ArticlePDF Available

Abstract and Figures

From analysis of published global site biomass data (n = 136) 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 (n = 44) than for sampled tropical (n = 36) and boreal (n = 52) forests (n is number of sites per forest biome). Spatially averaged Intergovernmental 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 regarding forest conservation, management, and restoration. Conserving 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.
Content may be subject to copyright.
Re-evaluation of forest biomass carbon stocks and
lessons from the world’s most carbon-dense forests
Heather Keith
1
, 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 (n136) 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 (n
44) than for sampled tropical (n36) and boreal (n52) 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 climate mitigation primary forest
deforestation and degradation 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-
.fao.org/forestry/site/10368/en).
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.
Australian
Eucalyptus regnans
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: heather.keith@anu.edu.au.
This article contains supporting information online at www.pnas.org/cgi/content/full/
0901970106/DCSupplemental.
www.pnas.orgcgidoi10.1073pnas.0901970106 PNAS
July 14, 2009
vol. 106
no. 28
11635–11640
ECOLOGY
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)ha
1
in living above-ground biomass
and 1,867 tCha
1
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
tCha
1
in living above-ground biomass and 2,844 tCha
1
in total
biomass from stands with a well-defined structure of overstory and
midstory trees (see Fig. 1) consisting of multiple age cohorts with
the oldest 250years (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 tCha
1
. Unexpectedly, we found the highest values
were from areas experiencing past partial stand-replacing natural
disturbances.
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 (n44) than they were for the sampled
tropical (n36) and boreal (n52) 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 (tCha
1
) and
total biomass carbon (tCha
1
) to temperature and precipitation
(Fig. 3).
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 224587 tCha
1
and total biomass
of 568–794 tCha
1
(22–25)]. A synthesis of site data for the Pacific
Northwest gave an average for evergreen needle leaf forest of 334
tCha
1
(26), and this is used as the continental biome value by the
IPCC (4). An upper limit of biomass accumulation of 500 –700
tCha
1
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 tCha
1
(28)]; and a synthesis based on forest
inventory data gave a mean of 180 tCha
1
with a range in means
for forest classes of 105–215 tCha
1
(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
1
(30–33)].
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 (tCha1)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 tCha1and ranges from 104 to 1,819 tCha1.The highest biomass
carbon occurs in the temperate latitudes.
11636
www.pnas.orgcgidoi10.1073pnas.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
Carbon Forests
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
2
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 (1myr
1
for
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 gcm
3
) (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 (tCha1)
(A) and total biomass carbon (tCha1)(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
vol. 106
no. 28
11637
ECOLOGY
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
America (40).
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 (tCha
1
) of each forest biome (mean, standard deviation,
and number of sites) and default biomass carbon values (IPCC; refs. 4 and 66)
Domain
Climate
region
Above-ground living
biomass carbon, tCha
1
Root dead biomass
carbon, tCha
1
Total living dead biomass
carbon, tCha
1
Average
site data
Biome default
value*
Average
site data
Biome default
value
Average
site data
Biome defaul
value
Tropical Tropical wet 171 (61) n18 146 76 (72) n7 67 231 (75) n7 213
Tropical moist 179 (96) n14 112 55 (66) n5 30 248 (100) n5 142
Tropical dry 70 n17341n1 32 111 n1 105
Tropical montane 127 (8) n3 71 52 (6) n3 60 167 (17) n3 112
Subtropical Warm temperate moist 294 (149) n26 108 165 (75) n 20 63 498 (200) n20 171
Warm temperate dry 75 65 140
Warm temperate montane 69 63 132
Temperate Cool temperate moist 377 (182) n18 155 265 (162) n18 78 642 (294) n18 233
Cool temperate dry 176 (102) n3 59 102 (77) n3 62 278 (173) n3 121
Cool temperate montane 147 n1 61 63 153 n1 124
Boreal Boreal moist 64 (28) n28 24 37 (16) n14 75 97 (34) n14 99
Boreal dry 59 (36) n24 8 25 (12) n9 52 84 (39) n960
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
3.2.2 (66)].
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)
Condition
Mean annual
temperature, ° C
Total annual
precipitation, mm
GEP,
gCO
2
m
2
y
1
k, year
1
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.
