Changes in plant functional traits and
water use in Atlantic rainforest: evidence of
conservative water use in spatio-temporal
scales
Bruno H. P. Rosado, Carlos A. Joly,
Stephen S. O. Burgess, Rafael S. Oliveira
& Marcos P. M. Aidar
Trees
Structure and Function
ISSN 0931-1890
Trees
DOI 10.1007/s00468-015-1165-8
1 23
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DOI 10.1007/s00468-015-1165-8
ORIGINAL PAPER
Changes in plant functional traits and water use in Atlantic
rainforest: evidence of conservative water use in spatio-temporal
scales
Bruno H. P. Rosado • Carlos A. Joly •
Stephen S. O. Burgess • Rafael S. Oliveira
Marcos P. M. Aidar
•
Received: 30 January 2014 / Revised: 13 December 2014 / Accepted: 26 January 2015
Ó Springer-Verlag Berlin Heidelberg 2015
Abstract
Key message Relationship between sap flow and
functional traits changes with altitude and changes in
water availability can impose a conservative water use
in woody species of tropical rainforest.
Abstract Using a trait-based approach, we have identified
that tropical trees are vulnerable to decreases in water
availability, especially in montane areas, where higher radiation and vapor pressure deficits lead to higher water loss
from trees. Changes to functional traits are useful descriptors of the response of species to variation in resource
availability and environmental conditions. However, how
these trait-environment relationships change with altitude
remains unclear. We investigated changes in xylem sap
flow along an altitudinal variation and evaluated the contribution of morphological traits to total plant water use.
We hypothesize that (1) at the Montane forest, plant species will show a more conservative water use and (2)
seasonally, there will be a much greater increase in conservative water use during the dry season at the Lowland
site, since the climate conditions in the Montane site impose constraints to water use throughout the year. Remarkably, although water is assumed to be a non-limiting
resource for Atlantic rainforest in general, we observed
ecophysiological adjustments for more conservative water
use in Montane forest. Our findings demonstrate that
changes to water supply and demand as determined by
rainfall, VPD and soil water storage can impose restrictions
to water loss which differ across spatio-temporal scales.
We suggest that the next steps for research in Montane
forest should focus on traits related to hydraulic failure and
carbon starvation to address the question whether the
higher conservative water use observed at the Montane
Forest translates into a higher or lower susceptibility to
intensification of drought which might arise due to climate
change.
Communicated by A. Braeuning.
Keywords Functional ecology Drought Wood
density Specific leaf area Sap flow Altitudinal variation
B. H. P. Rosado (&)
Departamento de Ecologia, IBRAG, Universidade do Estado
do Rio de Janeiro (UERJ), Rio de Janeiro, RJ, Brazil
e-mail: [email protected]
C. A. Joly R. S. Oliveira
Departamento de Biologia Vegetal, IB, Universidade Estadual
de Campinas, Campinas, SP, Brazil
S. S. O. Burgess
School of Plant Biology, University of Western Australia, Perth,
WA, Australia
M. P. M. Aidar
Centro de Pesquisa em Ecologia e Fisiologia, Núcleo de
Pesquisa em Fisiologia e Bioquı́mica, Instituto de Botânica
de São Paulo, São Paulo, SP, Brazil
Introduction
One of the most concerning possibilities for climate change
scenarios is the intensification of drought which may result
in tree mortality due to hydraulic failure, carbon starvation
and biotic agents (McDowell et al. 2008, 2011). In this
context, trait-based approaches have identified changes in
tropical rainforests due to different susceptibilities of species to decreases in water availability (Fauset et al. 2012;
Phillips et al. 2010; Tobin et al. 1999). Thus, the search for
functional traits as proxies of community responses to
environmental changes has been considered one of the
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most fundamental topics in ecology (Sutherland et al.
2013).
The search for traits to predict the responses of species
and communities to drought is urgent, but only a few traitbased approaches and precipitation manipulation experiments have been performed in tropical environments;
only 4 % performed at sites where mean annual temperature is [20 °C, and 6 % of studies where rainfall exceeds 1,500 mm year-1 (Beier et al. 2012). In this context,
many studies conducted along altitudinal variations have
been considered as natural experiments able to describe the
functional responses of species and communities to climate
changes (Bruijnzeel and Veneklaas 1998; Korner 2007;
Leuschner 2000; Rosado et al. 2012; Woodward 1993).
Along altitudinal variations in tropical forests, it has been
observed that at high altitudes, factors such as the lower
partial pressure of atmospheric CO2, requiring increased
stomatal conductance, and higher radiation, leading to
higher vapor pressure deficits (VPD), might combine to
impose greater water loss for trees (Leuschner 2000;
Korner 2007). To cope with these changes in environmental conditions, plants may adjust morphologically and
physiologically in terms of hydraulic functioning, including reductions in leaf area, lower specific leaf area and
decreased stomatal opening, all of which directly affect
whole tree water use (Cavelier 1996; Grubb 1977; Motzer
et al. 2005; Rada et al. 2009; Santiago et al. 2000;
Velázquez-Rosas et al. 2002; Woodward 1993). Despite
the fact that some of these functional traits have commonly
been used to describe light capture and trade-offs of carbon
gain and water loss (Wright et al. 2004), the relationship
between specific functional traits and xylem sap flow, a
measure of total tree water use (Bucci et al. 2004; Burgess
2006; Nadezhdina 1999) has not been properly assessed
along altitudinal variations in tropical rainforests.
Taking into account that tree water use (i.e. xylem sap
flow) is dependent on several morpho-physiological traits
(Burgess 2006; Cruiziat et al. 2002; Meinzer et al. 1999), it
is not clear whether functional traits commonly used to
describe response of species to varying environmental
conditions [e.g. changes to specific leaf area and wood
density; (Chave et al. 2009; Wright et al. 2004)] give insight into plant water use along altitudinal variations.
