Impact of vegetation community on litter decomposition: Evidence from a reciprocal transplant study with 13C labeled plant litter

Soil Biology & Biochemistry 112 (2017) 248e257

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Impact of vegetation community on litter decomposition: Evidence from a reciprocal transplant study with 13C labeled plant litter Wenjie Lu 1, Nan Liu 1, Yingjun Zhang*, Jiqiong Zhou, Yanping Guo, Xin Yang Department of Grassland Science, China Agricultural University, Beijing 100193, China

a r t i c l e i n f o

a b s t r a c t

Article history: Received 16 December 2016 Received in revised form 11 May 2017 Accepted 16 May 2017

Litter decomposition has been highlighted as one of the crucial biochemical carbon sequestration processes in grassland ecosystems. Vegetation changes of grasslands are associated with an alteration of litter quality and decomposer communities. How they affect litter decomposition and associated carbon flows at the plant-soil interface, is not well understood. We designed a reciprocal transplant litter experiment by incubating 13C-labeled litter in selected patches. The primary aim of this study was to (1) determine the relative effects of litter quality and soil microbial community on litter decomposition rates; (2) estimate the associated carbon incorporated into different groups of the soil microbial community; and (3) verify if the dominant litter decomposed faster at “home” sites, i.e. home-field advantage (HFA) effect. Our data indicated that the interaction between litter type and decomposition site significantly affected litter decomposition. Cellulose contributed the most C during decomposition, and fungal phospholipid fatty acids incorporated the highest level of 13C from labeled litter. There was a higher decomposition rate of cellulose and more 13C incorporation in fungi, when each type of litter was incubated in its dominated sites. HFA index presented positive values that illustrates that the dominant litter had advantage in mediating decomposition processes. Gram positive (GP) bacteria and actinomycetes, they were found to be closely associated with the C priming of native-SOM. From this perspective of HFA, our results help understanding mechanisms of leaf litteresoil feedbacks in grassland, including the return of carbon (C) to the soil through litter decomposition and fraction in functional microbial groups. Practically, the results also imply that a higher biodiversity of grassland will affect the carbon cycle and formation of soil organic matter in ecosystem. Once such litter-soil feedbacks process is considered, vegetation management in grassland will contribute to carbon cycle, formation of soil organic matter in ecosystem. © 2017 Published by Elsevier Ltd.

Keywords: Carbon sequestration Grassland vegetation Home-field-advantage Litter decomposition Reciprocal transplant experiment Stable isotope probing

1. Introduction Grasslands, which cover 40% of the earth land surface, possess about 20% of the soil organic carbon (SOC) stocks globally (Schuman et al., 2002). Annual litter fall and its decomposition process play important roles in the formation and turnover of soil organic matter in grassland ecosystems (Liski et al., 2002). Previous studies have built models for litter decomposition that aid the prediction of energy and matter flux in the decomposition process and can help develop better strategies for grassland management (Berg and McClaugherty, 2008). Climate, litter quality and related

* Corresponding author. E-mail address: [email protected] (Y. Zhang). 1 These authors contributed equally to this work. http://dx.doi.org/10.1016/j.soilbio.2017.05.014 0038-0717/© 2017 Published by Elsevier Ltd.

decomposer communities have traditionally been considered as the main drivers regulating the rate of the litter decomposition (Bradford et al., 2015). Biogeochemical models that describe litter decomposition have been extensively calibrated and validated based on these controlling factors. Recent studies have illustrated that the interactions between litter quality and soil decomposers may have both positive and negative effects on litter decomposition (Ayres et al., 2009; St John et al., 2011; Perez et al., 2013). However, few details are available regarding how such interactions affect decomposition and C flow. Plant species traits, which determine litter quality, are thought to be the predominant control on litter decomposition rates within biomes worldwide (Cornwell et al., 2008). Different species vary greatly in their rate of decomposition due to their chemical composition. Cleveland et al. (2014) noted that the decomposition of a species' litter is consistently correlated with that species’

