Blackwell Science, LtdOxford, UK
PCEPlant, Cell and Environment0016-8025Blackwell Science Ltd 2002
25
877
Wood respiration in tropical forests
P. Meir & J. Grace
10.1046/j.0016-8025.2002.00877.x
Original Article963973BEES SGML
Plant, Cell and Environment (2002) 25, 963–973
Scaling relationships for woody tissue respiration in two
tropical rain forests
P. MEIR & J. GRACE
Institute of Ecology and Resource Management, University of Edinburgh, Darwin Building, Kings Buildings, Mayfield Road,
Edinburgh EH9 3JU, UK
ABSTRACT
The relationship between gross primary productivity
(GPP) and net primary productivity (NPP) is not fully
understood. One of the uncertainties relevant to this issue is
the magnitude of woody tissue respiration. Although some
data exist for temperate and boreal zones, measurements of
woody tissue respiration in tropical forests are sparse. We
made in situ chamber measurements of woody tissue respiration in two tropical rain forests, one in the Brazilian
Amazon (Reserva Jarú) and one in Central Cameroon
(Mbalmayo Reserve). We made measurements on a wide
range of species at each site and over a range of stem diameters from 0·02 to 1·4 m. The rate of efflux of carbon dioxide
(CO2) from bark at 25 °C, Rt, varied from 0·1 to 5·2
µmol m−2 s−1 across the two sites, and the efflux was related
to both volume and surface area components of the measured stem sections. The temperature response in Rt was
slightly higher at Jarú than at Mbalmayo, with Q10 values of
± 0·1 SE) and 1·6 (± 0·1 SE), respectively. A log–log
1·8 (±
regression showed that Rt was significantly related to stem
diameter, D (P < 0·001; r2 = 0·58–0·62) and was significantly
higher at Mbalmayo than at Jarú (P < 0·001), but that the
rate of increase in Rt with stem diameter, D, was similar
between sites. At the Mbalmayo site, tree growth measurements made over a 4 month period were used to make two
estimates of the maintenance (Rm) and construction (Rc)
components of respiration embedded in Rt. The two methods agreed closely, suggesting that Rm was approximately
80% of Rc at this site. Rm could be strongly related to D
using a sigmoidal relationship that described both surface
area and volume components as sources of respiratory CO2
(r2 = 0·71). This functional model was combined with inventory, growth and climate data for the Mbalmayo site to
make a first estimate of annual above-ground woody tissue
respiration, RA, which was 257 (± 18 SE) g C m−2 year−1.
This value corresponds to approximately 10% of GPP,
slightly lower than that found for another tropical rain forest, but higher than for temperate forests. When combined
with data from six other sites in tropical, temperate and
boreal settings, a very strong relationship was found
Correspondence: Patrick Meir. Fax: + 44 (0)131 6620478;
e-mail: [email protected]
© 2002 Blackwell Science Ltd
between RA and leaf area index (LAI), and between RA/
GPP and LAI (P < 0·001, r2 = 0·98). This indicates that RA
exerts an appreciable constraint on NPP and that this constraint varies closely with LAI across widely differing types
of woody vegetation.
Key-words: Brazil; Cameroon; leaf area index; rain forest;
scaling; temperature response; woody tissue respiration.
INTRODUCTION
Net primary productivity (NPP) is determined by the difference between gross primary productivity (GPP) and
autotrophic respiration, the respiration of plants. However,
autotrophic respiration is difficult to estimate so its relationship with GPP is sometimes assumed in forest stand
growth models (e.g. Battaglia & Sands 1997; Landsberg &
Waring 1997). Some reports suggest that the ratio of NPP to
GPP is constant and close to 0·5, although data clearly supporting this are lacking (Waring, Landsberg & Williams
1998; Medlyn & Dewar 1999), and it has been argued elsewhere that this value varies instead from 0·5 to 0·7 among
stands (Amthor & Baldocchi 2001) or with age (Mäkelä &
Valentine 2001). Autotrophic respiration includes belowground and above-ground components, the latter comprising leaf and woody tissue. The last of these, the respiratory
flux from woody tissue, is relatively under-studied (Sprugel
& Benecke 1991) even though it varies significantly among
stands (Lavigne, Franklin & Hunt 1996; Ryan, Lavigne &
Gower 1997) and with temperature (Ryan 1991). Aboveground woody tissue respiration (RA) has been estimated to
be 6–13% of GPP (e.g. Lavigne, Ryan & Anderson 1997;
Law, Ryan & Anthoni 1999); there are very few data available for tropical forests although the upper limit of this
range has been reported (Ryan et al. 1994; Malhi, Baldocchi
& Jarvis 1999).
Respiration rates in tropical forests have traditionally
been considered to be large because of the higher temperatures at low latitudes (Yoda 1967; Yoda 1978; Whitmore
1984), but early measurements were made on excised sections of woody tissue which could have yielded inflated respiration rates through the effects of wound respiration.
More recent studies (e.g. Ryan 1990; Sprugel 1990) have
emphasized the utility of in situ chamber measurements.
963
964 P. Meir & J. Grace
The calculation of annual respiration totals has been facilitated by the separation of the costs resulting from the
growth of new cells from those resulting from the maintenance of existing cells, a distinction embodied in the ‘functional model’ (McCree 1970; Thornley 1970). Respiration
associated with the construction of cells can be calculated
from the mass and composition of newly produced tissue
(Penning de Vries 1975, Williams et al. 1987), whereas that
associated with maintenance is related to the mass and
activity of live cells. The exact distinction between the two
can be difficult to define (Sprugel & Benecke 1991; Thornley & Cannell 2000) but the model continues to provide a
useful analytical framework.
