeper, moister soil layers and hence the seedling stage is /jp
In the water stress condition, plants have thick leaves with most vulnerable to water stress (Comita and Engelbrecht e
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thick cuticles and small, thick-walled cells (Cunningham et al. 2009). Khurana and Singh (2004) have studied the effect rtic
1999; Niinemets 2001; Maximov 1929) and lower specific leaf of water stress on seedling growth of certain tropical trees le
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area (SLA; Cunningham et al. 1999; Fonseca et al. 2000; Specht with the help of traits such as SLA, net assimilation rate and bs
and Specht 1989). Since modifications in morphological and root:shoot ratio in pot culture experiments and found that tra
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physiological characteristics help to acquire both resources SLA and RGR in all species declined with water-stress. Some t/6
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and energy in a better way (van Kleunen and Fischer 2005), studies have correlated growth rate of woody seedlings with /1
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it is important to understand the adaptive value of such trait selected leaf traits in controlled conditions (e.g. Cornelissen 8
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changes in response to variable water availability. et al. 1996; Wright and Westoby 1999), however, extensive 20
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Among the leaf traits, SLA represents the light-intercepting studies relating leaf traits to growth in tree seedlings under 7
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area of a leaf per unit dry mass and is related to net photosyn- natural conditions especially in TDFs are scarce. by
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thetic rate (Reich et al. 1992, 1997) and relative growth rate We examined the intra- and inter-specific variations in u
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(Reich et al. 1997; Poorter and Garnier 2007). Generally, low physiological rates (Gsnet, Anet) and leaf traits (SLA, LDMC, st o
SLA is the characteristic of species growing in dry habitats with leaf N, leaf P, Chl) across spatial and temporal gradients of n
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nutrient poor soil and is associated with an increased leaf life water availability to identify the mechanisms by which dry 3 A
sisp anno ta npods ssliobwle t(iCsshuaep itnu rent oavl.e r1 9in9 3h;a Gbirtiamtse w 1h9e7r7e; rGarpuidb bg r1o9w8t6h; ttrhoep ifcoalllo twreine gs eqeudelsintigosn sc:o (pi)e hwoiwth awrea tleera fs ttrreasists, aanndd RadGdRr eossf pril 2
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Reich et al. 1992, 1999; Turner 1994). Leaf dry matter content the dominant seedling species of TDF affected by seasonal 9
(LDMC) is considered an approximation of leaf tissue density changes in SMC? (ii) what is the relationship of functional
and is related to nutrient retention within the plant (Poorter traits with each other? (iii) can leaf traits singly or in combi-
and Garnier 2007; Ryser and Urbas 2000). It is considered to nation predict the growth rate of seedling species of TDF? The
be a robust leaf trait (Roche et al. 2004) and has been shown study was conducted in situ on four sites within the tropical
to correlate negatively with potential relative growth rate and dry deciduous forest in northern India.
positively with leaf life span (Cornelissen et al. 2003). Leaf
chlorophyll concentration (Chl) provides information on the
mETHoDs
physiological adaptation of plants (Lichtenthaler 1998). Leaf
Study sites
nitrogen and phosphorus concentrations (leaf N and leaf P)
affect photosynthetic rate (A ), stomatal conductance (Gs ), The study was conducted in a TDF of India. The climate is
net net
SLA and RGR (Jurik 1986; Reich et al. 1991; Cornelissen et al. monsoon tropical. About 85% of the annual rainfall occurs
160 Journal of Plant Ecology
during the monsoon season from the south-west monsoon, Hathinala was the most moist site having a mean annual
and the remaining in few showers in December and in May– SMC of 13.4% and Ranitali was the driest with annual SMC
June. The maximum monthly temperature varies from 20°C of 7.8% (Table 1). Seasonal variation in SMC was high and
in January to 46°C in June, and the mean minimum monthly ranged from 25.8% in monsoon season at Hathinala to 2.5%
temperature reaches 12°C in January and 31°C in May. For in the early post-monsoon season at Ranitali (Fig. 1). Across
the purpose of this study, the year is divided into four sea- the sites, SMC as estimated in October 2005 was positively
sons: monsoon/rainy (July–September), early post-monsoon correlated with clay content (R = 0.96, P < 0.05, n = 12). Clay,
with gradually decreasing temperature (October–December), pH, organic carbon, total nitrogen and total phosphorus were
late post-monsoon with gradually increasing temperature high at the moist site whereas sand content was more at the
(January–March), and hot pre-monsoon (April–June). While dry site (Table 1).
