, 684 (2008);
et al.Stefano Manzoni,
The Global Stoichiometry of Litter Nitrogen
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Copenhagen. It is supported by funding agencies in
Denmark (Forskningsrådet for Natur og Univers),
Belgium (Fonds National de la Recherche Scientifique),
France (Institut Polaire Française and Institut
National des Science l’Univers/CNRS), Germany (AWI),
Iceland (Rannís), Japan (Ministry of Education,
Culture, Sports, Science and Technology), Sweden
(Polarforskningssekretariatet), Switzerland (Der
Schweizerische Nationalfonds) and the United States
(NSF, Office of Polar Programs).
Supporting Online Material
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Published online 19 June 2008;
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The Global Stoichiometry of Litter
Stefano Manzoni,1Robert B. Jackson,2John A. Trofymow,3Amilcare Porporato1*
Plant residue decomposition and the nutrient release to the soil play a major role in global carbon and
and its release in mineral forms are mainly controlled by the initial chemical composition of the residues.
We used a data set of ~2800 observations to show that these global nitrogen-release patterns can be
explained by fundamental stoichiometric relationships of decomposer activity. We show how litter quality
initial nitrogen concentration, a strategy used broadly by bacteria and consumers across trophic levels.
while providing energy to the decomposers,
decomposers (immobilized) and thus accumulate
in the litter. Typically, net nitrogen (N) release in
mineral forms (ammonium and nitrate) from a
given plant residue (net mineralization) only oc-
curs after N concentration reaches a critical value
(1). Knowledge of this threshold and how it is
related to biogeochemical or climatic factors is
in natural and agricultural settings (4–6), to im-
prove our understanding of ecosystem stoichi-
ometry (7, 8), and to constrain biogeochemical
models (9). The biological degradation of litter is
mainly carried out by microbial decomposers, in-
cluding bacteria and fungi, and their grazers,
which have higher N:C values compared with
most litter types (1). This creates a high N de-
mand,and, even though a considerable fraction of
assimilated C is respired, the decomposers often
still require some inorganic N uptake during at
least the early phases of decomposition. The de-
composer N:C and the respiration rate (comple-
mentary to the carbon-use efficiency) define the
actual nutrient requirement of the decomposers
(9–11). Although the decomposer N:C ratios have
beenobserved tobe relatively constantacross eco-
systems and litter types, the causes of patterns of
variation in carbon-use efficiency are still unclear.
to biological degradation (1–3). During this
process, litter carbon (C) is respired to CO2
We analyzed litter decomposition data includ-
ing the temporal evolution of both carbon and ni-
trogen, as measured in litterbags left to decompose
large branches and logs along decomposition chro-
nosequences. On the basis of 55 litter types classi-
to 3% (13), we show that the carbon-use efficiency
tends to increase with higher initial substrate N:C
ratio, which corresponds to a more-efficient ni-
trogen use and a less-efficient carbon use for N-
and low N:C). In turn, low carbon-use efficiencies
allow net mineralization to occur early during de-
composition, even in relatively N-poor residues.
The dynamics of net N immobilization, ac-
cumulation, and mineralization have been de-
scribed mathematically with mass balance
equations (9, 11, 14). We developed a general set
analytical curves of N accumulation and release
acteristics can be assumed relatively constant in
time (13). Specifically, the general expression for
the fraction of initial litter nitrogen content, n, as a
function of the fraction of remaining carbon con-
tent in the litter sample, c, can be written inde-
pendently of the specific decomposition model as
nðcÞ ¼ crB
where rL,0is the initial litter N:C ratio, rBis the
carbon-use efficiency (i.e., amount of C in new
biomass per unit C decomposed). Thus, the N
dynamics are represented in terms of the
fraction of remaining litter C content, avoiding
any explicit account of the temporal variability
of decomposition rates caused by climatic fac-
tors or nutrient limitation. On the basis of data
from 15 data sets containing observations at
more than 60 sites worldwide (table S1), this
universal representation of N immobilization
and release curves appears to be valid across
diverse terrestrial ecosystems and with different
initial litter N:C values.
