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Gross primary production (GPP) is partitioned to autotrophic respiration (Ra) and net primary production (NPP), the latter being used to build plant tissues and synthesize non-structural and secondary compounds. Waring et al. (1998) suggested that a NPP:GPP ratio of 0.47 ± 0.04 (s.d.) is universal across biomes, tree species and stand ages. Representing NPP in models as a fixed fraction of GPP, they argued, would be both simpler and more accurate than trying to simulate Ra mechanistically. This paper reviews progress in understanding the NPP:GPP ratio in forests during the 20 years since Waring et al.. Research has confirmed the existence of pervasive acclimation mechanisms that tend to stabilize the NPP:GPP ratio, and indicates that Ra should not be modelled independently of GPP. Nonetheless, studies indicate that the value of this ratio is influenced by environmental factors, stand age and management. The average NPP:GPP ratio in over 200 studies, representing different biomes, species and forest stand ages, was found to be 0.46, consistent with the central value that Waring et al. proposed but with a much larger standard deviation (± 0.12) and a total range (0.22 to 0.79) that is too large to be disregarded.
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Tree Physiology 39, 1473–1483
Is NPP proportional to GPP? Waring’s hypothesis 20 years on
A. Collalti 1,2,6 and I.C. Prentice 3,4,5
1National Research Council of Italy–Institute for Agriculture and Forestry Systems in the Mediterranean (CNR-ISAFOM), 87036, Rende, CS, Italy; 2Foundation
Euro-Mediterranean Centre on Climate Change–Impacts on Agriculture, Forests and Ecosystem Services Division (CMCC-IAFES), 01100, Viterbo, Italy; 3Department of Life
Sciences, AXA Chair of Biosphere and Climate Impacts, Imperial College London, Silwood Park Campus, Buckhurst Road, Ascot SL5 7PY, UK; 4Department of Biological
Sciences, Macquarie University, North Ryde, 2109 NSW, Australia; 5Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science,
Tsinghua University, Beijing 100084, China; 6Corresponding author (
Received September 24, 2018; accepted March 13, 2019; handling Editor Andrea Polle
Gross primary production (GPP) is partitioned to autotrophic respiration (Ra) and net primary production (NPP), the
latter being used to build plant tissues and synthesize non-structural and secondary compounds. Waring et al. (1998;
Net primary production of forests: a constant fraction of gross primary production? Tree Physiol 18:129–134) suggested
that a NPP:GPP ratio of 0.47 ±0.04 (SD) is universal across biomes, tree species and stand ages. Representing NPP
in models as a xed fraction of GPP, they argued, would be both simpler and more accurate than trying to simulate Ra
mechanistically. This paper reviews progress in understanding the NPP:GPP ratio in forests during the 20 years since the
Waring et al. paper. Research has conrmed the existence of pervasive acclimation mechanisms that tend to stabilize
the NPP:GPP ratio and indicates that Rashould not be modelled independently of GPP. Nonetheless, studies indicate
that the value of this ratio is inuenced by environmental factors, stand age and management. The average NPP:GPP
ratio in over 200 studies, representing dierent biomes, species and forest stand ages, was found to be 0.46, consistent
with the central value that Waring et al.proposed but with a much larger standard deviation (±0.12) and a total range
(0.22–0.79) that is too large to be disregarded.
Keywords: autotrophic respiration, carbon-use eciency, forest ecosystem, modelling, primary production.
Forest carbon budgets are dominated by two opposing
uxes: photosynthesis (or gross primary production, GPP)
and autotrophic respiration (Ra). The remainder is net primary
production (NPP), which accrues to tissues (eventually
becoming detritus and respired heterotrophically) and to a
variety of non-structural compounds that help to maintain plant
and rhizosphere function (Chapin et al. 2006). Estimation and
modelling of the net carbon balance of forests requires accurate
estimation of how GPP is partitioned, because a small relative
error in this partitioning could lead to a larger relative error in
thecarbonbalance(DeLucia et al. 2007,Hermle et al. 2010).
However, there is still large uncertainty about how GPP
is partitioned in forests. One school of thought emphasizes
constancy in the ratio of NPP to GPP.
McCree and Troughton (1966) argued that this ratio should
be more-or-less invariant (in plants generally) with respect
to ageing, CO2and temperature. Van Oijen et al. (2010)
suggested, moreover, that it should be stoichiometrically
constrained between 0.55 and 0.6. Giord (1995,2003)
and Van Oijen et al. (2010) emphasized that the substrate
for respiration originates from photosynthesis and so Ra
must inevitably depend on GPP, at least when averaged over
long enough periods; Giord (1995) provided experimental
evidence (from wheat) in support of the idea of a near
invariant of NPP to GPP. Waring et al. (1998) (hereafter W98)
subsequently reported, in this journal, that the NPP:GPP ratio in
a sample of 12 temperate and boreal forest stands was tightly
constrained, with a central value of 0.47 ±0.04 (here and
elsewhere, ‘±’ denotes one standard deviation) and a narrow
range from 0.40 to 0.52. This claim of a constant NPP:GPP
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1474 Collalti and Prentice
Figure 1. Regression of NPP versus GPP forced through the origin for
12 forest sites (from Waring et al. 1998, Table 2).
ratio near 0.5 was re-iterated in the recent review by Waring
and Landsberg (2016). The close relationship of NPP to GPP
in the data analysed by W98 is illustrated in Figure 1.
Giord (1995) and W98 noted that for modelling purposes,
assuming invariance would be more realistic that treating
respiration as if it were independent of GPP. A universal
value of the NPP:GPP ratio would indeed be convenient for
analysis and modelling, because it would allow straightforward
estimation of NPP, whose measurement requires either
destructive sampling or allometric approximations, from GPP.
Gross primary production can be estimated either from remote
sensing using a light-use eciency model, at a time scale
of around a week (Heinsch et al. 2006)oronasub-
daily basis by partitioning the net ecosystem CO2exchanges
measured by the eddy covariance network (Beer et al. 2010).
A number of vegetation models [including all published
versions of 3-PG, Landsberg and Waring 1997; CenW (as one
option), Kirschbaum 2005;PROMOD,Sands et al. 2000;C-Fix,
Veroustraete et al. 2002; early versions of TRIPLEX, Peng et al.
2002; FullCAM, Richards and Ewans 2004;HyLand,Levy et al.
2004; 4C, Lasch et al. 2005;BASFOR,Van Oijen et al. 2005;
TOPS-BGC, Nemani et al. 2009; ForCent, Parton et al. 2010;
G’DAY (as one option), Dezi et al. 2010; Picus, Seidl et al. 2012;
and early versions of 3D-CMCC FEM, Collalti et al. 2014]have
assumed a constant NPP:GPP ratio. W98 has been cited in many
carbon balance studies (in the Web of Science search engine,
the search string ‘Waring et al. 1998’ yielded 422 returns
and in Google Scholar, 596 returns; both accessed 1 March
2019). A constant NPP:GPP ratio has been invoked in local,
regional and global carbon storage assessments (e.g., Lenton
and Huntingford 2003,Magnani et al. 2007,Zhang et al.
2006,Zha et al. 2009,Peichl et al. 2010,Sun et al. 2014),
considered as a benchmark value (e.g., Gris et al. 2004),
described in textbooks (Landsberg and Sands 2010,Ågren and
Andersson 2012) and applied in one version of the MODIS NPP
product (Jay et al. 2016).
A number of empirical and theoretical studies carried out
since W98 have thus converged on the insight that Rashould
not be regarded as a process independent of GPP, but rather
regarded as a relatively conservative fraction of GPP, and
numerous ecosystem models have adopted the approximation
that Rais a constant fraction of GPP. The two uxes are indeed
closely coupled, and the ratio of NPP to GPP is therefore more
nearly constant than one would expect if they were independent.