the late post-monsoon period is characterized by leaf fall in The forest is tropical dry deciduous and the natural veg-
most deciduous species, the hot pre-monsoon season repre- etation comprises species such as Acacia catechu (L.f.) Willd.,
sents the leaf-flushing period for all species. Anogeissus latifolia (Roxb. ex DC.) Wallich ex Beddome, D
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Four sites, Hathinala, Gaighat, Harnakachar and Ranitali, Boswellia serrata Triana & Planch., Buchanania lanzan Spreng., w
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selected for the study are located in the Vindhyan highlands Diospyros melanoxylon Bakh., Hardwickia binata Roxb., lo
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(24°18′07″–24°24′13″ N, 83°04′22″–83°23′05″ E) of Lagerstroemia parviflora Roxb., Lannea coromandelica (Houtt.) de
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Sonebhadra district in Uttar Pradesh. The sites were selected Merrill, Shorea robusta Roth., and Terminalia tomentosa Roxb. In fro
to represent a range in soil water availability. The details of the four study sites total number of stems ≥30 cm girth were m
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four sites, including location, physico-chemical properties 467 (±54) ha-1 at Hathinala, 334 (±13) ha-1 at Gaighat, 339 ttp
of soil, and major tree species are integrated in Table 1. The (±14) ha-1 at Harnakachar and 202 (±20) ha-1 at Ranitali. s://a
elevation above mean sea level ranges between 315 and 485 c
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Species characteristics d
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Renukoot meteorological stations. Ranitali site is nearest to Seedlings of four dominant tree species, which were present on ic
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Obra and the Hathinala site nearest to Renukoot. According all the four sites, were selected. These are B. lanzan, D. melan- u
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to the data collected from the meteorological stations of oxylon, S. robusta and T. tomentosa belonging to Anacardiaceae, .c
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the state forest department during 1980–2010, the mean Ebenaceae, Dipterocarpaceae and Combretaceae, respectively. /jp
annual rainfall ranges from 1196 mm (Renukoot) to 952 mm The species differed in the degree of deciduousness, drought e
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(Obra). All the four sites have experienced disturbance in the tolerance, seedling growth and soil preference (Table 2). rtic
form of grazing and illegal felling. The disturbance intensity le
recorded at Ranitali was greatest and at Hathinala, the lowest monitoring seedling growth and soil moisture -abs
(Chaturvedi et al. 2011b). Three 50 × 20 m plots were demarcated randomly at each site. tra
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Soils are residual, ultisols, sandy-loam in texture. The Initially six seedlings of each species, uniform in size within- t/6
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most important rock of the area is red-coloured, fine-tex- species, at each plot were marked by permanent marker and /1
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tured sandstone generally underlain by shale and limestone. their initial height and stem circumference 10 cm above the 8
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table 1: location, physico-chemical properties of soil, and major tree species of the four study sites 5 b
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Parameter Hathinala Gaighat Harnakachar Ranitali gu
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Location 24° 18′ 07″ N & 24° 24′ 13″ N & 24° 18′ 33″ N & 24° 18′ 11″ N & t o
83° 05′ 57″ E 83° 12′ 01″ E 83° 23′ 05″ E 83° 04′ 22″ E n 0
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Altitude (m.a.s.l.) 291 245 323 287 A
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SBouillk m doeinstsuitrye ( cgo cnmte−n3)t (SMC, %) 11.33.04 ((±±01..0857)) 11.13.21 ((±±01..0964)) 11.02.72 ((±±01..0067)) 17..2768 ((±±01..0750)) ril 20
1
Clay (%) 10.6 (±1.85) 7.08 (±1.37) 4.83 (±0.69) 3.00 (±0.84) 9
Silt (%) 31.9 (±2.10) 32.1 (±2.22) 26.2 (±0.97) 26.8 (±1.90)
Sand (%) 57.5 (±0.90) 60.8 (±1.54) 69.0 (±0.97) 70.2 (±1.33)
Soil pH 6.93 (±0.16) 6.45 (±0.11) 6.52 (±0.20) 6.40 (±0.14)
Organic carbon (%) 1.61 (±0.15) 1.56 (±0.25) 1.20 (±0.27) 1.39 (±0.50)
Total nitrogen (%) 0.13 (±0.03) 0.13 (±0.01) 0.12 (±0.01) 0.12 (±0.02)
Total phosphorus (%) 0.04 (±0.02) 0.02 (±0.00) 0.03 (±0.01) 0.02 (±0.01)
Major tree species Shro, Teto, Lapa & Bula Shro, Bula, Teto & Dime Shro, Sofe, Teto & Bula Acca, Lapa, Anla & Teto
Values in parentheses show the standard error.