During decomposition, the fraction of remain-
ing N and lost C move along the curves from left
to right at a speed dictated by biogeochemical and
environmental conditions (Fig. 1). All the curves
show slower N loss than C loss, meaning that N
tends to accumulate, and the N:C ratio of the litter
increases throughout decomposition. Where the
curves increase with respect to the initial con-
dition, not only is N retained more efficiently than
C, but net immobilization occurs. At the point on
each curve where n is maximal, immobilization
ends and net mineralization begins. Conversely, if
the curve decreases monotonically there is no
initial net immobilization, as in Fig. 1, A and B.
The maximum of the N release curve thus cor-
responds to the litter critical N concentration,
C ratio as a function of the decomposer character-
istics, rCR= e·rB(9, 10). In general, the lower rCR
is, the earlier N release occurs, even in N-poor
residues. Moreover, when rCR< rL,0, net release
occurs from the beginning of decomposition.
Conversely, if rCR is high, large amounts of
mineral N have to be immobilized to increase the
litter N concentration to its critical value.
The litter decomposition observations and
of the litter rCRand decomposer characteristics.
Using the analytical N release curve provides a
onset of mineralization based on regressions of
field observations (4, 15) and offers robust esti-
mates of rCRand the decomposer parameters, e
and rB. In particular, rBdoes not vary system-
atically along gradients of organic matter and
litter N:C and typically remains in the range of
We thus assumed an average value of rB= 0.1
and fitted the remaining free parameter, e, for
each litter type (13). For given values of rBand e
well onto a single 1:1 curve (Fig. 2 and fig. S1),
showing that the variation of e alone explains
most of the variability in the data.
We assessed how rCRand e, which are simply
proportional when rBis a constant, respond to
changes in climatic variables and initial litter con-
ditions. Parton et al. (18) and Moore et al. (15)
noted that the N release patterns observed in two
1Civil and Environmental Engineering Department, Duke
University, Durham, NC 27708, USA.2Department of Biology
and Nicholas School of the Environment, Duke University,
Durham, NC 27708, USA.3Canadian Forest Service, Pacific
Forestry Centre, Victoria, BC V8Z 1M5, Canada.
*To whom correspondence should be addressed. E-mail:
1 AUGUST 2008VOL 321
on July 1, 2009
continental-scale decomposition experiments do
not depend on climatic variables. Our analysis,
which includes many additional data sets (table
S1), not only confirms the lack of a significant
correlation between rCRand mean annual precip-
power law relationship between rCRand rL,0(Fig.
residues are able to begin mineralization even
when the litter N concentration is still relatively
low. In fact, for a given rB, lower values of rCR
imply lower values of e (i.e., higher fractions of
respired C), indicating that some decomposers
with low energetic efficiency may be able to
decompose low-N litter without necessarily hav-
ing to immobilize much inorganic N. A low rCR
(and low e) also explains the low N immobi-
wood (19). Apparently, decomposers are able to
use the limited but relatively reliable N bound to
organic compounds, thus reducing their depen-
dence on the less-reliable or less-accessible in-
organic pool. Nevertheless, because estimated
values of rCRare generally higher than rL,0(data
points above the dashed line in Fig. 3A), some
to site effects. In fact, a trend for higher N accu-
mulation in litters from sites with higher soil N:C
ratios has been reported (15), although there are
not enough data to test for such an effect globally.
Lastly, the pattern of decline in e as a func-
tion of rL,0appears to be independent of pos-
sible changes in rB(shaded area in Fig. 3A).
Remarkably, a similar pattern has also been ob-
served [Fig. 3B; see also (13)] at different time
scales and trophic levels in bacterial cultures
(20), in aquatic bacteria (21), and in terrestrial
and aquatic grazers (22–25). The generality of
such a result hints at a common mechanism of
carbon utilization across diverse ecosystems and
trophic levels, where carbon “waste” occurs under
restricted nutrient availability. From a metabolic
perspective, the observation of low e may be
related to regulation of catabolic reactions in low-
nutrient conditions to maintain a stable cellular
composition (20, 21) or to increased C throughput
by the decomposers or decomposer food web for
obtaining N from recalcitrant substrates (17, 26).
A better understanding of the causes of this be-
havior is of fundamental interest and could reveal
the constraints on decomposer community func-
tioning under N-poor conditions, an important
goal for improving biogeochemical modeling. In
biogeochemical models of soil and litter, the
carbon-use efficiency of decomposers is general-
ly assumed constant or to decrease with substrate
N:C, in agreement with our results (14, 17, 27).