Furthermore, although it has been reported that species
with different crown exposures and sizes may show distinct
morphological traits and sap flow (Andrade et al. 1998;
Meinzer et al. 2001; Motzer et al. 2005; O’Brien et al.
2004; Poorter 2009), it is not clear what effects altitudinal
variation has on species, independent of different crown
exposures. Similarly, although differential responses
of plants to water availability across wet and dry seasons
have been reported (Graham et al. 2005; Kunert et al. 2010;
Myneni et al. 2007; Renninger et al. 2010), to our
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knowledge, there are not any studies evaluating how seasonal changes are modulated by altitude.
In our study, we evaluated changes in plant water use
and the contribution of morphological traits and crown
exposure to sap flow in four tropical woody species cooccurring in a Lowland (*100 m.a.s.l) and a Montane site
(*1,000 m.a.s.l) in the Atlantic Rain Forest, Brazil. In
both these sites, we already have evidence of significant
increases in solar radiation and VPD and decreases in atmospheric pressure with altitude (Rosado et al. 2010,
2012). We have also documented restricted nighttime
transpiration (Rosado et al. 2012) and higher fine root
biomass and root length density at the Montane site
(Rosado et al. 2011). Interestingly, palaeoecological data
indicate that during drier climates than today, in the Last
Glacial Maximum, the Atlantic rain forest was restricted to
the Lowland while the Montane forest was occupied by
grasslands (Behling 2008). Since the Atlantic rain forest is
a biodiversity hotspot for conservation (Myers et al. 2000),
our investigation is highly relevant to conservation goals in
particular predicting the response of species to climate
changes.
Based on the premise that the Montane forest is drier
than the Lowland forest, we have the following hypotheses:
(1) At the Montane forest, plant species will show a more
conservative water use, regardless of crown exposure. A
more conservative water use will be described by a lower
crown conductance [estimated by sap flow; (CavenderBares et al. 2007)] associated with adjustments in functional traits such as lower specific leaf area, leaf area/sapwood area and higher leaf water content (i.e. maximum
water storage capacity) which might be responses to cope
with drought (Lamont and Lamont 2000; Rosado and de
Mattos 2007; Vendramini et al. 2002; Westoby et al. 2002;
Wright et al. 2006); (2) seasonally, there will be a greater
increase in conservative water use during the dry season at
the Lowland forest, since the climate conditions in the
Montane site may impose higher constraints to water use
throughout the year.
Materials and methods
Our study was conducted in lowland forest (23°310 –23°
340 S and 45°020 –45°050 W), located at *100 m above sea
level, and montane forest (23°170 –23°240 S and 45°030 –
45°110 W), located at *1,000 m above sea level in the
Serra do Mar State Park, covering 315,000 hectares in the
Atlantic Rain Forest in the north of São Paulo state, Brazil.
Both sites are characterized as broadleaf evergreen tropical
forests.
The climate in Serra do Mar is humid subtropical with
hot summers (Cfa type in Köppen), up to 3 months per year
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with \100 mm rainfall and with 1 month per year with
\50 mm rainfall (Sentelhas et al. 1999). Lowland and
Montane forests differ in patterns of precipitation, air
temperature, VPD, solar radiation and atmospheric pressure (Fig. 1a–d). In the montane site, despite the frequent
cloud cover and fog (Rosado et al. 2010; Silva-Dias et al.
1995), solar radiation and VPD are higher in comparison to
the lowland forest (Rosado 2011, Rosado et al. 2010,
2012). Soils at both forests are classified as Inceptisols
without differences in depth (Alves et al. 2010; Martins
2010). Soil moisture, measured as water filled soil pore
space, is significantly lower at the Montane forest (Sousa
Neto et al. 2011).
Criteria for selecting plant species included their cooccurrence at both sites, contrasting canopy position
Fig. 1 Meteorological differences between sites across seasons.
a Daily rainfall (mm) at the Lowland (black bars) and Montane
Forest (gray bars) and daily mean air temperature (oC) for both sites.
Shaded areas represent three periods (dry season 2008, 2009 and wet
season) selected for the analysis of sap flow data. b Monthly mean
vapor pressure deficit ± standard error (VPD, kPa). b Monthly mean
solar radiation ± standard error (MJ m-2) and c Monthly mean
Atmospheric Pressure ± standard error (hPa) in both sites. In each
panel, Montane forest (dotted lines) and Lowland (solid lines)
(overstory, intermediate and understory) and contrasting
families to avoid phylogenetic bias. The species chosen
were: Hyeronima alchorneoides Allemão (Phyllanthaceae),
Alchornea triplinervia (Spreng.) Müll. Arg. (Euphorbiaceae), Mollinedia schottiana (Spreng.) Perkins (Monimiaceae); and Rustia formosa Klotzsch (Rubiaceae).
Hyeronima and Alchornea are overstory species while
Rustia is an intermediary and Mollinedia an understory
species. For simplicity, we will refer to each species by
their generic names.
Morphological traits
We collected one to three branches from three to five individuals of each species during the dry and wet seasons.
Collected branches were placed in humidified plastic bags
in the field. In the laboratory, each branch was cut under
water and placed in an aqueous solution of methylene blue
and covered with a plastic bag and equilibrated for about
5 h. After hydration, leaf thickness (TH, mm) was measured with a digital caliper in three or five leaves. From
each branch, the submersed section was cut, the bark was
removed and the sapwood area (SA) was measured with a
digital caliper. All leaves per individual branch were
weighed on a digital balance to estimate whole saturated
mass. Leaf area (cm2) was determined by scanning the
leaves with a flatbed scanner at 100 dpi resolution and
analyzed with a pixel-counting software (ImageJ). Leaves
were oven dried for at least 48 h at 70 °C and weighed.