Abbreviations: Acca = Acacia catechu, Anla = Anogeissus latifolia, Bula = Buchanania lanzan, Dime = Diospyros melanoxylon, Lapa = Lagerstroemia
parviflora, Shro = Shorea robusta, Sofe = Soymida febrifuga, Teto = Terminalia tomentosa.
Chaturvedi et al. | growth of tree seedlings in relation to soil moisture and leaf traits 161
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Figure 1: monthly SMC at the four experimental sites from July 2005 to June 2007. ://a
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table 2: characteristics of the selected species based on Troup (1921) and Verma et al. (1993) .o
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Parameter Buchanania lanzan Diospyros melanoxylon Shorea robusta Terminalia tomentosa .co
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Height Moderate Small Large Large /jp
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Leaf phenology Short-deciduous Short-deciduous Semi-evergreen Highly deciduous /a
Drought tolerance Low High Very low High rticle
Seedling growth Slow Slow Medium Medium -a
b
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Soil Clayey Loam Porous loam Stiff-clayey tra
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Habitat preference Dry deciduous forest Dry deciduous forest Moist deciduous forest Dry and moist deciduous t/6
forest /2
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ground, were measured in July 2005. However, during the height ± SD of seedlings was: 93 ± 19.9 cm for S. robusta, 20
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experimental period some individuals were damaged and the 66.2 ± 17.3 cm for B. lanzan, 85 ± 15.1 cm for T. tomentosa and 7
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number of seedlings of each species was reduced to three per 58.0 ± 21.1 cm for D. melanoxylon. Ten seedlings of each spe- by
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plot at the end of 2-year period, i.e. nine per site. All individual cies at each site were harvested for obtaining allometric equa- u
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seedlings occurred in the understory; care was taken to select tions relating height with shoot biomass (Table 3). Increments st o
seedlings which were exposed to similar light conditions as in height of the marked seedlings were recorded at 3-month n
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determined by a digital Lux meter (Model LX-101), Taiwan. As intervals for 2 years (i.e. July 2005 to June 2007) and the 3 A
mENe1as1u OreDdB b,y A tDheC LBCio Psrcoie Cnotinfisco Llet dP.h Eontogslaynndth);e osins m15e tJeurl y(M 20o0d5e,l a(sveearsaogne) bnioomn-adses sitnrucrcetimveelnyt sw witehr eth cea lhcuellpat eodf rfoegr reeascsiho nin eteqruvaa-l pril 2
0
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the light intensity averaged 1205 μmol m−2 s−1. Initial mean tions relating seedling biomass with height (Table 3). Biomass 9
table 3: allometric relationships between shoot biomass (Y, kg) and height (X, cm) for the four tree seedling species at four sites in the
tropical dry forest
a B R2 P
Buchanania lanzan 0.885 0.774 0.988 0.000
Diospyros melanoxylon −1.334 1.814 0.996 0.000
Shorea robusta −2.791 2.294 0.990 0.000
Terminalia tomentosa 1.118 0.757 0.958 0.004
All equations are of the form log Y = a + b log X; n = 40 per species.
10 10
162 Journal of Plant Ecology
increments of the three individuals of a species in a plot were Leaf N and leaf P are the total amounts of nitrogen and
averaged to obtain one biomass increment for a species per phosphorus, respectively, per unit of dry leaf mass, expressed
plot, i.e. three per site. RGR was calculated as: RGR = (lnW − as percentage dry weight. Chl concentration was estimated
2
lnW )/(t − t ), where, W and W are initial and final biomass according to Arnon (1949) by crushing 0.1 g of fresh leaf in
1 2 1 1 2
and t and t are initial and final time period, respectively. SMC 10 ml of 80% acetone, the absorbance (D) of the extract was
1 2
at a depth of 10 cm was measured as per cent by volume, every then measured at 645 and 663 nm wavelengths using 80%
month in triplicate at a distance of 25 cm from each marked acetone as blank.
