interactions between leaf litter quality, particle size, and microbial ... publications/2014...

Interactions between leaf litter quality, particle size,and microbial community during the earliest stage of decay

Zachary L. Rinkes • Jared L. DeForest •

A. Stuart Grandy • Daryl L. Moorhead •

Michael N. Weintraub

Received: 25 October 2012 / Accepted: 22 May 2013 / Published online: 5 June 2013

� Springer Science+Business Media Dordrecht 2013

Abstract With global change expected to alter

aspects of the carbon (C) cycle, empirical data describ-

ing how microorganisms function in different environ-

mental conditions are needed to increase predictive

capabilities of microbially-driven decomposition mod-

els. Given the importance of accelerated C fluxes during

early decay in C cycling, we characterized how varying

litter qualities (maple vs. oak) and sizes (ground vs.

0.25 cm2 vs. 1 cm2), and contrasting soils (sandy vs.

loamy), altered microbial biomass-carbon and commu-

nity structure, respiration, enzyme activities, and

inorganic nutrients over the initial 2 weeks of decom-

position. Our hypotheses were (1) mixing ground maple

with loam should result in a quicker, more prolonged

respiration response than other treatments; and (2)

‘‘priming’’, or substrate-stimulated soil organic matter

turnover, should be minimal over the first few days due

to soluble C substrate uptake. Respiration peaks,

biomass increases, nutrient immobilization, low

enzyme activities, and minimal priming occurred in all

treatments over the first 72 h. These general features

suggest soluble C compounds are degraded before

polymeric substrates regardless of litter size or type, or

soil. Ground litter addition to the high C and microbial

biomass loam resulted in a more prolonged respiration

peak than the poorly aggregated sand. Priming was

greater in loam than the C limited sandy soil after the

first 72 h, likely due to co-metabolism of labile and

recalcitrant substrates. We conclude that the general

features of early decay are widespread and predictable,

yet differences in litter and soil characteristics influence

the temporal pattern and magnitude of C flux.

Keywords Litter decomposition � Microbial

community � PLFA � Priming effect � Soil �Surface area

Introduction

Mineralization of freshly senesced leaf litter by

decomposer communities generates one of the greatest

carbon (C) fluxes in the global C cycle (Schlesinger

and Andrews 2000). However, predicting the magni-

tude of C flux at different stages of decomposition can

Responsible Editor: Colin Bell

Electronic supplementary material The online version ofthis article (doi:10.1007/s10533-013-9872-y) containssupplementary material, which is available to authorized users.

Z. L. Rinkes � D. L. Moorhead � M. N. Weintraub (&)

Department of Environmental Sciences, University of

Toledo, Toledo, OH 43606, USA

e-mail: [email protected]

J. L. DeForest

Department of Environmental and Plant Biology,

Ohio University, Athens, OH 45701, USA

A. S. Grandy

Department of Natural Resources and the Environment,

University of New Hampshire, Durham, NH 03824, USA

123

Biogeochemistry (2014) 117:153–168

DOI 10.1007/s10533-013-9872-y

http://dx.doi.org/10.1007/s10533-013-9872-y

be difficult as microorganisms have varying responses

to shifts in the environment. In fact, most decompo-

sition models do not explicitly include the decomposer

community, because changes in litter chemistry,

nutrient availability, and abiotic conditions have

variable effects on microbial activity and composition

(Allison and Martiny 2008; Berg and McClaugherty

2008). Although ‘‘black-boxing’’ the microbial com-

munity is common, models that link responses of

decomposer functional groups to temporal changes in

litter chemistry and nutrient availability may better

predict decomposition rates (Moorhead and Sinsab-

augh 2006). With global environmental change (e.g.,

nitrogen (N) deposition, global warming) expected to

alter many aspects of the C cycle, including the size

and composition of microbial communities (Frey et al.

2008; Treseder 2008), empirical data describing how

microbial communities respond to changes in the

environment are needed to increase predictive capa-

bilities of current microbial-based decomposition

models. For instance, data explaining how pulses of

litter inputs, varying litter qualities, and contrasting

soil types alter C mineralization rates and decomposer

dynamics may help predict the situations under which

decomposers potentially accelerate or mitigate the

effects of climate change (Treseder et al. 2011).

In temperate deciduous forests, plant litterfall

occurs as a pulse during autumn and is one of the

largest annual inputs of labile C into soil (Hibbard et al.

2005). Microorganisms rapidly metabolize soluble C

compounds in fresh litter, which significantly increases

short-term carbon dioxide (CO2) efflux rates (Gu et al.

2004). For instance, mass loss rates in the first

2–4 weeks of decomposition can be an order of

magnitude greater than in later stages, and the total C

flux during this early stage can be greater than the

following 4–6 months (Alvarez et al. 2008; Jacob et al.

2010). As the quality and quantity of litter changes

throughout decomposition, the microbial community

also changes (Berg and McClaugherty 2008). Thus,

shifting interactions between the decomposer commu-

nity and litter chemical constituents regulate decom-

position at different stages of decay. Although these

types of interactions between leaf litter chemical

characteristics and decomposer communities have

been recently quantified in long-term decomposition

studies (Wickings et al. 2011, 2012), we still know

little about the dynamic microbial-substrate relations

that regulate high rates of C turnover and CO2 flux

during early decay (i.e.,\20 % litter mass loss).

During the initial colonization of litter, the decom-

poser community is believed to consist mostly of

r-selected microorganisms, which take up highly

labile low-molecular weight C compounds (i.e.,

sugars, phenolics, organic acids, and amino acids)

that comprise the total soluble pool (TSP) (Berg and

McClaugherty 2008; Glanville et al. 2012; Van Hees

et al. 2005). Microorganisms decompose litter types

with a large TSP more rapidly than those with a small

TSP (Carreiro et al. 2000), especially in early decay,

due to the higher C and nutrient return from soluble

compounds compared to other litter constituents and

because no enzyme investment is required to obtain

them (Rinkes et al. 2011). Although microbial

substrate use may change in accordance with the

‘‘return on investment’’ that microorganisms get from

producing enzymes to obtain C and nutrients (Moor-

head et al. 2012; Schimel and Weintraub 2003),

decomposers can degrade plant structural tissues

immediately if the quantity and/or quality of the TSP

is not sufficient to support microbial C or nutrient

demand (Talbot and Treseder 2012).

The surface area of the litter also influences TSP

availability to decomposers, and can alter C and

nutrient mineralization rates during decomposition

(reviewed in Nielsen et al. 2011). For example, meso-

and macroinvertebrates (e.g., collembola, nematodes,

lumbricids) condition litter by increasing its surface

area to mass ratio through comminution, and incor-

porate fresh substrate into the soil through bioturba-

tion (Dungait et al. 2012; Frouz et al. 2007). This

physical fragmentation of litter and mixing with soil

increases contact with microorganisms, makes soluble

C substrates more accessible, and facilitates the

activity of soil microbiota (Bradford et al. 2002;

Wickings and Grandy 2011; Wolters 2000). Addition-

ally, soil physical, biological and chemical properties

influence microbial–substrate interactions, especially

as faunal mixing increases soil to litter contact. For

instance, fine textured soils with a high organic matter

content may alter C mineralization rates and microbial

responses to fresh litter addition by adsorbing extra-

cellular enzymes, protecting microbial biomass from

cell death and predation, and physically shielding

labile C compounds from decomposition (Grandy and

Neff 2008; Wallenstein and Weintraub 2008).

154 Biogeochemistry (2014) 117:153–168

123

While changes in litter quality and particle size, and

soil type influence microbial–substrate interactions,

especially TSP availability and C mineralization rates,

they may also regulate the turnover of soil organic

matter (SOM). For instance, fresh organic matter inputs

can stimulate the turnover of existing C pools, especially

in high C soils, resulting in a ‘‘priming effect’’

(Blagodatskaya and Kuzyakov 2008; Guenet et al.

2012; Sayer et al. 2007). The role of microorganisms in

priming may be explained by interactions between r-

and K-selected decomposers following fresh litter

addition. r-strategists thrive on soluble C compounds

when in high abundance, however many of these

organisms are also capable of releasing extracellular

enzymes to degrade polymeric substrates in fresh litter

(Fontaine et al. 2003). Metabolites released during the

partial degradation of polymeric substrates by r-strate-

gists can stimulate the activity of slow-growing K-strat-

egists, resulting in elevated enzyme production, and

further SOM turnover (reviewed in Lambers et al.

