Re-evaluation of forest biomass carbon stocks and
lessons from the world’s most carbon-dense forests
, Brendan G. Mackey, and David B. Lindenmayer
The Fenner School of Environment and Society, Australian National University, Canberra, ACT 0200, Australia
Communicated by Gene E. Likens, Cary Institute of Ecosystem Studies, Millbrook, NY, March 9, 2009 (received for review July 14, 2008)
From analysis of published global site biomass data (nⴝ136) from
primary forests, we discovered (i) the world’s highest known total
biomass carbon density (living plus dead) of 1,867 tonnes carbon per
ha (average value from 13 sites) occurs in Australian temperate moist
Eucalyptus regnans forests, and (ii) average values of the global site
biomass data were higher for sampled temperate moist forests (nⴝ
44) than for sampled tropical (nⴝ36) and boreal (nⴝ52) forests (n
is number of sites per forest biome). Spatially averaged Intergovern-
mental Panel on Climate Change biome default values are lower than
our average site values for temperate moist forests, because the
temperate biome contains a diversity of forest ecosystem types that
support a range of mature carbon stocks or have a long land-use
history with reduced carbon stocks. We describe a framework for
identifying forests important for carbon storage based on the factors
that account for high biomass carbon densities, including (i) relatively
cool temperatures and moderately high precipitation producing rates
of fast growth but slow decomposition, and (ii) older forests that are
often multiaged and multilayered and have experienced minimal
human disturbance. Our results are relevant to negotiations under
the United Nations Framework Convention on Climate Change re-
garding forest conservation, management, and restoration. Conserv-
ing forests with large stocks of biomass from deforestation and
degradation avoids signiﬁcant carbon emissions to the atmosphere,
irrespective of the source country, and should be among allowable
mitigation activities. Similarly, management that allows restoration of a
forest’s carbon sequestration potential also should be recognized.
Eucalyptus regnans 兩climate mitigation 兩primary forest 兩
deforestation and degradation 兩temperate moist forest biome
Deforestation currently accounts for ⬇18% of global carbon
emissions and is the third largest source of emissions (1).
Reducing emissions from deforestation and degradation (REDD)
is now recognized as a critical component of climate change
mitigation (2). A good understanding of the carbon dynamics of
forests (3) is therefore important, particularly about how carbon
stocks vary in relation to environmental conditions and human
land-use activities. Average values of biomass carbon densities for
the major forest biomes (4) are used as inputs to climate-carbon
models, estimating regional and national carbon accounts, and
informing policy debates (5). However, for many purposes it is
important to know the spatial distribution of biomass carbon within
biomes (6) and the effects of human land-use activities on forest
condition and resulting carbon stocks (refs. 3 and 7 and www-
Primarily because of Kyoto Protocol rules (ref. 8; http://
unfccc.int/resource/docs/convkp/kpeng.pdf), interest in carbon ac-
counting has been focused on modified natural forests and plan-
tation forests. It has been argued that primary forests, especially
very old forests, are unimportant in addressing the climate change
problem because (i) their carbon exchange is at equilibrium (9, 10),
(ii) carbon offset investments focus on planting young trees as their
rapid growth provides a higher sink capacity than old trees, and/or
(iii) coverage and hence importance of modified forest is increasing.
Recent research findings have countered the first argument for all
3 major forest biomes (namely, tropical, temperate, and boreal
forests) and demonstrated that old-growth forests are likely to be
functioning as carbon sinks (11–13). The long time it takes new
plantings to sequester and store the amount of carbon equivalent to
that stored in mature forests counters the second argument (14).
The third argument about the unimportance of old forest in
addressing climate change relates, in part, to the diminishing extent
of primary forest caused by land-use activities (15) and associated
depletion of biomass carbon stocks (16). However, significant areas
of primary forest remain (17), and depleted carbon stocks in
modified forests can be restored.
It is useful to distinguish between the carbon carrying capacity of
a forest ecosystem and its current carbon stock. Carbon carrying
capacity is the mass of carbon able to be stored in a forest ecosystem
under prevailing environmental conditions and natural disturbance
regimes, but excluding anthropogenic disturbance (18). It is a
landscape-wide metric that provides a baseline against which cur-
rent carbon stocks (that include anthropogenic disturbance) can be
compared. The difference between carbon carrying capacity and
current carbon stock allows an estimate of the carbon sequestration
potential of an ecosystem and quantifies the amount of carbon lost
as a result of past land-use activities.
This study re-evaluates the biomass carbon densities of the
world’s major forest biomes based on a global synthesis of site data
of biomass measurements in forest plots from publicly available
peer-reviewed articles and other reputable publications. Site data
were selected that (i) provided appropriate measurements of
biomass and (ii) sampled largely mature and older forests to provide
an estimate of carbon carrying capacity. The most reliable nonde-
structive source of biomass carbon data are from field measure-
ments of tree and dead biomass structure at sites that sample a given
forest type and condition. These structural measurements are
converted to biomass carbon densities by using allometric equa-
tions. Standard national forestry inventories contain site data but
they are not always publicly available and their suitability for
estimating carbon stocks at national and biome-levels has been
questioned (5, 6).
We identify those forests with the highest biomass carbon
densities and consider the underlying environmental c onditions and
ecosystem functions that result in high carbon accumulation. These
results (i) provide a predictive framework for identifying forests
with high biomass carbon stocks, (ii) help clarify interpretation of
average forest biome values such as those published by the Inter-
governmental Panel on Climate Change (IPCC), and (iii) inform
policies about the role of forests in climate change mitigation.