The choice of scalar from which stand-scale estimates of
woody tissue respiration are derived varies among studies.
Sapwood volume has been successfully related to respiration rate in some temperate and boreal forests where
detailed information is available (Lavigne et al. 1997; Law
et al. 1999). This has also been done for one humid tropical
forest, although measurements were made on only two species at this site, where maintenance costs for sapwood were
calculated to be 54 or 82% of total respiration (Ryan et al.
1994). However, sapwood volume has not always been
identified as the best correlate for respiration; other scalars,
such as nitrogen concentration, total tree size, and stem surface area, have proved equally or more successful (Lavigne
et al. 1996; Yokota & Hagihara 1998; Levy & Jarvis 1998).
At tree and stand scales, the requirement for respiratory
support tissue increases with leaf area, but biomechanical
and carbon gain trade-offs are associated with each marginal increase in leaf area, and it is not clear if this leads to
stand-specific or more general expressions of respiratory
cost (Givnish 1995). In species-diverse tropical forests,
where sapwood volume is very poorly known because of
interspecific variation, estimates of stem respiration based
on relatively simple measures of stem size may be appropriate. However, information on the variability in respiration rates amongst individuals is needed before we can
establish and evaluate any general relationship.
In this study we made measurements in two tropical rain
forest reserves, one in Cameroon and one in Brazil, in order
to identify factors governing woody tissue respiration at
these sites. We asked the following questions:
potential for a general relationship linking physical stand
properties and above-ground woody tissue respiration.
1 What is the response of woody tissue respiration to temperature; does this differ between sites?
2 Using simple measures of stem size can we account for
the variation in respiration rate among individuals, species and sites?
3 What proportions of total respiration are used for growth
and maintenance processes?
4 Can the functional model be used to make estimates of
total woody tissue respiration in the absence of detailed
measurements of sapwood volume?
forest) and Mbalmayo Reserve, Cameroon (secondary forest)
We then used inventory, growth and climate data at one site
to make a first estimate of above-ground woody tissue respiration, and compared this with estimates from other temperate, boreal and tropical sites in order evaluate the
METHODS
Sites
The site characteristics for each forest are given elsewhere
(Meir, Grace & Miranda 2001), and summarized in Table 1.
The first site was at Jarú Biological Reserve, Rondônia
State, SW Brazil (10°05′ S, 61°55′ W) and is referred to here
as ‘Jarú’. The forest is classed as undisturbed ‘open forest’
grading to ‘dense forest’ in places (IBGE 1993). The second
site was at the Mbalmayo Reserve, Central Province of
Cameroon (3°23′ N, 11°30′ W) and is referred to here as
‘Mbalmayo’. This is a secondary deciduous forest that was
selectively logged in 1988 (Lawson 1995). The forests are of
similar height (30–40 m) with Mbalmayo having a slightly
higher leaf area index (4·4 versus 4·0 m2 m−2). The soil at
Mbalmayo is a deep red or yellow oxisol (Ngeh 1989), with
a sandy clay surface layer, and at Jarú it is a red or yellow
orthic acrisol with a sandy surface layer (Hodnett, Oyama
& Tomasella 1996). Concentrations of nitrogen and organic
carbon in the surface soil layer are higher at Mbalmayo
(0·16 and 1·83%, respectively) than at Jarú (0·10 and
1·18%) (Meir et al. 2001). Rainfall is slightly lower at Mbalmayo (Table 1), with a bimodal annual rainfall distribution,
yielding wet season peaks in May and October, whereas
only one wet season is experienced at Jarú, from December
to March. Mean monthly temperatures at both sites vary little over the year, between 23 and 26 °C (Ngeh 1989; Culf et
al. 1996).
Gas exchange and stem growth measurements
Gas exchange measurements were made on trees at both
sites, but tree growth measurements were only made at
Mbalmayo. Sampling was designed to balance the needs to
account for a large number of species and range of stem
sizes, and as large a number of replicates as was logistically
Table 1. Site characteristics for Reserva Jarú, Brazil (undisturbed
Dominant tree families
Mean canopy height (m)
Leaf area index (m2 m−2)
Rainfall (mm year−1)
Above-ground biomass
(kg m−2)
Jarú, Brazil
Mbalmayo,
Cameroon
Moraceae,
Leguminoseae,
Palmeae
35a
4·0a
1900c
22·0a
Sterculiaceae,
Ulmaceae,
Leguminoseae
36a
4·4a
1520b
8·7 (0·47)a
Sources for data marked as superscripts: aMeir (1996) bNgeh, 1989,
Culf et, al., 1996). Error in biomass estimate is SE, obtained from
a 2 ha sample.
c
© 2002 Blackwell Science Ltd, Plant, Cell and Environment, 25, 963–973
Wood respiration in tropical forests 965
possible. A total of 101 measurements were made on the
stems of 23 species at Jarú and 15 species at Mbalmayo. The
range in stem diameter, D, was from 0·02 to 1·4 m; both pioneer- and climax-stage species were included (Table 2). At
Mbalmayo growth bands were attached to each of 38 trees
immediately above the point where the CO2 efflux chamber
was fixed. Girth measurements (resolution = 0·1 mm) were
made at monthly intervals from February to May 1994, at
0830–0930 h on each occasion.