2009). Thus, fresh litter and SOM can be co-metabo-

lized by K-strategists, which drives the priming effect in

soils (Kuzyakov 2010). This implies that SOM priming

should be magnified once the TSP dwindles and

polymeric substrate degradation begins, yet there

remains a paucity of data explaining temporal relation-

ships between microbial substrate use and priming early

in decay.

Our goals were: (1) to elucidate the variable effects of

litter and soil properties on microbial activity by

examining how interactions between litter quality

(maple and oak), particle size (ground, 0.25 cm2,

1 cm2), and soil type (sand and silty loam) alter

decomposition dynamics during early decay; and 2) to

evaluate temporal relationships between microbial

substrate use and the priming effect during the initial

2 weeks of decomposition. We hypothesized that

mixing ground maple litter with a loamy soil would

result in a quicker and more prolonged C mineralization

response to fresh litter addition relative to other litter and

soil combinations. This response would be due to high

TSP availability in maple and increased surface area of

ground litter, and greater microbial biomass and barriers

to substrate diffusion (i.e., high aggregation) in loam.

We predicted enzyme activities would be low during the

first few days in this treatment due to preferential uptake

of substrates in the TSP. Additionally, we made

predictions for how each individual factor (litter species,

particle size, and soil type) should affect C mineraliza-

tion dynamics, enzyme activities, and microbial bio-

mass based on the mechanisms described above

(Table 1). We also hypothesized that priming should

be higher in the loamy soil than the sand, due to its

higher C content. However, priming should be minimal

in loamy treatments during the initial days of the

incubation and increase over time as the TSP dwindles

due to increased enzymatic activity and co-metabolism

of fresh litter and SOM.

To accomplish our goals and test these hypotheses,

we monitored how varying litter qualities and sizes,

and contrasting soils, altered microbial biomass-

carbon and community structure, respiration, enzyme

activities, inorganic nutrients, and SOM priming over

the initial 2 weeks of decomposition in a laboratory

incubation (Fig. 1).

Materials and methods

Sample collection

Acer saccharum (sugar maple) and Quercus alba

(white oak) leaves were collected daily in litter traps

during October of 2011 at the Oak Openings Preserve

Metropark (41�330N, 83�500W) in Northwest Ohio.

These litter species were selected due to their

contrasting litter chemistries; sugar maple is reported

to have a 40 % higher water soluble component and

50 % lower lignin fraction than white oak (Aber et al.

1990). Litter was placed in paper bags, air dried, and

Table 1 Predictions for how different litter species, particle sizes, and soil types should influence decomposition rates and microbial

dynamics throughout the 2 week incubation

Factor Respiration peak height Total C mineralized Enzyme activities Microbial biomass

Litter species Maple [ Oak Maple [ Oak Oak [ Maple Maple [ Oak

Particle size Ground [ 0.25 cm2

= 1 cm2Ground [ 0.25 cm2

= 1 cm20.25 cm2 = 1 cm2

[ Ground

Ground [ 0.25 cm2

= 1 cm2

Soil type Sand [ Loam Loam [ Sand Loam [ Sand Loam [ Sand

Biogeochemistry (2014) 117:153–168 155

123

maintained at room temperature until incubation

setup. In order to manipulate substrate accessibility

and determine the impact of surface area on microbial

dynamics, leaves (including petioles) were either: (1)

ground into a fine powder with the use of a Wiley Mill

(20 mesh, 0.84 mm), (2) cut into 0.25 cm2 pieces, or

3) cut into 1 cm2 pieces.

Two soils varying in many soil properties (Table 2)

were collected in May of 2011. A Typic Udipsamment

soil (0.4 % C) was collected from the Oak Openings

Preserve Metropark, which is an area with sandy soils

with low nutrient and C content. A Typic Dystrudept soil

(4.1 % C), which is a silt loam with strong aggregation

and high organic matter content, was collected from the

Waterloo Wildlife Research Area (39�200N, 82�150W)

in Southeast Ohio. These sites were selected in part

because of similarities in tree species composition (i.e.,

oak and maple were dominant trees at both sites), which

minimized the potential of a microbial ‘‘home-field

advantage’’, where decomposers become specialized to

litter of certain plant species (Gholz et al. 2000). Soil

cores were collected from the top 5 cm (the depth with

the highest biological activity) from a 5 m2 area at both

sites, sieved (2 mm mesh) to remove as much coarse

debris and organic matter as possible, thoroughly mixed,

and pre-incubated for 5 months in a dark 20 �C

incubator at 45 % water-holding capacity (WHC). A

preliminary experiment established that this WHC

maximizes respiration in both soils (data not shown).

The pre-incubation allowed for microorganisms to

acclimate to experimental conditions and to metabolize

as much extant labile C as possible in order to better

isolate the specific response of litter additions. Although

this lengthy pre-incubation was necessary, the associ-

ated reduction in substrate availability could have

resulted in a shift in microbial community composition

to predominately K-strategists.

Incubation experiment

A two-week laboratory incubation was established in

237 ml wide mouth canning jars. Thirty-six litter and

soil treatments (2 litter types 9 3 litter particle

sizes 9 2 soil types 9 3 harvests) and six soil-only

control groups (2 soil types 9 3 harvests) were repli-

cated four times and incubated together. Litter treatment

jars contained 50 g dry soil adjusted to 45 % WHC and

1 g dry litter. Soil-only control jars contained 50 g dry

soil adjusted to 45 % WHC. Respiration was monitored

frequently and destructive harvests occurred on days 0,

3, and 14. Each destructive harvest included extracel-

lular enzyme analyses, determination of microbial

biomass-C and analyses for dissolved organic C

(DOC), ammonium (NH4?), nitrate (NO3

-), and phos-

phate (PO43-).

We used the component integration method to

quantify total primed C. This technique physically

separates different C pools contributing to CO2 fluxes

and measures specific rates of CO2 efflux from each

pool (Kuzyakov 2005). Specific rates of CO2 efflux

from each component are multiplied by their respec-

tive masses and summed to calculate integrated CO2

efflux. Respiration was measured in twelve litter-only

control groups (2 litter types 9 3 litter particle

sizes 9 2 soil types) that were incubated alongside

the soil ? litter treatments and soil-only controls.

Separate litter controls were established for each litter

size class, each containing 1 g dry litter adjusted to

45 % WHC mixed with 0.1 g of soil, which was added

as a microbial inoculum. All jars were sealed and kept

in a dark 20 �C incubator. The amount of respiration

attributable to SOM priming was calculated as the

difference in cumulative respiration for a given soil

and litter combination and the sum of the cumulative

respiration from the soil-only control and the same

size, litter-only control. A 2 day lag in peak respiration

rate occurred in all litter controls (not shown) when

compared to the treatments (Fig. 2). Therefore, esti-

mates of cumulative litter-control respiration were

Fig. 1 A schematic illustrating how interactions between litter

and soil characteristics may influence the microbial mechanisms

underlying decomposition processes during early decay


123

adjusted by adding two additional days of C miner-

alization at the rate observed on the final harvest date.

In addition, priming values were adjusted for this

2 day lag. By reducing the calculated difference in

respiration between treatments, this adjustment makes

the estimated amount of priming more conservative.

Microbial respiration

Respiration was measured after 24, 46, 66, 86, 130,

154, and 325 h in litter addition treatment groups,

soil-only controls, and litter controls. Sodium hydrox-

ide (NaOH) traps captured CO2 produced during

decomposition. The amount of NaOH in each trap was

optimized based on the anticipated respiration rate on

each harvest day (e.g., 8 ml of 1 M NaOH per trap on

day 2, but only 2 ml of 1 M NaOH on day 7). Traps

were analyzed using the BaCl2/HCl titration method

(Snyder and Trofymow 1984). In brief, 2 ml of BaCl2were added to the NaOH to precipitate the trapped

CO2 as BaCO3, followed by 5 drops of thymolphtha-

lein pH indicator. The carbonic acid trapped in the

NaOH was then back titrated with 0.1 N HCl. The

calculation of C trapped required subtracting the

equivalents of acid used in titrating a sample from the

equivalents used to titrate a blank.

Enzyme assays

High throughput microplate assays were conducted

following the procedures outlined by Saiya-Cork et al.