From these data, we estimated the SLA (the leaf blade area
per unit leaf mass; cm2 g-1), LA/SA (the total leaf area per
sapwood cross-sectional area; cm2 m-2) and leaf water
content (the saturated mass 1-dry mass/saturated mass,
g g-1). Leaf density (DEN; mg mm-3) was estimated as
SLA/TH (Witkowski and Lamont 1991). For wood density
(WD g cm-3), we standardized the branch diameter among
species. For each branch, we removed a section of the
branch (2–4 cm diameter and ca. 4 cm long), from which
we removed the bark. The volume of samples (cm3) was
obtained by the Archimedes principle, immersing them in a
receptacle containing water, placed over a digital balance.
WD was obtained by dividing the dry mass per fresh volume of sample (i.e. basic density). A full list of traits and
abbreviations/symbols is presented in Table 1.
Sap-flow probe installation and measurements
We used the heat ratio method (Burgess et al. 1998, 2001)
to make continuous measurements of sap flow in trunks of
three to four individuals per species at each site. The HRM
measures the increase in temperature following a heat pulse
at two symmetrical points, 5 mm above and below a heater
inserted 30 mm into the active sapwood. This technique
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Table 1 List of abbreviations/
symbols and units
Variables
Abbreviations/symbols
Unit
Specific leaf area
SLA
cm2 g-1
Leaf thickness
TH
mm
Leaf density
DEN
mg mm-3
Leaf area per sapwood area
LA/SA
cm2 m-2
Leaf water content
LWC
g g-1
Wood density
WD
g cm-3
Crown exposure
CE
–
Sap flow
Q
kg hr-1
Sap flow normalized by crown projected area
Qcrown
kg hr-1 m-2
Sapwood cross-sectional area
CSA
cm-2
Crown conductance
Gcrown
kg hr-1 m-2 kPa-1 day-1
Vapor pressure deficit
VPD
kPa
allows bi-directional measurements of sap flow and also
measures very slow flow rates which we might expect
during very dry conditions or periods with low atmospheric
demand. Sap flow sensors (HRM30 ICT International Pty
Ltd, Armidale, NSW, Australia) were inserted into the
xylem tissue of the trunks at breast height. The heater was
set up to send a pulse every 30 min and results were
recorded with a data logger (SL5 Smart Logger ICT International Pty Ltd, Armidale, NSW, Australia). We calculated the heat pulse velocity (cm hr-1) following
Burgess et al. (1998, 2001) as:
V ¼ kX 1 ln v1 ðv2Þ1 3600
where k is the thermal diffusivity of the fresh (green) wood,
X is the distance (cm) between the heater and the thermocouples, and v1 and v2 are the differences between the
initial temperature (oC) at the two thermocouples (downstream and upstream the flow in relation to the heater,
respectively) and the temperature measured 60–100 s after
a heat pulse. To estimate k, density of the sapwood, water
content and sap wood cross-sectional area (CSA), wood
cores were taken from the stems in September 2009. Since
it was not possible to cut the xylem to establish zero flow,
we selected a series of data from overcast dawn periods in
the absence of rain and used these conditions to estimate
zero flow (Burgess and Dawson 2004; Rosado et al. 2012).
Sap flow (Q; kg hr-1) for each individual was calculated
by scaling sap velocity by sapwood cross-sectional area
(CSA; cm-2). The measurements were performed from
June 2008 to September 2009. For the analysis of sap flow
data, we selected data from 13 to 30 days, within the periods indicated by the gray bars in Fig. 1, using the same
days for both sites. To compare water use of each species
regardless of differences in plant size (data not shown), sap
flow was weighted by crown projected area (Qcrown). We
measured crown area by measuring distance from the edge
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of the canopy to the stem in four cardinal directions and
then calculated the crown area using the ellipse (O’Brien
et al. 2004). Crown projected area was positively related to
stem diameter (R2 = 0.86). For the crown conductance
(Gcrown; kg hr-1 m-2 kPa-1 day-1) of each individual, sap
flow was divided by the VPD at the corresponding time of
measurement (Cavender-Bares et al. 2007) and the total
Gcrown for each day was obtained by the sum of the values.
The Gcrown per day in each season was used to estimate the
mean Gcrown per individual per season.
Environmental variables
Three air temperature and relative humidity sensors
(HOBO) were placed around 20, 10 and 2 m from the
ground (canopy, intermediate and understory, respectively,
at both sites) and set up to collect data every 30 min. These
data were used to calculate vapor pressure deficit (VPD,
kPa). Solar radiation (MJ m-2) and atmospheric pressure
(hPa) data at both sites were obtained from the dataset
provided by the Centro de Previsão de Tempo e Estudos
Climáticos (CPTEC/INPE, Projeto de eventos meteorologicos extremos na Serra do Mar) website (http://www.
cptec.inpe.br/). To compare differences of VPD and solar
radiation between seasons and the interactions sites:seasons, we selected the same periods used for the analysis of
sap flow data as indicated in Fig. 1a.
Statistical analysis
To test both hypothesis (differences between altitudes and
the higher similarity of responses in the Montane forest
between seasons), we ran a three-factor analysis of variance (three-way ANOVA, P \ 0.05), with repeated measurements since we performed repeated measurements
taken from the same individuals, to evaluate differences
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of traits and Gcrown between seasons and altitudes. For
morphological traits, sap flow and crown conductance,
data from the dry season 2008 and 2009 were combined
for a better characterization of the dry season in both
sites. Additionally, we ran a principal component analysis
(PCA) on a correlation matrix to test possible associations
between the maximum Qcrown and the average morphological traits in each altitude (hypothesis 1) and also to
evaluate the displacement of responses for each species,
per altitude, across dry and wet seasons (hypothesis 2).