W. Lu et al. / Soil Biology & Biochemistry 112 (2017) 248e257

carbon strategy. The more accessible C compounds (non-structural carbohydrates, phenolic) and less recalcitrant C (condensed tannins, lignin) can promote litter decomposition (H€ attenschwiler and Jørgensen, 2010). Soil microorganisms play a central role in litter decomposition and partitioning C between CO2 evolution and the sequestration of C into semi-permanent pools in soils. Litter decomposition is greatly influenced by the activities of soil decomposers. Bacteria and fungi comprise more than 90% of the soil microbial biomass and are the main agents in decomposition (Rinnan and Baath, 2009). Considerable progress has been made in understanding how the factors affect the rate of litter decomposition and formation of soil organic matter (Stevenson, 1994). The role of microbial functional groups during C decomposition and sequestration in soils is based on the methods such as activity measurements and biomass. Communities with relatively high proportions of fungi have advantages over communities dominated by bacteria because fungi are able to extend hyphae into the soil to extract nutrients and water (Holland and Coleman, 1987), whereas bacteria are limited in movement. In addition, fungi are major forces in decomposition and formation of soil organic matter (SOM), because they have a wide range of extracellular enzymes that can degrade recalcitrant materials. Stable isotope probing (SIP), combined with isotopic labeling techniques and microbial biomarkers, has been extensively used technique to elucidate the pathway for the translocation of focus elements in particular substrates (Cowie et al., 2010). It has been demonstrated that phospholipid stable isotopic probing could provide more details on soil biogeochemical cycles (Bai et al., 2016), in which microbial consumption and incorporation of 13C-labeled substrate processes are involved (Boschker et al., 1998; Watzinger, 2015). An understanding of the interactions between litter quality and decomposer is particularly important for revealing the biological driving power of the decomposition process. Inappropriate grassland management, such as overgrazing has led to serious degradation in typical steppes of northern China (Barger et al., 2004). In this area Leymus chinensis, Stipa krylovii as well as Artemisia frigida are native species. Meanwhile, the plant communities dominated by the three species represent vegetation conditions from better to worse condition (Li, 1994). Specifically, it results in deterioration (barren, drought) when plant communities change from L. chinensis (LC) patch to A. frigida (AF) patch. Litter and soils in such grasslands are therefore the ideal means to test the interactions of litter types and decomposers, as well as other associated issues. Furthermore, reciprocal litter transplant experiment design we used is helpful to estimate the interaction during litter decomposition. Plant community composition alters in grassland due to disturbances by activities of human being or climate change. This field-based study aimed to provide insights into the impact of vegetation community on litter decomposition. We hypothesized that (1) both litter quality and soil microbial community will affect litter decomposition rates; we expect that (2) carbon incorporated different groups of the soil microbial community; and finally we expect that (3) dominant litter decomposed faster at “home” sites (home-field advantage). 2. Materials and methods 2.1. Study site and experimental setup The study was performed in the Duolun Restoration Ecology Station of the Institute of Botany of the Chinese Academy of Sciences (42
020 N, 116
170 E), Inner Mongolian, China. The study area was located at a semi-arid steppe with a mean annual precipitation

