UC Irvine
Faculty Publications
Title
Microbial abundance and composition influence litter decomposition response to
environmental change
Permalink
https://escholarship.org/uc/item/5bg595vm
Journal
Ecology, 94(3)
ISSN
0012-9658
Authors
Allison, Steven D
Lu, Ying
Weihe, Claudia
et al.
Publication Date
2013-03-01
DOI
10.1890/12-1243.1
Copyright Information
This work is made available under the terms of a Creative Commons Attribution
License, availalbe at https://creativecommons.org/licenses/by/4.0/
Peer reviewed
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University of California
Ecology, 94(3), 2013, pp. 714–725
Ó 2013 by the Ecological Society of America
Microbial abundance and composition influence litter decomposition
response to environmental change
STEVEN D. ALLISON,
1,2,3
YING LU,
1
CLAUDIA WEIHE,
1
MICHAEL L. GOULDEN,
2
ADAM C. MARTINY,
1,2
KATHLEEN K. TRESEDER,
1
AND JENNIFER B. H. MARTINY
1
1
Department of Ecology and Evolutionary Biology, University of California, Irvine, California 92697 USA
2
Department of Earth System Science, University of California, Irvine, California 92697 USA
Abstract. Rates of ecosystem processes such as decomposition are likely to change as a
result of human impacts on the environment. In southern California, climate change and
nitrogen (N) deposition in particular may alter biological communities and ecosystem
processes. These drivers may affect decomposition directly, through changes in abiotic
conditions, and indirectly through changes in plant and decomposer communities. To assess
indirect effects on litter decomposition, we reciprocally transplanted microbial communities
and plant litter among control and treatment plots (either drought or N addition) in a
grassland ecosystem. We hypothesized that drought would reduce decomposition rates
through moisture limitation of decomposers and reductions in plant litter quality before and
during decomposition. In contrast, we predicted that N deposition would stimulate
decomposition by relieving N limitation of decomposers and improving plant litter quality.
We also hypothesized that adaptive mechanisms would allow microbes to decompose litter
more effectively in their native plot and litter environments. Consistent with our first
hypothesis, we found that drought treatment reduced litter mass loss from 20.9% to 15.3%
after six months. There was a similar decline in mass loss of litter inoculated with microbes
transplanted from the drought treatment, suggesting a legacy effect of drought driven by
declines in microbial abundance and possible changes in microbial community composition.
Bacterial cell densities were up to 86% lower in drought plots and at least 50% lower on litter
derived from the drought treatment, whereas fungal hyphal lengths increased by 13–14% in the
drought treatment. Nitrogen effects on decomposition rates and microbial abundances were
weaker than drought effects, although N addition significantly altered initial plant litter
chemistry and litter chemistry during decomposition. However, we did find support for
microbial adaptation to N addition with N-derived microbes facilitating greater mass loss in N
plots than in control plots. Our results show that environmental changes can affect rates of
ecosystem processes directly through abiotic changes and indirectly through microbial
abundances and communities. Therefore models of ecosystem response to global change may
need to represent microbial biomass and community composition to make accurate
predictions.
Key words: bacteria; community composition; drought; fungi; global change; grassland; home field
advantage; litter decomposition; microbes; nitrogen fertilization; precipitation; reciprocal transplant.
INTRODUCTION
Human activities are causing environmental changes
that may influence ecosystem processes. For example,
changes in climate and nutrient inputs can alter plant
productivity, decomposition rates, and ecosystem C
storage ( Mack et al. 2004, Dukes et al. 2005). Therefore,
a major goal in ecology is to predict ecosystem responses
to human-induced environmental change. However,
making these predictions is challenging because ecosys-
tems respond to environmental change through multiple
mechanisms at a range of timescales (Luo 2007). Often
these mechanisms occur simultaneously, making it
difficult to identify the most important drivers of
ecosystem response.
Most environmental changes affect both abiotic and
biological parameters that ultimately determine rates of
ecosystem processes. For instance, global climate change
is expected to alter abiotic conditions such as temper-
ature and soil moisture that have direct and immediate
effects on the organisms that control ecosystem pro-
cesses (IPCC 2007). Organisms often respond to abiotic
drivers through physiological mechanisms, such as the
closure of plant stomata during hot, dry conditions.
These physiological responses can have immediate
consequences for process rates, such as photosynthesis,
which declines when plants close their stomata. Thus
one important component of ecosystem response to
environmental change involves the direct, physiological
response of functionally relevant organisms.
Manuscript received 19 July 2012; revised 22 October 2012;
accepted 25 October 2012. Corresponding Editor: J. B. Yavitt.