The displacements of each species between seasons per
site were estimated by Euclidean distance matrix obtained
from the eigenvalues of the PCA. A two-factor analysis of
variance (two-way ANOVA, P \ 0.05) was performed to
detect differences in VPD and solar radiation across seasons between forests. We used Multiv software for PCA
analysis (Pillar 1997). ANOVA and boxplots were performed using the R version 2.15.1, http://www.R-project.
org.
We performed an error propagation analysis to evaluate
the potential error when upscaling from sap velocity to
crown conductance. Different sources of errors such as
sapwood cross-sectional area (CSA), crown projected area
(CA) and VPD are additive and must be taken into account
for upscaling procedures (Gotsch et al. 2014). The error
propagation (r) of Gcrown of each species per season and
site was calculated as the root square of [stdev of sap velocity/mean of sap velocity)2 ? (stdev CSA/mean of
CSA)2 ? (stdev of CA/mean of CA)2 ? (stdev of VPD/
mean of VPD)2], where stdev is the standard deviation of
each variable. The mean and standard deviation of VPD
were estimated per time of measurement (every 30 min)
for each season per site.
Results
Environmental variables
In the same periods used for the analysis of sap flow data,
VPD was significantly higher in the Montane in comparison to the Lowland (df = 1; F = 8.8; P \ 0.01).
Similarly, solar radiation was also significantly higher in
the Montane in comparison to the Lowland (df = 1;
F = 11.1; P \ 0.001), in accordance to previous patterns
reported in both sites (Rosado et al. 2010, 2012). Solar
radiation did not vary significantly between seasons. We
observed a significant interaction between sites and seasons
for VPD (df = 1; F = 6.602; P \ 0.05), where the only
differences observed were between the Lowland and
Montane forests during the dry season, without significant
differences between seasons within each site.
Table 2 Variation in functional traits among species and seasons in both forests
Site
Season
Lowland
Dry
Wet
Montane
Dry
Wet
Species
LA/SA
cm2 m-2
LWC
g g-1
SLA
cm2 g-1
DEN
mg mm-3
TH
mm
WD
g cm-3
Alchornea
0.53 ± 0.21
0.61 ± 0.01
153.57 ± 27.66
0.22 ± 0.07
0.32 ± 0.07
0.30 ± 0.01
Hyeronima
0.66 ± 0.22
0.72 ± 0.03
121.03 ± 25.04
0.27 ± 0.05
0.32 ± 0.08
0.42 ± 0.04
Mollinedia
1.20 ± 0.56
0.76 ± 0.01
237.41 ± 12.89
0.19 ± 0.01
0.23 ± 0.02
0.49 ± 0.03
Rustia
2.73 ± 0.82
0.92 ± 0.00
242.89 ± 134.31
0.15 ± 0.04
0.32 ± 0.08
0.35 ± 0.03
Alchornea
0.73 ± 0.52
0.62 ± 0.03
138.31 ± 58.26
0.50 ± 0.27
0.19 ± 0.09
0.30 ± 0.01
Hyeronima
0.90 ± 026
0.73 ± 0.04
129.63 ± 30.91
0.32 ± 0.09
0.25 ± 0.01
0.42 ± 0.04
Mollinedia
Rustia
0.89 ± 0.22
1.14 ± 0.48
0.72 ± 0.04
0.78 ± 0.01
194.40 ± 53.80
148.14 ± 6.00
0.26 ± 0.06
0.25 ± 0.01
0.21 ± 0.01
0.27 ± 0.02
0.49 ± 0.03
0.35 ± 0.03
Alchornea
0.18 ± 0.02
0.61 ± 0.05
114.69 ± 4.10
0.45 ± 0.07
0.20 ± 0.04
0.38 ± 0.05
Hyeronima
0.74 ± 0.44
0.76 ± 0.03
127.06 ± 6.27
0.32 ± 0.02
0.25 ± 0.01
0.34 ± 0.08
Mollinedia
0.35 ± 0.24
0.72 ± 0.05
148.27 ± 24.13
0.29 ± 0.07
0.25 ± 0.07
0.43 ± 0.01
Rustia
0.69 ± 0.22
0.71 ± 0.04
146.74 ± 31.90
0.39 ± 0.01
0.18 ± 0.03
0.47 ± 0.13
Alchornea
0.56 ± 0.15
0.60 ± 0.06
125.55 ± 26.41
0.56 ± 0.16
0.16 ± 0.08
0.36 ± 0.01
Hyeronima
0.88 ± 0.20
0.76 ± 0.03
131.25 ± 18.65
0.35 ± 0.07
0.23 ± 0.04
0.34 ± 0.08
Mollinedia
0.54 ± 0.19
0.73 ± 0.12
162.48 ± 34.97
0.39 ± 0.23
0.19 ± 0.08
0.49 ± 0.06
Rustia
0.80 ± 0.26
0.70 ± 0.02
135.80 ± 5.66
0.38 ± 0.08
0.20 ± 0.04
0.51 ± 0.07
Values are mean ± Standard error
The traits are leaf area per sapwood area (LA/SA), leaf water content (LWC), specific leaf area (SLA), leaf density (DEN), leaf thickness (TH),
wood density (WD)
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Table 3 Results of three-way ANOVA, with repeated measurements (individuals between seasons at each altitude), on crown conductance and