Measurements of CO2 efflux from woody tissue were
made from trees in Jarú, from May to June 1993, and in
Mbalmayo, from February to May 1994. Although the rate
of CO2 efflux from bark can occasionally be slightly
affected by the CO2 concentration in sap (Levy et al. 1999),
we treated our efflux rates as measures of woody tissue respiration. Measurements were made by attaching a chamber
to the stem of a tree and connecting it to an infra-red gas
analyser (IRGA). Chambers were constructed out of transparent acrylic plastic, and sealed to the bark using neoprene
gaskets; for narrow stems a split-cylinder design was used to
envelop the stem. For these chambers adequate mixing of
air was achieved by minimizing chamber volume and placing inlet and outlet nozzles on opposite sides of the measured wood section. For the larger chambers, which were
sealed against the stem, a small fan was inserted into the
back wall to provide gentle mixing. The smaller chambers
were 10–15 cm in length and 100–250 cm3 in volume
whereas the larger chambers covered a bark area 15 cm ×
6 cm, and including the fan, were 400–500 cm3 in volume. At
each site measurements were made under a closed canopy
with unshaded chambers, as a pilot experiment indicated a
change of less than 1% in efflux rate between unshaded and
shaded (black cloth) conditions at the measurement points.
The principal measurement method used was a closedpath analysis, where the chamber was connected in closed
circuit to an IRGA and CO2 efflux rates calculated from the
increase in CO2 concentration in the chamber (Licor 6200;
Licor Inc., Lincoln, NE, USA). In order to cancel possible
errors resulting from leaks, chamber CO2 concentration
was drawn down to a point below ambient levels (360–
450 µmol mol−1) and allowed to rise an approximately equal
amount above ambient (Hutchinson & Livingston 1993).
Measurements were made by logging data every 5 s for
60–120 s intervals. Bark surface temperature was measured
inside the chambers using a copper–constantan thermocouple. Means were taken of three consecutive measurements
made on each stem at the same location, and the diameter
of the woody section enclosed by the chamber recorded
(measurement resolution 0·1 mm). Measurements were
made on stems of 50 individuals at Jarú and 51 at Mbalmayo. Measurements were made on five or more individuals of four species at each site, and on one to three
individuals of other species (Table 2). At the Mbalmayo site
monthly measurements were made on a subsample of 20
trees from February to May in order to identify any seasonally related changes in CO2 efflux rates. Overnight measurements were made on six individuals at Jarú and five
individuals at Mbalmayo in order to characterize tempera© 2002 Blackwell Science Ltd, Plant, Cell and Environment, 25, 963–973
ture responses. The efflux rate of CO2, Ra, was calculated
using Eqn 1.
Ra = D[CO2 ]Vch A chVT ( mmol m -2 s -1 )
(1)
where ∆[CO2] is the change in concentration of CO2 in
chamber (µmol mol−1 s−1), Vch and Ach are the chamber volume (m3) and the enclosed leaf area (m2), respectively, and
VT is the volume (per mole) of a gas at ambient temperature and pressure.
A subsample of measurements was also made using an
open-path IRGA (LCA2; ADC, Hoddesdon, UK) at the
Mbalmayo site (Table 3) in order to obtain additional temperature response information on three of the five species
measured using the closed chamber system. The IRGA was
connected in series to a chamber and air was drawn in by a
mass-flow controlled air supply unit (MASU; ADC) at 350–
500 mL min−1. Before entering the cuvette, ambient air was
passed through a 2 L buffer chamber; and before entry into
the optical bench of the analyser it was passed through a
column of silica gel to remove cross-sensitivity to water
vapour in this instrument. Bark surface temperature inside
the chamber was measured using a copper–constantan
thermocouple, and all data were stored in a Campbell 21X
datalogger (Campbell Scientific, Leicester, UK) as 15 min
averages of raw data measured at 1 Hz. Efflux rates of CO2
were calculated according to Eqn 2.
Ra = D[CO2 ] Fch Ach ( mmol m -2 s -1 )
(2)
where Fch is the molar flow rate through the chamber and
Ach is the area of bark enclosed by the chamber.
Data analysis
Temperature response
An exponential model was fitted to data from both closed
and open system measurements made on individual trees
(Eqn 3).
Ra = R0 e(kT )
(3)
where T is temperature (°C), k (°C−1) is a temperature coefficient of R, and R0 is the rate of efflux at T = 0 °C. The rate
at which a process increases for an increase in T of 10 °C is
termed the Q10, and is given by k(e10k). Measured respiration rates were normalized to 25 °C (Rt) using species-specific temperature responses, or where these were not
available, using the mean value for each site.
The relationship between CO2 efflux and stem size
The relative contribution to total CO2 efflux (Rt) from surface area (S) and volume (V) components of each stem section was examined using the method of Levy & Jarvis
(1998). If the efflux rate is related to stem surface area,
then, if re-expressed on a volumetric basis, we would
expect: Rt ∝ 1/D. Alternatively, if the efflux rate was dependent on stem volume, then, expressed on an area basis, we
would expect: Rt ∝ D. The empirical relationship at each
site between Rt and D was analysed further using a regres-
966 P. Meir & J. Grace
Table 2. Species sampled at (a) Jarú, Brazil and (b) Mbalmayo, Cameroon
(a) Jarú, Brazil
(b) Mbalmayo, Cameroon
Species
Family
D
Rt
Type
Species
Family
D
Rt
Type
Astronium lecointei Ducke
Xylopia sp.