(2002). b-1,4-glucosidase (BG), a-1,4-glucosidase

(AG), b-1,4-N-acetyl-glucosaminidase (NAG), and

acid phosphatase (PHOS) activities were monitored in

the litter ? soil treatments and soil-only controls

using fluorigenic substrates. BG hydrolyzes glucose

from cellulose oligomers, especially cellobiose; AG

degrades starch oligomers into glucose monomers;

Table 2 General soil properties averaged (±SE) for the Typic

Udipsamment and the Typic Dystrudept soils (n = 4)

Soil Properties Udipsamment Dystrudept

Texture Sand Silty loam

pH 5.5 ± 0.3 5.5 ± 0.3

% C 0.4 ± 0.1 4.1 ± 0.5

% N 0.04 ± 0.01 0.3 ± 0.1

Biomass 11.3 ± 3.5 155.8 ± 14.9

Ammonium 0.2 ± 0.1 21.4 ± 0.2

Nitrate 14.4 ± 1.3 178.4 ± 10.1

Phosphate \0.1 \0.1

Units are lg-C g soil-1 for biomass and lg-N g soil-1 or lg-P

g soil-1 for inorganic nutrient concentrations. All soil

properties were significantly different between soil types

except pH and initial PO43-

Fig. 2 Respiration rates over the time intervals during which

CO2 was captured in NaOH traps over the 2 week incubation for

the A sugar maple and sand treatment, B oak and sand treatment,

C sugar maple and loam treatment, and D oak and loam

treatment. Values are expressed as lg-C g dry soil-1 day-1 and

were corrected for soil-only controls. Error bars show the

standard error of the mean (n = 4). Tukey’s posthoc test was

used to determine significant differences between treatments on

each day. Lowercase letters were used to designate significant

differences between treatments


123

NAG hydrolyzes N-acetyl glucosamine from chitin

and peptidoglycan derived oligomers; and PHOS

hydrolyzes phosphate from phosphate monoesters

such as sugar phosphates. We selected these enzymes

because they catalyze terminal reactions that release

assimilable nutrients from organic C, N, and P sources

(Sinsabaugh et al. 2010).

Sample slurries for the enzyme assays were

prepared to maintain a consistent 50:1 soil:litter ratio,

which allowed for direct comparison between the

ground and larger particle size treatments. Soil slurries

were made using 1.02 g wet soil/litter mixture for the

ground litter treatment, 1 g wet soil ? 20 mg wet

litter for the larger size treatments, and 1 g wet soil for

the soil-only controls homogenized with 125 ml of

50 mM pH 5.5 sodium acetate buffer for 1 min using a

Biospec Tissue Tearer (BioSpec Products, Bartles-

ville, OK). For the two larger litter size treatments, any

adhering soil particles were removed from the litter

using a 2 mm brush before being added to the slurry.

Soil/litter slurries were stirred continuously on a

magnetic stir plate, while 200 ll aliquots of slurry

were pipetted into 96-well black microplates. Sixteen

replicate wells were created for each assay and

sample.

Assay wells included 200 ll slurry and 50 ll

substrate (4-MUB-b-D-glucoside for BG; 4-MUB-a-

D-glucoside for AG; 4-MUB-N-acetyl-b-D-glucosam-

inide for NAG; and 4-MUB-phosphate for PHOS).

Blank wells were created using 200 ll slurry and 50 ll

buffer. Negative controls were created using 200 ll

buffer and 50 ll substrate. Quench standards were

created using 200 ll slurry and 50 ll of 10 mM

4-methylumbelliferone (MUB). Reference standards

were created using 200 ll buffer and 50 ll MUB

standard. Following substrate addition, microplates

were incubated at 20 �C in the dark for 2–3 h. Plates

were read using a Bio-Tek Synergy HT microplate

reader (Bio-Tek Inc., Winooski, VT, USA) with

365 nm excitation and 460 nm emission filters. After

correcting for quenching and for the negative controls,

enzyme activities were expressed as nmol reaction

product hour-1 g dry soil-1.

Microbial biomass and nutrients

Litter ? soil treatment and soil-only control samples

(including 3 sample-free blanks) were extracted for

DOC, NH4?, NO3

-, and PO43- by adding 25 ml of

0.5 M potassium sulfate and agitating on an orbital

shaker for 1 h. Samples were vacuum filtered through

Pall A/E glass fiber filters and frozen at -20 �C until

nutrient analyses were conducted. Microbial biomass

carbon (MB-C) was quantified using a modification of

the chloroform fumigation-extraction method

described by Scott-Denton et al. (2006). For the litter

treatments, 5.1 g (wet weight) of the ground soil/litter

mixture and 5 g wet soil ? 100 mg wet soil-free litter

from the larger size treatments were combined with

2 ml of ethanol free chloroform and incubated at room

temperature for 24 h in a stoppered 250 ml Erlen-

meyer flask. This fumigation procedure was replicated

for the soil-only controls using 5 g wet soil. Following

incubation, flasks were vented in a fume hood for

30 min and extracted as described above. Fumigated

extracts were analyzed for DOC on a Shimadzu TOC-

VCPN analyzer (Shimadzu Scientific Instruments Inc.,

Columbia, MD, USA). MB-C was calculated as the

difference between DOC extracted from fumigated

and non-fumigated samples. No correction factor for

extraction efficiency (kEC) was applied, as it is

unknown for these soils.

NH4?, NO3

-, and PO43- concentrations were

analyzed using colorimetric microplate assays of the

unfumigated sample extracts. NH4? concentrations

were measured using a modified Berthelot reaction

(Rhine et al. 1998). NO3- was determined using a

modification of the Griess reaction (Doane and

Horwath 2003), which involves the reduction of

nitrate to nitrite followed by colorimetric determina-

tion of nitrite. PO43- was analyzed following the

malachite green microplate analysis described by

D’Angelo et al. (2001). Absorbance values were

determined on a Bio-Tek Synergy HT microplate

reader (Bio-Tek Inc., Winooski, VT).

Phospholipid fatty acid (PLFA) analysis

Ground maple and oak treated samples from both soils

were immediately frozen after the day 0 and day 3

harvests, and then freeze dried within 5 days. Total

lipids were extracted from 5 g freeze dried soil using

4 ml of phosphate buffer, 10 ml of methanol, and 5 ml

of chloroform (White et al. 1979). A 19:0 PLFA

standard was added to determine analytical recovery.

Silicic acid chromatography using solid-phase extrac-

tion columns (500 mg 6 ml-1, Thermo scientific) was

used to separate neutral lipid, glycolipid, and polar


123

lipid fractions by eluting with chloroform, acetone, and

methanol, respectively (Zelles 1999). Separated polar

lipids were then subjected to an alkaline methanolysis

to form fatty acid methyl esters (FAMEs). FAMEs

were separated and quantified using a HP GC-FID

(HP6890 series, Agilent Technologies, Inc. Santa

Clara, CA, USA) gas chromatograph; peaks were

identified using the Sherlock Microbial Identification

System (v. 6.1, MIDI Inc., Newark, DE, USA). In

addition, five concentrations of an external FAME

standard mix (10:0, 12:0, 14:0, 16:0, 18:0, and 20:0;

K101 FAME mix, Grace, Deerfield, Il) were analyzed

among the samples to determine FAME mass (DeFor-

est et al. 2012).

Overall, the dominant PLFAs (highest relative abun-

dance) were classified as bacteria (19:0 iso) and ‘‘gen-

eral,’’ meaning common among divergent taxa, (16:0 and

20:0) functional groups (DeForest et al. 2004; Potthoff

et al. 2006; Steenwerth et al. 2006). The classification of

PLFA 18:1x9c varies between studies, as this biomarker

could be derived from either fungi or Gram - bacteria

(Fierer et al. 2003; Waldrop and Firestone 2004).

Biomarker abundance was calculated by dividing indi-

vidual biomarkers by total biomass (i.e., % mol fraction).