functional traits in sites, seasons and species (sp) and factor interactions
Trait
Df
Sum Sq
Mean Sq
F
P
sp
3
54,376
18,125
1.458
site
1
91,772
91,772
7.384
0.0146*
sp:site
3
65,626
21,875
1.76
0.1929
Residuals
17
211,289
12,429
Error:within
season
1
8,628
8,628
3.181
0.0923
sp:season
3
20,305
6,768
2.496
0.0947
site:season
1
9,027
9,027
3.328
0.0857
sp:site:season
3
26,441
8,814
3.25
0.0477*
17
46,105
2,712
sp
3
4.268
1.4226
8.8
0.000959***
site
1
3.114
3.1136
19.26
0.000401***
sp:site
3
2.549
0.8496
17
2.748
0.1617
season
1
0.0731
0.0731
0.667
0.4253
sp:season
3
1.8779
0.626
5.713
0.00681**
site:season
sp:site:season
1
3
0.965
1.4614
0.965
0.4871
8.807
4.446
0.00863**
0.01762*
17
1.8627
0.1096
3
26,135
8,712
4.178
0.0218*
Gcrown
Error: factor(individual)
Residuals
0.2612
LA/SA
Error:factor(individual)
Residuals
5.255
0.009495**
Error:within
Residuals
SLA
Error:factor(individual)
sp
site
1
14,331
14,331
6.873
0.0179*
sp:site
3
8,707
2,902
1.392
0.2793
17
35,445
2085
season
1
2,749
2,749
1.687
0.2113
sp:season
3
6,189
2,063
1.266
0.3175
site:season
1
5,001
5,001
3.069
0.0978
sp:site:season
3
3,499
1166
0.716
0.5561
17
27,701
1,629
Residuals
Error:within
Residuals
LWC
Error:factor(individual)
sp
3
0.17177
0.05,726
site
1
0.01233
0.01233
5.232
0.03527*
sp:site
3
0.05732
0.01911
8.106
0.00144**
17
0.04007
0.00236
season
1
0.00469
0.004685
2.214
0.155
sp:season
3
0.01322
0.004406
2.082
0.141
site:season
1
0.00345
0.003452
1.631
0.219
sp:site:season
3
0.0098
0.003268
1.545
0.239
17
0.03597
0.002116
Residuals
24.29
0.00000223***
Error:within
Residuals
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Table 3 continued
Trait
Df
Sum Sq
Mean Sq
F
P
3
1
0.0146
0.03777
0.00487
0.03777
1.637
12.703
0.2182
0.00239**
2.252
0.1193
TH
Error:factor(individual)
sp
site
sp:site
3
0.02009
0.0067
17
0.05055
0.00297
season
1
0.02687
0.026866
8.714
0.00892**
sp:season
3
0.00862
0.002873
0.932
0.4468
site:season
1
0.00406
0.004059
1.317
0.26709
sp:site:season
3
0.0077
0.002567
0.833
0.49419
17
0.05241
0.003083
sp
3
0.11362
0.03787
2.858
site
1
0.17259
0.17259
13.023
sp:site
3
0.03695
0.01232
0.929
Residuals
Error:within
17
0.22528
0.01325
season
1
0.10116
0.10116
8.792
0.00868**
sp:season
3
0.05101
0.017
1.478
0.25608
site:season
1
0.01037
0.01037
0.901
0.35577
sp:site:season
3
0.01743
0.00581
0.505
0.68409
17
0.1956
0.01151
sp
3
0.1427
0.04757
12.29
site
1
0.00406
0.00406
1.05
0.319798
sp:site
3
0.09553
0.03184
8.228
0.001336**
17
0.06579
0.00387
season
1
0.00223
0.002231
0.901
0.356
sp:season
site:season
3
1
0.00355
0.00174
0.001182
0.001737
0.477
0.701
0.702
0.414
sp:site:season
3
0.00311
0.001038
0.419
0.742
17
0.0421
0.002477
Residuals
Error:within
Residuals
DEN
Error:factor(individual)
Residuals
0.06774
0.00217**
0.44792
WD
Error:factor(individual)
Residuals
0.000161***
Error:within
Residuals
The traits are crown conductance (Gcrown), leaf area per sapwood area (LA/SA), specific leaf area (SLA), leaf water content (LWC), leaf thickness
(TH), leaf density (DEN), wood density (WD), Df degrees of freedom, SS sum of squares, Mean Sq mean square, F F ratio, and P value. Asterisks
indicate significant differences: 0 ‘***’ 0.001 **0.01 ‘*’ 0.05
Morphological traits
We observed significant differences between sites and seasons for most traits (Tables 2, 3; Fig. 3). At the Lowland site,
SLA, LA\SA, and TH were significantly higher while DEN
was lower in comparison to the Montane site (Tables 2, 3;
Fig. 3). WD did not differ between sites. TH and DEN were
significantly different between seasons for both sites
(P \ 0.001). While TH was higher in the dry season, DEN
showed the opposite pattern with lower values in the dry
season. Only for LA/SA, we observed a significant interaction between sites and seasons. LA/SA was significantly
higher in the Lowland in the dry season only compared to the
Montane forest in both seasons (P \ 0.01, Table 3; Fig. 5).