Orbigynia speciosa
Licania sp.
Hironima sp.
Ocotea cf caudata (Nees.) Mez
Bertolettia excelsa
Sclerolobium sp.
Anacardiaceae
Annonaceae
Arecaceae
Chrysobalanaceae
Euphorbiaceae
Lauraceae
Lecythidaceae
Leguminoseae;
Caes
Meliaceae
0·04
0·05–0·11 [5]
0·26–0·30 [3]
0·35
0·03
0·14
1·44
0·04–0·29 [3]
0·050
0·29–1·24
0·55–0·79
1·22
0·17
0·29
3·18
0·12–1·82
2
1
1
2
0
2
2
1
Annonaceae
Asteraceae
Burseraceae
Combretaceae
Leguminoseae; Caes
Leguminoseae; Pap.
Icacinaceae
Irvingaceae
0·13–0·26 [2]
0·05
0·12
0·03–0·55 [2]
0·02–0·59 [8]
0·08
0·02
0·08–0·22 [2]
2·34–4·21
0·07
1·79
0·18–1·71
0·48–5·36
0·91
0·23
1·64–2·69
1
1
2
1
2
0
0
2
0·12–0·25 [2]
0·36–0·38
2
Irvingaceae
0·13
1·80
2
Meliaceae
Moraceae
Moraceae
Moraceae
Moraceae
0·18
0·07
0·04–0·65 [3]
0·05–0·08 [2]
0·02–0·10 [5]
0·42
0·46
0·22–1·45
0·23–0·47
0·21–0·44
2
1
1
2
2
Xylopia etiopica
Vernonia conferta
Santira trimera (Oliv.) Aubr.
Terminalia superba Engl. & Diels
Distemonanthus benthamianus Baill.
Ptercarpus soyauxii Taub.
Desmostachys tenuifolius
Desbordesia glaucescens (Engl.) Van
Tiegh.
Klainedoxa gabonensis Pierre ex Engl.
var oblongifolia
Musanga cecropoides R.Br.
Coelocaryon preussi Warburg
Lophira alata Banks ex Gaertn.f.
Panda oleosa Pierre
Triplochiton scleroxylon K. Schum.
Moraceae
Myristicaceae
Ochnaceae
Olacaceae
Sterculieaceae
0·02–0·51 [10]
0·05
0·09–0·34 [2]
0·53
0·05–0·55 [7]
0·39–3·33
0·80
0·96–4·55
2·73
1·01–3·84
1
0
1
2
1
Moraceae
Moraceae
Moraceae
0·12
0·15
0·24–0·40 [2]
0·71
0·43
0·32–1·15
2
2
0
Trema orientalis (Linn.) Bl.
Ulmaceae
0·04–0·19 [10]
0·77–3·96
1
Myristicaceae
Myristicaceae
Sterculiaceae
Sterculiaceae
Violaceae
0·06–0·12 [4]
0·03–0·40 [2]
0·02–0·57 [6]
0·17
0·15
0·08–0·44
0·16–1·00
0·28–1·16
0·25
0·21
2
2
0
0
2
Guarea kunthii A. juss.
© 2002 Blackwell Science Ltd, Plant, Cell and Environment, 25, 963–973
Trichilia quadrijuga H.B.K.
Cecropia ficilifolia Snethl.
Cecropia sciadophylla Mart.
Naucleopsis glabra Spr. ex Baill.
Naucleopsis krunnii (Standl.) C.C.
Berg
Pseudomeldia sp.
Sorocea guilleminiana Grand.
Trymatococcus amazonicus Poepp
et Endl.
Virola calophylla Warb.
Virola michelii Hackel
Sterculia pruriens (Aubl.) Schum
Theobroma microcarpum Mart.
Rinorea pubiflora (Benth.) Spreng.
Rt rate of CO2 efflux (µmol m−2 s−1), corrected to 25 °C; mean of three measurements per stem. D is diameter of measured stem sections; where more than one individual is measured, the range
in D is given and number of individuals specified in parentheses (individual tree data in Fig. 2). ‘Type’ describes ecological class of each species: 1 denotes pioneer, 2 denotes shade-tolerant
and/or climax, and 0 denotes unknown ecology (D. Edwards, J. Ratter & T. Pennington, personal comms)
Wood respiration in tropical forests 967
Table 3. Temperature responses for woody tissue CO2 efflux at
Jarú and Mbalmayo.
Species
Jarú
N. krunnii
Pseudomeldia sp.