3
E-mail: allisons@uci.edu
714
Shifts in the abundance and composition of biological
communities contributing to a process represent another
route by which an ecosystem can respond to environ-
mental change (Manning et al. 2006, Sheik et al. 2011).
Community composition may shift as organisms that
are physiologically better adapted to the new conditions
become more abundant and vice versa. Even if relative
abundances of the taxa within a community do not
change, ecosystem p rocess es could be affected by
changes in absolute abundance of the community, such
as a change in total plant or fungal biomass. These
indirect mechanisms, whereby process rates respond to
environmental changes through an altered community,
could therefore influence ecosystem responses to envi-
ronmental change on generational timescales (Kardol et
al. 2010).
Because physiological responses and indirect process-
es can occur simultaneo usly, t easing apar t these
mechanisms requires independent manipulation of
abiotic conditions and biological c ommunities. Al-
though such manipulations have been done with plants
(Reich et al. 2001), fewer studies have examined indirect
effects on ecosystem processes driven by microorgan-
isms. For some processes such as litter decomposition,
changes in both plant and microbial communities may
contribute to the environmental response. Thus there is
a need for studies that explicitly examine the importance
of the microbial community in mediating ecosystem
responses to environmental change (Reed and Martiny
2007, Strickland et al. 2009).
The goal of our study was to assess the importance of
short-term physiological responses vs. indirect microbial
and plant community changes in determining the rate of
litter decomposition under environmental change (Fig.
1). Rates of litter decomposition depend on many biotic
and abiotic factors such as microbial activity, processing
by invertebrates, chemical composition of the decaying
material, and climate (Swift et al. 1979). Although
microbes, especially fungi and bacteria, play a major
role in the decomposition of plant litter (Waksman
1927), it is not clear how the environmental responses of
microbial communities will ultimately affect decompo-
sition in most ecosystems (Ha
¨
ttenschwiler et al. 2005,
Gessner et al. 2010).
The environmental changes we studied were drought
and nitrogen (N) deposition in southern California.
Climate models predict substantially drier conditions for
this region during the 21st century (Seager and Vecchi
2010). Drought could affect decomposition by limiting
decompose r act ivity through physiological stress or
constraints on enzyme and substrate diffusion (Manzoni
et al. 2012). Indirect effects on decomposition might
operate through the microbial community if drought
adaptation leads to changes in the abundance and
composition of decomposer microbes (Schimel et al.
2007). In addition, drought-induced changes in plant
community composition and leaf chemistry could affect
the chemical quality and decomposition rate of litter
inputs (Morecroft et al. 2004).
Emissions from automobiles, industry, and agricul-
ture have substantially increased reactive N deposition
in southern California (Fenn et al. 2010). This deposi-
tion could directly stimulate decomposition by allowing
microbial decomposers to produce more extracellular
enzymes or shift allocation toward carbon-acquiring
enzymes (Carreiro et al. 2000, Sinsabaugh et al. 2002,
Allison et al. 2009). As with drought, N addition may
indirectly alter decomposition through effects on plants
and microbes. Additional N could shift plant commu-
nities and increase leaf and litter N concentrations,
thereby enhancing litter quality and decomposition rates
(Vitousek 2004, Suding et al. 2005). In the microbial
community, N addition could select for nitrophilic
microbes that require more N but decompose recalci-
trant carbon compounds more efficiently (Treseder et al.
2011). Changes in microbial communities resulting from
FIG. 1. Conceptual model of drought and nitrogen effects on litter decomposition. These environmental drivers alter decay
rates through direct effects on microbial biomass and physiology (solid arrows), as well as indirect effects mediated through
changes in plant communities, litter chemistry, and microbial communities (dashed arrows).
March 2013 715MICROBIAL COMPOSITION AND LITTER DECAY
these adaptive mechanisms could allow decomposition
rates to increase, decrease, or remain constant with
environmental change.
To examine the mechanisms underlying decomposi-
tion responses to environmental change, we used a
reciprocal transplant design to manipulate abiotic
conditions (precipitation and N), the microbial commu-
nity, and plant litter in a California grassland ecosystem.
We hypothesized that drought would have a negative
effect on litter decomposition rates through moisture
limitation of decomposer physiological processes (Fig.
1). Over time, we predicted that the altered abiotic
environment would also select for microbial communi-
ties that were more effective at decomposition under
drought conditions. Furthermore, we expected that
drought-induced changes in plant community composi-
tion and leaf physiology would alter litter chemistry and
have negative effects on decomposition. In contrast to
the drought response, we predicted that decomposition
rates would increase with N addition because litter
decomposers are often N-limited (Allison et al. 2009).