seedling on their three sides at each plot for 2 years (i.e. July
Data analysis
2005 to June 2007) by theta probe instrument (Type ML 1,
Delta-T devices, Cambridge, England) and averaged for each Gsarea and Aarea were converted to Gsnet (=Gsmass, mass-based
species at each plot, giving three values per species per site stomatal conductance) and Anet (=Amass, mass-based photo-
per month. synthetic rate) with the help of SLA. The average seasonal
leaf trait values of each species in three plots were considered
trait measurements as replicates for a site. Finally, at the end of 2 years the total Do
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Area-based stomatal conductance (Gsarea) and photosynthetic number of data points for each leaf trait, physiological rates nlo
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rate (A ) were measured on a fully expanded leaf of each and RGR was 384 (n = 3 replicates × 4 species × 4 sites × 4 d
area e
obyf thLeC mParork eCdo nsesoedlel inPghso (ttohsryenet hreepsilsic amteest epre re qspueipcpieesd p ewri tshit ea) seaDsoatnas o×n 2 l eyaefa rtsr)a.its, physiological rates and RGR were ana- d from
standard 2.5 × 2.5 cm broadleaf cuvette. The measurements lysed by Repeated Measures analysis of covariance with h
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were made between 09:30 and 11:30 hours under ambient SMC as covariate. Differences between the mean values of s
conditions. Photosynthesis measurements were made on leaf traits were tested by Tukey’s post-hoc test. Two-tailed ://ac
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clear days. Light intensity, as measured by the LC Pro Console Pearson’s correlation coefficients among leaf traits, physiolog- d
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Photosynthesis meter, varied between 905 and 1210 μmol m−2 ical rates and RGR were calculated to observe the relation- mic
s−1 during Jan–Mar, 1248–1486 μmol m−2 s−1 during Apr–Jun, ships among these variables. A step-wise multiple regression .o
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1153–1321 μmol m−2 s−1 during Jul–Sep and 753–1062 μmol was performed to identify the best predictor of seedling RGR. .c
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m−2 s−1 during Oct–Dec. There were no significant differences All the statistical analyses were performed using SPSS soft- m
in light intensity between sites. For the analysis of other leaf ware (ver. 16; SPSS Inc, Chicago, Illinois). Effects of SMC on /jpe
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traits, 10 healthy and fully expanded leaves were collected the leaf traits, physiological rates and RGR of the four spe- rtic
each month from as many seedlings visually comparable in cies were studied with the help of regression graphs by using le
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size with the marked ones, from each plot and composited SigmaPlot (ver. 11; SigmaPlot, San Jose, CA). b
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to obtain one sample per plot or three samples per site. Principal component analysis (PCA) was performed by tra
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Measurements of selected leaf traits were done at 1-month using the PC-ORD 5 program (McCune and Mefford, 2005) to t/6
interval for the 2-year period starting in July 2005. Leaves observe the extent of intra- vs. inter-specific variability in the /2/1
of S. robusta were available throughout the year whereas B. leaf traits and physiological rates. Annual mean values of all 58
/9
lanzan and D. melanoxylon were leafless for 1 month (March) leaf traits and physiological rates were used for the PCA. 2
0
and T. tomentosa was leafless for 2 months (March and April) 67
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each year. Thus, for S. robusta, there were 12 samples, for rEsulTs by
B. lanzan and D. melanoxylon, 11 samples each and for T. g
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Differences in leaf traits among species, sites e
tomentosa, 10 samples for each year. From the monthly data, s
seasonal mean values were calculated as the average for three and seasons t on
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months in a season. The results indicate the response of species to temporal and 3
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The collected leaf samples were quickly wrapped in moist spatial variations in water availability. Repeated measures p
paper for rehydration. The rehydrated leaves were weighed analysis of covariance with SMC as covariate indicated sig- ril 2
0
immediately to determine their saturated fresh mass. Leaf nificant effects of year on LDMC, season on LDMC, Chl, Gs 1
net 9
area was recorded by leaf area meter (SYSTRONICS, Leaf and A , site on LDMC, leaf P, Chl, Gs and A , and species
net net net
Area Meter-211, New Delhi, India). Fresh leaves were oven on all leaf traits and RGR (Table 4).The relative growth rates
dried at 60°C for 72 h to estimate dry mass. Using the area were significantly lower during the dry seasons than rainy
and dry mass, SLA was determined. LDMC was calculated season with a significant season × species interaction. Season
by using water-saturated fresh mass of leaf and its dry mass × species interaction was also significant for all leaf traits, and
following the protocol of Cornelissen et al. (2003). Dried leaf physiological rates. Interestingly with controlled SMC, RGR
samples were weighed and ground separately in an electronic was not affected either by site, season or year.