11638
www.pnas.orgcgidoi10.1073pnas.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/
resource/docs/2007/cop13/eng/06a01.pdf#page8). Conserving
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.
Concluding Comments
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.
Methods
Biomass of
E. regnans
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 Wm2. 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
vol. 106
no. 28
11639
ECOLOGY
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 gCg1was 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
site data.
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
B324:369–392.
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.
Nature 457:1003–1007.
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–
7429.2009.00495.
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
22:1536–1546.
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
164:265–275.
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
122:380–388.
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,
Canberra, Australia).
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
Manage 124:193–203.
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
314:1417.
57. Schulze ED, Wirth C, Heimann M (2000) Managing forests after Kyoto. Science
289:2058–2059.
58. Schulze ED (2000) Carbon and Nitrogen Cycling in European Forest Ecosystems
(Springer, Heidelberg).
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
21:345–348.
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).
11640
www.pnas.orgcgidoi10.1073pnas.0901970106 Keith et al.
... Climatic variations are driving forests to become increasingly dynamic systems [17], resulting in changes in tree species composition within ecosystems [11]. Simultaneous shifts in temperature and precipitation lead to either reductions or increases in ecosystem biomass, thereby altering global forest distribution patterns [18]. ...
... It has been demonstrated that hthe bioclimatic variables of temperature (Bio1 and Bio5) and precipitation (Bio12) are associated with the accumulation of AGB in forests [20], boreal ecosystems [19], temperate seasonal ecosystems [18], tropical rainforests [50], and tropical seasonal ecosystems [4,5]. As can be observed, Bio5 and Bio12 (Appendix A) are good predictors of AGB across different types of ecosystems. ...
... In contrast to this study, in boreal and temperate forests, a positive relationship has been found between cd AGB and MAT [18], but a negative one in humid regions [27]. ...
Article
Full-text available
Climate variations in temperature and precipitation significantly impact forest productivity. Precipitation influences the physiology and growth of species, while temperature regulates photosynthesis, respiration, and transpiration. This study developed bioclimatic models to assess how climate change will affect the carbon density of aboveground biomass (cdAGB) in Mexico’s coniferous forests for 2050 and 2070. We used cdAGB data from the National Forest and Soils Inventory (INFyS) of Mexico and 19 bioclimatic variables from WorldClim ver. 2.0. The best predictors of cdAGB were obtained using machine learning techniques with the “caret” library in R. The model was trained with 80% of the data and validated with the remaining 20% using Generalized Linear Models (GLMs). Current cdAGB prediction maps were generated using the best predictors. Future cdAGB was calculated with the average of three general circulation models (GCMs) of future climate projections from the Coupled Model Intercomparison Project Phase 5 (CMIP5), under four Representative Concentration Pathways (RCPs): 2.6, 4.5, 6.0, and 8.5 W/m2. The results indicate cdAGB losses in all climate scenarios, reaching up to 15 Mg C ha−1, and could occur under the RCP 8.5 scenario by 2070 in the central region of the country. Temperature-related variables are more important than precipitation variables. Bioclimatic variables can explain up to 20% of the total variance in cdAGB. The temperature in the study area is expected to increase by 2.66 °C by 2050 and 3.36 °C by 2070, while precipitation is expected to fluctuate by ±10% relative to the current values, which could geographically redistribute the cdAGB of the country’s coniferous forests. These findings underscore the need for forest management to focus not only on biodiversity conservation but also on the carbon storage capacity of these ecosystems.
... Temperate rainforests are a rare forest ecosystem globally, restricted to cool, moist climates biomes that cover less than 1% of the Earth's land surface and account for 2.5% of total forest cover (Alaback, 1991;DellaSala, 2011). They are recognized for their global ecological importance, high ecosystem productivity and carbon storage, with intact temperate rainforest having higher carbon density than intact forests in other latitudes, and regions of temperate rainforest in Australia having the highest known carbon density in the world (>1,000 tonnes of carbon ha 1 ) (Brandt et al., 2014;Buma et al., 2019;Carpenter et al., 2014;Keith et al., 2009;Kranabetter et al., 2021;Smith-Ramírez, 2004). However, they have lower average gross ecosystem productivity rates compared with tropical rainforest (1318 vs. 1961 g CO 2 m 2 year 1 ), demonstrating that their carbon storage is slower to accumulate (Keith et al., 2009). ...