On the other hand, a growing body of research since W98
has emphasized variation in the NPP:GPP ratio, and focused on
identifying its controls. Responding to W98, Medlyn and Dewar
(1999) argued for a broader range of NPP:GPP ratios (0.31–
0.59) than was reported there. They noted that the methods
used by W98 to calculate NPP may have predetermined the
nding of a near-invariant NPP:GPP ratio. They concluded that
the hypothesis of a xed NPP:GPP ratio, although ‘having some
basis in theory’, was just one option for modelling—and not
a desirable avenue to pursue in the absence of experimental
In this paper we review studies on the partitioning of forest
GPP since the publication of W98. Some of these studies have
pointed to an approximately constant ratio of NPP to GPP, others
to a variable one. To some extent this has been a question of
emphasis (is the glass ‘half full’ or ‘half empty’?). Thus, some
publications have reported negative results (e.g., no eect of
forest type or stand age on the ratio), others have reported
such eects while downplaying their importance, while others
have focused on the importance of considering these eects.
We summarize results of these various studies approximately
chronologically within each of three broad categories of study,
according to their principal focus on eects of forest type and
stand age, eects of climate (temperature and drought) or
eects of site fertility, disturbance and management. We nally
summarize data on NPP:GPP ratios in a new data set compiled
from over 200 studies, representing dierent biomes, species
and stand ages, and draw some general conclusions about the
state of knowledge and research needs.
Denitions of terms
GPP is the balance between carbon xed through photosyn-
thesis and carbon lost through photorespiration, expressed per
unit ground area and time (Wohlfahrt and Lu 2015). NPP is
GPP minus autotrophic respiration (Clark et al. 2001). Biomass
production (BP; Vicca et al. 2012) is the part of NPP that
is used for biomass growth (taken to include litter and fruit
production). Biomass production and NPP dier because part of
NPP can be allocated to organic compounds that are not used for
growth, including non-structural carbohydrates (NSCs; including
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Is NPP proportional to GPP? 1475
starch, sugars and other polysaccharides), labile root exudates
(primarily organic acids) that support biological activity in
the rhizosphere and secondary metabolites (including biogenic
volatile organic compounds) that are involved in signalling,
defence against pathogens and herbivores or protection of
tissues against thermal oxidative stress. Following the denitions
by Roxburgh et al. (2005), BP is constrained to be always zero
or positive (tissues consumed by herbivores, for example, are
considered to be part of BP), while NPP can be potentially
negative (Ra>GPP) for limited periods. Over periods of years,
NPP must equal or exceed BP.
Giord (1995) proposed the term ‘carbon use eciency’
(CUE = 1 Ra/GPP), which is equivalent to the NPP to GPP ratio
as dened by W98. Vicca et al. (2012) more recently introduced
the term ‘biomass production eciency’ (BPE = BP/GPP),
which is equivalent to ‘gross growth eciency’, as dened
in the comprehensive review—across all kinds of organisms,
both autotrophic and heterotrophic—by Manzoni et al. (2018).
Although in general BPE CUE, none of the papers reviewed
here, apart from Vicca et al. (2012),Fernández-Martínez et al.
(2014) and Campioli et al. (2015), make a clear distinction
between BP and NPP—compelling us, for comparison with
the wider literature, to treat BPE and CUE as if they were
synonymous although they clearly are not.
As data on ‘NPP’ have often been obtained by biometric
measurements, some reported values may be better considered
as estimates of BP rather than NPP (see also Malhi et al. 2015).
However, even if the dierence is usually small, the distinction
is worth making in future research and should allow better
quantication than is possible based on the current literature.
Studies examining eects of forest type and stand age
Law et al. (1999) compared two patches at dierent succes-
sional stages (45 and 250 years old) in a Pinus ponderosa
(Douglas ex C. Lawson) forest in a summer-dry climate in
Oregon, USA. They found the same NPP:GPP ratio (0.45) in
both patches. Cannell and Thornley (2000) and Thornley and
Cannell (2000) showed a relatively stable ratio of Raand GPP
(implying a range of only 0.55–0.65 for the NPP:GPP ratio)
over an age range of 0–60 years. However, they noted that
assuming a single constant value in models might overlook
both dierences among sites and variations from year to year.
Amthor (2000), analysing 30 years of studies on the NPP:GPP
ratio (obtained by subtracting respiration estimates from GPP),
maximum growth rate per unit of photosynthesis and minimum
tissues maintenance costs (0.65) to limited growth (if any)
and maximum maintenance costs (0.2). He reported the lowest
values for moist tropical forests, and the highest value for a
temperate Fraxinus plantation.
Mäkelä and Valentine (2000) applied a process-based model
of forest growth in conjunction with measurements from a Pinus
sylvestris (L.) forest. They found that increasing sapwood mass
with increasing height and age increased the respiring biomass,
and thus Ra. Their model estimated a decline in the NPP:GPP
m. They concluded it was unlikely that Racould be a constant
fraction of photosynthesis over the full time course of stand
development. Later, Vanninen and Mäkelä (2005), also studying
aP. sylvestris (L.) forest, measured a reduction in the NPP:GPP
ratio, from 0.65 to 0.45, with increasing tree height.
Ryan et al. (2004) used data from an experimental Eucalyptus
saligna (Sm.) forest to explicitly challenge the long-standing
forest dynamics paradigm of Kira and Shidei (1967) and Odum
(1969), in which increasing Rawas assumed to drive a decline
in the NPP:GPP ratio with stand age.Ryan et al.found instead
that an age-related decline in GPP was accompanied by a decline
in Ra. The NPP:GPP ratio did vary with stand age, but only
slightly, from 0.66 at age 2 years to 0.62 at age 6 years.
They concluded that NPP:GPP should be considered ‘roughly’
constant and eectively independent of biomass or stand age.
Litton et al. (2007) reviewed the constancy, or otherwise, of
NPP:GPP in the literature available at the time, and their study
was updated with new data by Ise et al. (2010). Litton et al.
conducted a meta-analysis of annual carbon budgets based on
63 forest ecosystems varying in fertility, structure and stand
age. They found a highly signicant correlation between Raand
GPP (R2= 0.95, n= 23, P<0.01). The NPP:GPP ratio was
approximately constant across sites (0.43 ±0.02), but the
total range was from 0.29 to 0.58. Three outliers (two boreal,
0.29–0.34. No eect of either stand age (n= 4) or soil fertility
(n= 7) was found, probably due to the paucity of data.
De Lucia et al. (2007) analysed published data from 60
forest sites with stand ages varying from 5 to 500 years.
They found that the NPP:GPP ratio, largely based on biometric
estimates of BP standing in for NPP, varied substantially among
biomes and age classes. The highest value (0.83) was found
in a 5-year-old plantation of Populus nigra (L.), experimentally
exposed to a high CO2concentration. The lowest (0.22) was
found in a 115-year-old Picea mariana (Mill.) stand. Figure 2,
based on the data analysed by De Lucia et al., shows a clear
dierence among biomes—with low ratios of NPP:GPP in boreal
forests and high ratios in temperate deciduous forests.
Thornley (2011) found the NPP:GPP ratio to vary from 0.5
to 0.6 and argued that this ratio is conservative among ecosys-
tems, but that it varies with stand age depending on growth
eciency and recycling fraction. Goulden et al. (2011),
analysing biometric data from a chronosequence of seven
even-aged boreal forest stands, found that the NPP:GPP ratio
decreased from 0.5 to 0.3 with increasing stand age.
Tang et al. (2014) found variability in the NPP:GPP ratio across
biomes (obtained mostly from biometric BP measurements)
from 0.3 to 0.45, but no signicant correlation between
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1476 Collalti and Prentice
Figure 2. Regressions of NPP versus GPP forced through the origin
for dierent forest types, from data in DeLucia et al. (2007).Circles
represent boreal; squares, temperate deciduous (TD); triangles, temper-
ate coniferous (TC); diamonds, west coast maritime (WCM); crosses,
temperate mixed (TM); plus signs, tropical (T).