Forests Have the World’s
Highest Biomass Carbon Density
Evergreen temperate forest dominated by E. regnans (F. Muell.)
(Mountain Ash) in the moist temperate region of the Central
Author contributions: H.K., B.G.M., and D.B.L. designed research; H.K., B.G.M., and D.B.L.
performed research; H.K. analyzed data; and H.K., B.G.M., and D.B.L. wrote the paper.
The authors declare no conﬂict of interest.
Freely available online through the PNAS open access option.
1To whom correspondence should be addressed. E-mail: email@example.com.
This article contains supporting information online at www.pnas.org/cgi/content/full/
July 14, 2009
Highlands of Victoria, southeastern Australia has the highest
known biomass carbon density in the world. We found that E.
regnans forest in the O’Shannassy Catchment of the Central High-
lands (53 sites within a 13,000-ha catchment) contains an average
of 1,053 tonnes carbon (tC)䡠ha
in living above-ground biomass
and 1,867 tC䡠ha
in living plus dead total biomass in stands with
cohorts of trees ⬎100 years old sampled at 13 sites. We examined
this catchment in detail because it had been subject to minimal
human disturbance, either by Indigenous people or from post-
European settlement land use. We compared the biomass carbon
density of the E. regnans forest with other forest sites globally by
using the collated site data (Table S1). No other records of forests
have values as high as those we found for E. regnans.
Our field measurements and calculations revealed that maximum
biomass carbon density for a E. regnans-dominated site was 1,819
in living above-ground biomass and 2,844 tC䡠ha
biomass from stands with a well-defined structure of overstory and
midstory trees (see Fig. 1) consisting of multiple age cohorts with
the oldest ⬇250⫹years (19). There was substantial spatial vari-
ability in total biomass carbon density across the sites in the
catchment within an ecologically mature forest type, ranging from
262 to 2,844 tC䡠ha
. Unexpectedly, we found the highest values
were from areas experiencing past partial stand-replacing natural
In February 2009, extensive areas of the O’Shannassy Catchment
and elsewhere in the Central Highlands of Victoria were burned in
a major conf lagration. We will be undertaking a major sur vey of the
network of permanent field sites in the catchment (20) to assess
changes in postfire carbon stocks. It will be important that these
sites are not subject to postfire salvage logging over the coming
years to prevent the extensive removal of dead biomass carbon (21).
Some Temperate Moist Forest Types Can Have Higher Biomass
Carbon Density Than Both Boreal and Tropical Forests
Average values of the collated global site biomass data from largely
mature or primary forests were much higher for the sampled
temperate moist forests (n⫽44) than they were for the sampled
tropical (n⫽36) and boreal (n⫽52) forests, where nis the number
of sites in each forest biome (Table S1) (Fig. 2). The locations of the
global site biomass data are shown in Fig. S1. They do not represent
all forest types or environmental conditions within a given biome
(reflecting the difficulty of finding published field data) and there-
fore are insufficient to calculate biome spatial averages. We related
site values of above-ground living biomass carbon (tC䡠ha
total biomass carbon (tC䡠ha
) to temperature and precipitation
Fig. 3 shows that temperate moist forests occurring where
temperatures were cool and precipitation was moderately high had
the highest biomass carbon stocks. Temperate forests that had
particularly high biomass carbon density included those dominated
by Tsuga heterophylla,Picea sitchensis,Pseudotsuga menziesii, and
Abies amabilis in the Pacific Northwest of North America [range in
living above-ground biomass of 224⫺587 tC䡠ha
and total biomass
of 568–794 tC䡠ha
(22–25)]. A synthesis of site data for the Pacific
Northwest gave an average for evergreen needle leaf forest of 334
(26), and this is used as the continental biome value by the
IPCC (4). An upper limit of biomass accumulation of 500 –700
in the Pacific Northwest of the United States has been
derived from an analysis of global forest data of carbon stocks and
net ecosystem productivity in relation to stand age (11, 27). In New
Zealand, the highest biomass carbon density reported is for Agathis
australis [range in living above-ground biomass of 364 –672 and tot al
biomass of 400–982 tC䡠ha
(28)]; and a synthesis based on forest
inventory data gave a mean of 180 tC䡠ha
with a range in means
for forest classes of 105–215 tC䡠ha
(29). In Chile, the highest
biomass carbon densities reported are for Nothofagus,Fitzroya,
Philgerodendron, and Laureliopsis [range in living above-ground
biomass 142–439 and total biomass of 326–571 tC ha
IPCC Tier-1 Biome Default Values
IPCC biome default values are shown in Table 1 alongside the
published global site biomass data (Table S1). The site data were
averaged for each biome but they are not equivalent to a spatial
average for each biome. The comparison helps identify biomes
where site averages differ significantly from default values. The
biome-averaged values of the global site biomass carbon data were
2.5–3 times higher than the IPCC biome default values for warm
and cool temperate moist forests (Table 1). The IPCC default
Fig. 1. E. regnans forest with midstory of Acacia and understory of tree ferns.
The person in the bottom left corner provides a scale.