... They are recognized for their global ecological importance, high ecosystem productivity and carbon storage, with intact temperate rainforest having higher carbon density than intact forests in other latitudes, and regions of temperate rainforest in Australia having the highest known carbon density in the world (>1,000 tonnes of carbon ha 1 ) (Brandt et al., 2014;Buma et al., 2019;Carpenter et al., 2014;Keith et al., 2009;Kranabetter et al., 2021;Smith-Ramírez, 2004). However, they have lower average gross ecosystem productivity rates compared with tropical rainforest (1318 vs. 1961 g CO 2 m 2 year 1 ), demonstrating that their carbon storage is slower to accumulate (Keith et al., 2009). The moist climate within temperate rainforests supports a high diversity of bryophyte and lichen epiphytes (Ellis & Eaton, 2021;Galloway, 1992) including many endemic species. ...
Article
Full-text available
Temperate rainforests are rare ecosystems globally; restricted to cool, moist conditions that are sensitive to a changing climate. Despite their crucial conservation importance, a global assessment of how temperate rainforests will be impacted by climate change is lacking. We calculated historical (1970–2000) climate conditions for the temperate rainforest biome using ERA5 reanalysis data for three key bioclimatic variables: warmest quarter temperature, annual precipitation and proportion of rainfall during warmest quarter. We used high‐spatial resolution climate projections for these variables to identify regions likely to become unsuitable for temperate rainforests under four future shared socioeconomic pathway (SSP) scenarios. We predict unmitigated climate change (SSP 5–8.5) would lead to a 68.3 (95% confidence interval (95 CI): 53.4–81.3)% loss in the existing temperate rainforest biome by 2100 at a global scale with some national‐level reductions exceeding 90%. Restricting global warming to <2°C (consistent with SSP 1–2.6), limits loss of global temperate rainforest biome to 9.7 (95 CI: 7.8–13.3)% by 2100 and is crucial to ensuring temperate rainforest persistence. Deforestation has resulted in loss of up to 43% of the current temperate rainforest biome with only 37% of primary forest remaining, and some regions like Europe with virtually none. Protection and restoration of the temperate rainforest biome, along with emissions reductions, are vital to its climate future.
... The cultivation of plantations has emerged as an important strategy for sequestering carbon. Forest ecosystems account for ~90% of the global terrestrial C uptake, with this C sequestered as biomass or soil organic matter [4]. The potential for increasing the C sink capacity of forestry has emerged as a component of efforts to mitigate climate and environmental change. ...
Article
Full-text available
Accurate estimation of the potential increase in the carbon (C) sink function of forests is required for climate mitigation and C neutrality assessments. Also, accurate forest carbon density estimates are critical for understanding national- and global-level carbon cycling and storage and can inform climate change mitigation. This study established a stand C density growth model to further analyze the C sink potential of planted Mongolian pine (Pinus sylvestris var. mongolica) forests. Samples (390) from fixed plots of Mongolian pine were collected in Heilongjiang Province, Northeast China. The site index (SCI) and stand density index (SDI) were introduced to a constructed stand C density growth model, with an optimal model selected through model fitting. The effect of SDI on stand C density in different SCI grouping intervals was assessed. Total C sequestration of Mongolian pine was calculated using the established C density model. Sample plots with higher C density in each forest age stand were selected to establish a model of potential C sequestration for Mongolian pine, and the difference between this rate and the average was compared to obtain the potential increase in C sink capacity of the forest stand. Slightly different fitting accuracies among the different C density growth models were observed, with the Richards model showing the best performance, which improved through the introduction of the SCI and SDI. Stand C density was associated with an increasing trend in SCI, which within each SCI subgroup was related to the increasing SDI trend. The potential C sequestration rate of the stand was close to the average between years 5 and 13. The average C sequestration rate peaked at 3.86 Mg·ha−1·year−1 at year 13, whereas the potential C sequestration rate peaked at 4.42 Mg·ha−1·year−1 in year 15. A gap between the potential and average C sequestration rate existed between ages 13 and 45, indicating the possibility for an increased C sink function in this forest age range. The Richards growth model incorporating SCI and SDI provided a better reflection of the C density of the Mongolian pine plantation, and the established stand C sequestration rate model showed that the optimal increment in the plantation C sink function can be obtained between years 13 and 45. The results of this study can guide C sink management in the Mongolian pine plantation.