NPP:GPP and age—suggesting that declining GPP during
stand development (due to hydraulic limitations) is paralleled
by decreasing Raas proposed by Ryan et al. (1997b) and
Drake et al. (2011). They also speculated that biome-specic
dierences might be due to soil fertility and/or temperature.
Studies examining eects of temperature
Saxe et al. (2000) noted that the short-term relationship of
respiration to temperature, as observed in the laboratory and
driven by enzyme kinetics, is likely to be unrepresentative
of the long-term behaviour of respiration because the crucial
acclimatory response of the base rate to temperature is missing.
They argued, instead, that acclimation should cause NPP to be
proportional to GPP.
Dewar et al. (1999) noted that a short-term increase in
Rawith temperature could be fuelled by non-structural carbon
reserves, whereas in the longer term Ramust be constrained by
the supply of substrates from photosynthesis. They accepted
the idea that NPP:GPP might be conservative. However, they
expressed caution with regard to applying a single value across
a wider range of temperatures (and other environmental factors)
than were considered in W98.
Giord (2003), analysing data (obtained in some cases from
Ra, in others from biometric measurements) from various earlier
works (Giord 2003, Table 3 and references therein), noted
that while the average NPP:GPP ratio for eld-grown trees varies
only slightly (0.47 ±0.05), glasshouse-grown seedlings in
controlled environments generally show higher average values
(0.58 ±0.03). Citing Tjoelker et al. (1999),hesuggested
that (i) species may acclimate to increasing temperature to
dierent extents and (ii) that the overall NPP:GPP ratio is likely
to decrease slightly with increasing temperature.
Piao et al. (2010), analysing the global forest carbon budget
data set (n= 104) compiled by Luyssaert et al. (2007),
considered variations of Ra, obtained by dierent methods, in
relation to mean annual temperature (MAT), NPP, total biomass,
height, maximum Leaf Area index (LAI) and stand age. This
analysis indicated a non-linear relationship of the Ra:GPP ratio
to MAT across latitudes (R2= 0.43, P= 0.03): decreasing at
rst, levelling o around 11 C and thereafter increasing again.
This analysis implies a range in the NPP:GPP ratio from 0.25 to
0.42, with a maximum at 11 C. No relation to forest age was
found outside the MAT range of 8–12 C.
Keith et al. (2010), in common with Dewar et al.(1999),
noted that W98’s methods for estimating GPP and NPP were not
independent, thus potentially biasing W98’s conclusion towards
a constant ratio. They noted that asynchrony between the pro-
duction and utilization of assimilated and stored carbohydrates
must inevitably produce interannual variations in the NPP:GPP
ratio in response to a temporarily variable climate. In a global
sample of 27 forests, they found the NPP:GPP ratio to vary
between 0.29 and 0.61, being non-linearly related to GPP (see
also Malhi et al. 2015), with MAT and solar radiation accounting
for about half of the variation.
Chambers et al. (2004) and Metcalfe et al. (2010), analysing
data from a throughfall exclusion experiment in Amazonian
rainforest, found NPP:GPP ratios ranging from 0.24 ±0.04 for
experimentally drought trees to 0.32 ±0.04 for control trees.
In an assessment of the carbon balance in a Fagus sylvatica
(L.) forest over a 5-year period, Wu et al. (2013) found
that NPP:GPP varied from 0.32 to 0.4, due to asynchronous
interannual variations in GPP and NPP linked to interannual
variability in climate.
Studies examining eects of soil fertility, disturbance and
Malhi et al. (2009,2011,2015) and Malhi (2012) estimated
the NPP:GPP ratio of primary tropical forests to be in the range
from 0.3 to 0.4, varying because of disturbances and across
dierent soil fertility classes. They also argued that their values
were likely underestimated to some extent because of missing
components of NPP, in particular the poorly quantied transfer of
carbon to the rhizosphere through root exudates and transfers
to mycorrhizal symbionts.
Maier et al. (2004) found that experimentally increasing
nutrient availability in a Pinus taeda (L.) plantation had no eect
on the NPP:GPP ratio. In contrast, Giardina et al. (2003) and
Vicca et al. (2012) found that site fertility was a major control
of this ratio to GPP, which was found to range from 0.4 to
0.6. Vicca et al.(2012) described temperate forests as being
usually more fertile than boreal forests and consequently having
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Is NPP proportional to GPP? 1477
Figure 3. Regressions of BP versus GPP forced through the origin at
dierent level of soil fertility, from data in Vicca et al. (2012).Circles,
squares and triangles represent dierent soil nutrient availability classes,
‘H’, ‘M’ and ‘L’ refers to high-, medium- and low-soil fertility, respectively.
a higher BP:GPP ratio. Forest management emerged as the
next best predictor of the BP:GPP ratio, followed by stand age.
Figure 3shows the string eect of site fertility in the data of
Vicca et al. Doughty et al. (2018), analysing 14 tropical forest
sites across dierent rainfall and soil regimes in Amazonia and
the Andes, found no signicant relationship between tempera-
ture and CUE (see also Malhi et al. 2015), but did nd lower
CUE in less fertile sites.
Campioli et al. (2015) analysed ratios of BP to GPP in
131 managed and unmanaged sites, mainly in Europe and
North America. They found a constant ratio (0.46 ±0.01)
in unmanaged forests and a higher ratio in managed forests
(0.53 ±0.03). They described how management can shift
carbon allocation patterns to favour above-ground production,
at least for a certain period after intervention. Figure 4shows
the eect of forest management in the data of Campioli et
al. Recently, Kunert et al. (2019) conrmed that disturbed
forests have a higher NPP:GPP ratio in comparison with the
undisturbed ones.
Variability across measurement methods
Methodological dierences could account for some of the
divergent results obtained in dierent studies. Curtis et al.
(2005) compared independent methods to estimate BP and
eddy covariance for GPP. Working in the transition zone between
temperate deciduous and boreal forests in North America, they
estimated an average NPP:GPP ratio of 0.42 ±0.016 using
biometric methods for both NPP and GPP and 0.54 ±0.04
using biometric methods for NPP against eddy covariance GPP.
Figure 4. Regressions of BP versus GPP forced through the origin
comparing managed versus unmanaged sites, from data in Campioli
et al. (2015). Circles represent managed sites; squares, unmanaged
By comparison with other data they suggested that the eddy
covariance method was overestimating GPP at this site.
Maseyk et al. (2008) analysed the NPP:GPP ratio in a man-
aged plantation of Pinus halepensis (Mill.) in Israel by comparing
chamber, ux and biometric data. They also found rather large
dierences (up to 0.15) in annual NPP:GPP ratios estimated
by the dierent methods (but see also Zha et al. 2007,
Hermle et al. 2010;Wu et al. 2013).
Zanotelli et al. (2013), combining biometric and eddy covari-
ance measurements for an apple orchard, found that NPP:GPP
varied depending on the methodology from 0.79 ±0.13 to
0.64 ±0.10. They attributed the dierences to the large fraction
of NPP allocated to fruit, reducing total respiration and causing
higher values of the NPP:GPP ratio when compared with data
reported in literature for forests.
A further potential complication in the measurement of
NPP:GPP ratios, which was not been studied to our knowledge,
is the possibility that CO2originating from sapwood respiration
could be transported to and re-assimilated by the leaves. This
would essentially lead to systematic underestimation of stem
respiration, and thus, potentially, somewhat lower NPP:GPP
Despite the large number of publications since W98 that have
attempted to clarify and quantify the controls on the NPP:GPP
ratio, no universal picture has emerged. Dierent studies have
come to dierent conclusions about the role of stand age,
climate and soil fertility on this ratio (or on the ratio of BP to
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1478 Collalti and Prentice
GPP, in some recent works that have made the distinction). The
potential role of management is a complicating factor that has
only recently been recognized. The diculty of generalization is
compounded by the fact that dierent measurement techniques
for both NPP (or BP) and GPP have been shown to yield dierent
values. However, the range of variation in the NPP:GPP ratio
appears to be substantially wider than was indicated by W98.