Fig. 2. Global forest site data for above-ground biomass carbon (tC䡠ha⫺1)in
relation to latitude (north or south). Points are values for individual or average of
plots, and bars show the range in values at a site. The O’Shannassy Catchment has
a mean of 501 tC䡠ha⫺1and ranges from 104 to 1,819 tC䡠ha⫺1.The highest biomass
carbon occurs in the temperate latitudes.
www.pnas.org兾cgi兾doi兾10.1073兾pnas.0901970106 Keith et al.
values were ⬍1 SD from the averaged site values. Average site data
were comparable with IPCC default values for tropical and boreal
biomes. However, the IPCC biome default value for tropical moist
forest was marginally ⬍1 SD from the averaged site values. Also, the
site data for the boreal biome reflected higher above-ground living
biomass carbon values but lower below-ground plus dead biomass
carbon values compared with the IPCC default values (Table 1).
The differences between the collated global site biomass dat a and
IPCC biome default values for temperate moist forests reflect the
diversity of forest ecosystem types considered under the temperate
biome category. Biome default values likely under-represent South-
ern Hemisphere evergreen temperate moist forest types and do not
distinguish forest condition caused by land-use history (5). The
differences between site biomass data and IPCC default values for
boreal forests could reflect the effect of land-use history and fire on
carbon stocks at the site level.
Toward a Predictive Framework for High Biomass
We developed a framework for identifying forests with high bio-
mass carbon stocks based on an understanding of underlying
mechanisms and using the E. regnans forests as an example. The
factors in the framework include (i) environmental conditions, (ii)
life history and morphological characteristics of tree species, and
(iii) the impacts of natural disturbance such as fire and land-use
history. It is the interactions and feedbacks among these factors that
influence vegetation community dynamics and ultimately lead to
very high carbon densities.
Derivation of Carbon Stocks. Stock of carbon represents the net
exchange of carbon fluxes in an ecosystem (net ecosystem ex-
change). In living biomass, the carbon stock is determined by the
balance between the fluxes of carbon gain by photosynthetic
assimilation by the foliage [gross ecosystem production (GEP)] and
carbon loss by autotrophic respiration, which results in net primary
productivity (NPP). In the tot al ecosystem (living plus dead biomass
plus soil), the carbon stock is determined by the balance between
the fluxes of carbon gain by NPP and carbon loss by decomposition
of dead biomass and heterotrophic respiration. Ecosystem carbon
stocks vary because environmental conditions inf luence the carbon
fluxes of photosynthesis, decomposition, and autotrophic and het-
erotrophic respiration differently (34).
Environmental Conditions. The key climatic variables of precipita-
tion, temperature, and radiation are broadly correlated with veg-
etation structure and function (35, 36), although such empirical
correlations do not necessarily reveal underlying biochemical pro-
cesses or the dependence of these processes on environmental
factors (37). Climatic influences on photosynthesis include effects
of (i) irradiance and temperature on carboxylation rates, (ii)
temperature and soil water status on stomatal conductance and
thus diffusion of CO
from the atmosphere into the intercellular air
spaces, and (iii) temperature-dependent nitrogen uptake (37). The
climatic conditions and relatively fertile soils of the Central High-
lands of Victoria favor rapid growth of E. regnans (⬎1m䡠yr
the first 70 years), and these trees eventually become the world’s
tallest flowering plant (up to 130 m) (38).
Both dark respiration and maintenance respiration are temper-
ature dependent (37). Soil respiration is correlated with tempera-
ture and water availability, although substrate also has an important
influence (34). Rates of coarse woody biomass decomposition
have been found to decrease with lower temperatures in tem-
perate forests (39) and are also related to wood density, chemistry,
and size (40–42).
Climatic conditions that favor higher rates of GEP relative to
rates of respiration and decomposition should, other factors being
equal, lead to larger biomass carbon stocks. Table 2 gives the
average and range in climatic conditions (annual precipitation and
temperature) for the global site data from Table S1 and compares
estimates of GEP (34) and decomposition rates (k) (42). Estimates
of the climate conditions and derived variables are also shown for
E. regnans forests in the Central Highlands of Victoria. Temperate
forests are characterized by higher rates of GEP than boreal forests
but lower decomposition rates than tropical forests. There is
considerable variation evident in rates of carbon f luxes within each
forest biome, along with overlap between biomes.
Life History and Morphological Characteristics of Tree Species. E.
regnans can live for ⬇450 years, with stem diameters up to 6 m (38,
43). In our analysis, the stands of E. regnans with high values of
biomass carbon density were at least 100 years old. E. regnans wood
density is high (450–550 g䡠cm
) (44), so that biomass is greater for
a given volume. Limited crown development in E. regnans (through
crown shyness or reduced crown area caused by abrasion of growing
tips by neighboring crowns) and the isolateral leaf form of this
Fig. 3. Global forest site data for above-ground living biomass carbon (tC䡠ha⫺1)
(A) and total biomass carbon (tC䡠ha⫺1)(B), in relation to mean annual tempera-
ture and mean annual precipitation for the site. Site data are shown in relation
to their distribution among biomes of boreal (dark green), temperate (midg-
reen), and tropical (light green) forests. The highest biomass carbon density
occurs in cool, moderately wet climates in temperate moist forest biomes. Some
sites had values for above-ground living biomass carbon but not dead biomass, so
there was no value for total biomass carbon.
Keith et al. PNAS
July 14, 2009
species enable high levels of light to penetrate the forest floor,
allowing luxuriant understory layers to grow (45). Eucalypt foliage
is evergreen and minimum winter temperatures in the Central
Highlands are moderate, so E. regnans trees can grow all year.