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of 383 mm and a mean annual temperature of 2.1
C. The study area has a long history of grazing and haymaking for animal production. Soil types were classified as Haplic Calcisols according to FAO classification. The plant community was dominated by L. chinensis, S. krylovii, A. frigida, Cleistogenes squarrosa and Agropyron cristatum (Yang et al., 2014). The plot was fenced off in 2003 for ecological research. We chose 3 types of patches for the experiment according to the community dominance. Study sites dominated by L. chinesis (lc) were recognized as L. chinesis sites (LC). Similarly, the community dominated by S. krilovii (sk) and A. frigida (af) were denominated as S. krilovii sites (SK) and A. frigida sites (AF), respectively. Prior to initiating the experiment, soil cores (6 cm diameter; 10 cm in depth) were randomly taken from each plot to estimate physical and chemical properties, including pH, bulk density, and soil texture. 2.2. Labeling of plant litter The plants were labeled in July at the time when RGR (Relative Growth Rate) of the plant is photosynthetically most active. Three days prior to the labeling, a collar of 50 cm  100 cm in size was installed to the depth of 5 cm. The collar possessed a groove on aboveground part to connect the chambers so they had an airtightly seal when labeling. For 13CO2 labeling of the plants, a 250 L (50 cm  50 cm  100 cm) polyethylene plastic chamber was set on the collar over the plants. Labeled CO2 was added in pulses through the chemical reaction between H2SO4 and 13C-NaHCO3 (99 atom % 13C; Cambridge Isotope Laboratories, Inc. USA). Plants within the chamber were labeled by 13C throughout photosynthesis. Litters of labeled S. krylovii, A. frigida and L. chinensis were thoroughly mixed and cut into 5 mm pieces to ensure uniformity. 2.3. Experimental design We used a reciprocal transplant design (i.e., all litter types crossed with all sites) with 3 types of plant litter and 3 sites in our study. The experiments were arranged in a complete randomized design with 5 replicates. A total of 60 litter samples were used for the entire study ([3 litter speciesþ1blank]  3sites  5 replications per site ¼ 60). In each plot, 4 PVC collars (20 cm diameter) were inserted into the soil to 2 cm depth in the selected patches. In October 2014, the reciprocal litter transplant experiment was performed. Surface soils in the traps, apart from the blank ones were incubated with 5 g litter, which was a higher amount of plant litter than has been previously investigated in prior experiments. No litter was applied in the equivalent controls. This constituted an attempt to minimize other potential non-microbial community effects on litter decomposition and isotopic fraction. To avoid fresh litter from falling into the collars, we placed a coarse high density PVC nylon net (mesh size: 1 mm  1 mm) on all collar as soon as we clipped the entire canopy. 2.4. Sample analysis 2.4.1. Soil sampling and measurements After a full year of decomposition, the remaining litters in the collar were collected. Soils samples were taken from the upper layer (0e2 cm) of each treatment in September 2015, and were crumbled and sieved through 2 mm mesh sieves to removed plant material and stones. One portion of the samples was air-dried at room temperature for 2 weeks for chemical analysis, while the other was kept on ice in the field, transported to the laboratory and stored in the 80
C refrigerator for PLFA analysis.

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Soil texture was determined using the hydrometer method. Soil pH was measured in a 1:5 (w/v) soil to reverse osmosis (RO) water ratio after 1 h end-over-end shaking. Total organic carbon of soil and plant residues was determined after Walkley and Black (1934). Nitrogen of soil and plant residues was measured using the Kjeldahl method.

2.4.2. Litter collection and measurements We collected the incubated litter after one-year of incubation. The samples were washed gently using deionized water and were oven-dried for 48 h at 65
C, and then weighed. The percentage of litter mass loss (D) during decomposition was calculated using following formula:

Dð%Þ ¼ 100  ðM0  Mt Þ=M0 where M0 and Mt are the weights of dried leaf litter before and after incubation, respectively. Loss in lignin as well as cellulose was calculated by the equation below (take lignin loss for example):

Dlignin ð%Þ ¼ 1 

Mt Lt  M0 L0

where, Dlignin represents the decomposition rate of lignin (or cellulose) within the litter, Mt represents the final litter mass, M0 represents the initial litter mass, Lt and L0 represents the final and initial lignin concentrations (or cellulose), respectively.