Moreover, there are sucient indications in the recent literature
for eects of forest type (although whether due to species
characteristics, climate or soil properties is unclear), stand age,
site fertility and management to motivate further investigations
of the controls on partitioning of GPP in forests.
Data survey
Data on annual GPP, NPP (or Ra) and NPP:GPP (or BP:GPP)
ratios in forest ecosystems were compiled for this review based
on previously published global data sets (e.g., De Lucia et al.
2007,Vicca et al. 2012,Tang et al. 2014,Campioli et al.
2015), supplemented by missing or more recent data from the
literature (Table S1 available as Supplementary Data at Tr ee
Physiology Online). NPP (or Ra) values obtained by assuming a
xed ratio to GPP were excluded from consideration. In the case
of multi-year estimates, average values across years were used.
Data were cross-checked to avoid repetition. The combined
data set included data from 211 records for more than 100
forest stands between 5 and 500 years, with a worldwide dis-
tribution. Data collected come by diverse methodologies (e.g.,
eddy covariance, chamber and biometric measurements, site-
level modelling) and represent dierent forests, which include
managed and non-managed forests, mixed or pure forests,
disturbed by re or not and with dierent levels of soil nutrients
availability at dierent MAT and precipitation.
The mean value for the NPP:GPP ratio in the data set is
statistically indistinguishable from that given by W98, i.e., 0.46
±0.12 (R2= 0.77, P<0.0001, n= 211) (Figure 5). However,
specic values ranged from 0.22 (Turner et al. 2003)to0.79
(Valentini et al. 2000), and the standard deviation was three
times larger than reported by W98. Including 17 additional sets
of data that included only the ratios of NPP to GPP changed
the slope mean value slightly, to 0.47, but not the standard
deviation (±0.12, n= 228). Net primary production:GPP ratios
by biome were 0.42 (±0.12, n= 48) for boreal sites, 0.48
(±0.12, n= 162) for temperate sites and 0.41 (±0.11,
n= 18) for tropical sites, thus presenting no evidence for a
consistent trend with latitude and (in particular) no evidence
for higher ratios of Ra:GPP in tropical sites, as might have been
expected if Radid not adapt/acclimate to temperature. However,
generally higher values of the NPP:GPP ratio (0.50 ±0.13, n
= 71) were shown by deciduous broad-leaf species than for
evergreen needle leaf forests (0.45 ±0.11, n= 12), evergreen
broad-leaf forests (0.44 ±0.11, n= 127) and mixed forests
(0.43 ±0.09, n= 18). These general ndings are consistent
Figure 5. Regression forced through the origin (R2= 0.77, P<0.0001,
n= 211) based on the present literature survey (red dots) and data from
Waring et al. (1998) (blue triangles).
with Luyssaert et al. (2007,2009),Malhi (2012),Vicca et al.
(2012) and Campioli et al. (2015), who also found that
temperate deciduous forests are slightly more ecient than
boreal and tropical forests in converting photosynthates into
biomass. Cannell and Thornley (2000) (citing Goetz and Prince
1998) speculated that conifers might generally have smaller
NPP:GPP ratios than broad-leaved species because of larger
foliage biomass, which increases maintenance respiration costs
but not necessarily their assimilation capacity. Values lower than
0.22 were not encountered, and it seems likely that values
below 0.2 cannot be physiologically maintained (Amthor 2000;
Keith et al. 2010).
What factors stabilize the NPP:GPP ratio or cause
it to vary?
Twenty years on, it is now possible to answer to the question
‘Net primary production of forests: a constant fraction of gross
primary production?’ (W98). Literature review has revealed
that it is not. There is a compelling body of evidence that
the NPP:GPP ratio is not a universal constant. However, there
are mechanisms at work that tend to stabilize this ratio at a
more constant value than would occur if Raand GPP were
independent. Dierent classes of mechanisms, tending either to
stabilize or to perturb the NPP:GPP ratio, are discussed below.
The role of carbohydrate reserves
To a limited degree, plants can buer the eects of altered
carbon demand—that is, seasonal or interannual variations in
Ra—by tapping into the pool of NSC (Cannell and Thornley
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Is NPP proportional to GPP? 1479
2000,Thornley and Cannell 2000,Trumbore 2006,Sala et al.
2012,Martínez-Vilalta et al. 2016). Over a longer time period
(a few years in trees), however, increased demand for NSC
to fuel increases in Ramust be reected in reduced tissue
growth (Collalti et al. 2018). This is a negative feedback
mechanism, which would be expected to stabilize the NPP:GPP
(Van Oijen et al. 2010), but not necessarily the BP:GPP ratio
(Collalti et al. in review). In a purely ‘active’ view of carbon
storage (i.e., storage has priority in current assimilates allocation
over the structural growth; e.g., Sala et al. 2012,Collalti et al.
2016), NSC increases at the expense of BP and thus would
not be accounted for, while it would be mirrored in a stepwise
reduction (seasonal or for longer periods) on the NPP:GPP
ratio. Conversely, in a ‘passive’ view of carbon storage (e.g.,
Kozlowski 1992), BP would outcompete reserve accumulation
and, thus, reecting narrower range of variations in the NPP:GPP
ratio. There is mounting evidence in support of an, at least
partial, active view of NSC accumulation (Dietze et al. 2014,
Martínez-Vilalta et al. 2016).
W98 argued that for every mole of GPP, about half must
be expended on Ra(see also Enquist et al. 2007). However,
biomass produced in one year may be derived from the previous
year’s photosynthates that had been allocated to NSC and
subsequently remobilized and used for growth or metabolism
(Gough et al. 2009,Vargas et al. 2009,Drake et al. 2016,
Solly et al. 2018). Asynchrony between (photosynthetic) source
and (utilization) sink implies some degree of uncoupling of
Ra, and consequently NPP, from GPP. These processes are
controlled in the short term by dierent environmental drivers:
photosynthesis by light, temperature, atmospheric CO2concen-
tration and water supply; respiration primarily by temperature.
Noting that NSC has often been observed to increase with tree
size (Sala and Hoch 2009,Richardson et al. 2013)andthe
potential variability of the NPP:GPP ratio due to the asynchrony
of source and sink might also be expected to increase with
tree size (Sala et al. 2012,Collalti et al. 2019, Collalti et al.
in review), in contrast to the limited variability generally seen in
herbaceous plants. However, how this regulation could occur at
the whole-tree level is not known (Sala et al. 2012). A useful
task for the future would be to compare the NPP:GPP ratio and
the BP:GPP ratio across forests in dierent stages of develop-
ment, allowing quantication of the fraction of GPP allocated
to non-structural components and—we hope—contributing to
an improved understanding of the regulation of the dierent
components of the forest carbon balance.
Responses to disturbance
Plants live in a dynamic environment and are subjected to a
variety of disturbances including ozone damage, re and pest
outbreaks—see, for example, the major eects of pine beetle
outbreaks, as described by Edburg et al. (2011). Disturbances
may force plants to deviate from homoeostasis between GPP and
Ra. The consistently higher BP:GPP ratio found by Campioli et al.
(2015) for managed stands relative to unmanaged ones is
likely to be attributable to thinning practices, which include
the removal of suppressed and moribund trees in order to
encourage the growth of younger and more ecient trees, and
improve their nutrient status (see also Vanninen and Mäkelä
2005,Grant et al. 2007,Manzoni et al. 2018). More generally, it
seems that any practice that leads to rejuvenation of the stands,
through lowering the mean stand age and competition between
individuals, may eectively tend to increase the NPP:GPP ratio
(Collalti et al. 2018,Doughty et al. 2018,Kunert et al. 2019).