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Table 4 Mean of Sap flow per day (Q; kg day-1) and crown conductance (Gcrown; kg hr-1 m-2 kPa-1 day-1) ± standard error for each species
per altitude and season
Crown conductance
r
65.1 ± 23.3
146.2 ± 66.9
1.6
Hyeronima
432.6 ± 62.2
126.3 ± 37.9
1.7
Mollinedia
40.0 ± 29.6
101.1 ± 88.8
1.6
Rustia
60.2 ± 26.0
163.7 ± 64.3
1.5
48.8 ± 14.5
91.1 ± 34.3
1.6
Hyeronima
447.8 ± 50.5
105.0 ± 24.3
1.6
Mollinedia
Rustia
21.6 ± 11.2
55.4 ± 25.9
66.7 ± 27.7
274.3 ± 98.4
1.7
1.7
Site
Species
Season
Lowland
Alchornea
Wet
Alchornea
Montane
Alchornea
Dry
Wet
Sap flow
53.3 ± 21.8
9.6 ± 2.7
1.3
Hyeronima
17.4 ± 2.8
51.1 ± 16.1
1.0
Mollinedia
4.1 ± 1.5
15.0 ± 4.2
1.5
Rustia
4.7 ± 1.7
13.5 ± 3.3
1.2
57.8 ± 18.6
31.0 ± 6.3
1.4
Hyeronima
20.8 ± 4.9
208.2 ± 110.5
1.2
Mollinedia
6.3 ± 3.0
22.0 ± 6.2
1.5
Rustia
9.5 ± 2.2
40.0 ± 10.0
1.3
Alchornea
Dry
Error propagation (r) estimated for crown conductance of each species per season and altitude due to scaling sap velocity by sapwood crosssectional area, crown projected area and vapor pressure deficit
Sap flow parameters
During the three seasons, the average volume of sap flow
per individual was higher in the lowland ranging from
14.43 to 496.09 kg day-1 contrast to a range from 4.13 to
53.62 kg day-1 for the Montane site (Table 4). At the
Lowland forest, the strata occupied by each species did not
appear to affect sap flow since the average sap flow for
each species was: Hyeronima (overstorey) [ Rustia (midstrata) [ Alchornea (overstorey) [ Mollinedia (understorey). However, at the Montane site, the average sap flow
corresponded to the strata occupied by each species
(Alchornea [ Hyeronima [ Rustia [ Mollinedia). In general, Qcrown was lower at the Montane site in both seasons,
except for Hyeronima (Fig. 2). Crown conductance
(Gcrown), was significantly lower at the Montane site, and
there was no difference between seasons (Fig. 3). The error
propagation associated to the scaling of sap flow by CSA,
crown projected area and VPD varied from 1.0 to 1.7
among species in both sites and seasons.
the wet to dry season in the Lowland forest showed a trend
of higher values (Euclidean distance) in comparison to the
Montane (Figs. 4a, 6) and occurred preferentially along the
second axis for the overstory species (Alchornea and
Hyeronima) and along the first axis for the intermediate
and understory species. While maximum Qcrown showed
positive relationships with SLA LWC and LA/SA, maximum Qcrown was not negatively related to any trait at this
site. At the Montane site, the first and second axes explained 47.26 and 32.98 % of the variation among species
and seasons (Fig. 4b). LWC, CE and TH had greater
contribution in the first axis, while WD, SLA and maximum Qcrown had the highest scores in the second axis
(Table 5). The displacement of all species from the wet to
dry season in the multivariate space occurred preferentially
along the second axis (Fig. 4b). Positive relationships between traits were between maximum Qcrown and LA/SA
and TH. In contrast to that observed at the Lowland site,
maximum Qcrown was negatively associated with SLA
and WD.
Multivariate analysis
Discussion
The first and second axes of the PCA explained 43.16 and
24.80 % of the variation among species and seasons at the
Lowland site, (Fig. 4a). LA/SA, SLA and LWC were the
traits that had the highest scores in the first axis, while TH,
CE and WD had the highest in the second axis (Table 5).
The displacement of species in the multivariate space from
123
Our findings demonstrate that changes to water availability
as determined by rainfall, VPD, solar radiation and soil
water storage can impose a conservative water use in tropical rainforest species in spatial scales (Lowland versus
Montane forest; e.g. lower crown conductance at Montane
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Fig. 2 In each panel, diurnal
patterns of vapor pressure
deficit (VPD, dotted lines) and
mean of sap flow normalized by
crown projected area (Qcrown,
solid lines) per species in each
altitude. Vertical lines in each
panel divide 48 h of diurnal
patterns selected from the dry
season 2008 and the wet season,
as indicated in Fig. 1
site) and temporal scales (Dry versus Wet season; e.g.
higher LA\SA at the Lowland in dry season and higher TH
and lower DEN during the dry season for both sites). This
is remarkable since water availability is assumed to be a
non-limiting resource due to a lack, or not marked, dry
season at the Atlantic rainforest (Bencke and Morellato
2002; Morellato et al. 2000; Oliveira-Filho and Fontes
2000). Beyond our previous results indicating restricted
nighttime transpiration and increase in fine root biomass
and root length density with altitude (Rosado et al. 2011,
2012), for most traits in the present study, the functional
changes between altitudes indicate ecophysiological adjustments for more conservative water use related to higher
radiation and VPD (Rosado et al. 2010, 2012), and lower
soil moisture (Sousa Neto et al. 2011) at the Montane
forest. Our results are in line with the recent perspective
(Anderegg et al. 2013) that the significance of drought must
be understood not only based on abiotic parameters (e.g.
soil water potential, rainfall amounts), but also on an
ecological basis, comprising both individual species responses (e.g. our study) and community-level interactions
(e.g. hydraulic redistribution and water partitioning/competition) (Anderegg et al. 2013).
Hypothesis 1: at the Montane forest, plant species
will show a more conservative water use.
In agreement to our first hypothesis, the significant
lower crown conductance (Gcrown; Fig. 3a) at the Montane
forest was remarkable. Only Hyeronima showed an opposite pattern of increases in sapflow at the Montane forest.
Although we did not measure additional traits in these
species, we may speculate that this behavior might be associated to deeper roots. Additionally, it has been pointed
out that Hyeronima shows a small change in leaf area between seasons what keeps high rates of canopy transpiration (Bigelow 2001). Regardless of the distinct behavior of
123
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Fig. 3 Boxplots of crown conductance (Gcrown) and morphological
traits between sites. Leaf density (DEN), leaf area/sapwood area (LA/
SA), leaf water content (LWC), specific leaf area (SLA) and leaf
thickness (TH). Outliers (circles) are data points more than 1.5
interquartile ranges below the first quartile or above the third quartile.