2.4.3. 13C analysis of soil, plant litter and PLFAs The 13C in the sampled litter and soil were analyzed. The 13C incorporated into soil microbial community was determined by analyzing the 13C in ester-linked phospholipid fatty acids (PLFA) composition of the soil and PLFAs were extracted from triplicate subsamples of the 60 soil samples using the standard procedure for PLFA extraction (Frostegård and Bååth, 1996). PLFA nomenclature was also used as described by Frostegård et al (1996) and individual PLFA markers were used to quantify the relative abundance of specific microbial groups (Table 2). Then, the extracted fatty acids were measured by capillary gas chromatography combustion isotope ratio mass spectrometry (GCc-IRMS; GC-C/Delta PLUS XP Thermo Scientific) via a GC/C III interface, and a total of 60 PLFAs were quantified (Balasooriya et al., 2014). Natural abundances of 13C are expressed asd13C (‰), which represents the ratios (R) of 13C/12C relative to Vienna Pee Dee belemnite (V-PDB). The d13C values are defined as:

d13 C ¼




Rsample  Rstandard Rstandard

  1000

Quantitative amounts of individual PLFAs are presented as ng PLFA g1 soil (DW). Subsequently, label allocation in individual PLFAs (ng PLFA-13C g-1 soil) was calculated:

ng PLFA13 C g1 soil ¼ at%13 C  ng PLFA g1 soil 
M ðPLFA  CÞ  M ðPLFAÞ where at%13C is atom percentage value of 13C (at% 13C excess), ng PLFA g1soil is the quantitative amount of PLFA, M (PLFA-C) is the molar mass of the C in the PLFA molecule and M(PLFA) is the molar mass of the PLFA molecule. The d13 C values of the FAMEs were corrected for the addition of a methyl group by using a mass balance equation (e.g. Denef and Six, 2006):

13

d C PLFA ¼

13

13

ðNPLFA þ 1Þ  d CFAME  d CMeOH N ðPLFAÞ

!

where the NPLFA refers to the number of C atoms in the PLFA component, d13 CFAME is the d13C value of the FAME after transesterification, and d13 CMeOH is the d13C value of the methanol used for transesterification.

2.4.4. Calculations to partition the sources of PLFA incorporated 13C Considering the original concentrations of SOM- and plantderived PLFA at the beginning of the measurement were not zero, we use the ratios of increased PLFA to initial plant-derived PLFA to compare the relative PLFA C fractions in microbial groups. Then the proportion of PLFA C derived from added litter and native SOM was estimated by the mass balance equation (Blaud et al., 2012; Bai et al., 2016). Firstly, the amount of litter originated from 13C in individual PLFAs was calculated based on d13C of the added plant litter, native SOM and the individual PLFA:

d13 CPLFA;t  d13 CPLFA;0 %PLFAL ¼ d13 CL;0  d13 CSOM;0

!  100

where %PLFAL is the fraction of the litter-derived part of the individual PLFA when sampled (time t); d13CPLFA,t and d13CPLFA,0 are the d13C of the individual PLFA at sampling time t and at the beginning of the incubation, respectively; d13CL,0 and d13CSOM,0 are the d13C of the added plant litters and native SOM at the beginning of the incubation experiment, respectively. Then, the amount of litter-originated 13C was calculated as:

PLFAL ¼ PLFAT  %PLFAL Finally, we calculated the d13C value of SOM-derived C in individual PLFAs based on a mass balance equation:

PLFASOM ¼ PLFAT  PLFAL

2.5. Data analysis To ensure normality, the PLFA mole percentages were logtransformed prior to analysis. SAS 8.2 (SAS Institute, Cary, NC, USA, 2002) was used to perform ANOVA and correlation analysis. To analyze the effects of sites as well as the combined effects on the amounts of PLFAs (log transformed), Tukey's one-way ANOVA and Duncan's multiple range tests were performed. Two-way ANOVA was applied to examine the effects of site, litter species and their combined effects on indices in the litter decomposition process. Correlation between the 13C changes in litter and litter mass loss was analyzed. To quantify the effect of litter-site pairs, we introduced the home-field-advantage index (HFA) as described by Ayres et al. (2009): HDDi ¼ (DiI e DjI) þ (DiI e DkI) ADDi ¼ (DiJeDjJ) þ (DiK e DkK) H ¼ (HDDi þ HDDj þ HDDk)/(N e 1) ADHi ¼ HDDi e ADDi e H/(N e 2)