Changes during stand development
It is generally agreed that photosynthesis and Raincrease in
parallel during early stand development. But what happens after
canopy closure, when LAI stabilizes (or even slightly decreases)
and GPP cannot be increased any further (Thornley and Cannell
2000)? If the NPP:GPP ratio is constant, respiration must then
become constant after canopy closure (Maier et al. 2004).
This is plausible for leaf respiration (and presumably also
for ne root respiration), because leaf and ne root biomass
are not expected to change substantially. How woody tissue
respiration could remain stable, despite a continuing increase
in woody biomass, is less obvious. There could be constant
turnover from live to dead woody tissues, or specic respiration
rates, and/or tissue nitrogen concentrations, could decrease. But
there is only limited evidence that the maintenance respiration
of woody biomass stabilizes (Hunt et al. 1999,Pruyn et al.
2000,Mäkelä and Valentine 2000,Vanninen and Mäkelä 2005,
Grant et al. 2007,Piao et al. 2010,Goulden et al. 2011), and
woody tissue respiration rates and nitrogen concentrations do
not appear to change signicantly (Machado and Reich 2006,
Reich et al. 2008). Stem respiration may instead continue to
increase, because of the continuing accumulation of sapwood
biomass as trees become taller (Saxe et al. 2000;Reich et al.
2006;Mori et al. 2010), resulting in a decline in the NPP:GPP
ratio over the course of stand development. Malhi (2012),
Malhi et al. (2015) and Doughty et al. (2018) argued that
there might be a link between high mortality rates (at least in dry
tropical and more fertile sites) and high NPP:GPP ratios because
of strategies in favour of inherently shorter life history and with
consequent low residence time (i.e., higher turnover rates) and
maintenance costs—suggesting that demographic traits might
contribute to dierences in NPP:GPP ratios among species.
Responses to temperature
Higher temperatures might be expected to accelerate the
kinetics of all biochemical processes in plants, up to high-
temperature thresholds beyond which enzymes are inactivated
(Saxe et al. 2000). There is also evidence, cited also in
textbooks (e.g., Larcher 2003), that the threshold temperature
for inactivation of respiration is generally higher than that for
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1480 Collalti and Prentice
photosynthesis. So it might be inferred that the NPP:GPP ratio
must decline at high temperatures. However, this reasoning
overlooks the fact that the specic respiration rates of plant
tissues (and the respiration rates of whole plants) acclimate
response to temperature (driven by enzyme kinetics) remains
steeply increasing (Heskel et al.2016), the base rate changes
in such a way that the rate of respiration at the new growth
temperature diers little from the previous rate (Atkin and
Tjoelker 2003,Giord 2003,Medlyn et al. 2005,Smith and
Dukes 2012,Atkin et al.2015,Slot and Katajima 2015,
Vanderwel et al. 2015,Reich et al. 2016). This acclimation
process implies that the NPP:GPP ratio is considerably more
stable with respect to growth temperature than textbook
physiology would suggest. However, a comprehensive, quan-
titative treatment of respiratory acclimation to temperature is
still missing.
Responses to soil fertility and drought
There is strong evidence that the ratio of BP to GPP varies
among sites dependent on their fertility (Vicca et al. 2012,
Fernández-Martínez et al. 2014), even if the mechanisms for
this response are not rmly established. Across biomes, carbon
allocation (below- versus above-ground) varies such that where
either nutrients or water are scarce, total below-ground carbon
allocation is greater (Gill and Finzi 2016). Total below-ground
carbon allocation includes not only allocation to ne roots
(production, respiration and turnover) but also exudation of
low molecular-weight organic compounds that are unaccounted
by classical measurements, which may constitute a substantial
fraction (up to 30%) of NPP (Hobbie 2006,Courty et al.
2010). Vicca et al. (2012) inferred that under conditions of
low nutrient availability (which can be either due to poor soils
or cold climates inhibiting microbial activity) a greater fraction of
assimilates are ‘lost’ through carbon transfer to root symbionts
and the rhizosphere. These ndings are consistent with the idea
that carbon allocation follows an adaptive programme, which
balances the demands of growth with the acquisition of water
and nutrients required to support growth.
There are known mechanisms that of course couple NPP to
GPP because ‘plants cannot respire what they did not photosyn-
thesize before’ (Giord 2003). But there is also now sucient
evidence to reject the hypothesis of a universal, constant or even
tightly variable ratio of NPP to GPP, as it is used as a simplifying
concept in a large number of ecosystem models. Ageing and
biomass accumulation, climate, soil fertility and management
have all been indicated to inuence the ratio of NPP (or BP) to
GPP likely in a non-mutually exclusive way. Currently available
data do not allow straightforward and clear generalizations
about each of these inuences: in part because of inconsistent
and contrasting results among dierent studies, in part because
of a widespread failure to distinguish NPP and BP and in
part because of unresolved methodological issues aecting the
measurement of NPP, Raand GPP. The determination of whole-
tree carbon budgets under dierent environmental conditions,
at dierent developmental stages and even after disturbances
remains a key issue for analysis. Without a clear understanding
of these processes, ecosystem models are likely to continue to
yield highly uncertain projections of forest carbon budgets in a
changing world.
Data accessibility statement
The database used in this analysis is provided in the Supporting
Information and is freely available.
Supplementary Data
Supplementary Data for this article are available at Tree Physiol-
ogy Online.
We are grateful for help and invaluable assistance from A. Ibrom
in conceiving and preparing the manuscript. The authors are also
indebted to A. Mäkelä, G. Matteucci and B.E. Medlyn for early
motivation, constructive comments and thoughtful suggestions,
and to E. Grieco for data compilation and checking. We are also
thankful to two anonymous reviewers for constructive comments
that helped us to improve the manuscript substantially. This work
is a contribution to the AXA Chair Programme in Biosphere
and Climate Impacts and the Imperial College initiative on
Grand Challenges in Ecosystems and the Environment (I.C.P.).
I.C.P. has also received funding from the European Research
Council under the European Union’s Horizon 2020 research
and innovation programme (grant agreement no: 787203
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... The CUE estimates compare well with previous literature. Collalti and Prentice (2019) found in a review covering different biomes that Fig. 10. Uncertainty of CUE estimates at (a, b) country level, (c, d) site-specific level, and (e, f) uncertainty of the relation between CUE and ETS. ...
... The temperature dependence of GPP and NPP estimated by West (2020) would suggest CUE of young stands to vary between 0.1 and 0.3 and of old stands between 0.05 and 0.2 within the temperature range of Finland. Our mean results fall between those of Collalti and Prentice (2019) and DeLucia et al. (2007). Our latitudinal trend is somewhat weaker than that shown by West (2020) and the absolute values of CUE are larger. ...
... Few data are available to evaluate the environmental responses of metabolic rates. Variability unaccounted for here could shift the predicted trend one way or another, depending on the impact (see review by Collalti and Prentice, 2019). ...
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There is evidence that carbon fluxes and stocks decrease with increasing latitude in boreal forests, suggesting a reduction in carbon use efficiency. While vegetation and soil carbon dynamics have been widely studied, the empirical finding that ectomycorrhizal fungi (ECM) become more abundant towards the north has not been quantitatively linked to carbon use efficiency. We formulated a conceptual model of combined fine-root and ECM carbon use efficiency (CUE) as NPP/GPP (net primary production/gross primary production). For this, we included the mycorrhiza as gains in plant NPP but considered the extramatrical hyphae as well as exudates as losses. We quantified the carbon processes across a latitudinal gradient using published eco-physiological and morphological measurements from boreal coniferous forests. In parallel, we developed two CUE models using large-scale empirical measurements amended with established models. All models predicted similar latitudinal trends in vegetation CUE and net ecosystem production (NEP). CUE in the ECM model declined on average by 0.1 from latitude 60 to 70 with overall mean 0.390 ± 0.037. NEP declined by 200 g m⁻² yr⁻¹ with mean 171 ± 79.4 g m⁻² yr⁻¹. ECM had no significant effect on predicted soil carbon. Our findings suggest that ECM can use a significant proportion of the carbon assimilated by vegetation and hence be an important driver of the decline in CUE at higher latitudes. Our model suggests the quantitative contribution of ECM to soil carbon to be less important but any possible implications through litter quality remain to be assessed. The approach provides a simple proxy of ECM processes for regional C budget models and estimates.