... For example, burning 1 ha of dense forest can result in exorbitant greenhouse gas emissions, contributing to global warming [56]. In particular, if only the carbon from aboveground living biomass is considered, burning 1 ha of old-growth tropical forest could cause the emission of 70 to 300 Mg of carbon [57][58][59]. However, this trend depends on the quantity (e.g., fuel load tons per ha) and quality (e.g., fine vs. slightly coarse litter) of the plant biomass, as well as on the climatic conditions, including wind speed and air humidity, during the burning of vegetation [60][61][62][63]. ...
Article
Full-text available
Slash-and-burn agriculture (SBA) is critical to maintaining rural peoples' livelihoods. Yet, it causes environmental degradations that challenge its sustainability. Such degradations are often underestimated, as they are usually assessed at the local (stand) scale, overlooking larger-scale impacts. Here, we drew upon existing SBA and landscape ecology knowledge to assess the multiscale abiotic and biotic effects of SBA. This agroecosystem involves four stages (slashing of vegetation, burning of vegetation, farming, and forest recovery) but the SBA research is biased towards biotic impacts, especially during forest recovery. Despite its importance for key abiotic (e.g., soil fertility) and biotic (e.g., species richness) attribute recovery, this stage is typically too short (<10 years) to compensate for the environmental degradation caused by the previous stages. Successional and landscape ecology theory suggests that such compensatory dynamics can promote SBA sustainability in landscapes dominated by old-growth forests. Yet, when old-growth forest loss exceeds certain boundaries, abiotic and biotic SBA impacts may compromise the conservation value and sustainability of this ancient agroecosystem. We highlight that SBA sustainability should be comprehensively assessed by including landscape-scale variables (e.g., percent old-growth forest cover) that may be key for maintaining biodiversity patterns and processes in landscapes where SBA is practiced.
... In addition, this carbon debt is likely an underestimate because natural forests typically contain more biomass compared to mature forestry plantations. Natural forests possess older trees, higher biodiversity, a greater abundance of dead wood, and intact underground vegetation [6,[34][35][36]. ...
Preprint
Full-text available
This article presents an evaluation of the environmental impact of forestry based on landscape theory. It has been argued that this type of forestry offers a positive impact on the climate because there is a balance between the amount of greenhouse gas emissions and the absorption of these gases within an entire forested area. However, this analysis will demonstrate that the arrangement and composition of managed forests are linked to a significant carbon debt. This debt represents the disparity between the carbon that would typically be stored in a natural forest and the actual amount of carbon stored in the managed forest. While this excess carbon remains in the atmosphere rather than being sequestered, it contributes to the greenhouse effect. Using the Swedish forestry as an example, the carbon debt is estimated to be comparable in scale to the total accumulated fossil fuel emissions of the country.
... Forests cover approximately 30% of the Earth's land surface and serve as the largest carbon sinks [2]. They play crucial roles in carbon storage, cycling, regulation, and maintenance [3][4][5][6]. Photosynthesis is the key process through which forests function as carbon sinks, which is influenced by factors such as the species, leaf traits [7][8][9], and environmental changes involved [10][11][12]. Climate change driven by rising atmospheric CO 2 levels and temperatures is expected to expand East Asia's subtropical evergreen broadleaf forests northward [13]. ...