However, our estimates are generally lower than
the efficiency values typically assumed, suggest-
ing that current models might underestimate the
heterotrophic respiration flux per unit mass of
decomposed litter or organic matter.
In summary, the N-release patterns of de-
composing litter appear to be regulated by the
initial chemical composition of the litter and the
stoichiometric requirements of the decomposers
(Fig. 1). In particular, the critical N:C ratio, below
which net immobilization occurs, is uncorrelated
with climatic variables but strongly correlated with
initial litter chemistry (Fig. 3A). Because decom-
Fig. 2. Normalized representation of the nitrogen release curves. Plots of the normalized variable x =
(rL– rB)/(rL,0– rB) (eq. S5) against ce/(1–e)for litters of different origin [(A) broadleaved tree and shrub
leaves,□, and conifer needles,▲; (B) grass leaves,○, and woody residues,■], showing that the analytical
N release curves (Eq. 1) fitted to the data with the only free parameter e is able to capture most of the
variability in all litter types.
Fig. 1. Nitrogen release patterns across litter types. (A to F) Observed and modeled fractions of initial
are represented by●and solid lines; data from the CIDET data set (12, 15), by□and dashed lines.
VOL 3211 AUGUST 2008
on July 1, 2009
poser N:C ratio is relatively constant, this pattern
suggests that the decomposer communities are able
to adapt partially to low-nitrogen substrates (i.e.,
low rL,0) by decreasing their C-use efficiency and
thus the critical N:C of the litter (Fig. 3A). Such a
pattern has been observed in aquatic environments
and at other trophic levels (21–25) and appears to
be a universal response of decomposers in nutrient-
poor conditions (Fig. 3B). Decreasing efficiency
results in higher heterotrophic respiration per unit
mass of litter humified or unit nutrient released,
suggesting that the soil carbon cycle is likely
more open than currently thought.
References and Notes
1. B. Berg, C. A. McClaugherty, Plant Litter: Decomposition,
Humus Formation, Carbon Sequestration (Springer,
2. M. J. Swift, O. W. Heal, J. M. Anderson, Decomposition
in Terrestrial Ecosystems, vol. 5 of Studies in Ecology
(Univ. of California Press, Berkeley, 1979).
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6. B. Berg, G. Ekbohm, Ecology 64, 63 (1983).
7. C. C. Cleveland, D. Liptzin, Biogeochemistry 85, 235 (2007).
8. R. W. Sterner, J. J. Elser, Ecological Stoichiometry: The
Biology of Elements from Molecules to the Biosphere
(Princeton Univ. Press, Princeton, NJ, 2002).
10. G. I. A˚gren, E. Bosatta, Theoretical Ecosystem Ecology:
Understanding Element Cycles (Cambridge Univ. Press,
11. E. Bosatta, H. Staaf, Oikos 39, 143 (1982).
12. J. A. Trofymow, CIDET, “The Canadian Intersite
Decomposition Experiment (CIDET): Project and site
establishment report,” Tech. Rep. No. BC-X-378 (Pacific
Forestry Centre, Victoria, Canada, 1998).
13. See supporting materials on Science Online.
14. W. J. Parton, D. S. Schimel, C. V. Cole, D. S. Ojima,
Soil Sci. Soc. Am. J. 51, 1173 (1987).
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B. D. Titus, Ecosystems (New York) 9, 46 (2006).
16. S. C. Hart, Ecology 80, 1385 (1999).
17. H. W. Hunt et al., Biol. Fertil. Soils 3, 57 (1987).
18. W. Parton et al., Science 315, 361 (2007).
19. O. N. Krankina, M. E. Harmon, A. V. Griazkin, Can. J. For.
Res. 29, 20 (1999).
20. J. B. Russell, G. M. Cook, Microbiol. Rev. 59, 48 (1995).
21. P. A. del Giorgio, J. J. Cole, Annu. Rev. Ecol. Syst. 29, 503
22. J. J. Elser et al., Nature 408, 578 (2000).
23. W. J. Mattson, Annu. Rev. Ecol. Syst. 11, 119 (1980).
24. T. J. Pandian, M. P. Marian, Freshw. Biol. 16, 93 (1986).
25. F. Slansky, P. Feeny, Ecol. Monogr. 47, 209 (1977).
26. J. M. Craine, C. Morrow, N. Fierer, Ecology 88, 2105
27. W. B. McGill, H. W. Hunt, R. G. Woodmansee, J. O. Reuss,
in Terrestrial Nitrogen Cycles: Processes, Ecosystem
Strategies and Management Impacts, F. E. Clark,
T. Rosswall, Eds. (Ecological Bulletins, Stockholm, 1981),
vol. 33, pp. 49–115.