T. microcarpum
V. michelii
N. krunnii
Mean
Mbalmayo
M. cecropioides
X. etiopica
T. orientalis
V. conferta
D. benthamianus
Mean
D
Ro
k
Q10
r2
0·04
0·1
0·02
0·04
0·05
0·03
0·06
0·05
0·27
0·08
0·09
0·07
0·06
0·06
0·04
0·06 (0·01)
2·38
2·07
1·80
1·75
1·49
1·90 (0·12)
0·90
0·84
0·89
0·71
0·78
0·04
0·06
0·05
0·06
0·05
0·05 (0·01)
1·54 (1·46)
1·45
1·57 (1·53)
1·82
1·57 (1·59)
1·65 (0·06)
0·93
0·85
0·68
0·75
0·91
0·34
0·25
0·14
0·05
0·23
1·17
0·41
0·41
0·22
0·96
Q10 is the multiple by which the efflux rate (µmol m−2 s−1) increases
in response to a 10 °C increase in temperature, obtained by fitting
Eqn 3. For Mbalmayo, open-path measurements of three species
(*) gave very similar Q10 values (specified in brackets). Mean (±
SE) values are of the fitted values for all species; r2 values are for
fits to Eqn 3 of the closed chamber measurements; D is the
diameter of each measured stem section (m)
sion of ln Rt on ln D. After estimating maintenance respiration, Rm, from measurements of total and construction
respiration at the Mbalmayo site (see below), the overall
relationship between Rm and D was modelled as a sigmoidal curve (Eqn 4) representing the contributions from S
and V components of each stem to the total respiration rate
over the measured range in D.
Rm = a [1 + exp([D - c] b)]
new woody tissue and experimental determinations show
good agreement (0·46, Sprugel & Benecke 1991 and 0·47,
Ledig, Drew & Clark 1976). Taking the mean value of these,
and converting to grams of carbon expended per gram of
carbon in newly constructed wood yields a value of 0·248 g
g−1. This was used to calculate Rc based on stem growth
measurements, expressed on an area basis for each tree,
and was subtracted from Rt to give Rm, the maintenance respiration rate.
M2. Initial stem diameters and growth measurements
were used to obtain relative growth rates (RGR, m−1) of
each tree. Using the proportional differences between measured and modelled Rt, the empirical regression between
the natural logarithms of D and Rt was used to normalize Rt
for each tree to the mean diameter of all trees for which
growth rate had been measured. This efflux rate, Rtd, was
then plotted against RGR, and the regression between
them extended back to the ordinate (RGR = 0) in order to
determine the mean Rtd at zero growth, assumed to represent the mean maintenance respiration rate, Rm0. The mean
Rc across all trees, Rcm, was then calculated as the difference
between the mean value for Rtd and Rm0.
RESULTS
Variation in CO2 efflux with respect to
temperature and stem diameter
A strong response in CO2 efflux to temperature was found
at each site using both open and closed measurement systems (Fig. 1); measurements made on the same areas of
(4)
where a, b and c are fitted parameters in the model.
Separating maintenance and construction respiration
Since stem growth measurements were needed to separate
construction and maintenance costs, this analysis was
restricted to the Mbalmayo dataset. Temperature-corrected
efflux rates were assumed to represent ‘total’ respiration
(Rt), the sum of maintenance respiration, Rm, and construction respiration, Rc. Calculations of Rc and Rm were then
obtained from the growth and respiration data, using two
methods, M1 and M2.
M1. The increase in wood volume under the chamber was
calculated from growth measurements and the specific
gravity of each species (Reyes, Brown & Lugo 1992) was
then used to obtain the mass of new wood. Where specific
gravity data were unavailable (three species), a value of
0·5 g cm−3 was assumed. The amount of carbon per gram of
dry wood was assumed to be 50% of the ash-free dry weight
(Edwards et al. 1980; Matthews 1993) and ash-free dry
weight was taken to be 99·3% of dry weight (Ryan et al.
1994). Penning de Vries (1975) estimated a minimum metabolic construction requirement of 0·43 g CO2 per gram of
© 2002 Blackwell Science Ltd, Plant, Cell and Environment, 25, 963–973
Figure 1. The relationship between temperature and rate of CO2
efflux from woody tissue in four species (Db** and Mc** from
Mbalmayo; Nk* and Vm* from Jarú). Species identity is given by
the letters Xx which represent, respectively, the first letter of the
genus and species of each individual (full names provided in Table
2); * denotes closed- and ** denotes open-path measurement
system.
968 P. Meir & J. Grace
Figure 2. Relationships at Mbalmayo
and Jarú between rate of CO2 efflux
from woody tissue (respiration, Rt) and
stem section diameter (D). (a) variation
in respiration rate (on area basis) and
D; (b) variation in respiration rate (on
volumetric basis) and 1/D.
bark of individual trees using both systems gave similar respiration rates (paired t-test, P = 0·43, n = 8). The temperature coefficient, k (Eqn 3), varied from 0·040 to 0·087 in
Brazil and from 0·037 to 0·060 in Cameroon, with the means
for each site yielding similar Q10 values (1·8 ± 0·1 SE and 1·6
± 0·1 SE, respectively; Table 3). Bark surface temperatures
ranged from 18 to 30 °C during the diurnal cycle, with mean
daily values during measurements of 24·2 °C (Jarú) and
26·5 °C (Mblamayo), close to the reference temperature of
25 °C at which respiration rates were compared.
The value of Rt at Jarú was between 0·1 and 3·3 µmol
m−2 s−1, measured on woody sections of diameter (D) =
0·02–1·4 m (Table 2). At Mbalmayo, Rt was higher, between
0·2 and 5·2 µmol m−2 s−1, measured from woody sections of
D = 0·02–0·6 m. Measurements made at different points
around the circumference of woody stems where D was
large showed that radial variation in Rt at constant D was
very slight. Tests for the source of CO2 indicated that the
efflux rate was proportional to both woody tissue volume
(V) and bark surface area (A). Figure 2a & b suggest that
the contribution from A was more important at low D and
that from V was more important at high D. This pattern was
also observed for individual species (data not shown).