We also expected that N addition would influence
decomposition through the plant community by increas-
ing leaf and lit ter N concentrations. Finally, we
hypothesized that microbial communities would adapt
to drought and N addition through changes in
composition. If adaptation occurs, then microbial
communities derived from a given treatment should
drive faster decomposition in litter and plots receiving
that treatment, a mechanism known as ‘‘home field
advantage’’ (Gholz et al. 2000).
M
ETHODS
Site description and field manipulation
Our experiment took place in a California grassland
ecosystem 5 km north of Irvine, California, USA (33844
0
N, 117842
0
W, 365 m elevation), dominated by exotic
annual grasses and forbs (Potts et al. 2012; M. L.
Goulden, G. C. Winston, S. Parker, K. Suding, and D.
Potts, unpublished manuscript). In spring 2010, the site
was dominated by the annual grass genera Avena,
Bromus, and Lolium; the annual forb genera Erodium
and Lupinus; and the native perennial grass Nassella
pulchra. The climate is mediterranean with a mean
annual temperature of 178C, mean annual precipitation
of 325 mm, and little rai nfall bet ween April and
October. Estimates of total annual N deposition in the
region are ;15 kg
ha
1
yr
1
(Fenn et al. 2010).
For our experiment, we used a subset of plots from an
existing field manipulation of precipitation and N inputs
that began in February 2007 (see Plate 1). The field
manipulation involves three levels of precipitation
(ambient, reduced, or added) applied at the plot scale
and two levels of N (ambient or added) applied to
subplots within precipitation treatments. This design is
replicated in eight experimental blocks. Within each
block, we used only subplots with (1) ambient precip-
itation and N (‘‘control’’ plots), (2) reduced precipitation
þ ambient N (‘‘drought’’ plots), and (3) ambient
precipitation þ added N (‘‘N’’ plots). Thus we did not
study any effects of added precipitation or interactions
between precipitation and N. Rainfall was reduced by
covering the 6.7 3 9.3 m wh ole plots with clear
polyethylene during a subset of the rainstorms each
winter to achieve an ;50 % reduction in annual
precipitation. This treatment reduced rainfall from 369
to 194 mm during the 2009–2010 winter and from 540 to
213 mm during the 2010–2011 winter. Every year, added
N subplots received 20 kg N/ha as soluble CaNO
3
prior
to the growing season and 40 kg N/ha as 100-day release
CaNO
3
during the growing season.
Reciprocal transplant
After the treatments were in place for 3.5 years, we set
up a reciprocal transplant within the field manipulation
to isolate the effects of plot environment, microbe
origin, and litter origin on decomposition rates (Reed
and Martiny 2007). Plot environment represents the
direct manipulation of abiotic conditions (precipitation
or inorganic N inputs). Microbe origin represents
indirect changes in microbial abundance and composi-
tion, and litter origin represents indirect changes in plant
community composition and litter chemistry (Fig. 1).
These main effects were crossed in a fully factorial
design within either the drought or N experiment (Fig.
2). Thus the drought and N experiments are statistically
independent, and we did not examine any drought 3 N
interactions. There were two levels of each f actor
(control and drought or N), and th e design was
replicated within each block of the field experiment.
To manipulate litter origin, we collected senesced
plant material from treatment and control plots. During
the 2009–2010 growing season, drought increased
relative abundances of Erodium, Lolium, and the native
forb Phacelia distans, while reducing relative abundanc-
es of Bromus, Lupinus,andNassella. N addition
increased relative abundances of Bromus, Lolium, and
Phacelia, but reduced Avena, Lupinus, and Nassella
relative abundances (M. Goulden, unpublished data). We
collected litter from hapha zardly located 0.07-m
2
quadrats in each plot (drought, N, or control) on 29
June and 2 July 2010, and returned to the same quadrats
on 14 September 2010, to sample plant material that had
not yet senesced in June (mainly deep-rooted annual
forbs). In each block, we sampled two, two, or four
quadrats in the drought, N, or control plots, respectively
(we needed twice as much control litter to transplant
into both drought and N plots). Litter from all plots
within a treatment was pooled and homogenized by
hand.
We made litterbags containing litter from t he
drought, N, or control plots by placing 2 g (air dry
mass) litter into nylon membrane bags with 0.45-lm
pores. We sterilized all bags and their contents with at
least 22 kGy gamma irradiation. The bags allow water,
nutrients, and possibly small bacteria to pass through.
STEVEN D. ALLISON ET AL.716 Ecology, Vol. 94, No. 3
Preliminary work showed that environmental conditions
(particularly moisture levels) were similar inside and
outside the bags, and that fungi could not move through
the nylon material. Sterility was verified by plating out
litter extracts on LB (lysogeny broth) and fungal media.