Statistics

Instantaneous respiration data were analyzed using a

3-way repeated measures analysis of variance (rmA-

NOVA) with litter species, litter size, and soil type as

factors. Cumulative respiration data were compared

among treatments using a 3-way analysis of variance

(ANOVA). Cumulative respiration was also compared

between each soil and litter combination treatment and

the sum of the cumulative respiration from the soil-

only control and the same size, litter-only control to

determine if there was a ‘‘priming effect’’ using a

4-way ANOVA with litter species, litter size, soil type,

and experimental group (i.e., treatment or controls) as

factors. MB-C, DOC, BG, NAG, PHOS, NH4?, NO3

-,

and PO43- means were compared using 3-way multi-

variate analysis of variance (MANOVA). Biomass to

total system C (B:C) ratios on days 3 and 14 were

compared with a 4-way ANOVA with day, litter

species, litter size, and soil type as factors. Mean % mol

abundance for the 4 most abundant PLFAs (16:0,

18:1x9c, 20:0, and 19:0 iso) were compared using

2-way MANOVA with litter species and soil type as

factors. PLFA biomass increased from day 0 to day 3,

however day was not a significant factor overall

(P = 0.29, F = 0.80) when included in a 3-way

MANOVA with day, litter species, and soil type as

factors. Therefore, day 0 and day 3 values were

combined for the 2-way MANOVA.

For all analyses, differences among groups were

considered significant if P B 0.05. Respiration data

were log10 transformed to meet assumptions of

normality and homogeneity of variance. Differences

between groups were compared using a Tukey multi-

ple comparison post hoc test. Data were analyzed

using SPSS Statistics version 17.0.

Results

C mineralization

Litter species, litter particle size, and soil type had

significant main effects on respiration rates (P \ 0.01

for all) with no significant interactions among factors.

Mixing ground litter with sand resulted in peak respi-

ration rates for both maple and oak between 25 and 46 h,

which were significantly higher than for the 0.25 cm2

and 1 cm2 size pieces, respectively (P \ 0.01 for all;

Fig. 2A, B). Respiration for the 0.25 cm2 and 1 cm2

sizes peaked between 47 and 66 h for both litters in sand

with the 0.25 cm2 pieces having the higher peaks

(Fig. 2A, B).

In the loam, peak respiration rates for most sizes of

both litter types occurred between 47 and 66 h (Fig. 2C,

D), the only exception being ground maple litter, which

had consistently high rates over 25–66 h. There were no

significant differences between peak rates of different

maple litter sizes in loam, but peak rates for all sizes of

oak litter were significantly different from one another

(ground [ 0.25 cm2 [ 1 cm2). Overall, maple had

significantly higher peak respiration rates than oak for

all litter sizes in sand (P \ 0.05 for all), but not in loam.

The total amounts of C mineralized over the study

period varied between litter types, soil types and

occasionally, litter particle sizes resulting in signifi-

cant 3-way interaction between factors (Table 3). In

sand, post hoc tests found no significant differences in

cumulative respiration for the three sizes of oak litter.

In contrast, the total C respired significantly decreased

with increasing size of oak litter in loam (Table 3).

There was a significant decrease in total C respired in

1 cm2 maple litter compared to the ground and


123

0.25 cm2 pieces in sand, but not in loam (Table 3).

Litter mass loss ranged from 6–8 % in sandy soil to

9–15 % in loam for both maple and oak.

There was a significant 4-way interaction between

species, particle size, soil type, and experimental group

(P \ 0.01; F = 9.57) on the total amount of C miner-

alized. Although the total C respired varied between

litter species and particle sizes in both soils, the amount

of respiration for a given soil and litter combination

treatment was only significantly higher than the sum of

the cumulative respiration from the soil-only control and

the same size, litter-only control (i.e., a ‘‘priming

effect’’) in loam (P \ 0.05 for all; Fig. 3). No significant

priming occurred over the first 3 days in any treatment,

except for when ground maple was mixed with loam

(P = 0.01; F = 15.6), although priming was 33 %

higher after day 3 than before in this treatment. Priming

was significant in the ground maple (P = 0.02;

F = 11.4), 0.25 cm2 maple (P \ 0.01; F = 163.5),

1 cm2 maple (P \ 0.01; F = 358.5), ground oak

(P \ 0.01; F = 42.3), and 0.25 cm2 oak (P = 0.02;

F = 11.4) loamy treatments between 3 and 14 days.

Microbial biomass and enzyme activities

Although MB-C was greater in the loam soil-only

control compared to sand on day 0 (Table 2), there

were no significant differences in MB-C between

treatments after values were corrected for soil-only

controls. However, MB-C changed significantly over

time (P \ 0.01; F = 22.7), as MB-C increased from

day 0 to day 3 for all treatments and decreased (not

always significantly) between days 3 and 14 (data not

shown). On day 14, MB-C was significantly higher

than day 0 in oak litter only. Peak values did not differ

between treatments on day 3 and ranged from 140 to

300 lg-C g dry soil-1. DOC also changed signifi-

cantly over time (P \ 0.01; F = 48.7), as concentra-

tions decreased between day 0 and day 14 for all

treatments (P \ 0.05 for all; Supplementary Fig. 1).

B:C ratios were significantly higher in sand than

loam (P \ 0.01; F = 20.9). Overall, B:C values did

not differ between litter particle sizes, but were

significantly higher on day 3 than day 14 (P \ 0.01;

F = 17.7). Values ranged between 2.4 and 2.9 % in

the 0.25 cm2 and 1 cm2 particle sizes in sand on day 3,

which were coincident with peak respiration rates. B:C

ratios ranged from 2.1 to 2.3 % in the ground litter and

sand treatments on day 3, which was the day following

the respiration peak for both ground maple and oak.

On day 14, B:C ratios decreased to\1.6 % in all sandy

treatments. Ratios averaged 0.73 % on day 3 and

decreased to 0.32 % on day 14 in loamy treatments.

Table 3 Cumulative carbon (C) respired (mg C kg-1 soil) for

each litter/soil treatment at the conclusion of the two-week

incubation. Data are corrected for soil-only controls

Litter treatment C respired in

sandy soil

(mg C kg-1 soil)

C respired in

loamy soil

(mg C kg-1 soil)

Ground

Maple 994.03 ± 17.99a 1415.27 ± 54.18x

Oak 820.12 ± 9.39b 1417.38 ± 5.93x

0.25 cm2

Maple 990.86 ± 21.38a 1392.09 ± 36.11x

Oak 692.64 ± 28.07b 1067.35 ± 35.81y

1 cm2

Maple 785.33 ± 10.30b 1309.26 ± 33.99x

Oak 722.17 ± 53.52b 890.04 ± 19.22z

Values represent the mean cumulative C respired (±SE) for

each treatment (n = 4) and were compared among the different

treatments with a 3-way ANOVA. Differences between groups

within each soil type were compared with Tukey’s post hoc

test. Lowercase letters designate significant differences

between treatments within each soil type

Fig. 3 Cumulative carbon (C) respired in each litter ? soil

treatment (Trt) and soil ? litter (S ? L) control group at the

conclusion of a two-week incubation. Cumulative C respired for

each S ? L control group was calculated as the sum of the total C

mineralized in each of4 litter-only and soil-only control replicates.

A ‘‘priming effect’’ is apparent when cumulative respiration in a

given soil and litter combination treatment was significantly

higher than the sum of the cumulative respiration from the soil-

only control and the same size, litter-only control. Error bars show

the standard error of the mean (n = 4). Values were compared

among the different treatments with a 4-Way ANOVA followed

by Tukey’s post hoc test. Lowercase letters were used to designate

significant differences between treatments


123

However, all B:C estimates are conservative as no

correction factor for microbial biomass extraction

efficiency was applied.

AG activity was not detectable in this study. All

other enzyme activities significantly increased over

time, but showed relatively few effects of treatments or

interactions between treatment factors after values

were corrected for soil-only controls (Fig. 4). BG

activity for the 1 cm2 maple and oak litter in loam was

twice as high as all other treatments on day 14 (Fig. 4A,

B). This resulted in a significant overall effect of litter

size on BG activity (P = 0.02, F = 4.18). NAG

activity did not differ between treatment factors.

PHOS showed a significant interaction between litter

size and soil type (P = 0.03, F = 3.68). PHOS was

low in maple litter in sand throughout the incubation

(Fig. 4E). In maple, PHOS was significantly higher for

all sizes in loam compared to sand on day 14 (P \ 0.03

for all). On day 14, PHOS activity in oak litter was

significantly higher for 1 cm2 pieces than ground litter

in loam (Fig. 4F), and both these activity levels were

significantly higher than in all other oak litter

size 9 soil combinations (Fig. 4F).