However, logarithmic transformation of the data produced
strong linear relationships between D and Rt at both sites
(P < 0·001, n = 50, Jarú, P < 0·001, n = 51, Mbalmayo; Fig. 3a
& b). There was little interspecies variation in this relationship, with non-significant differences found between regres-
Figure 3. Log–log relationships at
Mbalmayo and Jarú between CO2
efflux rate from woody tissue
corrected to 25 °C (Rt), and stem
section diameter (D), including SE
errors. Open symbols are Mbalmayo;
closed symbols are Jarú. Data for four
different species at each site are
shown by: M-Xx or J-Xx, where M
and J denote the sites Mbalmayo and
Jarú, respectively, and the letters Xx
are, respectively, the first letter of the
genus and species of each species (full
names provided in Table 2). At each
site, where the sample size for a
species is less than three, the data
have been pooled and denoted M-Spp
and J-Spp, respectively.
© 2002 Blackwell Science Ltd, Plant, Cell and Environment, 25, 963–973
Wood respiration in tropical forests 969
Table 4. Estimate of the contribution (%) to total respiration (Rt)
by maintenance respiration at Mbalmayo Reserve
Calculation method
Maintenance respiration
as percentage of Rt
n
M1
M2
80 (4)
85 (7)
51
38
Maintenance respiration is calculated by two methods (M1 and
M2, see Methods), using growth measurements on individual trees:
M1 yields estimates for individual trees (Rm) and M2 gives an
estimate of average maintenance respiration across all individuals
(Rm0). n = number of trees in each estimate; uncertainties are ± SE
obtained from the mean value of Rm in M1 and the regression fit in
M2 (Fig. 4).
sions for individual species, and between individual species
and the pooled data set (P > 0·1 for all tests, Fig. 3a & b).
The slopes of the regressions for the overall data sets from
each site (Fig. 3, Table 2) were almost identical, but the
intercept was significantly higher (P < 0·01) at Mbalmayo,
reflecting the higher Rt values there.
Maintenance and construction respiration
Growth measurements were obtained for 38 trees at Mbalmayo. Maintenance respiration, calculated using M1, was
80% of Rt across all individuals (sample mean), with construction respiration (Rc) varying among individuals by up
to 53% of Rt. The cross-species value for maintenance respiration (Rm0), calculated using M2, was very similar, 85%
of Rtd (Table 4, Fig. 4). The fit of Eqn 4 to variation in Rm
with D was highly significant (P < 0·001, r2 = 0·71; Fig. 5),
indicating that for this site, mean Rt could be estimated well
Figure 4. Relationship between normalized CO2 efflux rate (Rtd)
and relative growth rate (RGR) at Mbalmayo. RGR is calculated
from measurements of changes in D over 4 months (February to
May); Rtd is normalized by diameter, as described in Methods.
© 2002 Blackwell Science Ltd, Plant, Cell and Environment, 25, 963–973
by combining estimates of Rm from Eqn 4 and calculations
of Rc from growth measurements.
DISCUSSION
The temperature response of woody tissue respiration
tends to have a Q10 between 1·5 and 2·5 (Ryan 1991),
although results for tropical species have spanned a smaller
range (Q10 = 1·6–2·2; Ryan et al. 1994; Levy & Jarvis 1998).
Our data fall within this range: the Q10 for Jarú was not significantly different from 2·0, with that for Mblamayo
slightly lower. Hagihara & Hozumi (1991) note that Q10 values for woody tissue respiration tend to decline slightly
above 25 °C, as found here for Mbalmayo. The Q10 values of
woody tissue respiration clearly do not vary widely, consistent with the assumption that the underlying biochemical
processes are similar. Differences in measured efflux rates
from bark may be affected by changes in the CO2 concentration in sap, especially in the early morning (Levy et al.
1999), but our open system measurements did not suggest
that this process was significant in our study.
The overall range in Rt in both forest reserves (0·1–
5·2 µmol m−2 s−1) was also consistent with previous studies
(Ryan et al. 1994; Edwards & Hanson 1996; Lavigne et al.
1996), but Rt at Jarú was significantly lower than at Mbalmayo (Fig. 3). The same measurement system (closed) was
used at both sites, and the apparent sources of respiration
were also similar, including both surface area (principally
cambium and phloem cells) and volume (also including
xylem parenchyma cells) components (Fig. 2). This discrepancy in Rt between sites suggests a basic difference in metabolic activity. Significant differences in respiration rate
were not detected in relation to the ecological characteristics of the sampled species at either site (Table 2, Figs 3 &
5). However, because the lower biomass in the secondary
forest at Mbalmayo supported a similar leaf area index
(LAI) to that at Jarú (Table 1), it is possible that a relatively
higher respiration rate per stem was required at Mbalmayo
to maintain the necessary associated phloem and xylem tissues. The nitrogen concentration of the woody tissue samples was not measured, but the significantly higher levels of
leaf nitrogen reported for the Mbalmayo forest over that at
Jarú (Meir et al. 2001) imply that the higher Rt at Mbalmayo
also reflected a higher nitrogen concentration and hence
respiratory enzyme activity in the woody tissue (Lavigne
et al. 1996).