Similarly, evergreen temperate forests of the Pacific Northwest of
North America with high biomass have been found to photosyn-
thesize throughout the year (46).
Natural Disturbance Such as Fire. Fire affects vegetation structure
and biomass carbon stocks at multiple spatial scales, such as the
landscape, stand, and individual tree levels. Fire can kill but not
combust all of the material in trees, leading to much of the biomass
carbon changing from the living biomass pool to the standing dead
and fallen dead biomass pools. The amount of carbon lost from the
forest floor and the soil profile may var y depending on ecosystem
type, fire regimes, and postdisturbance weather conditions (47).
The dead biomass then decays as the stand grows (48). Slow
decomposition rates can therefore result in large total carbon stocks
of dead biomass and regrowing liv ing biomass. A study of temperate
forests along a subalpine elevation gradient in the United States
estimated coarse woody debris turnover time to be 580 ⫾180 years
(39). Large amounts of coarse woody debris biomass are also
typical of old-growth forests of the Pacific Northwest of North
Unlike the majority of eucalypt species, E. regnans does not
regenerate by epicormic growth or sprouting from lignotubers after
a wildfire. Rather, a tree is killed if its canopy is c ompletely scorched
by fire. It then sheds seeds that germinate in the postfire ash-bed
conditions (49). In the Central Highlands of Victoria, wetter sites
on lower slopes and shaded aspects support longer fire intervals and
less intense fires, leading to a greater probability of multiaged
stands (50). Whether environmentally controlled or the result of
stochastic processes, past partial stand-replacing wildfires produce
younger cohorts of fast-growing E. regnans trees, mixed with an
older cohort of living and dead trees, together with rejuvenating the
understory of Acacia spp. and other tree species (Fig. 1).
Table 1. Average published site data (from Table S1) for biomass carbon (tC䡠ha
) of each forest biome (mean, standard deviation,
and number of sites) and default biomass carbon values (IPCC; refs. 4 and 66)
biomass carbon, tC䡠ha
Root ⫹dead biomass
Total living ⫹dead biomass
Tropical Tropical wet 171 (61) n⫽18 146 76 (72) n⫽7 67 231 (75) n⫽7 213
Tropical moist 179 (96) n⫽14 112 55 (66) n⫽5 30 248 (100) n⫽5 142
Tropical dry 70 n⫽17341n⫽1 32 111 n⫽1 105
Tropical montane 127 (8) n⫽3 71 52 (6) n⫽3 60 167 (17) n⫽3 112
Subtropical Warm temperate moist 294 (149) n⫽26 108 165 (75) n ⫽20 63 498 (200) n⫽20 171
Warm temperate dry 75 65 140
Warm temperate montane 69 63 132
Temperate Cool temperate moist 377 (182) n⫽18 155 265 (162) n⫽18 78 642 (294) n⫽18 233
Cool temperate dry 176 (102) n⫽3 59 102 (77) n⫽3 62 278 (173) n⫽3 121
Cool temperate montane 147 n⫽1 61 63 153 n⫽1 124
Boreal Boreal moist 64 (28) n⫽28 24 37 (16) n⫽14 75 97 (34) n⫽14 99
Boreal dry 59 (36) n⫽24 8 25 (12) n⫽9 52 84 (39) n⫽960
Boreal montane 21 55 76
The site data represent an average and variance of point values whereas the default values represent a spatial average. The site data have been taken from
mature and older forests with minimal human land use impact whereas the default values do not distinguish between natural undisturbed forest and
regenerating forest nor forest age (unless ⬍20 years). Domain and climate region classiﬁcation are according to Table 4.5 and deﬁned in Table 3A.5.2 (4).
*Default values are from the IPCC (4). Above-ground biomass from Table 4.7 (4) averaged across continents for each ecological zone. Carbon fraction in above-ground
biomass [Table 4.3 (4)].
†Default values are from the IPCC (4, 66). Litter carbon stocks [Table 3.2.1 (66)]. Ratio of below- to above-ground biomass [Table 4.4 (4)]. Dead wood stocks [Table
Table 2. Comparison of mean and range climatic conditions for boreal, temperate, and
tropical forest biomes based on the global site data (Table S1 and Fig. 3)
temperature, ° C
Boreal: mean ⫺0.6 581 822 0.01
Minimum ⫺10.0 213 382 0.01
Maximum 8.0 2,250 1,228 0.03
Temperate: mean 9.9 1,850 1,318 0.04
Minimum 1.5 404 923 0.02
Maximum 18.9 5,000 1,740 0.08
Tropical: mean 23.6 2,472 1,961 0.12
Minimum 7.2 800 1,190 0.03
Maximum 27.4 4,700 2,140 0.17
E. regnans: mean 11.1 1,280 1,374 0.04
Minimum 7.0 661 1,181 0.03
Maximum 14.4 1,886 1,529 0.06
Shown is the climatic proﬁle for E. regnans calculated by Lindenmayer et al. (65). GEP is estimated from a
regression correlation derived from ﬂux tower data as a function of mean annual temperature by Law et al. (34).
kis the decomposition rate constant of coarse woody debris calculated from an empirical relationship derived by
Chambers et al. (42) using forest biome characteristic temperatures.
www.pnas.org兾cgi兾doi兾10.1073兾pnas.0901970106 Keith et al.