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where i, j and k are litters from i, j and k, respectively; I, J and K stand for sites dominated by species i, j and k; D is a measure of decomposition (e.g. litter mass loss or 13C incorporation in decomposers et al); HDD and ADD represent home decomposition differences and away decomposition differences, respectively; H represents the total HFA for all species combined; N represents the number of species; ADH is the additional decomposition for litter species at home. If ADHi > 0, litter from species decomposed faster than at home (i.e. HFA); if ADHi ¼ 0, litter decomposition at home occurred at the rate that was expected (i.e. no HFA); and if ADHi < 0, litter decomposition at home occurred slower than expected (i.e. home-field disadvantage). 3. Results 3.1. Effect of litter type and site on litter mass loss Using ANOVA, both the litter type and decomposition site significantly affected the litter mass loss (F2,44 ¼ 6640.69, P < 0.001; F2,44 ¼ 10.71, P < 0.001), and a significant interaction between litter type and decompose site was observed (F2,44 ¼ 71.53, P < 0.001). As indicated in Fig. 1, the mass loss rate of ar was the highest, followed by lc, and then sk. Mass loss was greatest from litter ar at site AR (72%), and the least from litter sk at site LC (39.33%). Across all sites, the mass loss of litter lc at site LC was significantly higher while the mass loss of litter sk at site LC was significantly lower. Cellulose tended to show a slower decomposition rate and the final decomposed proportions were all under 50%. Furthermore, the decomposition rate of cellulose was affected by the litter type (Fig. 2a; F2, 44 ¼ 94.33, P < 0.05), but no significant difference was observed between sites. Significant interactions between sites and litter type were also detected (F4,44 ¼ 14.25, P < 0.001). The proportion of lost cellulose ranges from 12.78% (sk) to 46.8% (ar). Generally, the loss proportion of litter sk is less than litter ar and lc. Across the sites, litter ar that decomposed at site AR lost the most cellulose, while litter sk lost the least cellulose at site AR. In contrast, cellulose from litter sk and ar possessed relatively higher loss rates at their original sites, respectively. The lost cellulose was significantly correlated to the total mass loss (R2 ¼ 0.7538, P < 0.01).

251

Lignin in the litter exhibited mass loss from 3.71% to 8.14%. No significant correlation was found between lignin loss and total mass loss, but both litter quality and sites had significant effects on degradation (Fig. 2b; F2,44 ¼ 307.6, P < 0.001; F2,44 ¼ 18.4, P < 0.001). Significant interactions between litter type and sites were also observed (F4,44 ¼ 51.97, P < 0.001). At site LC, the originated litter lc showed a higher lignin loss. Litter of sk, though containing higher lignin levels (see Table 1), lost a higher amount of lignin than lc and ar at site SK and AR. With regards to litter ar, the highest lignin loss occurred at site AR and the lowest decomposition rate was observed at site SK (3.71%). 3.2. PLFA profiles 124 individual PLFAs were identified in all sampled soils and only 60 types of individual PLFAs were labeled by 13C (Table 2). The extracted PLFA profiles showed distinctions among the 3 sites, and the individual PLFAs within each type of site also differed in their mole percentage. Furthermore, PLFAs of microbial groups varied between sites, however the PLFAs extracted from the litterincubated soil showed no significant differences to the control within each site type. No significant changes in the PLFA content of AMF and saprophytic fungi were found. GP, GN and actinomycetes at site LC were significantly higher than at AF, and GN in AF sites were higher than in site SK. Both AF and LC possessed a greater abundance of actinomycetes than site SK (P<0.05). The ratio of cy17:0/16:1u7c was higher at site LC compared with sites AF and SK which indicated that bacteria at LC are suffering from stress. 3.3.