We manipulated microbe origin by reinoculating the
sterile litterbags with non-sterile litter collected from
either drought, N addition, or control plots. Three
haphazardly located litter samples (;5 g each) from
each of the eight drought, N, or control plots were
collected by hand on 30 November 2010, and combined
within each treatment to generate three batches of litter
inoculum. The inoculum litter was air dried, ground
(Wiley mill, 1-mm mesh), and added in 50-mg aliquots
to bags containing sterilized litter.
Mass loss and litter chemistry
A total of 360 litterbags were placed in the field on 15
December 2010 and retrieved in batches of 120 (15
treatment combinations 3 8 blocks; Fig. 2) on 3 March
2011, 14 June 2011, and 14 November 2011, for analysis
of percentage mass loss and litter chemistry. We weighed
the fresh litter in each bag and dried a subsample to
constant mass at 658C to obtain dry mass; all mass losses
are repor ted as percentage initial dry mass. This
subsample was sent to Cumberland Valley Analytical
Services ( Maugansville, Maryland, USA) for near
infrared (nIR) spectroscopy analysis (Shepherd et al.
2005). The following chemical fractions are reported
here as a percentage of dry mass: lignin, starch, protein
equals crude protein, cellulose equals acid detergent
fiber minus lignin, hemicellulose equals neutral detergent
fiber minus acid detergent fiber, sugars equal ethanol
soluble sugars, and fat equals crude fat. Percentages of
each chemical fraction were obtained by matching the
nIR spectrum for each sample to a database of spectra
from plant materials with known chemical composition
based on wet chemistry assays. Another subsample was
ground in a ball mill and analyzed for percentage C and
percentage N by combustion on an elemental analyzer.
Chemical parameters were also analyzed in 8–10
subsamples of each initial litter treatment.
Fungal hyphal length and bacterial cell density
Fungal hyphal lengths were determined using a
modified procedure of Sylvia (1992). Litter subsamples
(0.1 g) were ground to 1–2 mm, dried at 608C, and
dispersed in 10-mL sodium hexametaphosphate solution
(0.395% mass/volume) with vigorous stirring. A 1.5-mL
subsample of this solution was vacuum-filtered through
a 0.2-lm nylon filter (Millipore, Billerica, Massachu-
setts, USA) and stained with acid fuchsin. This process
was repeated with a second 1.5-mL subsample, and both
filters were dried and mounted on a microscope slide
with Permount (Fisher Scientific, Pittsburgh, Pennsyl-
vania, USA). After drying at 208C overnight, hyphal
lengths (m/g dry litter) were determined with a Nikon
Eclipse E400 microscope (Nikon Instruments, Melville,
New York, USA) in phase contrast mode under 1003
magnification using the grid-intercept method (Newman
1966, Giovannetti and Mosse 1980) and 50 grids per
filter.
Bacterial cell densities were measured by extraction
and flow cytometry. A 0.1-g subsample of fresh litter
was ground to 1–2 mm and fixed with 5-mL phosphate-
buffered glutaraldehyde solution within 8 h of collec-
tion. The solution contained 0.9% NaCl, 1% glutaral-
dehyde, and 0.12 mol/L phosphate. Fixed samples were
stored at 48C up to four weeks. Samples were extracted
by adding 0.55 mL of 0.1 mol/L tetrasodium pyrophos-
phate solution and gently sonicating for 30 min at 48C.
The extract was pushed through a 2.7-lm GF/D syringe
filter to remove large particles, stained with SYBR
Green (13), and incubated for 15 min at 208C in the
dark. Particles in stained extracts and unstained controls
were counted by flow cytometry (BD Accuri C6; BD
Biosciences, San J ose, California, USA), and cell
densities are reported as the number of stained counts
minus unstained counts per gram dry litter. Unstained
counts correspond to particles that auto-fluoresce at the
same wavelength as SYBR Green but may not contain
FIG. 2. Reciprocal transplant design for one block (n ¼ 8
blocks) in the plant litter manipulation. For each experiment
(drought or nitrogen), the three main effects of plot environ-
ment, litter origin, and microbe origin were crossed in a fully
factorial design with two levels of each factor (control and
treatment). The control plots (3.3 3 9.3 m) were common to
both drought and nitrogen experiments, but each experiment
was treated separately (i.e., no drought 3 nitrogen interactions
were examined). The design was sampled once on each of three
dates in 2011 (3 March, 14 March, and 14 November) for a
total of 360 litterbags. Control plots were unmanipulated,
drought plots received an ;50% reduction in rainfall, and
nitrogen plots were fertilized with 60 kg N
ha
1
yr
1
.
March 2013 717MICROBIAL COMPOSITION AND LITTER DECAY