Land-Use Activity. The final reason for high biomass carbon densities
in E. regnans forests is a prolonged absence of direct human
land-use activity. The O’Shannassy Catchment has been closed to
public access for ⬎100 years to provide water for the city of
Melbourne. It had an almost complete absence of Indigenous land
use before European settlement. Natural disturbances have in-
cluded wildfire, windstorms, and insect attacks. Logging has been
excluded, including postwildfire salvage logging that removes large
amounts of biomass in living and dead trees (thus preventing the
development of multiple age cohorts) (21, 51, 52).
Some types of temperate moist forests that have had limited
influence by human activities can be multiaged and do not neces-
sarily consist exclusively of old trees, but often have a complex
multiaged structure of multiple layers produced by regeneration
from natural disturbances and individual tree gaps in the canopy
(53). Net primary production in some types of multiaged old forests
has been found to be 50–100% higher than that modeled for an
even-aged stand (54). Both net primary production and net eco-
system production in many old forest stands have been found to be
positive; they were lower than the carbon fluxes in young and
mature stands, but not significantly different from them (55).
Northern Hemisphere forests up to 800 years old have been found
to still function as a carbon sink (11). Carbon stocks can continue
to accumulate in multiaged and mixed species stands because stem
respiration rates decrease with increasing tree size, and continual
turnover of leaves, roots, and woody material contribute to stable
components of soil organic matter (56). There is a growing body of
evidence that forest ecosystems do not necessarily reach an equi-
librium between assimilation and respiration, but can continue to
accumulate carbon in living biomass, c oarse woody debris, and soils,
and therefore may act as net carbon sinks for long periods (12,
57–59). Hence, process-based models of forest growth and carbon
cycling based on an assumption that stands are even-aged and
carbon exchange reaches an equilibrium may underestimate pro-
ductivity and carbon accumulation in some forest types.
Large carbon stocks can develop in a particular forest as a result
of a combination and interaction of environmental conditions, life
history attributes, morphological characteristics of tree species,
disturbance regimes, and land-use history. Very large stocks of
carbon occur in the multiaged and multilayered E. regnans forests
of the Central Highlands of Victoria. The same suite of factors listed
above operate, to varying degrees, across other evergreen temper-
ate forests, particularly in the northwestern United States, southern
South America, New Zealand, and elsewhere in southeastern
Australia. Collectively, they provide the basis of a generalized
framework for predicting high biomass carbon density forests.
However, construction of a quantitative predictive model inclusive
of all factors is complicated by a lack of process understanding (37),
knowledge of species life history characteristics and dynamics, and
many interactions and feedback effects (60).
Climate Change Policy Implications
Our results about the magnitude of carbon stocks in forests,
particularly in old forests that have had minimal human distur-
bance, are relevant to negotiations under the United Nations
Framework Convention on Climate Change (UNFCCC) concern-
ing reducing emissions from deforestation and forest degradation.
In particular, our findings can help inform discussions regarding the
roles of conservation, sustainable management of forests and
enhancement of forest carbon stocks (ref. 61; http://unfccc.int/
forests with large stocks of biomass from deforestation and degra-
dation avoids significant carbon emissions to the atmosphere,
irrespective of the source country, and should be among allowable
mitigation activities negotiated through the UNFCCC for the
post-2012 commitment period. Similarly, where practical, manage-
ment that allows restoration of a forest’s carbon sequestration
potential should be a recognized mitigation activity.
Our insights into forest types and forest conditions that result in
high biomass carbon density can be used to help identify priority
areas for conservation and restoration. The global synthesis of site
data (Fig. 3 and Table 2) indicated that the high carbon densities
of evergreen temperate forests in the northwestern United States,
southern South America, New Zealand, and southeastern Australia
should be recognized in forest biome classifications.
Our findings highlight the value of field-based site measurements in
characterizing forest carbon stocks. They help reveal the variability
within forest biomes and identify causal factors leading to high
carbon densities. Further analyses of existing site data from forests
around the world, along with new field surveys, are warranted to
improve understanding of the spatial distribution of biomass carbon
inclusive of land-use and fire history.
Forest. The 13,000-ha O’Shannassy Catchment (37.62° S,
145.79° E) has a mean annual rainfall of 1,670 mm, mean annual temperature of
9.4 °C, and annual radiation of 178 W䡠m⫺2. Average elevation of the catchment
is 830 m, and the area has a generally southerly aspect. Soils are deep red earths
overlying igneous felsic intrusive parent material. These are fertile soils with high
soil water-holding capacity and nutrient availability compared with most forest
soils in Australia. The vegetation is classiﬁed as tall eucalypt forest with small
pockets of rainforest. The forest is multilayered with an overstory of E. regnans,
a midstory tree layer of Acacia dealbata,A. frigiscens,Nothofagus cunninghamii,
and Pomaderis aspera, and a tall shrub layer that includes the tree ferns Cyathea
australis and Dicksonia antarctica.
Inventory sites were established by using a stratiﬁed random design to sample
the range in dominant age cohorts across the catchment. Stands were aged by a
combination of methods, including historical records of disturbance events, tree
diameter–age relationships, and cross-checking with dendrochronology. Ages of
understory plants ranged from to 100 to 370 years, as determined by radiocarbon
dating (62). Different components of the ecosystem survive and regenerate from
various previous disturbance events. All living and dead plants ⬎2 m in height and
⬎5 cm in diameter were measured at 318 10-m ⫻10-m plots nested within 53 sites
(each measuring 3 ha) within the catchment. Tree size ranged from 486-cm
diameter at breast height (DBH) to 84 m in height (Fig. 1).