grinder for the analysis of nitrogen and phosphorus contents. Highest mean values across years, sites and species for leaf
Nitrogen was estimated through Kjeldahl technique N, leaf P, Chl, Gs , A and RGR were recorded in the mon-
net net
(Bradstreet 1965)  and phosphorus by phosphomolybdic soon season and maximum values for SLA and LDMC were
blue colorimetric method (Anderson and Ingram 1993). observed in the pre-monsoon and early post-monsoon season,
Chaturvedi et al. | growth of tree seedlings in relation to soil moisture and leaf traits 163
table 4: summary of repeated measures analysis of covariance with SMC as covariate on leaf traits and RGR of four tree seedling species
(only main effects and two-way interactions are shown)
df SLA LDMC Leaf N Leaf P Chl Gs A RGR
net net
YR 1 0.03ns 7.02* 0.13ns 0.05ns 0.14ns 0.12ns 0.00ns 3.63ns
SS 1 0.74ns 7.92** 2.37ns 0.41ns 38.9*** 38.7*** 15.8*** 0.96ns
ST 3 2.69ns 75.6*** 1.37ns 4.39* 104*** 14.3*** 6.62** 2.02ns
SP 3 267*** 3540*** 473*** 18.5*** 332*** 205*** 113*** 17.5***
YR × ST 3 0.10ns 2.58ns 1.20ns 0.27ns 0.65ns 11.25*** 0.16ns 1.83ns
YR × SP 3 2.29ns 3.60* 3.77* 0.75ns 0.35ns 3.43* 4.62** 0.88ns
SS × ST 3 1.12ns 44.7*** 8.31*** 5.85** 23.3*** 24.4*** 12.8*** 2.01ns
SS × SP 3 304*** 999*** 108*** 75.7*** 846*** 529*** 361*** 20.1***
YR × SS 3 0.00ns 1.82ns 0.16ns 3.12ns 0.73ns 0.06ns 2.11ns 0.84ns D
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ST × SP 9 1.33ns 84.2*** 9.43*** 5.89*** 54.0*** 2.85* 1.12ns 2.82* w
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The residual df is 31. de
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AnsPb b>r e0v·0ia5t,i*oPn s<:  S0P·0 =5,  s*p*ePc i<e s0, ·S0S1 ,= * *s*ePa s<o n0,· 0S0T1 =. site, YR = year. from
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LDMC which was lowest in the pre-monsoon season. greatest RGR in monsoon season at all the four sites (Fig. 3). de
m
Among the four species, SLA varied 1.8-fold, LDMC Average RGR for all the four species showed highest value ic
1.4-fold, leaf N 1.6-fold, leaf P 1.4-fold, Chl 1.3-fold, Gsnet at Hathinala and least at the Ranitali site. RGR of B. lanzan, .oup
1.9-fold and A 1.9-fold. SLA, LDMC, leaf N and leaf P were S. robusta and T. tomentosa was greatest at the Hathinala site .c
net o
greatest in S. robusta, whereas, Chl, Gs and A were great- whereas that of D. melanoxylon was highest at the Harnakachar m
net net /jp
est in T. tomentosa. Lowest SLA, leaf N, leaf P, Gs and A site (Fig. 3). e
net net /a
were observed in B. lanzan. T. tomentosa exhibited the low- Results of the PCA using all data on traits and physiological rtic
est value for LDMC and D. melanoxylon for Chl at all the sites rates showed a high extent of inter-specific variation in the le
-a
and in all seasons (Fig. 2). SLA, leaf N, leaf P, Chl, Gs and leaf traits and physiological rates (Fig. 4). The distribution of b
net s
A were highest at the Hathinala site for all species (Fig. 2). species jointly with sites in the ordination space also indicated tra
net c
Among the four sites, LDMC varied 1.1-fold, leaf P 1.2-fold, a marked level of intra-specific variation. The percentage of t/6
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Chl 1.2-fold, Gsnet 1.2-fold and Anet 1.1-fold. S. robusta exhib- variance accounted for by the axes 1, 2 and 3 were 60%, /1
5
ited the greatest Leaf N and B. lanzan the lowest at all the sites 22% and 8%, respectively. The Eigenvalues were 4.2, 1.6 8
/9