... In individual plants, carbon allocation is a highly dynamic process that changes during plant ontogeny to allow them to respond to changes in the environment. Carbon allocation to individual plant parts and their corresponding respiration is often decoupled from GPP and biomass (Collalti and Prentice, 2019). For example, when plants become carbon limited, as may happen during environmental stress like drought, cold, or defoliation, the proportional provision of carbon to Ra decreases, likely to free up resources to maintain allocation to defense (Huang et al., 2019a, b). ...
... These constant ratios promoted a simplification in the representation of production and growth in models, with NPP often computed as 50 % of annual GPP. Synthesis studies have challenged the constancy of these ratios for different biomes, stand ages, climates, and soils (DeLucia et al., 2007;Collalti and Prentice, 2019). Although some models may continue to use a constant ratio to obtain Ra, many other models now have more dynamic implementations to obtain Ra. ...
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Carbon allocation in vegetation is an important process in the terrestrial carbon cycle; it determines the fate of photoassimilates, and it has an impact on the time carbon spends in the terrestrial biosphere. Although previous studies have highlighted important conceptual issues in the definition and metrics used to assess carbon allocation, very little emphasis has been placed on the distinction between the allocation of carbon from gross primary production (GPP) and the allocation from net primary production (NPP). An important number of simulation models and conceptual frameworks are based on the concept that C is allocated from NPP, which implies that C is respired immediately after photosynthetic assimilation. However, empirical work that estimates the age of respired CO2 from vegetation tissue (foliage, stems, roots) shows that it may take from years to decades to respire previously produced photosynthates. The transit time distribution of carbon in vegetation and ecosystems, a metric that provides an estimate of the age of respired carbon, indicates that vegetation pools respire carbon of a wide range of ages, on timescales that are in conflict with the assumption that autotrophic respiration only consumes recently fixed carbon. In this contribution, we attempt to provide compelling evidence based on recent research on the age of respired carbon and the theory of timescales of carbon in ecosystems, with the aim to promote a change in the predominant paradigm implemented in ecosystem models where carbon allocation is based on NPP. In addition, we highlight some implications for understanding and modeling carbon dynamics in terrestrial ecosystems.
... Given that the European forested area is composed of a mix of differing-aged stands, and since forest C cycle processes may respond differently to climate factors at different ages (e.g. Collalti and Prentice, 2019;Collalti et al., 2020b;Huber et al., 2018Huber et al., , 2020Migliavacca et al., 2021), we developed a Composite Forest Matrix (CFM) consisting of a mixture of stands of different age, structure and associated biomass. Starting from the real stands, we generated a prescribed number of virtual stands in order to obtain representative model outputs of a larger set of different age-classes (with their associated forest attributes) to cover an entire rotation period (~140 years, depending on species), similar to the approach in in Bohn and Huth (2017). ...
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Forest management practices might act as nature-based methods to remove CO2 from the atmosphere and slow anthropogenic climate change and thus support an EU forest-based climate change mitigation strategy. However, the extent to which diversified management actions could lead to quantitatively important changes in carbon sequestration and stocking capacity at the tree level remains to be thoroughly assessed. To that end, we used a state-of-the-science bio-geochemically based forest growth model to simulate effects of multiple forest management scenarios on net primary productivity (NPP) and potential carbon woody stocks (pCWS) under twenty scenarios of climate change in a suite of observed and virtual forest stands in temperate and boreal European forests. Previous modelling experiments indicated that the capacity of forests to assimilate and store atmospheric CO2 in woody biomass is already being attained under business-as-usual forest management practices across a range of climate change scenarios. Nevertheless, we find that on the long-term, with increasing atmospheric CO2 concentration and warming, managed forests show both higher productivity capacity and a larger potential pool size of stored carbon than unmanaged forests as long as thinning and tree harvesting are of moderate intensity.
... However, increasing year-round heterotrophic respiration must be responsible for the overall shift to higher net carbon release, despite its smaller magnitude. This is because carbon release through autotrophic respiration offsets only about half of carbon uptake through photosynthesis (Collalti, Prentice, and Polle 2019). The increase in heterotrophic respiration is likely due to higher availability of carbon as a microbial energy source, increasing soil temperatures, and the presence of taliks, which provide unfrozen soil conditions year-round Pegoraro et al. 2020). ...
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Abrupt thaw could cause permafrost ecosystems to release more carbon than is predicted from gradual thaw alone. However, thermokarst feature mapping is limited in scope, and observed responses of carbon fluxes to abrupt thaw are variable. We developed a thermokarst detection algorithm that identifies thermokarst features from a single elevation dataset with 71.5 percent accuracy and applied it in Healy, Alaska. Additionally, we investigated the landscape-level variation in carbon dioxide and methane fluxes by extent of abrupt thaw using eddy covariance. Seven percent of the site was classified as thermokarst. Water tracks were the most extensive form of thermokarst, although small pits were much more numerous. Abrupt thaw was positively correlated with carbon uptake during the growing season, when increases in gross primary productivity outpaced increases in ecosystem respiration in vegetation-dense water tracks. However, this was outweighed by higher carbon release in thermokarst features during the nongrowing season. Additionally, abrupt thaw was positively correlated with methane production nearly year-round. Our findings support the hypothesis that abrupt thaw of permafrost carbon will contribute to the permafrost climate feedback above and beyond that associated with gradual thaw and highlights the need to map thermokarst and incorporate abrupt thaw into Earth System Models.
... Annual GPP (0.42 Pg C/yr) in 2020 for the 366 forest grid cells is close to the multi-year average annual GPP (Fig. 6D). The ratio between NPP and GPP (NPP/GPP, or carbon use efficiency) of Eucalyptus saligana (Sm.) forest varies with stand age slightly, ranging from 0.66 at age two years to 0.62 at age six years (Collalti and Prentice, 2019;Ryan et al., 2004). When the NPP/GPP ratio of 0.66 is used, an annual GPP of 0.42 Pg C in 2020 could result in an annual NPP of 0.28 Pg C in 2020, which is slightly higher than forest AGB gain estimate (0.26 Pg C) in 2020. ...
Australia experienced multi-year drought and record high temperatures, and massive forest fires occurred across the southeast in 2019 and early 2020. In the fire-affected forest areas, understory and often tree canopies were burned, and in-situ observations in late 2020 reported rapid vegetation recovery, including grasses, shrubs, and tree canopies from burned-but-not-dead eucalyptus trees. Considering the strong fire resilience and resistance of eucalyptus trees and above-average rainfall in 2020, we assessed how much and how quickly vegetation structure and biomass changed from loss to post-fire and drought recovery in 2020 for all forest areas in Australia. Here, we analyzed space-borne optical, thermal, and microwave images to assess changes in the structure and function of vegetation using four vegetation indices (VIs), leaf area index (LAI), solar-induced chlorophyll fluorescence (SIF), gross primary production (GPP), and aboveground biomass (AGB). We found that all eight variables show large losses in 2019, driven by fires and climate (drought and high temperature), but large gains in 2020, resulting from the high resilience of most trees to fire and rapid growth of understory vegetation under wet condition in 2020. In 2019, the forest area has an AGB loss of 0.20 Pg C, which is ~15% of the pre-fire AGB. Attribution analyses showed that both fire and climate (prior and co-occurring severe drought and record high temperatures) are responsible for the AGB loss in 2019, approximately 0.09 Pg C (fire) and 0.11 Pg C (climate), respectively. In 2020, the forest area has a total AGB gain of 0.26 Pg C, composed of 0.22 Pg C from fire-affected forest area and 0.04 Pg C from fire-unaffected forest area. Fire-adapted Eucalyptus forests and above-average annual precipitation in 2020 brought by a moderate La Niña drove the recovery of vegetation cover, productivity, and AGB. The results from this study shows the potential of multiple sensors for monitoring and assessing the impacts of fire and climate on the forest areas in Australia and their post-fire recovery.