Living and dead biomass carbon for each site were calculated by using an
allometric equation applied to the inventory data for the individual trees in the
plots. The equation related biomass to stem volume and wood density. A reduc-
tion factor was included in the equation to account for the reduction in stem
volume caused by asymmetric buttresses, based on measurements of stem cross-
sections and the area deﬁcit between the actual wood and the perimeter derived
from a diameter measurement (43). A second reduction factor was included in the
equation to account for decay and hollows in stems of E. regnans calculated as a
proportion related to tree size. Trees ⬎50 cm DBH begin to show signs of internal
decomposition, and by 120 cm DBH actual tree mass is ⬇50% of that predicted
from stem volume (52). Accounting for decay is an important aspect of estimating
biomass from allometric equations derived from stem volume that requires
further research, but that is overcome by using direct biomass measurements for
the derivation of the allometric equations. Selection of trees for measurement
that cover the full range of conditions is also important. Unlike many allometric
equations developed for forest inventory purposes, the equation used here was
calculated from data representing ecologically mature E. regnans trees. Carbon
in dead biomass was calculated by using this allometric equation for standing
stems with a reduction for decay. Coarse woody debris on the forest ﬂoor was
measured along 100-m transects (63). The structure of stands with high biomass
was described by a bimodal frequency distribution of tree sizes that represented
different age cohorts. The maximum amount of biomass carbon occurred in tree
sizes 40–100 and 200–240 cm DBH. A lack of comparable high-quality soil data
meant we could not provide estimates of below-ground carbon stocks nor
consider associated soil carbon dynamics.
Our analyses of biomass carbon stocks used a combination of techniques
including ﬁeld inventory data, biomass measurements, and understanding of
carbon cycling processes, as has been recommended by the IPCC (64). The rela-
tionship between reﬂectance from spectral bands, leaf area index, and biomass
accumulation is not linear. This is exempliﬁed by the relatively low leaf area of E.
regnans for the high biomass accumulation in the stemwood of these tall trees.
Hence, it is important that all of these types of information are used to estimate
biomass carbon stocks and that models are well calibrated with site data, rather
than relying solely on remote sensing.
Keith et al. PNAS
July 14, 2009
Global Site Biomass Data. Data on forest biomass were obtained from the
literature where biomass was calculated from individual plot data at sites that
represent largely mature or primary forest with minimal human disturbance
(Table S1). The data were categorized into forest biomes (deﬁned by the IPCC;
Table 4.5 in ref. 4). We used ﬁeld plot data that were available in the published
literature as they constitute the most reliable primary data sources. We did not
use modeled estimates of biomass carbon or regional estimates derived from
forest inventory data and expansion factors to derive wood volume and
biomass. A carbon concentration of 0.5 gC䡠g⫺1was used where only biomass
data were provided. Where site information was not given, latitude and
longitude were obtained from Google Earth (http://earth.google.com) by
using the described site location, and mean annual temperature and precip-
itation were obtained from a global dataset (www.cru.uea.ac.uk/cru/data/
tmc.htm). Little or no information was provided by most of the publications
concerning how internal decay in trees was accounted for in the biomass
estimates. Hence, our estimates of biomass of E. regnans that were reduced
to account for decay are considered conservative compared with the global
1. Intergovernmental Panel on Climate Change (2007) The Fourth Assessment Report
Climate Change 2007: Synthesis Report. Contribution of Working Groups I, II, and III,
eds Pachauri RK, Reisinger A (Intergovernmental Panel on Climate Change, Geneva).
2. United Nations Framework Convention on Climate Change (2008) Conference of the
Parties 14, Poznan, December 2008.
3. Food and Agriculture Organization (2007) Global Forest Resources Assessment 2010
Speciﬁcation of National Reporting Tables for FRA 2010. Forest Resources Assessment
Programme Working Paper 135 (Forestry Department, Food and Agriculture Organi-
zation of the United Nations, New York).
4. Intergovernmental Panel on Climate Change (2006) Intergovernmental Panel on
Climate Change Guidelines for National Greenhouse Gas Inventories. Vol. 4 Agricul-
ture, Forestry and Other Land Use, Prepared by the National Greenhouse Gas
Inventories Programme, eds Eggleston S, Buendia L, Miwa K, Ngara T, Tanabe K
(Institute for Global Environmental Strategies, Kanagawa, Japan).
5. Gibbs HK, Brown S, Niles JO, Foley JA (2007) Monitoring and estimating tropical forest
carbon stocks: Making REDD a reality. Environ Res Lett 2:045023.
6. HoughtonRA (2005) Aboveground forest biomass and the global carbon balance. Glob
Change Biol 11:945–958.
7. Food and Agriculture Organization (2006) Responsible Management of Planted For-
ests: Voluntary Guidelines. Planted Forests and Trees Working Paper 37/E (Food and
Agriculture Organization, Rome).
8. United Nations (1998) Kyoto Protocol to the United Nations Framework Convention
on Climate Change: Article 2.1.a.iii (United Nations, New York).
9. JarvisPG (1989) Atmospheric carbon dioxide and forests. Philos Trans R Soc London Ser
10. Melillo J, Prentice IC, Farquhar GD, Schulze ED, Sala OE (1995) Terrestrial biotic
responses to environmental change and feedbacks to climate. Climate Change: The
Science of Climate Change, eds Houghton JT, et al. (Cambridge Univ Press, New York),
pp 444– 481.