Asterisks indicate significant differences between sites: 0 ***0.001
**0.01 *0.05
Hyeronima, the lower Gcrown at the Montane forest (in
comparison to Lowland) indicates a more conservative
water use which is presumably related to increased VPD
and lower soil moisture (Sousa Neto et al. 2011). Interestingly, the significantly lower LA/SA in Montane site
(Table 3; Fig. 3c), where plants are exposed to higher radiation, VPD and lower soil moisture, indicates a hydraulic
adjustment to minimize cavitation risk which may be associated with a higher hydraulic conductivity (Gotsch et al.
2010; Martı́nez-Vilalta et al. 2004; Wright et al. 2006).
This demonstrates that the view that rainforests are not
water limited is overly simplistic.
A lower SLA, as observed at the Montane site (Table 2;
Fig. 3e), indicates higher leaf construction cost which is a
common response in dry habitats (Westoby et al. 2002;
Wright et al. 2002). Contrary to observations of increases
in TH along a gradient of increasing altitude (VelázquezRosas et al. 2002), we observed decreases in TH, associated with increases in DEN, leading to lower LWC, with
altitude (Table 2; Fig. 3f). Although lower TH at the
montane site might be related to more negative leaf water
potentials, suggesting a lower drought tolerance in comparison to thicker leaves (Cavelier 1996), increases in DEN
may be related to higher volumetric elastic modules which
is a strategy for water uptake in drought-prone plants
(Niinemets 2001; Rosado and de Mattos 2010). Additionally, the higher DEN and lower SLA at the Montane site
might be related to increases in leaf longevity (Bruijnzeel
and Veneklaas 1998) as observed for dry environments
(Kikuzawa and Lechowicz 2011), due to an increase in
fiber and sclereids that increase the tissues durability
(Ryser 1996; Witkowski and Lamont 1991). Indications of
a higher leaf longevity at the Montane site are supported by
the fact that, despite the higher aboveground biomass
(Alves et al. 2010), litter production is lower at the Montane site (Martins 2010) which, therefore, may be associated with lower rates of leaf death.
According to the first hypothesis, we expected that a
more conservative water use would be associated, for instance, with a lower crown conductance related to lower
specific leaf area and leaf area/sapwood area. From the
PCA, at both sites, maximum Qcrown was positively associated with LA/SA, LWC and TH (Table 5; Fig. 4).
However, we advocate that SLA and WD are the best descriptors of maximum Qcrown due to the changes in their
relationships between sites (Table 5; Fig. 4). From the
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Fig. 5 Boxplots of leaf area/sapwood area (LA/SA) for the interaction
between site and season. Different letters indicate significant difference (P \ 0.05)
Table 5 Eigenvalues for each trait per altitude. The traits are specific
leaf area (SLA), leaf area/sapwood area (LA/SA), leaf water content
(LWC), maximum sap flow weighted by crown projected area
(Qcrown), crown exposure (CE), wood density (WD) and leaf thickness
(TH)
Lowland
Traits
Axis 1
43.16 %
Axis 2
24.80 %
Montane
Traits
Axis 1
47.26 %
LA/SA
20.93
-0.25
LWC
20.99
Axis 2
32.98 %
0.12
SLA
20.86
0.35
CE
0.93
-0.31
LWC
20.84
-0.29
TH
20.72
-0.29
Qcrown
-0.70
-0.04
Qcrown
-0.64
20.70
TH
-0.16
20.85
LA/SA
-0.63
-0.08
WD
CE
-0.03
0.45
0.48
20.71
SLA
WD
-0.39
0.04
0.87
0.93
In bold, the traits with higher eigenvalues for each axis
Fig. 4 PCA ordination on the basis of four species in two seasons for
each site. The traits are specific leaf area (SLA), leaf area/sapwood area
(LA/SA), leaf water content (LWC), maximum sap flow normalized by
crown projected area (Qcrown), crown exposure (CE), wood density
(WD) and leaf thickness (TH). Each species, in the wet and dry seasons
respectively, are represented as: Alchornea—AlcWet and AlcDry,
Hyeronima—HyeWet and HyeDry, Rustia—RusWet and RusDry and
Mollinedia—MolWet and MolDry
Lowland to the Montane site, the change from a positive to
a negative relationship between maximum Qcrown and SLA
would indicate that the ability to sustain maximum Qcrown
is only possible when leaves have adjusted to avoid the
damaging effects of water deficit (i.e. lower SLA).
Similarly, Hao et al. (2010) reported the importance of a
conservative water use associated with functional traits
conferring a higher leaf persistence, such as lower SLA in
conferring an advantage to hemiepiphytic species under
drought. Additionally, although Bucci et al. (2004) have
indicated WD as an important descriptor of sap flow, we
found that only at the drier site (Montane forest). WD was
negatively related to maximum Qcrown since a higher WD
should tend to increase resistance to water flow, reducing
efficiency in the transport of water through xylem (Bucci
et al. 2004; Meinzer 2003). Although the positive association between maximum Qcrown and LWC seems less
obvious, we can envisage some connections, i.e. leaves
with higher water contents may buffer fluctuations of leaf
water potential under high transpiration rates (Sack and
Tyree 2005) thus promoting greater overall efficiency, and
therefore total amount, of water supply.
Unlike Sack and Frole 2006, who reported that hydraulic
architecture is unrelated to leaf traits commonly measured,
sap flow parameters were associated with traits (i.e. SLA
and WD; Table 5; Fig. 4) from the economic spectrum
(Chave et al. 2009; Wright et al. 2004). This highlights the
importance of correctly choosing functional traits (Rosado
et al. 2013) especially when their relative importance to
describe response of species to drought seems to change
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Fig. 6 Euclidean distance of species between seasons per site.