Nutrient dynamics

NH4?, NO3

-, and PO43- concentrations significantly

decreased over time (P \ 0.05 for all) in all treatments

that had detectable concentrations on day 0 (Fig. 5).

NH4? showed a significant interaction between litter and

soil type (P \ 0.01, F = 7.44). NH4? was low

(\5.0 lg-N g dry soil-1) in sand for all litter treatments

and the no-litter controls throughout the incubation

(Fig. 5A). The loam had three times higher extractable

NH4? on day 0 (between 15.0 and 30 lg-N g dry soil-1),

but significantly decreased in all treatments to \5 lg-

N g dry soil-1 by day 14 (P \ 0.04 for all). On day 0 in

loam, NH4? was significantly higher in oak than maple

for all litter sizes (Fig. 5B). On day 3 in loam, ground

maple litter had significantly lower NH4? than all other

treatments (P \ 0.01; Fig. 5B). Also in loam, NH4?

increased in the soil-only control from *15 to 45 lg-

N g dry soil-1 from day 0 to day 3, respectively, and then

decreased to 5 lg-N g dry soil-1 on day 14 (Fig. 5B).

Extractable NO3- only showed a significant differ-

ence between soil types (P \ 0.01, F = 879.51). On

day 0 in sand, NO3- approached 20 lg-N g dry soil-1

Fig. 4 b-glucosidase (BG), N-acetyl-b-glucosaminidase (NAG),

and acid phosphatase (PHOS) activities measured at three harvest

dates over a 2 week period. BG activity is displayed in A maple

and B oak, NAG activities in C maple and D oak, and PHOS

activities in E maple and F oak. Values are expressed as

nmol reaction product h-1 g-1. Activities are corrected for soil-

only controls. Error bars show the standard error of the mean

(n = 4). Lowercase letters were used to designate significant

differences between treatments


123

but decreased by day 3 and was undetectable through-

out the remainder of the incubation (Fig. 5C). NO3-

was significantly higher in loam and more variable,

decreasing in the no-litter control from day 0 to day 3,

and then increasing from day 3 to day 14 (Fig. 5D).

PO43- also was only significantly different between

soil types (P \ 0.01, F = 26.44). It ranged from 35 lg-

P g dry soil-1 to 45 lg-P g dry soil-1 on day 0 in sand for

all litter treatments, but decreased to \10 lg-P g dry

soil-1 by day 3 (P \ 0.01 for all; Fig. 5E). Initial PO43-

was significantly lower in the loam ? litter treatments

(\15 lg-P g dry soil-1) than sand, and decreased to an

undetectable level by day 3 for all treatments (Fig. 5F).

Phospholipid fatty acid profiles

Overall, 57 PLFA biomarkers were identified. The

most abundant PLFAs based on mean % mol fraction

(relative biomarker abundance) were 16:0 (general),

18:1x9c (Gram - bacteria or fungi), 20:0 (general),

and 19:0 iso (bacteria) (Fig. 6). The only biomarkers

to differ between treatments were PLFAs 16:0 and

18:1x9c (P \ 0.01 for both; Fig. 6). Concentrations

of PLFAs 16:0, 18:1x9c, and 19:0 iso were higher in

the loamy than the sandy soil (P \ 0.01 for all), while

PLFA 20:0 showed a difference between soil types

approaching significance (P = 0.09, F = 2.95).

Fig. 5 Ammonium (NH4?), nitrate (NO3

-), and phosphate

(PO43-) concentrations measured at three harvest dates over a

2 week period. NH4? concentrations are displayed in A (sand)

and B (loam), NO3- concentrations in C (sand) and D (loam),

and PO43- concentrations in E (sand) and F (loam). Values are

expressed as lg-N g soil-1 (NH4? and NO3

-) or lg-P g soil-1

(PO43-). Soil-only controls were included in the figures for

comparison, but were not analyzed in the MANOVA. Litter

treatments were not corrected for soil-only controls. Error bars

show the standard error of the mean (n = 4). Lowercase letters

were used to designate differences between treatments

Fig. 6 Mean % mol fraction (day 0 and day 3 data were

combined) for the 4 most abundant PLFAs in the soil ? ground

litter treatments. The mean % mol fraction data were compared

among the different treatments with a 2-Way MANOVA

followed by Tukey’s post hoc test. Error bars show the standard

error of the mean (n = 3). Lowercase letters were used to

designate differences between treatments


123

Discussion

Microbial dynamics early in litter decay

Rapid increases in respiration and microbial biomass

occurred during the first 72 h in all litter treatments,

indicating that fast-growing microorganisms quickly

degraded C substrates in newly added litter. Most

likely these C substrates are soluble and can be

quickly assimilated by decomposers, including those

that lack complex enzymatic capabilities (Van Hees

et al. 2005). This conclusion is supported by a

decrease in DOC concentrations, low enzyme activity

and minimal priming until after the peaks in respira-

tion and biomass occurred, despite high initial abun-

dance of two bacterial PLFAs (18:1x9c and 19:0 iso),

and NH4?, NO3

- and PO43- immobilization over the

first 3 days. Thus, our results provide experimental

evidence in support of conceptual models illustrating

that microbial uptake of C substrates during decom-

position occurs in a step-wise fashion, where soluble

substrates are rapidly consumed before the enzymatic

breakdown of polymeric substrates begins (i.e., Berg

2000).

No study that we are aware of has examined

individual and combined effects of factors such as

litter quality, particle size, and soil properties and their

interactions with microbial communities during early

stage decomposition. Rinkes et al. (2011) observed

rapid increases in C mineralization and MB-C, high

rates of N and P immobilization, and high abundance

of a Gram ? bacterial PLFA over the first 2 days of

decomposition when ground maple litter was mixed

with a sandy soil. However, the present study demon-

strates that uptake of soluble C compounds, DIN, and

DIP by opportunistic decomposers in early decay is

not just an artifact of adding ground maple litter to a

C-limited sandy soil, but can also occur in litter with a

lower soluble content, larger particle sizes, and in a

higher C soil. Therefore, we believe this initial pattern

is likely to be a general feature of decomposition. Our

results show that while differences in litter quality and

particle size, and soil type influence the temporal

pattern and magnitude of C flux during early stage

decomposition, the uptake of soluble C compounds,

DIN, and DIP by opportunistic microorganisms is a

predictable and robust process occurring in different

litter and soil types.

Controls on early microbial dynamics

Rapid decreases in the TSP characterize the initial

phase of fresh litter decay, with the sharpest declines

typically observed in low lignin litter because it has a

higher initial TSP (Berg 2000; Moorhead and Rey-

nolds 1993). Maple is reported to have as much as a

40 % higher TSP than oak (Aber et al. 1990;

McClaugherty et al. 1985) and we found that maple

C mineralization rates were greater than oak for every

litter size within each soil type over the first 66 h.

Additionally, maple has high concentrations of soluble

phenolics (Lovett et al. 2004) and a portion of the

phenolic content can be easily degraded, as indicated

by the commonly reported positive relationships

between the soluble phenolic content of litter and

early respiration rates (Bernhard-Reversat et al. 2003;

Meier and Bowman 2008; Reber and Schara 1971).

Furthermore, MB-C was significantly higher in all oak

treatments on day 14 compared to day 0, although no

differences in MB-C occurred in maple treatments

between these days. Therefore, early stage microbial

dynamics likely were stimulated by higher maple TSP

quality and quantity, which resulted in more rapid C

mineralization and microbial turnover.

In addition to litter quality, particle size also

directly affects microbial activity (Ekschmitt et al.