... The two different stands and each stand over different years provided various scenarios of NSC flux. Accordingly, we were able to assess the impact of NSC on allocation and BP, specifically by estimating the deviations between GPP and C consumption, between BP and NPP, and between BPE and CUE, which are all of great importance in C cycle modeling and estimating C turnover rate, but it remains unclear (Collalti & Prentice, 2019). These deviations are best demonstrated by the differences between the ratio of annual R i /GPP (i.e., without specifying NSC, flux ratio-based) and the slope of R i and GPP regression (i.e., accounting for NSC, flux regressionbased; Appendix S1: Figure S2). ...
Carbon (C) allocation and non‐structural carbon (NSC) dynamics play essential roles in plant growth and survival under stress and disturbance. However, quantitative understanding of these processes remains limited. Here we propose a framework, where we connect commonly measured carbon cycle components (eddy covariance fluxes of canopy CO2 exchange, soil CO2 efflux, and allometry‐based biomass and net primary production) by a simple mass balance model, to derive ecosystem‐level NSC dynamics (NSCi), C translocation (dCi) to and the biomass production efficiency (BPEi) in above‐ and below‐ground plant (i = agp and bgp) compartments. We applied this framework to two long‐term monitored loblolly pine (Pinus taeda) plantations of different ages in North Carolina and characterized the variations of NSC and allocation in years under normal and drought conditions. The results indicated that the young stand did not have net NSC flux at the annual scale whereas the mature stand stored a near‐constant proportion of new assimilates as NSC every year under normal conditions, being comparable in magnitude to new structural growth. Roots consumed NSC in drought and stored a significant amount of NSC post‐drought. The above‐ and below‐ground dCi and BPEi varied more from year to year in the young stand and approached a relatively stable pattern in the mature stand. The belowground BPEbgp differed the most between the young and mature stands, and was most responsive to drought. With the internal C dynamics quantified, this framework may also improve the biomass production estimation that reveals the variations resulting from droughts. Overall, these quantified ecosystem‐scale dynamics were consistent with existing evidence from tree‐based manipulative experiments and measurements, and demonstrated that combining the continuous fluxes as proposed here can provide additional information about plant internal C dynamics. Given that it is based on broadly available flux data, the proposed framework is promising to improve the allocation algorithms in ecosystem C cycle models, and offers new insights into observed variability in soil‐plant‐climate interactions.
According to the United Nations International Children's Emergency Fund (UNICEF) assessment report released in 2021, South Asian countries were among the most vulnerable in the world to the effects of climate change on future generations. Hence it is become crucial to assess how resilient the ecosystems are to these changes. The current study incorporated a novel approach, the Combined Ecological Resiliency Indices Approach (CERIA), to assess ecological resiliency status at various scales during hydroclimatic disturbances. Water and carbon use efficiency (WUE and CUE, respectively) were used as indicators for the examination of ecological resilience. The standardized Precipitation Index (SPI) was adopted to assess the initial stage of hydroclimatic disturbances (meteorological drought). A resiliency analysis based on combined Rd and Rd' indices (derived from WUE and CUE, respectively) revealed that just 1.87% land cover area of the entire SAARC (South Asian Association for Regional Cooperation) region's total 17 land cover classes was resilient to meteorological drought. At the river basin scale, only 16.58% of the total 62 river basins were found resilient. Only 11 (27.46%) of the 21 climate classes on the Koppen climate classification scale were resilient to the hydro-climatic disturbance period. To achieve the United Nations sustainable development goals (SDGs goal-2 and goal-13) of ‘No Hunger’ and ‘Protect the Planet’, the Joint Ecosystem Resiliency Enhancement Programme (JEREP) should be adopted in land cover, river basins, or climatic classes of the SAARC region that were highly affected.
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Areas undergoing forest restoration need to be monitored to achieve ecosystem services. This work was carried out to evaluate the establishment of the riparian forest area in the restoration process, after 18 years of intervention, through temporal analysis of the landscape, biotic and soil indicators. Moreover, a temporal analysis of the landscape, biomass and Gross Primary Production (GPP) was carried out, via geoprocessing, at five-intervals within the period from 2002 to 2020, as well as biotic indicators (seed rain, seed bank, seedlings), and edaphic indicators from 2019 to 2020. The seed rain presented 1,197 propagules, belonging to 27 different species. The soil seed bank showed higher density in the rainy season (21.3 seeds/m ² ), 25 seeds, seven species, and only one botanical family recorded. In the seedling bank, 1,193 seedlings were reported, belonging to 28 botanical families, in which 57% of the individuals are arboreal-shrubby of the forest. Edaphic conditions improved compared to the initial project implementation. In 2010 using the temporal analysis of the landscape, the planting area was 100% covered with dense vegetation. For biomass and the GPP is a linear increment over time. The successional stage of the area is advanced, with a significant representation of secondary and climax species. The monitoring favored understanding the dynamics of the restoration environment and conservation.
Full-text available
Areas undergoing forest restoration need to be monitored to achieve ecosystem services. This work was carried out to evaluate the establishment of the riparian forest area in the restoration process, after 18 years of intervention, through temporal analysis of the landscape, biotic and soil indicators. Moreover, a temporal analysis of the landscape, biomass and Gross Primary Production (GPP) was carried out, via geoprocessing, at five-intervals within the period from 2002 to 2020, as well as biotic indicators (seed rain, seed bank, seedlings), and edaphic indicators from 2019 to 2020. The seed rain presented 1,197 propagules, belonging to 27 different species. The soil seed bank showed higher density in the rainy season (21.3 seeds/m ² ), 25 seeds, seven species, and only one botanical family recorded. In the seedling bank, 1,193 seedlings were reported, belonging to 28 botanical families, in which 57% of the individuals are arboreal-shrubby of the forest. Edaphic conditions improved compared to the initial project implementation. In 2010 using the temporal analysis of the landscape, the planting area was 100% covered with dense vegetation. For biomass and the GPP is a linear increment over time. The successional stage of the area is advanced, with a significant representation of secondary and climax species. The monitoring favored understanding the dynamics of the restoration environment and conservation.
Full-text available
Phenological responses of vegetation to global warming impact ecosystem gross primary production and evapotranspiration. However, high resolution and large spatial scale observational evidence of such responses in undisturbed core forest areas is lacking. Here, we analyse MODIS satellite data to assess monthly trends in gross primary productivity and evapotranspiration across undisturbed core forest areas in Europe between 2000 and 2020. Both parameters increased during the early spring and late autumn in nearly half of the total undisturbed core forest area (3601.5 km2). Enhanced productivity drove increased water-use-efficiency (the ratio of gross primary productivity to evapotranspiration). However, productivity increases during spring and autumn were not sufficient to compensate for summertime decreases in 25% of core forest areas. Overall, 20% of total gross primary productivity across all European forest core areas was offset by forest areas that exhibited a net decrease in productivity.