28. M. E. Harmon, Long-Term Ecological Research (LTER)
Intersite Litter Decomposition Experiment (LIDET), Forest
Science Data Bank code TD023, Corvallis, OR, 2007,
29. H. L. Gholz, D. A. Wedin, S. M. Smitherman, M. E. Harmon,
W. J. Parton, Glob. Change Biol. 6, 751 (2000).
30. S. C. Hart, G. E. Nason, D. D. Myrold, D. A. Perry, Ecology
75, 880 (1994).
31. This research was supported by Department of Energy
(DOE) Forest-Atmosphere Carbon Transfer and Storage
project (FACT-1), NSF DEB 0235425 and 0717191, and
DOE PER 64242-0012346. LIDET data sets were provided
by the Forest Science Data Bank, a partnership between
the Department of Forest Science, Oregon State
University, and the U.S. Forest Service Pacific Northwest
Research Station, Corvallis, Oregon. Significant funding
for these data was provided by the NSF Long-Term
Ecological Research program (DEB-02-18088). Funding
for the CIDET experiment was provided by Climate Change
and Ecosystem Processes Network of the Canadian Forest
Service and Natural Resources Canada Panel on Energy
Research Development. We also thank G. Katul, D. Richter,
and two anonymous reviewers for useful comments.
Supporting Online Material
Materials and Methods
29 April 2008; accepted 1 July 2008
Regulation of CD45 Alternative
Splicing by Heterogeneous
Shalini Oberdoerffer,1Luis Ferreira Moita,2* Daniel Neems,1Rui P. Freitas,2*
Nir Hacohen,2,3Anjana Rao1†
The transition from naïve to activated T cells is marked by alternative splicing of pre-mRNA encoding the
transmembrane phosphatase CD45. Using a short hairpin RNA interference screen, we identified
heterogeneous ribonucleoprotein L-like (hnRNPLL) as a critical inducible regulator of CD45 alternative
and sufficient for CD45 alternative splicing. Depletion or overexpression of hnRNPLL in B and T cell
lines and primary T cells resulted in reciprocal alteration of CD45RA and RO expression. Exon array
analysis suggested that hnRNPLL acts as a global regulator of alternative splicing in activated T cells.
Induction of hnRNPLL during hematopoietic cell activation and differentiation may allow cells to rapidly
shift their transcriptomes to favor proliferation and inhibit cell death.
t is estimated that greater than 75% of genes
yield alternative transcripts, contributing to
considerable functional diversity within the
genome (1, 2). SR (serine-arginine rich) proteins
are key positive regulators of alternative splicing
that bind enhancer sequences on nascent tran-
Fig. 3. Effect of litter quality on decom-
poser stoichiometry. (A) Decomposer effi-
ciency, e (left), or rCR(right) as a function
of rL,0when rB= 0.1. Symbols indicate
different litter types as in Fig. 2;◊and ♦
refer to a decomposing log (rB= 0.122)
and the underlying soil (rB= 0.135), re-
spectively [data elaborated after (16, 30)].
The solid line is a linear least square fit of
the log-transformed rCRand rL,0(rCR=
0.45 × rL,0
shaded area shows the effects on e of
different rBaround 0.1 (solid line). The
dashed curve indicates points where rCR=
rL,0: Litter points above this curve need to
immobilize N; points below release N
since the beginning of decomposition.
(B) Estimates of e as a function of the ratio
between food source N:C (rF) and consumer
N:C (rB) at different trophic levels:□, ter-
restrial plant residue decomposers (this
study); +, marine bacteria (21);○, terres-
trial larvae (25);●, terrestrial insects (23);
and ×, aquatic insects (24). The solid line is a
linear least square fit of the log-transformed
e and rF/rB[e = 0.43 × (rF/rB)0.60; R = 0.72;
P < 0.0001].
0.76; R = 0.88; P < 0.0001). The
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