2005; Hanlon and Anderson 1980; Xin et al. 2012) by

altering litter surface area available for microbial

colonization (Anderson et al. 1983). Furthermore,

litter grinding may increase the availability of the TSP

by disrupting plant cell walls that shield these

compounds (Romani et al. 2006). To determine the

effects of litter particle size on microbial biomass and

activity and because the relationship between respira-

tion and biomass was not constant, we examined ratios

of microbial biomass to total soil C (B:C). In all our

treatments, B:C ratios peaked early (day 3) and were

close to the 1–3 % range often used to characterize the

relative microbial biomass pool size (Anderson and

Domsch 1989). B:C ratios did not differ between

particle sizes on day 3, which was the day respiration

and biomass peaked in the larger sizes. However,

respiration peaked earlier in most ground litter treat-

ments and it is likely that MB-C and the peak in B:C

ratios occurred before day 3 in the highest surface area

litter treatments due to enhanced microbial coloniza-

tion (Yang et al. 2012). B:C values were also higher in


123

sand than loam, likely due to its lower soil C content

and inability to physically and/or chemically protect C

substrates from microorganisms (Ahn et al. 2009). For

instance, labile C compounds can become bound

within aggregates or adsorbed to mineral surfaces in

finer textured soils, thus decreasing vulnerability to

microbial degradation (Grandy and Neff 2008; Plante

et al. 2006; Six et al. 2002). It is also possible that

soluble substrates had fewer barriers to diffusion in the

low C sandy soil, thus making them more available as

a primary resource to decomposers. Oxygen (O2)

availability may have also limited B:C ratios in the

loam, as non-uniform O2 distribution and anaerobic

aggregate centers have been found in otherwise

aerobic silty loam soils (Sexstone et al. 1985).

Grinding litter substantially increased the surface

area to mass ratio of litter, and when mixed with sand,

accelerated the peak in respiration by 24 h and

increased the total amount of C mineralized by as

much as 15 % over the study period compared to the

larger sand particle sizes. The rapid peak in respiration

in sand mixed with ground litter was coincident with

high concentrations of PLFA 18:1x9c, a biomarker

associated with Gram - bacteria, which are likely

r-strategists (Fierer et al. 2007). Therefore, opportu-

nistic microorganisms responded quickly to the avail-

ability of fresh substrate in this C-limited soil.

However, these early biomass and respiration peaks

were fleeting, likely due to depletion of soluble C

compounds (TSP), or perhaps depletion of soluble N

and/or P, and the poor competitive ability of r-strat-

egists when resources become limited (Bouvy et al.

2011; Mula-Michel and Williams 2012; Rinkes et al.

2011). As soluble C substrates and inorganic nutrients

dwindle, community composition can shift to decom-

posers that produce a wider array of enzymes targeting

more complex litter substrates and SOM (Snajdr et al.

2011). Our results are consistent with other studies in

that C, N and P acquiring enzymes were induced as

soluble C substrates and inorganic nutrients were

depleted in sandy treatments (DeForest et al. 2012;

Olander and Vitousek 2000). Therefore, it is likely that

a threshold was reached when the demand for C, N and

P exceeded the available supply, which triggered

enzyme production and the enzymatic breakdown of C

and nutrient rich organic compounds in the sandy soil

(DeForest and Scott 2010; Rinkes et al. 2011).

In contrast to enzyme activities, respiration in loam

increased within the first 24 h and remained elevated for

66 h when ground litter was added. We suggest that the

higher initial microbial biomass and soil C content in

loam (both were 10 times higher than sand) allowed for

quicker initial litter colonization by opportunistic bacteria

and subsequent use of soluble C substrates. This is likely

as concentrations of PLFAs 18:1x9c and 19:0 iso, both

potentially representative of r-strategists (Fierer et al.

2007), were greater in loam than sand. NH4? immobi-

lization was also significantly greater in the ground maple

and loam mixture on day 3 compared to all other

treatments, which further supports the hypothesis that

higher TSP quantity/quality, greater surface area, and

higher soil C promotes microbial growth and coloniza-

tion. It is possible that the prolonged uptake of these

soluble compounds from ground litter was due to the

greater physical (e.g., occlusion within aggregates) and

chemical (e.g., sorption to minerals) protection of labile C

substrates and by-products of early decay (Moni et al.

2010; Plante et al. 2006). Alternatively, soluble substrates

from fresh litter may have not been as important as a

resource due to the greater C substrate pool in loam

compared to sand, thus prolonging their uptake.

BG activity was lower in ground and 0.25 cm2 than

1 cm2 litter of both types in the loamy soil on day 14. It is

probable that the low surface area per unit mass

associated with larger fragments decreased microbial

access to soluble C substrates in the TSP. Therefore,

microorganisms likely increased BG activity to degrade

cellulose, as there is a tight correlation between BG and

the bioavailability of C sources (Canizares et al. 2011).

However, BG activity was not elevated in the 1 cm2

treatments in sand, perhaps due to lower microbial

biomass, which in turn reduces microbial C demand.

Interestingly, NAG activity also increased in the loamy

treatments on day 14 even though nitrate concentrations

remained elevated throughout the incubation, possibly a

result of increased nitrification due to high ammonium

concentrations. Although NAG is a primary means of

acquiring N from chitin, decomposers can produce this

enzyme to obtain C or as an antagonistic response towards

fungi (Talbot and Treseder 2012), which may explain

why NAG activity increased in the presence of mineral N.

Priming effect

Overall, priming was greater for most litter treatments in

loam compared to the C limited sandy soil. For instance,

sandy soil treatments and the 1 cm2 oak treatment in

loam had no priming response or even displayed an


123

antagonistic response after litter addition. This was

likely due to the scarcity of readily accessible high

quality substrates, which typically increase the priming

effect in soils (Kuzyakov and Bol 2006). Additionally,

priming effects in C rich soils are larger than those in C

poor soils (reviewed in Kuzyakov et al. 2000), possibly

due to both a higher microbial inoculum and higher

potential C substrate pool. Kuzyakov (2002) summa-

rized a series of longer-term experiments where priming

was found to be 30–100 times greater in a 4.7 % C

loamy soil than a 0.7 % sandy soil. In our two-week

study, priming was as much as 15 times greater in the

4.1 % C loam than the 0.4 % C sand. Likewise, we

observed more priming in treatments with smaller

particle sizes, higher quality litter, and higher soil C.

The relationship between microbial substrate use and

priming in loamy treatments may be explained by co-

metabolism of fresh litter and SOM by K-strategists.

r-strategists respond rapidly to increases in soluble C

substrates (Fig. 2), but these compounds are metabolized

quickly and microbial turnover occurs when the readily

available C supply is exhausted (Blagodatskaya et al.

2007). Many r-strategists also produce enzymes to

decompose polymeric litter substrates, such as cellulose,

however enzyme production is typically not induced

until the TSP dwindles (Fig. 4). In contrast, K-strategists

metabolize poor quality substrates, such as SOM, and,

although they grow too slowly to compete with r-strat-

egists for compounds in the TSP, benefit from metab-

olites released when higher energy polymeric substrates

in fresh litter are degraded (Fontaine et al. 2003). Thus,

K-strategists stimulated by polymeric substrates in fresh

litter may increase enzymatic activity and SOM decom-

position rates, further driving the priming effect (Fig. 3)

in soils (Kuzyakov 2010). We hypothesize that r-strat-

egists outcompeted K-strategists for soluble C substrates,

which can be taken up without enzymatic breakdown,

during the first 66 h of our incubation, as priming was

minimal in most treatments. However, the significant

priming effect throughout the remainder of the incuba-

tion was likely a result of increased K-strategist popu-

lations, elevated enzyme activities, and co-metabolism

of labile and recalcitrant substrates.

Conclusions

Litter decomposition models often poorly character-

ize early decay, primarily because we lack a clear

understanding of the mechanisms that regulate the

temporal dynamics of microbial responses to changes

in the environment. Given the potential for acceler-

ated litter and soil C fluxes during early decay and

the importance of these fluxes to ecosystem-scale C

cycling and global climate change, we provide high-

resolution data needed to understand how microbial

communities respond to fresh litter addition in

varying litter qualities, particle sizes, and soil types.

Our results suggest that soluble C compounds are

preferentially consumed following fresh litter addi-

tion to soil, as we observed rapid increases in

respiration and MB-C, immobilization of N and P,

low enzymatic activities, and a minimal priming

effect over the first 72 h in all treatments. However,

differences in litter quality and particle size and soil

type influenced the temporal pattern and magnitude

of C flux following fresh litter addition. Soil type was

a strong determinant of the magnitude and longevity

of increased C flux in response to litter addition,

especially when mixed with ground litter (i.e., high

TSP availability), which suggests differences in C

substrate availability, microbial biomass, and the

soil’s capacity to protect SOM can regulate microbial

access to the TSP. Furthermore, our data suggest that

priming is a more important phenomenon in finer

textured soils, and even litter types with a minimal

TSP (i.e., oak) and larger particle sizes (i.e., 0.25 cm2

and 1 cm2) can accelerate SOM turnover and mag-

nify CO2 flux during early decay when added to a

high C soil.