except for the Harnakachar where B. lanzan had 1.3% leaf and 0.6 for the axes 1, 2 and 3, respectively. SMC showed a 2
0
6
N and T. tomentosa 1.2% (Fig. 2). Leaf P generally followed significant correlation with PCA axis 1 (R = −0.48, P < 0.05, 7
5
the pattern of leaf N. Chl was greatest at Hathinala for all the n = 16). b
y
species (Fig. 2) except for D. melanoxylon which exhibited the gu
greatest Chl at Harnakachar among the species on that site. relationships among traits and physiological rates es
t o
Among the four seasons, SLA varied 2-fold, LDMC 1.5-fold, Pearson’s correlation between traits across species, seasons n
0
leaf N 2.6-fold, leaf P 2.8-fold, Chl 6-fold, Gs 4-fold and A and sites showed significant relationships for all traits except 3
net net A
8.6-fold. T. tomentosa was richest in Chl and also showed great- for the relationship of LDMC with SLA and RGR which p
est seasonal variation, with the highest value in the monsoon was statistically not significant (Table  5). However, the ril 2
0
and the lowest in the late post-monsoon season. Similar to correlations of LDMC with RGR, across species and sites in 19
other traits, T. tomentosa exhibited maximum variation in Gs different seasons showed a significant negative relationship
net
(5.37 mmol g−1 s−1 in monsoon season and 0.07 mmol g−1 s−1 in monsoon season (R = −0.48, P < 0.01) and a significant
in late post-monsoon season) and A (225 nmol g−1 s−1 in positive relationship (R = 0.23, P < 0.05) in late post-monsoon
net
monsoon season and 2.87 nmol g−1 s−1 in late post-monsoon season.
season; Fig. 2). B. lanzan and D. melanoxylon showed greatest
A at Harnakachar (i.e., 57.2 nmol g−1 s−1 and 73.1 nmol g−1 relationships of leaf traits and physiological rates
net
s−1, respectively) whereas A of S. robusta and T. tomentosa with SmC
net
was greatest at the Hathinala site (i.e., 81.0 nmol g−1 s−1 and Relationships of SMC with all trait variables were significant,
94.9 nmol g−1 s−1, respectively). except for that between SMC and SLA for B. lanzan and D.
The variation in RGR was 2.5-fold in the studied species. melanoxylon, and between SMC and LDMC for B. lanzan and
The seasonal variation in RGR was 9.8-fold, which shows a T. tomentosa; although in these species also SLA tended to
164 Journal of Plant Ecology
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Figure 2: mean values of leaf traits across site, season and species. Bula, Buchanania lanzan; Dime, Diospyros melanoxylon; EPM, early post-monsoon;
GG, Gaighat; HK, Harnakachar; HN, Hathinala; LPM, late post-monsoon; M, monsoon; PM, pre-monsoon; RT, Ranitali; Shro, Shorea robusta; Teto,
Terminalia tomentosa. Narrow bars represent 1 SE. Different letters above bars indicate significant differences after Tukey’s post-hoc test (α = 0.05).
Chaturvedi et al. | growth of tree seedlings in relation to soil moisture and leaf traits 165
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Figure 3: seasonal variation in relative growth rates (RGR) in four seedling species across four sites. M, monsoon; EPM, early post-monsoon;
LPM, late post-monsoon; PM, pre-monsoon.
increase with SMC (Table 6). Further, all the traits showed other three species (Table 6). The variability in SMC explained
positive relationships with SMC, except for the relationship of the greatest amount of variability in leaf N (45%), leaf P
SMC with LDMC of all the four species which were negative (61%), RGR (74%), A (65%) and Gs (72%) in T. tomen-
net net
(Table 6). Among species, the variability in SMC explained tosa, and in Chl (67%) in B. lanzan.