11. LuyssaertS, et al. (2008) Old-growth forests as global carbon sinks. Nature 455:213–215.
12. Lewis SL, et al. (2009) Increasing carbon storage in intact African tropical forests.
13. PhillipsOL, Lewis SL, Baker TR, Chao KJ, Higuchi N (2008) The changing Amazon forest.
Philos Trans R Soc London Ser B 363:1819–1827.
14. Righelato R, Spracklen DV (2007) Carbon mitigation by biofuels or by saving and
restoring forests? Science 317:902.
15. Shearman PL, Ash J, Mackey BG, Bryan JE, Lokes B (2009) Forest conversion and
degradation in Papua, New Guinea 1972–2002. Biotropica, 10.1111/j.1744–
16. Gibbs HK, Brown S (2007) Geographical Distribution of Woody Biomass Carbon Stocks
in Tropical Africa: An Updated Database for 2000 (Carbon Dioxide Information Center,
Oak Ridge National Laboratory, Oak Ridge, TN).
17. Bryant D, Nielsen D, Tangley L (1997) Last Frontier Forests: Ecosystems and Economies
on the Edge (World Resources Institute, Washington, DC).
18. Gupta RK, Rao DLN (1994) Potential of wastelands for sequestering carbon by refor-
estation. Curr Sci 66:378–380.
19. Lindenmayer DB, Incoll RD, Cunningham RB, Donnelly CF (1999) Attributes of logs on
the ﬂoor of Australian mountain ash (Eucalyptus regnans) forests of different ages. For
Ecol Manage 123:195–203.
20. Lindenmayer DB, Cunningham RB, MacGregor C, Incoll RD, Michael D (2003) A survey
design for monitoring the abundance of arboreal marsupials in the Central Highlands
of Victoria. Biol Conserv 110:161–167.
21. Lindenmayer DB, Franklin J, Burton PJ (2008) Salvage Logging and Its Ecological
Impacts. (Island Press, Washington, DC)
22. Fujimori T, Kawanabe S, Saito H, Grier CC, Shidei T (1976) Biomass and primary
production in forests of three major vegetation zones of the Northwestern United
States. J Jap For Soc 58:360–373.
23. Smithwick EAH, Harmon ME, Remillard SM, Acker SA, Franklin JF (2002) Potential upper
bounds of carbon stores in forests of the Paciﬁc Northwest. Ecol Appl 12:1303–1317.
24. Grier CC, Logan RS (1977) Old-growth Pseudotsuga menziesii communities of a western
Oregon watershed: Biomass distribution and production budgets. Ecol Mon 47:373–400.
25. Means JE, MacMillan PC, Cromack K (1992) Biomass and nutrient content of Douglas-ﬁr
logs and other detrital pools in an old-growth forest, Oregon, USA. Can J For Res
26. Hessl AE, Milesi C, White MA, Petersen DL, Keane RE (2004) Ecophysiological Param-
eters for Paciﬁc Northwest Trees (U.S. Department of Agriculture, Washington, DC),
U.S. Department of Agriculture Forest Service General Technical Report PNW-GTR-618.
27. van Tuyl S, Law BE, Turner DP, Gitelman AI (2005) Variability in net primary production and
carbon storage in biomass across Oregon forests: An assessment integrating data from
forest inventories, intensive sites, and remote sensing. For Ecol Manage 209:273–291.
28. Silverster WB, Orchard TA (1999) The biology of kauri (Agathis australis)inNew
Zealand 1. Production, biomass, carbon storage, and litter fall in four forest remnants.
NZ J Bot 37:553–571.
29. Hall GMJ, Wiser SK, Allen RB, Beets PN, Goulding CJ (2001) Strategies to estimate
national forest carbon stocks from inventory data: The 1990 New Zealand baseline.
Glob Change Biol 7:389– 403.
30. Romero P, Neira E, Lara A (2007) Forest Cover and Carbon Changes in Coastal
Temperate Rainforest, Chile (Universidad Austral de Chile, Valdivia, Chile and The
Nature Conservancy, Arlington, VA).
31. VannDR, et al (2002) Distribution and cycling of C, N, Ca, Mg, K, and P in three pristine,
old-growth forests in the Cordillera de Piuchue´, Chile. Biogeochem 60:25– 47.
32. CarmonaMR, Armesto JJ, Aravena JC, Pe´ rez CA (2002) Coarse woody debris biomass in
successional and primary temperate forests in Chiloe´ Island, Chile. For Ecol Manag
33. Schlegel BC, Donoso PJ (2008) Effects of forest type and stand structure on coarse
woody debris in old-growth rainforests in the Valdivian Andes, south-central Chile. For
Ecol Manag 255:1906–1914.
34. Law BE, et al. (2002) Environmental controls over carbon dioxide and water vapour
exchange of terrestrial vegetation. Agric For Meteor 113:97–120.
35. PrenticeKC (1990) Bioclimatic distributions of vegetation for general circulation model
studies. J Geophys Res 95:11811–11839.
36. Lieth H (1972) Modeling the primary productivity of the world. Trop Ecol 13:125–130.
37. Woodward FI, Smith TM, Emanuel WR (1995) A global land primary productivity and
phytogeography model. Glob Biogeochem Cycles 9:473–490.
38. Ashton DH (1975) The root and shoot development of Eucalyptus regnans F. Muell.
Aust J Bot 23:867–887.