Respiration from woody stems has been found to scale
with both surface area (Levy & Jarvis 1998) and sapwood
volume (e.g. Ryan 1990; Law et al. 1999), and in some cases
equally well with both (Lavigne et al. 1996). In our data respiration scaled with volume and surface area components,
but was better represented by a log–log graph of Rt on D
(Fig. 3; r2 = 0·58–0·62). Although there was a significantly
larger intercept for the Mbalmayo data, the slope was very
similar at each site, and the fits did not differ significantly
among species or between species and the overall datasets
(Fig. 3). This similarity in the relative change in Rt with D
970 P. Meir & J. Grace
Figure 5. Variation in maintenance respiration
rate (Rm) and stem section diameter, D, at
Mbalmayo. Rm is calculated from growth
measurements of individual stems (see Methods,
M1). Species data are shown for four species and
the remaining pooled dataset; the legend follows
the coding used in Figure 3.
suggests that the rate of increase with stem size in the volume of physiologically active cells is quite well conserved in
tropical rain forests.
Since some of the variation in the relationship between
Rt and D may have resulted from unknown quantities of
respiration used for growth processes, we decomposed Rt
for Mbalmayo into maintenance (Rm) and construction
components (Rc), using stem growth measurements. The
two methods (M1 and M2) gave very similar mean estimates across all species and individuals, indicating that Rm
constitutes approximately 80% of Rt. This is in close agreement with Paembonan, Hagihara & Hozumi (1992) who
obtained 79% for Chamaecyparis obtusa, and with Ryan et
al. (1994) who obtained 84% for a slow-growing wet-forest
species in Costa Rica, Minquartia guianensis; but it is rather
higher than that for a faster growing tree, Simarouba amara
(54%) from the same study. The wide variation in Rm calculated using M1 (Rm = 47–100% of Rt) describes the range
of growth rates (Rc) encountered at Mbalmayo. Our mean
values derived from M1 and M2 are closer to that reported
by Ryan et al. (1994) for a slower-growing species and indicate that overall growth patterns were representative of a
closed mature forest dominated by slow-growing species,
even though both slow- and fast-growing species were considered in our sample (Table 2).
After removing Rc from Rt, D explained 71% of the variation in Rm using Eqn 4. In this relationship Rm is a multiple
of D where D = 0·05–0·30 m, but at D > 0·30 m Rm stops
increasing, implying that sapwood thickness (i.e. the respiratory activity of sapwood per unit surface area of bark) is
roughly constant for larger stems. Data for individual species also fitted this model, with the clearest pattern visible
for Musanga cecropioides (Fig. 4). Consistent with this,
examination of Rm using the analysis employed in Fig. 2,
indicated that at D < 0·30 m, Rm was proportional to surface
area, and at D > 0·30 m, Rm was proportional to volume
(data not shown). Equation 4 explains more of the variation
in respiration than the logarithmic model in Fig. 3, and predicts lower Rt at D > 0·6 m. Measurements on larger trees
are needed to distinguish between the two models, but we
hypothesize that Fig. 4 more accurately represents Rm for
this forest because it is based on a functional interpretation
of woody tissue respiration. Corresponding results
obtained by Ryan et al. (1994) indicated that variation in
sapwood thickness in a wet tropical forest in Costa Rica (5–
30 mm) was one-third of that found in temperate conifers,
implying that the increase in sapwood thickness with diameter tends to zero at relatively low D.
In order to make a first estimate of annual stand-scale
above-ground woody tissue respiration (RA) from our data
we calculated Rc and Rm separately [RA = Rc + Rm (g C
m−2 ground area year−1)]. To obtain Rc we assumed that
growth rates over the year remained similar to the values
measured during the study period; tree growth measurements by Ngeh (1989) for a nearby site support this
assumption. To calculate Rm using Eqn 4 we needed tree
height, basal area and monthly temperature data for the
site, for which we used annual temperature and tree-bytree inventory data from Ngeh (1989) and Meir (1996).
Using a cone form for tree boles, we estimate RA to be 214
(± 18 SE) g C m−2 year−1 (the standard error was calculated
from the asymptotic SE to the fit of Eqn 4 in Fig. 4 and the
uncertainty in the inventory data, Table 1). This value
excludes any estimate of respiration by branches. If scaled
by biomass, branch respiration is approximately 23% of
bole respiration (Deans, Moran & Grace 1996), although
this could represent a minimum value as cellular respiration rates in the canopy are sometimes higher than in
stems, as is the proportion of physiologically active cells
(Sprugel 1990). Including branch respiration, RA at Mbalmayo is 257 g C m−2 year−1, approximately 10% of GPP
(Meir 1996; Grace, Meir & Malhi 2001). This value,
although based on a simple up-scaling procedure, is higher
than the 6% estimated by Law et al. (1999) for a temperate
© 2002 Blackwell Science Ltd, Plant, Cell and Environment, 25, 963–973
Wood respiration in tropical forests 971
Figure 6. (a) Variation in above-ground woody tissue respiration (RA) with leaf area index (LAI). (b) Variation in RA as a percentage of
gross primary production (GPP) at seven sites in tropical (four sites), temperate (two sites) and boreal (one site) woody vegetation. The
datum for Mbalmayo is shown with uncertainty (± SE) in respiration based on uncertainties in parameter estimates to Eqn 4 and in biomass
from a 2 ha inventory (Deans et al. 1996; Meir 1996); GPP is obtained from eddy covariance, physiology measurements and a canopy model
(Meir 1996). GPP and RA for sites 3, 5 and 6 were obtained from eddy covariance measurements, measurements of leaf and woody tissue
activity and modelling of canopy physiology (Baldocchi & Harley 1995; Baldocchi 1997, Lavigne & Ryan 1997; Rayment 1998; Malhi et al.