Article
Full-text available
Climate change alters vegetation patterns, pushing subtropical forests further north. These forests play a crucial role for carbon neutrality efforts due to their significant CO2 assimilation potential. This study investigated CO2 assimilation rate along with growth, morphological, and physiological traits in 23 half-sib families of Quercus acuta and 26 half-sib families of Q. glauca, two prominent East Asian evergreen broadleaf species. Q. acuta exhibited significantly higher growth rates, with diameter at breast height (DBH) and aboveground biomass exceeding those for Q. glauca by 12.1% and 69.9%, respectively (p < 0.001). Leaf traits, including leaf mass pear area (LMA), leaf nitrogen, and chlorophyll content, were also greater in Q. acuta, showing 24.5%, 45.8%, and 15.6% higher values (p < 0.001). While photosynthetic traits were similar, Q. acuta exhibited a 12.7% higher intrinsic water-use efficiency (iWUE) (p < 0.01). Among half-sib families, marginal differences were observed in growth traits (p < 0.1), and significant differences in leaf morphology and physiological traits (p < 0.05) were observed. A positive correlation was found between growth and physiological traits associated with the CO2 assimilation rate in Q. acuta, but not in Q. glauca. These findings highlight the potential of Q. acuta and Q. glauca for supporting future carbon neutrality efforts and provide traits supporting carbon uptake, valuable for selecting tree species with enhanced carbon sequestration potential.
Article
Full-text available
Primary forests are of paramount importance for biodiversity conservation and the provision of ecosystem services. In Europe, these forests are scarce and threatened by human activities. However, a comprehensive assessment of the magnitude of disturbances in these forests is lacking, due in part to their incomplete mapping. We sought to provide a systematic assessment of disturbances in primary forests in Europe based on remotely sensed imagery from 1986 to 2020. We assessed the total area disturbed, rate of area disturbed, and disturbance severity, at the country, biogeographical, and continental level. Maps of potential primary forests were used to mitigate gaps in maps of documented primary forests. We found a widespread and significant increase in primary forest disturbance rates across Europe and heightened disturbance severity in many biogeographical regions. These findings are consistent with current evidence and associate the ongoing decline of primary forests in Europe with human activity in many jurisdictions. Considering the limited extent of primary forests in Europe and the high risk of their further loss, urgent and decisive measures are imperative to ensure the strict protection of remnants of these invaluable forests. This includes the establishment of protected areas around primary forests, expansion of old‐growth zones around small primary forest fragments, and rewilding efforts.
Article
Full-text available
Land and ocean ecosystems are strongly connected and mutually interactive. As climate changes and other anthropogenic stressors intensify, the complex pathways that link these systems will strengthen or weaken in ways that are currently beyond reliable prediction. In this review we offer a framework of land–ocean couplings and their role in shaping marine ecosystems in coastal temperate rainforest (CTR) ecoregions, where high freshwater and materials flux result in particularly strong land–ocean connections. Using the largest contiguous expanse of CTR on Earth—the Northeast Pacific CTR (NPCTR)—as a case study, we integrate current understanding of the spatial and temporal scales of interacting processes across the land–ocean continuum, and examine how these processes structure and are defining features of marine ecosystems from nearshore to offshore domains. We look ahead to the potential effects of climate and other anthropogenic changes on the coupled land–ocean meta‐ecosystem. Finally, we review key data gaps and provide research recommendations for an integrated, transdisciplinary approach with the intent to guide future evaluations of and management recommendations for ongoing impacts to marine ecosystems of the NPCTR and other CTRs globally. In the light of extreme events including heatwaves, fire, and flooding, which are occurring almost annually, this integrative agenda is not only necessary but urgent.
Chapter
Globally, forests cover about 30% of the world’s land area but contain nearly 80% of the total terrestrial biomass. In humid conditions, annual dry matter production increases with increasing temperature from less than 2 Mg ha−1 yr.−1 in the boreal zone to more than 20 Mg ha−1 yr.−1 in the tropical zone. On a global scale, the total amount of carbon in forest ecosystems is 758 Gt. Boreal forests extend over Canada, China, Finland, Japan, Norway, Russia, Sweden, and the United States, where there are still large areas of unmanaged forest across the high-latitude regions. The mean carbon stock in boreal forests is 60–100 Mg C ha−1, i.e., 60–70% in the belowground biomass (roots and dead biomass), and the rest in the aboveground in living biomass of trees, shrubs, and ground vegetation. The mean carbon residence time in boreal forest is 100 years, but the decay rate varies depending on the temperature and moisture conditions.