Euclidean distance matrix was obtained from the eigenvalues
(PCA) of each species per season in each site
depending on the environment. Similar to Oren et al.
(1996) who reported that transpiration among trees was not
related to vertical positions of crowns, we did not observe
relationships between maximum Qcrown and CE in both
sites, reinforcing the importance of functional traits as
indicators of plant water use.
The lower Gcrown at the Montane forest (Fig. 3a) is in
line with the observation the LA/SA was less related to
maximum Qcrown (Table 5; Fig. 4), in comparison to the
Lowland. The lower LA/SA at the Montane site could
minimize higher water losses that would lead to stomatal
closure, as observed in drought-prone environments
(Gotsch et al. 2010; Wright et al. 2006). In fact, tropical
montane forest plants may be sensitive to variations in
water availability and have a strong stomatal closure in
response to small variations in VPD (Cavelier 1996).
Further evidence for the ability of stomata to control
transpiration even under mild conditions such as early
morning can be found in the fact that even nighttime
transpiration at the Montane site shows a non-linear response to VPD, presumably as a result of both physiological and abiotic controls (Rosado et al. 2012).
Hypothesis 2: seasonally, there will be a greater increase in conservative water use during the dry season at the Lowland forest, since the climate
conditions in the Montane site may impose higher
constraints to water use throughout the year.
In agreement with our hypothesis, the higher LA/SA at
the Lowland during the dry season, only in comparison to
the Montane forest in both seasons, suggests a change in
the water use strategy which might be related to a lower
hydraulic conductivity to minimize cavitation (Wright
et al. 2006). This result indicates that the functional similarity between the Lowland and Montane might be seasonality dependent, which is also supported by our results
123
showing the significant difference in VPD between sites
only during the dry season.
Although a deeper understanding of changes of LA/SA
requires knowledge of variables not estimated in this
study, such as hydraulic conductivity and the conductance
of water vapor between leaves and bulk air (Martı́nezVilalta et al. 2004), we can still broadly postulate that
reductions in LA/SA might reduce the gradient in water
potential throughout the plant system during droughts
(Bucci et al. 2004; Martı́nez-Vilalta et al. 2004; Wright
et al. 2006). This subject would benefit from further study
of other hydraulic traits to elucidate the mechanisms behind the variation of LA/SA (Wright et al. 2006), again
taking into account spatio-temporal scales. Interestingly,
in line with our second hypothesis, evidence of greater
sensitivity of montane plants to daily and seasonal variations in climatic factors (lower Gcrown), their sensitivity
to overall drier conditions led to more uniform responses,
leading to the lower Euclidean distances in the PCA.
(Figs. 4a, b,6).
Additionally, the increases in TH during the dry season
in both sites may be related to a higher leaf water storage
that might act as an alternative water source (Lamont and
Lamont 2000) as observed for drought-prone habitats
(Rosado and de Mattos 2007). This view is reinforced by
TH association with LWC in both sites in PCA. Therefore,
the similar Gcrown between seasons at each altitude might be
the result of different arrays and adjustments of morphological traits buffering the total water use in each season.
Conclusions and future directions
Although it is usually assumed that the main limiting factors in tropical rainforests are solar radiation and nutrients
(Grubb 1977), our study provides evidence of plant hydraulic adjustments in response to small changes in water
availability, suggesting that water use constraints exist for
tropical rainforest trees when exposed to higher VPD, solar
radiation and lower soil moisture, regardless crown exposure. This suggests that future changes to water availability
(e.g. changes to rainfall patterns) in these regions could
impact forest structure and function considerably (Oliveira
et al. 2014a, b).
In light of our results indicating that conservative water
use by rainforest woody species increases with altitude,
recent studies indicate that montane sites may be vulnerable to climate changes due to reductions in fog events
which are an important water source (Eller et al. 2013;
Ponce-Reyes et al. 2012; Pounds et al. 1999; Still et al.
1999). Therefore, we suggest that the next steps for research in montane tropical rainforest should focus on
physiological traits related to hydraulic failure and carbon
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Trees
starvation (e.g. vulnerability curves, leaf water potential
and non-structural carbohydrate) (McDowell et al. 2008,
2011) to address the question whether the higher conservative water use observed at the Montane Forest translates
into a higher or lower susceptibility to intensification of
drought which might arise due to climate change (Oliveira
et al. 2014b).
Author contribution statement B.H.P.R., C.A.J.,
S.S.O.B., R.S.O. and M.P.M.A. supervised the research.
B.H.P.R., C.A.J., R.S.O. and M.P.M.A. collected data.
B.H.P.R., S.S.O.B., R.S.O. and M.P.M.A. interpreted the
results and B.H.P.R. wrote the paper. B.H.P.R., S.S.O.B.,
R.S.O. and M.P.M.A. commented on the manuscript during
the final stages.
Acknowledgments We are grateful to Kathy Steppe for organizing
the 9th International Workshop on Sap Flow, which prompted the
publication of this paper. We thank both reviewers for good critiques
and suggestions which improved the paper. We thank E. McLean, P.
Grierson and E. Veneklaas for good discussions, A.T.C. Dias and
G.R. Winck for helping with some statistical analysis and H. Rocha
and H. Freitas for providing rainfall data (FAPESP 08/58120-3).
Special thanks go to A. Downey and A. Arias, from ICT International
Pty Ltd, and R. Belinello for the great technical support. The authors
were supported by grants from CNPq and the Biota-FAPESP Program
- Projeto Temático Gradiente Funcional (03/12595-7). COTEC/IF
41.065/2005 and IBAMA/CGEN 093/2005.
Conflict of interest SSOB has a commercial interest in the sap flow
sensors used in this study but declares that this did not influence any
decisions made in the course of this research. The other authors declare that they have no conflict of interest.
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