1999; Rayment & Jarvis 2001); GPP and RA for site 2 was obtained from measurements of net primary productivity and net gas exchange for
foliage and woody tissue (Law et al. 1999); GPP for site 7 was obtained from measurements of biomass increment and woody tissue
respiration (Ryan et al. 1994). LAI and other site details are specified in the above references, except site 7, where LAI is estimated at
6·5 m2 m−2 (R. Chazdon, personal comm.). LAI and RA for site 1 are obtained from Levy & Jarvis (1998); GPP has not been estimated for
this site. LAI was indirectly measured at all sites [using hemispherical photography or an LAI 2000 sensor (Licor Inc.)], except site 5, where
the canopy was directly sampled; destructive LAI measurements made for sites 1 and 6 agree with indirect measurements (Levy & Jarvis
1999, Meir, Grace and Miranda 2001).
pine forest but lower than much earlier estimates for tropical forests (23–50%; Müller & Nielson 1965; Yoda 1967;
Whitmore 1984) made using data from excised woody sections. A more recent study of a wet tropical forest using in
situ measurements gives a similar value to ours (13%; Ryan
et al. 1994). The slightly lower annual respiration cost (i.e.
RA/GPP) found for Mbalmayo may reflect the lower biomass at this forest, but could also represent a more general
trend consistent with the lower LAI at this site. Combining
data from seven tropical, temperate and boreal sites,
including conifer and broadleaf stands, we find an expo© 2002 Blackwell Science Ltd, Plant, Cell and Environment, 25, 963–973
nential relationship between LAI (indirectly measured)
and RA (r2 = 0·85), and a strong linear relationship (r2 =
0·98) between LAI and RA expressed as a fraction of GPP
(Fig. 6a & b). The data describe a general pattern which is
consistent with the observed correlation between sapwood
area and leaf area in trees (Shinozaki et al. 1964; Mencuccini & Grace 1995). The relationship shows that the total
amount of respiratory activity required per unit of leaf area
depends strongly on LAI across a range of forests that
differ widely in ecology, growth form and latitude. The
increased marginal cost in RA associated with supporting a
972 P. Meir & J. Grace
marginal increase in LAI (Fig. 6b) also suggests that total
autotrophic respiration increases with GPP. This outcome
contradicts the hypothesis that the ratio of NPP to GPP is
constant for all forests (Waring et al. 1998; but see Medlyn
& Dewar 1998), although Mäkelä & Valentine (2001) also
argue that NPP/GPP may change during stand development. Indeed for NPP/GPP to be constant, Fig. 6b implies
that there should be a relative reduction in leaf and/or root
respiration with increasing LAI, despite the expected allometric increases in leaf and root biomass (Vanninen et al.
1996). Such reductions are not impossible, but measurements and further modelling are needed to determine
whether or not the increase in RA/GPP with LAI is also
reflected in other components of the autotrophic respiration budget.
CONCLUSION
Woody tissue respiration rates in Mbalmayo and Jarú are
similar to those found at other tropical and temperate sites
and have mean Q10 values ranging between 1·6 and 1·9. The
relative rate of increase in respiration with stem diameter is
almost identical between the two sites, but the higher absolute respiration rates at Mbalmayo, perhaps determined by
higher tissue nitrogen concentrations, indicate that measurements are necessary to characterize diameter–efflux
relationships at different sites. The proportion of total respiration, Rt, that is used for maintenance processes, Rm, varies upwards from 47%, with higher values for slowergrowing climax-stage species. The mean value for tropical
rain forests is probably close to the 80% thought to be representative of slower-growing species, as most large trees in
closed forests are climax-stage species. Stand-scale estimates of annual above-ground woody tissue respiration
(RA) can be made by calculating maintenance and construction respiration costs, but their accuracy is inevitably limited by our knowledge of the physiologically active woody
volume in the boles and branches of a canopy. Despite
these sources of uncertainty, estimates from a wide range of
forests show RA to represent 6–13% of gross primary productivity (GPP), and that this variability between sites in
RA and RA/GPP is strongly and positively related to leaf
area index.
ACKNOWLEDGMENTS
We are grateful to ABRACOS and TIGER for financial
and infrastructural support in Brazil and Cameroon.
ABRACOS was a collaboration between the Agência Brazileira de Cooperação and the UK Overseas Development
Administration; TIGER was the ‘Terrestrial Initiative for
Global Environment Research’ programme which was
funded by the UK NERC (grant no. GST/02/065). We
gratefully acknowledge the support and help of local collaborating institutions, including INCRA in Brazil and
ONADEF in Cameroon. We would also like to thank L.
Kruuk, L. Gormley, J. Gash, M. Mencuccini, and P. Levy for
providing comments on the manuscript and/or technical
support. We particularly thank R. Chazdon for generously
making available data on the leaf area index of the forest at
La Selva, Costa Rica.
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Received 14 November 2001; received in revised form 27 February
2002; accepted for publication 7 March 2002