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The future trajectory of atmospheric CO2 concentration depends on the development of the terrestrial carbon sink, which in turn is influenced by forest dynamics under changing environmental conditions. An in-depth understanding of model sensitivities and uncertainties in non steady-state conditions is necessary for reliable and robust projections of forest development and under scenarios of global warming and CO2-enrichment. Here, we systematically assessed if a bio-geochemical process-based model (3D-CMCC-CNR), which embeds similarities with many other vegetation models, applied in simulating net primary productivity (NPP) and standing woody biomass (SWB), maintained a consistent sensitivity to its 55 input parameters through time, during forest-ageing and-structuring as well as under climate-change scenarios. Overall, the model applied at three contrasting European forests showed low sensitivity to the majority of its parameters. Interestingly, model sensitivity to parameters varied through the course of >100 years of simulations. In particular, the model showed a large responsiveness to the allometric parameters used for initialize forest carbon-and nitrogen-pools early in forest simulation (i.e. for NPP up to ~37%, 256 g C m-2 yr-1 and for SWB up to ~90%, 65 t C ha-1 , when compared to standard simulation), with this sensitivity decreasing sharply during forest development. At medium-to longer-time scales, and under climate-change scenarios, the model became increasingly more sensitive to additional and/or different parameters controlling biomass accumulation and autotrophic respiration (i.e. for NPP up to ~30%, 167 g C m-2 yr-1 and for SWB up to ~24%, 64 t C ha-1 , when compared to standard simulation). Interestingly, model outputs were shown to be more sensitive to parameters and processes controlling stand development rather than to climate-change (i.e. warming and changes in atmospheric CO2 concentration) itself although model sensitivities were generally higher under climate-change scenarios. Our results suggest the need for sensitivity and uncertainty analyses that cover multiple temporal scales along forest developmental stages to better assess the potential of future forests to act as a global terrestrial carbon sink.
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The cycling of carbon (C) between the Earth surface and the atmosphere is controlled by biological and abiotic processes that regulate C storage in biogeochemical compartments and release to the atmosphere. This partitioning is quantified using various forms of C-use efficiency (CUE) – the ratio of C remaining in a system to C entering that system. Biological CUE is the fraction of C taken up allocated to biosynthesis. In soils and sediments, C storage depends also on abiotic processes, so the term C-storage efficiency (CSE) can be used. Here we first review and reconcile CUE and CSE definitions proposed for autotrophic and heterotrophic organisms and communities, food webs, whole ecosystems and watersheds, and soils and sediments using a common mathematical framework. Second, we identify general CUE patterns; for example, the actual CUE increases with improving growth conditions, and apparent CUE decreases with increasing turnover. We then synthesize >5000CUE estimates showing that CUE decreases with increasing biological and ecological organization – from unicellular to multicellular organisms and from individuals to ecosystems. We conclude that CUE is an emergent property of coupled biological–abiotic systems, and it should be regarded as a flexible and scale-dependent index of the capacity of a given system to effectively retain C.
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Forest carbon use efficiency (CUE, the ratio of net to gross primary productivity) represents the fraction of photosynthesis that is not used for plant respiration. Although important, it is often neglected in climate change impact analyses. Here, we assess the potential impact of thinning on projected carbon-cycle dynamics and implications for forest CUE and its components (i.e. gross and net primary productivity and plant respiration), as well as on forest biomass production. Using a detailed process-based forest-ecosystem-model forced by climate outputs of five Earth System Models under four Representative- climate scenarios, we investigate the sensitivity of the projected future changes in the autotrophic carbon budget of three representative European forests. We focus on changes in CUE and carbon stocks as a result of warming, rising atmospheric CO 2 concentration and forest thinning. Results show that autotrophic carbon sequestration decreases with forest development and the decrease is faster with warming and in unthinned forests. This suggests that the combined impacts of climate change and changing CO2 concentrations, lead the forests to grow faster mature earlier but also die younger. In addition, we show that under future climate conditions, forest thinning could mitigate the decrease in CUE, increase carbon allocation into more recalcitrant woody-pools and reduce physiological-climate-induced mortality risks. Altogether, our results show that thinning can improve the efficacy of forest-based mitigation strategies and should be carefully considered within a portfolio of mitigation options.
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Fine roots support the water and nutrient demands of plants and supply carbon to soils. Quantifying turnover times of fine roots is crucial for modeling soil organic matter dynamics and constraining carbon cycle-climate feedbacks. Here we challenge widely used isotope-based estimates suggesting the turnover of fine roots of trees to be as slow as a decade. By recording annual growth rings of roots from woody plant species, we show that mean chronological ages of fine roots vary from <1 to 12 years in temperate, boreal and sub-arctic forests. Radiocarbon dating reveals the same roots to be constructed from 10 ± 1 year (mean ± 1 SE) older carbon. This dramatic difference provides evidence for a time lag between plant carbon assimilation and production of fine roots, most likely due to internal carbon storage. The high root turnover documented here implies greater carbon inputs into soils than previously thought which has wide-ranging implications for quantifying ecosystem carbon allocation.
Full-text available
The cycling of carbon (C) between the Earth surface and the atmosphere is controlled by biological and abiotic processes that regulate C storage in biogeochemical compartments and release to the atmosphere. This partitioning is quantified using various forms of C-use efficiency (CUE) – the ratio of C remaining in a system over C entering that system. Biological CUE is the fraction of C taken up allocated to new biomass. In soils and sediments C storage depends also on abiotic processes, so the term C-storage efficiency (CSE) can be used. Here we first review and reconcile CUE and CSE definitions proposed for autotrophic and heterotrophic organisms and communities, food webs, whole ecosystems, and soils and sediments using a common mathematical framework. Second, we identify general CUE patterns, such as the CUE increase with improving growing conditions, and apparent decrease due to turnover. We then synthesize > 6000 CUE estimates showing that CUE decreases with increasing biological and ecological organization – from unicellular to multicellular organisms, and from individuals to ecosystems. We conclude that CUE is an emergent property of coupled biological-abiotic systems, and it should be regarded as a flexible and scale-dependent index of the capacity of a given system to effectively retain C.
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Why do some forests produce biomass more efficiently than others? Variations in Carbon Use Efficiency (CUE: total Net Primary Production (NPP)/ Gross Primary Production (GPP)) may be due to changes in wood residence time (Biomass/NPPwood), temperature, or soil nutrient status. We tested these hypotheses in 14, one ha plots across Amazonian and Andean forests where we measured most key components of net primary production (NPP: wood, fine roots, and leaves) and autotrophic respiration (Ra; wood, rhizosphere, and leaf respiration). We found that lower fertility sites were less efficient at producing biomass and had higher rhizosphere respiration, indicating increased carbon allocation to belowground components. We then compared wood respiration to wood growth and rhizosphere respiration to fine root growth and found that forests with residence times <40 yrs had significantly lower maintenance respiration for both wood and fine roots than forests with residence times >40 yrs. A comparison of rhizosphere respiration to fine root growth showed that rhizosphere growth respiration was significantly greater at low fertility sites. Overall, we found that Amazonian forests produce biomass less efficiently in stands with residence times >40 yrs and in stands with lower fertility, but changes to long-term mean annual temperatures do not impact CUE.
Carbon (C) allocation plays a central role in tree responses to environmental changes. Yet, fundamental questions remain about how trees allocate C to different sinks, for example, growth vs storage and defense. In order to elucidate allocation priorities, we manipulated the whole‐tree C balance by modifying atmospheric CO2 concentrations [CO2] to create two distinct gradients of declining C availability, and compared how C was allocated among fluxes (respiration and volatile monoterpenes) and biomass C pools (total biomass, nonstructural carbohydrates (NSC) and secondary metabolites (SM)) in well‐watered Norway spruce (Picea abies) saplings. Continuous isotope labelling was used to trace the fate of newly‐assimilated C. Reducing [CO2] to 120 ppm caused an aboveground C compensation point (i.e. net C balance was zero) and resulted in decreases in growth and respiration. By contrast, soluble sugars and SM remained relatively constant in aboveground young organs and were partially maintained with a constant allocation of newly‐assimilated C, even at expense of root death from C exhaustion. We conclude that spruce trees have a conservative allocation strategy under source limitation: growth and respiration can be downregulated to maintain ‘operational’ concentrations of NSC while investing newly‐assimilated C into future survival by producing SM.