Acknowledgments This research was supported by the NSF

Ecosystems Program (Grant # 0918718). For field and

laboratory assistance, we thank Mallory Ladd, Ryan Monnin,

Steve Solomon, Heather Thoman, Logan Thornsberry, and

Megan Wenzel. We are also grateful to Jason Witter for

assistance in freeze-drying samples for PLFA analysis. For help

with CN analysis, we thank Doug Sturtz, Russ Friederich, and

Jonathan Frantz from the USDA ARS at the University of

Toledo. We also thank two anonymous reviewers whose

suggestions greatly improved this work.

References

Aber JD, Melillo JM, McClaugherty CA (1990) Predicting long-

term patterns of mass loss, nitrogen dynamics, and soil

organic matter formation from initial fine litter chemistry

in temperate forest ecosystems. Can J Bot 68:2201–2208

Ahn M, Zimmerman AR, Comerford MB, Sickman JO, Grun-

wald S (2009) Carbon mineralization and labile organic


123

carbon pools in the sandy soils of a North Florida water-

shed. Ecosystems 12:672–685

Allison SD, Martiny BH (2008) Resistance, resilience, and

redundancy in microbial communities. PNAS 115:11512–

11519

Alvarez E, Marcos M, Torrado V, Sanjurjo M (2008) Dynamics

of macronutrients during the first stages of litter decom-

position from forest species in a temperate area. Nutr Cycl

Agroecosyst 80:243–256

Anderson TH, Domsch KH (1989) Ratios of microbial biomass

carbon to total organic-carbon in arable soils. Soil Biol

Biochem 21:471–479

Anderson JM, Ineson P, Huish SA (1983) Nitrogen and cation

mobilization by soil fauna feeding on leaf litter and soil

organic matter from deciduous woodlands. Soil Biol Bio-

chem 15:463–467

Berg B (2000) Litter decomposition and organic matter turnover

in northern forest soils. For Ecol Manag 133:13–22

Berg B, McClaugherty C (2008) Plant litter: decomposition,

humus formation, carbon sequestration. Springer, Berlin

Bernhard-Reversat F, Main G, Hall K, Loumeto J, Ngao J (2003)

Fast disappearance of the water-soluble phenolic fraction

in eucalypt leaf litter during laboratory and field experi-

ments. Appl Soil Ecol 23:273–278

Blagodatskaya EV, Kuzyakov Y (2008) Mechanisms of real and

apparent priming effects and their dependence on soil

microbial biomass and community structure: critical

review. Biol Fertil Soils 45:115–131

Blagodatskaya EV, Blagodatsky SA, Anderson TH, Kuzyakov

Y (2007) Priming effects in Chernozem induced by glucose

and N in relation to microbial growth strategies. Appl Soil

Ecol 37:95–105

Bouvy M, Bettarel Y, Bouvier C, Domaizon I, Jacquet S, Le-

Floc’h E, Montanie H, Mostajir B, Sime-Ngando T, Torr-

eton P, Vidussi F, Bouvier T (2011) Trophic interactions

between viruses, bacteria and non flagellates under various

nutrient conditions and simulated climate change. Environ

Microbiol 13:1842–1857

Bradford MA, Tordoff GM, Eggers T, Jones TH, Newington JE

(2002) Microbiota, fauna, and mesh size interactions in

litter decomposition. Oikos 99:317–323

Canizares R, Benitez E, Ogunseitan OA (2011) Molecular

analysis of b-glucosidase diversity and function in soil. Eur

J Soil Biol 47:1–8

Carreiro MM, Sinsabaugh RL, Repert DA, Parkhurst PF (2000)

Microbial enzyme shifts explain litter decay responses to

simulated nitrogen deposition. Ecology 81:2359–2365

D’Angelo E, Crutchfield J, Vandiviere M (2001) Rapid, sensi-

tive, microscale determination of phosphate in water and

soil. J Environ Qual 30:2206–2209

DeForest JL, Scott LG (2010) Available organic soil phosphorus

has an important influence on microbial community com-

position. Soil Sci Soc Am J 74:2059–2066

DeForest JL, Zak DR, Pregitzer KS, Burton AJ (2004) Atmo-

spheric nitrate deposition and the microbial degradation of

cellobiose and vanillin in a northern hardwood forest. Soil

Biol Biochem 36:965–971

DeForest JL, Smemo KA, Burke DJ, Elliott HL, Becker JC

(2012) Soil microbial responses to elevated phosphorus

and pH in acidic temperate deciduous forests. Biogeo-

chemistry 109:189–202

Doane TA, Horwath WR (2003) Spectrophotometric determi-

nation of nitrate with a single reagent. Anal Lett 36:2713–

2722

Dungait JAJ, Hopkins DW, Gregory AS, Whitmore AP (2012)

Soil organic matter turnover is governed by accessibility

not recalcitrance. Glob Change Biol 18:1781–1796

Ekschmitt K, Liu MK, Vetter S, Fox O, Wolters V (2005)

Strategies used by soil biota to overcome soil organic

matter stability-why is dead organic matter left over in the

soil? Geoderma 128:167–176

Fierer N, Schimel JP, Holden PA (2003) Variations in microbial

community composition through two soil depth profiles.

Soil Biol Biochem 35:167–176

Fierer N, Bradford MA, Jackson RB (2007) Toward an eco-

logical classification of soil bacteria. Ecology 88:1354–

1364

Fontaine S, Mariotti A, Abbadie L (2003) The priming effect of

organic matter: a question of microbial competition? Soil

Biol Biochem 35:837–845

Frey SD, Drijber R, Smith H, Mellilo J (2008) Microbial bio-

mass, functional capacity, and community structure after

12 years of soil warming. Soil Biol Biochem 40:2904–2907

Frouz J, Elhottova D, Pizl V, Tajovsky J, Sourkova M, Picek T,

Maly S (2007) The effect of litter quality and soil fauna

composition on organic matter dynamics in post mining

soil: a laboratory study. Appl Soil Ecol 37:72–80

Gholz HL, Wedin DA, Smitherman SM, Harmon ME, Parton

WJ (2000) Long-term dynamics of pine and hardwood

litter in contrasting environments: toward a global model of

decomposition. Glob Change Biol 6:751–765

Glanville H, Rousk J, Golyshin P, Jones DL (2012) Minerali-

zation of low molecular weight carbon substrates in soil

solution under laboratory and field conditions. Soil Biol

Biochem 48:88–95

Grandy AS, Neff JC (2008) Molecular C dynamics downstream:

the biochemical decomposition sequence and its impact on

soil organic matter structure and function. Sci Total

Environ 404:297–307

Gu L, Post W, King A (2004) Fast labile C turnover obscures

sensitivity of heterotrophic respiration from soil to temper-

ature: a model analysis. Global Biogeochem Cycl 18:1022

Guenet B, Juarez S, Bardoux G, Abbadie L, Chenu C (2012)

Evidence that stable C is as vulnerable to priming effect as

is more labile C in soil. Soil Biol Biochem 52:43–48

Hanlon RDG, Anderson JM (1980) Influence of macroarthropod

feeding activities on macroflora in decomposing oak

leaves. Soil Biol Biochem 12:255–261

Hibbard KA, Law BE, Reichstein M, Sulzman J (2005) An

analysis of soil respiration across northern hemisphere

temperate ecosystems. Biogeochemistry 73:29–70

Jacob M, Viedenz K, Polle A, Thomas F (2010) Leaf litter

decomposition in temperate deciduous forest stands with a

decreasing fraction of beech (Fagus sylvatica). Oecologia

164(4):1083–1094

Kuzyakov Y (2002) Review: factors affecting rhizosphere

priming effects. J Plant Nutr Soil Sci 165:382–396

Kuzyakov Y (2005) Theoretical background for partitioning of

root and rhizomicrobial respiration by d 13C of microbial

biomass. Eur J Soil Biol 41:1–9

Kuzyakov Y (2010) Priming effects: interactions between living

and dead organic matter. Soil Biol Biochem 42:1363–1371


123

Kuzyakov Y, Bol R (2006) Sources and mechanisms of priming

effect induced in two grassland soil amended with slurry

and sugar. Soil Biol Biochem 38:747–758

Kuzyakov Y, Friedel JK, Stahr K (2000) Review of mechanisms

and quantification of priming effects. Soil Biol Biochem

32:1485–1498

Lambers H, Mougel C, Jaillard B, Hinsinger P (2009) Plant–

microbe–soil interactions in the rhizosphere: an evolu-

tionary perspective. Plant Soil 321:83–115

Lovett GM, Weather KC, Arthur MA, Schultz JC (2004)

Nitrogen cycling in a northern hardwood forest: do species

matter? Biogeochemistry 67:289–308

McClaugherty CA, Pastor J, Aber JD, Melillo JM (1985) Forest

litter decomposition in relation to soil nitrogen dynamics

and litter quality. Ecology 66:266–275

Meier CL, Bowman WD (2008) Phenolic-rich leaf carbon

fractions differentially influence microbial respiration and

plant growth. Oecologia 158:95–107

Moni C, Rumpel C, Virto I, Chabbi A, Chenu C (2010) Relative

importance of sorption versus aggregation for organic

matter storage in subsoil horizons of two contrasting soils.