10% (B. lanzan) to 39% (T. tomentosa) of the variability in The slope of SMC:trait relationships varied remarkably
SLA (Table 6). Greatest amount of variability in LDMC was among species (Table 6). T. tomentosa registered highest values
explained by SMC in S. robusta (48%) as compared with the for the slope for all traits except for LDMC where the slope
166 Journal of Plant Ecology
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Figure 4: ordination of the four seedling species at four sites on the basis of average leaf characteristics in the forests of Vindhyan highlands by ://a
principal component analysis. c
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of S. robusta was greatest among the four species. Minimum condition of TDF has pronounced effect on ecosystem struc- u
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values of slopes for leaf N, leaf P and Chl were exhibited by S. ture and function (Murphy and Lugo 1986). Seedling traits .c
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robusta. B. lanzan showed minimum slope values for LDMC, vary strongly across the tropical forest biome to cope with
/jp
Gs , A and RGR and D. melanoxylon showed minimum the variation in the distribution and amount of rainfall e
net net /a
slope for SLA. (Khurana and Singh 2001). The leaf traits examined by us rtic
The step-wise multiple regression revealed that among were affected strongly by season, site and species, and their le
-a
the traits and physiological rates, Gs , and among the envi- interaction. However, the effect of season was substantially b
net s
ronmental factors, SMC had the largest influence on RGR more obvious than the other two factors indicating the impor- tra
c
of tree seedlings. It was observed that the variation in Gs tance of the availability of soil water. Tropical tree species are t/6
net /2
alone accounted for 62% variation in RGR and Gsnet and known to reduce physiological function between the wet and /15
SMC together explained 64% variation in RGR. The final dry seasons, and species differ in their adaptive capacity to 8
/9
model was RGR = −0.01 + 0.59 Gsnet + 0.25 SMC (R2 = 0.64, down-regulate leaf photosynthesis between seasons (Craven 20
6
P < 0.001). et al. 2011). 7
5
Reich et al. (1999) and Prior et al. (2003) for SLA and A b
net y
DisCussioN and Reich et al. (1999) for Leaf N and Gsnet reported greater gue
inter-specific variations than the present study, probably st o
The study area experiences relatively low annual rainfall because of fewer number of species studied by us. LDMC n
0
and a high seasonality in rainfall distribution. This climatic values reported in this study are in the range examined by 3
A
Markesteijn et al. (2011) for a TDF in the eastern lowlands of p
Bolivia, near Concepciόn, Santa Cruz. ril 2
table 5: pearson’s correlation coefficients between functional 0
1
traits across species, seasons and sites (n = 384) In our study, seedlings of the four species differed 9
significantly in terms of RGR. Seasonal variation in RGR
SLA LDMC Leaf N Leaf P Chl Gs A
net net was 9.8-fold with the maximum value measured during
LDMC 0.08ns the monsoon season. Comita and Engelbrecht (2009)
Leaf N 0.80** 0.28** found that for 26 out of 33 tropical seedling species, RGR
Leaf P 0.65** 0.13* 0.76** was significantly lower in the dry season than in the wet
Chl 0.55** 0.26** 0.73** 0.69** season. Gerhardt (1993) also reported low growth rates in
Gs 0.57** 0.11* 0.67** 0.66** 0.88** the seedlings of four canopy tree species in a secondary dry
net
A 0.60** 0.24** 0.72** 0.67** 0.88** 0.97** forest in a long-time experiment in Guanacaste National
net
RGR 0.44** 0.05ns 0.52** 0.53** 0.72** 0.79** 0.76** Park, Costa Rica in the part of the study period when there