39. Kueppers LA, Southon J, Baer P, Harte J (2004) Dead wood biomass and turnover time,
measured by radiocarbon, along a subalpine elevation gradients. Oecologia 141:641–651.
40. HarmonME, et al. (1986) Ecology of coarse woody debris in temperate ecosystems. Adv
Ecol Res 15:133–302.
41. BrownS, Mo J, McPherson JK, Bell TB (1996) Decomposition of woody debris in Western
Australian forests. Can J For Res 26:954–966.
42. ChambersQC, Higuchi N, Schimel JP, Ferreira LV, Melack JM (2000) Decomposition and
carbon cycling of dead trees in tropical forests of the Central Amazon. Oceologia
43. Dean C, Roxburgh S, Mackey BG (2003) Growth modeling of Eucalyptus regnans for
carbon accounting at the landscape scale. Modeling Forest Systems, eds Amaro A, Reed
D, Soares P (ACBI, Wallingford, UK), pp 27–40.
44. Illic J, Boland D, McDonald M, Downes G, Blakemore P (2000) Wood Density: Phase 1
State of Knowledge (Australian Greenhouse Ofﬁce, Canberra), National Carbon Ac-
counting System Technical Report 18.
45. Jacobs MR (1955) Growth Habits of the Eucalypts (Forestry and Timber Bureau,
46. Xiao J, et al (2008) Estimation of net ecosystem carbon exchange for the conterminous
United States by combining MODIS and AmeriFlux data. Agric For Meteorol 148:827–1847.
47. Asbjornsen H, Vela´zquez-Rosas N, Garcia-Soriano R, Gallardo-Herna´ ndez C (2005)
Deep ground ﬁres cause massive above- and below-ground biomass losses in tropical
montane cloud forests in Oaxaca, Mexico. J Trop Ecol 21:427–434.
48. Tinker DB, Knight DH (2000) Coarse woody debris following ﬁre and logging in
Wyoming lodgepole pine forests. Ecosystems 3:472–483.
49. McCarthy MA, Gill AM, Lindenmayer DB (1999) Fire regimes in mountain ash forest:
evidence from forest age structure, extinction models, and wildlife habitat. For Ecol
50. Mackey BG, Lindenmayer DB, Gill AM, McCarthy AM, Lindesay JA (2002) Wildlife, Fire,
and Future Climate: A Forest Ecosystem Analysis (Commonwealth Scientiﬁc and
Industrial Research Organization Publishing, Collingwood, Australia).
51. BrownS, Schroeder P, Birdsey R (1997) Aboveground biomass distribution of US eastern
hardwood forests and the use of large trees as an indicator of forest development. Fort
Ecol Manage 96:37–47.
52. Roxburgh SH, Wood SW, Mackey BG, Woldendorp G, Gibbons P (2006) Assessing the
carbon sequestration potential of managed forests: A case study from temperate
Australia. J Appl Ecol 43:1149–1159.
53. Bormann FH, Likens GE (1979) Catastrophic disturbance and the steady state in
northern hardwood forests. Am Sci 67:660– 669.
54. CareyEV, Sala A, Keane R, Callaway RM (2001) Are old forests underestimated as global
carbon sinks? Glob Change Biol 7:339–344.
55. LawBE, Sun OL, Campbell J, van Tuyl S, Thorntom PE (2003) Changes in carbon storage
and ﬂuxes in a chronosequence of ponderosa pine. Glob Change Biol 9:510–524.
56. Zhou G, et al. (2006) Old-growth forests can accumulate carbon in soils. Science
57. Schulze ED, Wirth C, Heimann M (2000) Managing forests after Kyoto. Science
58. Schulze ED (2000) Carbon and Nitrogen Cycling in European Forest Ecosystems
59. Valentini R, et al. (2000) Respiration as the main determinant of carbon balance in
European forests. Nature 404:861–865.
60. SuW, Brown MJ, Mackey B (2001) Agent-based dynamic modeling of forest ecosystems
at the Warra LTER Site. Tasforests 13:129–140.
61. United Nations Framework Convention on Climate Change (2007) Report of the
Conference of the Parties on its 13th session, held in Bali from 3 to 15 December 2007
(United Nations Framework Convention on Climate Change, Bonn, Germany).
62. Mueck SG, Ough K, Banks JCG (1996) How old are wet forest understories? Aust J Ecol
63. Lindenmayer DB, Cunningham RB, Donnelly CF, Franklin JF (2000) Structural features
of old-growth Australian mountain ash forests. For Ecol Manage 134:189–204.
64. Nabuurs GJ, et al. (2007) Forestry. Climate Change 2007:Mitigation. Contribution of
Working Group III to the Fourth Assessment Report of the Intergovernmental Panel
on Climate Change, eds Metz B, Davidson O, Bosch P, Dave R, Meyer L (Cambridge Univ
Press, Cambridge, UK), pp 542–584.
65. Lindenmayer DB, Mackey BG, Nix HA (1996) The potential bioclimatic domain of four
species of commercially-important eucalypt tree species from south-eastern Australia.
Aust J For 59:74– 89.
66. Intergovernmental Panel on Climate Change (2003) Good Practice Guidance for Land
Use, Land-Use Change, and Forestry, eds Penman J, et al. (Institute for Global Envi-
ronmental Strategies, Kanagawa, Japan).
www.pnas.org兾cgi兾doi兾10.1073兾pnas.0901970106 Keith et al.