Eur J Soil Sci 61:958–969

Moorhead DL, Reynolds JF (1993) Changing carbon chemistry

of buried creosote bush litter during decomposition in the

Northern Chihuahuan Desert. Am Midl Nat 130:83–89

Moorhead DL, Sinsabaugh RL (2006) A theoretical model of

litter decay and microbial interaction. Ecol Monogr

76:151–174

Moorhead DL, Lashermes G, Sinsabaugh RL (2012) A theo-

retical model of C- and N-acquiring exoenzyme activities,

which balances microbial demands during decomposition.

Soil Biol Biochem 53:133–141

Mula-Michel HP, Williams MA (2012) Soil type modestly

impacts bacterial community succession associated with

decomposing grass detrituspheres. Soil Sci Soc Am J

77:133–144

Nielsen UN, Ayres E, Wall DH, Bardgett RD (2011) Soil bio-

diversity and carbon cycling: a review and synthesis of

studies examining diversity–function relationships. Eur J

Soil Sci 62:105–116

Olander LP, Vitousek PM (2000) Regulation of soil phosphatase

and chitinase activity by N and P availability. Biogeo-

chemistry 49:175–190

Plante AF, Conant RT, Stewart CE, Paustian K, Six J (2006)

Impact of soil texture on the distribution of soil organic

matter in physical and chemical fractions. Soil Sci Soc Am

J 79:287–296

Potthoff M, Steenwerth KL, Jackson LE, Drenovsky RE, Scow

KM, Joergensen RG (2006) Soil microbial community

composition as affected by restoration practices in Cali-

fornia grassland. Soil Biol Biochem 38:1851–1860

Reber H, Schara A (1971) Degradation sequences in wheat

straw extracts inoculated with soil suspensions. Soil Biol

Biochem 3:381–383

Rhine ED, Sims GK, Mulvaney RL, Pratt EJ (1998) Improving

the Berthelot reaction for determining ammonium in soil

extracts and water. Soil Sci Soc Am J 62:473–480

Rinkes ZL, Weintraub MN, DeForest JL, Moorhead DL (2011)

Microbial substrate preference and community dynamics

during the decomposition of Acer saccharum. Fungal Ecol

4(6):396–407

Romani AM, Fischer H, Mille-Lindblom C, Tranvik LJ (2006)

Interactions of bacteria and fungi on decomposing litter:

differential enzyme activities. Ecology 87:2559–2569

Saiya-Cork KR, Sinsabaugh RL, Zak DR (2002) The effects of

long term nitrogen deposition on extracellular enzyme

activity in an Acer saccharum forest soil. Soil Biol Bio-

chem 34:1309–1315

Sayer EJ, Powers JS, Tanner EVJ (2007) Increased litter fall in

tropical forests boosts the transfer of soil CO2 to the

atmosphere. PLoS One 2(12):e1299

Schimel JP, Weintraub MN (2003) The implications of exoen-

zyme activity on microbial carbon and nitrogen limitation

in soil: a theoretical model. Soil Biol Biochem 35:549–563

Schlesinger WH, Andrews JA (2000) Soil respiration and the

global carbon cycle. Biogeochemistry 48:7–20

Scott-Denton LE, Rosensteil TN, Monson RK (2006) Differ-

ential controls by climate and substrate over the hetero-

trophic and rhizospheric components of soil respiration.

Glob Change Biol 12:205–216

Sexstone AJ, Revsbech NP, Parkin TB, Tiedje JM (1985) Direct

measurement of oxygen profiles and denitrification rates in

soil aggregates. Soil Sci Soc Am J 49:645–651

Sinsabaugh RL, Van Horn DJ, Follstad Shah JJ, Findlay S

(2010) Ecoenzymatic stoichiometry in relation to produc-

tivity for freshwater biofilm and plankton communities.

Microb Ecol 60:885–893

Six J, Conant RT, Paul EA, Paustian K (2002) Stabilization

mechanisms of soil organic matter: implications for

C-saturation of soils. Plant Soil 241:155–176

Snajdr J, Cajthaml T, Valaskova V, Merhautova P, Petrankova

M, Spetz P, Leppanen K, Baldrian P (2011) Transforma-

tion of Quercus petraea litter: successive changes in litter

chemistry are reflected in differential enzyme activity and

changes in the microbial community composition. FEMS

Microbiol Ecol 75:291–303

Snyder JD, Trofymow JA (1984) A rapid accurate wet oxidation

diffusion procedure for determining organic and inorganic

carbon in plants and soil. Commun Soil Sci Plant Anal

15:587–597

Steenwerth KL, Jackson LE, Carlisle EA, Scow KM (2006)

Microbial communities of a native perennial bunchgrass do

not respond consistently across a gradient of land-use

intensification. Soil Biol Biochem 38:1797–1811

Talbot JM, Treseder KK (2012) Interactions among lignin,

cellulose, and nitrogen drive litter chemistry-decay rela-

tionships. Ecology 93(2):345–354

Treseder KK (2008) Nitrogen additions and microbial biomass:

a meta-analysis of ecosystem studies. Ecol Lett 11:1111–

1120

Treseder KK, Balser TC, Bradford MA, Brodie EL, Dubinsky

EA, Eviner VT, Hofmockel KS, Lennon JT, Levine UY,

MacGregor BJ, Pett-Ridge J, Waldrop MP (2011) Inte-

grating microbial ecology into ecosystem models: chal-

lenges and priorities. Biogeochemistry 109:7–18

Van Hees PAW, Jones DL, Finlay R, Godbold DL, Lundstrom

US (2005) The carbon we do not see-the impact of low

molecular weight compounds on carbon dynamics and

respiration in forest soils: a review. Soil Biol Biochem

37:1–13

Waldrop MP, Firestone MK (2004) Microbial community uti-

lization of recalcitrant and simple carbon compounds:


123

impact of oak-woodland plant communities. Oecologia

138:275–284

Wallenstein MD, Weintraub MN (2008) Emerging tools for

measuring and modeling the in situ activity of extracellular

enzymes. Soil Biol Biochem 40:2098–2106

White DC, Davis WM, Nickels JS, King JD, Bobbie RJ (1979)

Determination of the sedimentary microbial biomass by

extractable lipid phosphate. Oecologia 40:51–62

Wickings K, Grandy AS (2011) The oribatid mite Scheloribates

moestus (Acari: Oribitada) alters litter chemistry and

nutrient cycling during decomposition. Soil Biol Biochem

43:351–358

Wickings K, Grandy AS, Reed S, Cleveland C (2011) Man-

agement intensity alters decomposition via biological

pathways. Biogeochemistry 104:365–379

Wickings K, Grandy AS, Reed S, Cleveland C (2012) The origin

of litter chemical complexity during decomposition. Ecol

Lett 15:1180–1188

Wolters V (2000) Invertebrate control of soil organic stability.

Bio Fertil Soils 31:1–19

Xin WD, Yin XQ, Song B (2012) Contribution of soil fauna to

litter decomposition in Songnen sandy lands in northeast-

ern China. J Arid Environ 77:90–95

Yang X, Yang Z, Warren MW, Chen J (2012) Mechanical

fragmentation enhances the contribution of Collembola to

leaf litter decomposition. Eur J Soil Biol 53:23–31

Zelles L (1999) Fatty acid patterns of phospholipids and lipo-

polysaccharides in the characterization of microbial com-

munities in soil: a review. Biol Fertil Soils 29:111–129


123

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