was low precipitation due to effects of the El Niño Southern
**P < 0.01, *P < 0.05, nsP > 0.05. Oscillation.
Chaturvedi et al. | growth of tree seedlings in relation to soil moisture and leaf traits 167
table 6: parameters of regression equations (in the form: y = a + bx) relating functional attributes (y) of the four tree seedling species
with SMC (x)
a b R2 a b R2 a b R2
SLA LDMC Leaf N
B. lanzan 59.5 1.7 0.10ns 37.5 −0.22 0.02ns 0.68 0.04 0.25**
D. melanoxylon 67.9 1.8 0.12ns 41.7 −0.24 0.16* 0.75 0.04 0.39***
S. robusta 115 2.1 0.36*** 46.0 −0.43 0.48*** 1.48 0.03 0.40***
T. tomentosa 65.8 5.2 0.39*** 33.7 −0.30 0.02ns 0.55 0.06 0.45***
Leaf P Chl Gs
net
B. lanzan 0.03 6.18 0.45*** 0.03 0.07 0.67*** –0.02 0.10 0.59***
D. melanoxylon 0.09 2.98 0.16* 0.06 0.06 0.60*** 0.13 0.12 0.57***
S. robusta 0.10 2.60 0.23** 0.42 0.04 0.60*** 0.11 0.16 0.62*** D
o
T. tomentosa 0.02 9.02 0.61*** –0.07 0.08 0.57*** –1.17 0.29 0.72*** w
n
Anet RGR loa
d
B. lanzan 3.80 4.00 0.53*** −0.01 2.21 0.39*** e
d
D. melanoxylon 10.70 5.30 0.53*** −0.02 4.20 0.67*** fro
m
S. robusta 30.00 5.60 0.60*** −5.66 3.32 0.58*** h
T. tomentosa –59.0 12.4 0.65*** −0.03 6.11 0.74*** ttp
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***P < 0.001, **P < 0.01, *P < 0.05, nsP > 0.05. ca
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Leaf traits appear to be good proxies for physiological rates area is associated with low A , Gs , leaf N, leaf P and RGR. .c
net net o
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as we found significant positive correlations, irrespective of Photosynthetic capacity is influenced both by Gsnet and by the /jp
species, sites and seasons between physiological rates and drawdown of CO concentration inside the leaf, i.e. carboxy- e
2 /a
RGR, except that of LDMC with SLA and RGR, which were lation capacity, a process affected by leaf structure (Wright rtic
statistically not significant. However, the LDMC relationships et al. 2004). In this study, Gs and A were strongly related le
net net -a
with SLA and RGR were significantly negative in the mon- to RGR, and leaf Chl and leaf N were strongly related to Gsnet bs
soon season when SMC was at optimal level conforming to and A . Therefore, leaf N, Chl, Gs or A can be used to tra
net net net c
the reports that increased SLA is associated with decreased study the growth of seedlings of the dry tropical forest trees. t/6
/2
LDMC (Wilson et al. 1999; Garnier et al. 2001; Shipley and An important component of the drought-tolerant strategy /1
5
Vu 2002). On the other hand, in seasons when SMC was low of plant species in TDF is their deciduousness. Among the four 8
/9
the relationship was inconsistent as also reported by Li et al. species, T. tomentosa is most deciduous and S. robusta is the 20
6
(2005) who observed non-significant relationship of LDMC least. Poorter and Markesteijn (2008) studied functional traits 7
5
with SLA in the plants growing in water stress condition at in tropical deciduous forest of Bolivia and reported that decid- by
the Naiman Desertification Research Station in eastern Inner uousness was positively associated with SLA and negatively gu
e
Mongolia, China. Seasonal dynamics in LDMC are governed with LDMC. During the monsoon season, when the SMC is st o
by the fundamental trade-offs between a rapid assimilation at optimum level, it was observed that the SLA, leaf N, leaf P, n
0
and growth at one extreme, and efficient conservation of Chl, Gsnet, Anet and RGR were greatest and LDMC lowest in T. 3 A
r2e0s0o4u;r Rceesa wd iatnhdin S wtoeklle ps r2o0te0c6t;e Kd atizsaskuoeus aett  tahl.e 2 o0t0h6e)r. (IDní asezv eet raal.l toobmseenrvtoesda tahs acto imn ptharee ddr wieistth s ethaseo ont h(ie.re .t hproeset- smpeocniseos.o Int wseaass oanls)o, pril 2
0
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earlier studies also a negative relationship between LDMC and LDMC (48%) was greatest in T. tomentosa as compared with 9
RGR has been reported (Garnier 1992; Poorter and Bergkotte the other three species.
1992; Ryser and Aeschlimann 1999). Thus, when RGR of the Tropical species do show plasticity and ability to acclimatize
present seedlings was maximum during the monsoon season, to variable moisture conditions (Khurana and Singh 2001).
the LDMC was minimum. Seedlings growing in moist condi- Phenotypic plasticity is also argued to help the species to
tions tend to have greater leaf area per unit biomass invested adjust to the composition of their communities, promoting
(higher SLA) for maximum light absorption, and greater leaf coexistence and community diversity (Callaway et  al.
N and A , whereas seedlings growing in water stress condi- 2003). The slope of the relationship between a trait and an
net
tions increase the proportion of leaf tissues for mechanical environmental variable is traditionally taken as a measure of
support and defence resulting in greater biomass investment plasticity, i.e. the steeper the slope, the greater the plasticity
per unit leaf area (lower SLA), and lower leaf N and A . (Valladares et al. 2006). Our study indicated that the degree of
net
According to Wright et al. (2004), high leaf mass per unit phenotypic plasticity across the SMC gradient differed among