Article
Full-text available
The current stock of organic carbon in Indian soils (24.3 Pg) can be increased to 34.9 Pg, the difference representing the potential for sequestering additional carbon in soils. Reforestation of 35 m ha of wastelands with suitable tree and grass species can sequester 0.84 and 1.06 Pg of carbon in vegetation and soil respectively. Restoration, maintenance and enlarging the carbon stocks of Indian soils are an urgent developmental priority. -Authors
Book
Full-text available
PUBLISHER'S DESCRIPTION: Salvage logging (€”removing trees from a forested area in the wake of a catastrophic event such as a wildfire or hurricane) €”is highly controversial. Policymakers and those with an economic interest in harvesting trees typically argue that damaged areas should be logged so as to avoid "€œwasting"€ resources, while many forest ecologists contend that removing trees following a disturbance is harmful to a variety of forest species and can interfere with the natural process of ecosystem recovery. Salvage Logging and Its Ecological Consequences brings together three leading experts on forest ecology to explore a wide range of issues surrounding the practice of salvage logging. They gather and synthesize the latest research and information about its economic and ecological costs and benefits, and consider the impacts of salvage logging on ecosystem processes and biodiversity. The book examines: what salvage logging is and why it is controversial; natural and human disturbance regimes in forested ecosystems; differences between salvage harvesting and traditional timber harvesting; scientifically documented ecological impacts of salvage operations; the importance of land management objectives in determining appropriate post-disturbance interventions. Brief case studies from around the world highlight a variety of projects, including operations that have followed wildfires, storms, volcanic eruptions, and insect infestations. In the final chapter, the authors discuss policy management implications and offer prescriptions for mitigating the impacts of future salvage harvesting efforts. Salvage Logging and Its Ecological Consequences is a €œmust-read€ volume for policymakers, students, academics, practitioners, and professionals involved in all aspects of forest management, natural resource planning, and forest conservation.
Chapter
This book, containing 34 papers presented at a workshop held in Portugal in June 2002, reviews current thinking on various models and presents applications in several contexts in relation to forest ecosystems. Topics covered include: forest reality and modelling strategies; mathematical approaches and reasoning; estimation processes and models; validation and decision making under uncertainty; and model archives and metadata. This book will be of significant interest to those in areas of forestry, applied ecology, and statistics and economics.
Book
The storage of carbon in forest ecosystems has received special attention in the Kyoto protocol of the Climate Convention, which attempts to equilibrate fossil fuel emissions with biological sinks. This volume quantifies carbon storage in managed forest ecosystems not only in biomass, but also in all soil compartments. It investigates the interaction between the carbon and nitrogen cycles by working along a north-south transect through Europe which starts in northern Sweden, passes through a N-deposition maximum in central Europe and ends in Italy. Surprisingly, C storage in soils increases with N deposition; in addition, not young reforestations, but old growth forests have the highest rate of carbon sequestration. For the first time biogeochemical processes are linked to biodiversity on a large geographic scale and with special focus on soil organisms. The enclosed CD-ROM provides a complete database of all flux, storage and species observations for modellers.
Article
Placing an upper bound to carbon (C) storage in forest ecosystems helps to constrain predictions on the amount of C that forest management strategies could sequester and the degree to which natural and anthropogenic disturbances change C storage. The potential, upper bound to C storage is difficult to approximate in the field because it requires studying old-growth forests, of which few remain. In this paper, we put an upper bound (or limit) on C storage in the Pacific Northwest (PNW) of the United States using field data from old-growth forests, which are near steady-state conditions. Specifically, the goals of this study were: (1) to approximate the upper bounds of C storage in the PNW by estimating total ecosystem carbon (TEC) stores of 43 old-growth forest stands in five distinct biogeoclimatic provinces and (2) to compare these TEC storage estimates with those from other biomes, globally. Finally, we suggest that the upper bounds of C storage in forests of the PNW are higher than current estimates of C stores, presumably due to a combination of natural and anthropogenic disturbances, which indicates a potentially substantial and economically significant role of C sequestration in the region. Results showed that coastal Oregon stands stored, on average, 1127 Mg C/ha, which was the highest for the study area, while stands in eastern Oregon stored the least, 195 Mg C/ha. In general, coastal Oregon stands stored 307 Mg C/ha more than coastal Washington stands. Similarly, the Oregon Cascades stands stored 75 Mg C/ha more, on average, than the Washington Cascades stands. A simple, area-weighted average TEC storage to I m soil depth (TEC,,,) for the PNW was 671 Mg C/ha. When soil was included only to 50 cm (TEC(50)), the area-weighted average was 640 Mg C/ha. Subtracting estimates of current forest C storage from the potential, upper bound of C storage in this study, a maximum of 338 Mg C/ha (TEC(100)) could be stored in PNW forests in addition to current stores.
Article
Above-ground biomass and net primary production of representative 90 to 130 year-old stands in the Picea sitchensis, Tsuga heterophylla, and Abies amabilis vegetation zones of the northwestern United States were determined by destructive analysis and leaf litter collection. Total above-ground biomass, leaf biomass, and above-ground net production were, respectively 875 t/ha, 7. 9 t/ha, and 10. 3 t/ha/yr for a 100—120 year-old T. heterophylla-P. sitchensis stand in the P. sitchensis zone; 669 t/ha, 11.1 t/ha, and 12. 7 t/ha/yr for a 90~110 year-old Pseudotsuga menziesii-T. heterophylla stand in the T. heterophylla zone; and 882 t/ha, 17. 5 t/ha, and 13. 0 t/ha/yr for a 100~130 year-old Abies procera-P. menziesii stand in the Abies amabilis zone. Production structure, production efficiency, volumetric density, and other stand characteristics were presented and compared. Potential biomass accumulation for forests of T. heterophylla and A. amabilis zones was assessed by nondestructive stem biomass estimates of mature P. menziesii-T. heterophylla and A. procera-P. menziesii stands on sites comparable to those of corresponding younger stands. Stem biomass of these mature stands was 1591 t/ha and 1687 t/ha respectively.
Article
At the cellular scale, much is known about the role of CO2 as a substrate in photosynthesis, but only little about its role as an activator and regulator. At the leaf scale, the response of CO2 assimilation to CO2 concentration has been described often and is well represented by biochemically based models, but there is inadequate information to parameterize the models of CO2 -acclimated leaves. At larger scales, direct measurements of responses to increase in atmospheric CO2 are impractical but models of canopy processes suggest that significant increases in CO2 assimilation will result from the rise in atmospheric concentration. Inferences from the increase in ampitude of the seasonal oscillation in the global atmospheric CO2 concentration at different latitudes suggest that forest is having a significant impact on the global atmospheric concentration, but it seems unlikely that expansion of the forest resource could effectively reduce the increase in atmospheric CO2. -from Author
Article
Living biomass, organic matter distribution, and organic matter production budgets were determined for plant communities of a small watershed dominated by 450-yr-old Pseudotsuga menziesii (Mirb.) Franco forests. Dominant trees in the communities were large, up to 175 cm diam and 80 m tall. Aboveground tree biomass of the various communities ranged from 491.8-975.8 tonnes/hectare, total aboveground living biomass ranged from 500.4-982.5 t/ha, total leaf biomass ranged from 10.4-16.3 t/ha and total organic matter accumulations ranged from 1,008.3-1,513.7 t/ha. Total tree biomass in the various communities was more related to past mortality than habitat differences. Biomass of standing dead trees and fallen logs was generally inversely related to aboveground tree biomass. Amounts of woody detritus were large, ranging from 59.0-650.6 t/ha or 4.3%-43.0% of total community organic accumulation. Aboveground tree biomass increment was negative in all communities, ranging from -2.9 to -6.2 t/ha. Positive increment by shrubs and trees <15 cm dbh, produced overall aboveground biomass increment -2.5 to -5.0 t/ha. Mortality averaged 1% of standing biomass. Aboveground net primary production in the various communities ranged from 6.3 to 10.1 t@?ha^-^1@?^-^1 and was roughly proportional to standing biomass. Net primary production consisted entirely of detritus. Total community autotrophic respiration ranged from 102.9-203.7 t@?ha^-^1@?yr^-^1 of which @?70% was by foliage. Gross primary production ranged from 111.2-216.8 t@?ha^-^1@?yr^-^1 of which only 6.0%-7.9% was net primary production. Net ecosystem production ranged from 0.12-5.6 t@?ha^-^1@?yr^-^1, entirely as an accumulation of woody detritus on the soil surface. Available evidence indicates larger peak biomass in seral P. menziesii than in climax Tsuga heterophylla forests. These communities may be in the process of declining from seral peak to steady-state climax biomass.