13

C enrichment in groups of soil microbial PLFAs

The incorporation of 13C into components of the microbial community was investigated. Individual PLFAs that were incorporated the most included 16:1u7c, 16:1u5c, 16:0 and 18:1u7c. The 3 litter types offered distinct quantities of carbon when transplanted across sites. After incubation with 13C-labeled litter, 13C shifts were significantly detected in the clustered PLFAs that represent fungi, GP and actinomycetes (Fig. 3 a b c). Apart from these sorted PLFAs, minor 13C changes were also detected in other “general” PLFAs

Fig. 1. Mass loss of studied plant litter decomposed at three site types. Both the litter type and decomposition site are significantly affected by the litter mass loss (F2,44 ¼ 6640.69, P < 0.001; F2,44 ¼ 10.71, P < 0.001), and there is a significant interaction between litter type and decompose site (F2,44 ¼ 71.53, P < 0.001). Data are means ± SE.

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Fig. 2. Proportion of the lost cellulose (a) and lignin (b) in litter between the three sites. Lost cellulose is affected by litter type (F2,44 ¼ 94.33, P < 0.001), but there is no significant differences between sites. Significant interaction between sites and litter type were also detected (F4,44 ¼ 14.25, P < 0.001). Lignin was the least decomposed carbon fraction in litter, with a mass loss from 3.71% to 8.14%. Both sites and litter quality had significant effects on its degradation (F4,44 ¼ 307.60, P < 0.001; F4,44 ¼ 18.40, P < 0.001). Significant interaction between sites and litter type is also detected (F4,44 ¼ 51.97, P < 0.001). Data are means ± SE.

Table 1 Descriptions of study sites and litters. Study sites LC

SK

Importance values of 3 dominant species between sites lc 0.62 ± 0.05 0.26 ± 0.05 sk 0.14 ± 0.04 0.75 ± 0.08 af 0.20 ± 0.04 0.21 ± 0.03 Soil physical and chemical properties Bulk density 1.24 ± 0.09 1.3 ± 0.1 sand (g/kg) 639 650 silt (g/kg) 314 290 clay (g/kg) 47 60 PH 7.2 ± 0.15 6.98 ± 0.28 SOC (%) 2.06 ± 0.08 2.31 ± 0.06 N-NH4 (%) 0.030 0.030 N-NO3 (%) 0.140 0.120 Content of structural carbon compounds in litter lc sk Hemicellulose (%) 17 39 Cellulose (%) 13.5 3.8 Lignin (%) 12 19

AF 0.11 ± 0.03 0.15 ± 0.02 0.46 ± 0.07 1.53 ± 0.14 671 275 54 6.7 ± 0.08 2.41 ± 0.08 0.020 0.090 af 25 17.1 8

Italic abbreviations in capital letters represent selected plant communities; lowercase letters represent litter types.

(Fig. 3d). As indicated in Fig. 4a, fungi possessed a relatively higher

preference for 13C, from 1.57 to 4.74 ng PLFA-13C g1 soil (Fig. 4). Both site and litter type affected 13C shifts in fungal PLFAs (P < 0.01). At site LC, a shift of 4.28 ng g1soil 13C in PLFAs occurred after the addition of labeled lc litter. When the litter decomposed “away from home”, the shifts in PLFA-13C were lower, from 3.58 to 3.70 ng g1soil 13C. It also exhibited higher 13C inputs when labeled litter sk or ar were incubated at their original sites (site SK or AR). The exceeded 13C incorporation at home ranged from 13.5% to 110.3% as represented in Fig. 3 a. With the exception of fungi, 13C shifts in GP and actinomycetes were also positive. GP 13C was significantly affected by litter type (P < 0.01) as well as the interaction of litter type and site type (P < 0.05). However, site type was not found to be significant. GP bacteria possessed a relatively stronger ability at LC to sequester 13C from litter lc and ar than that of litter sk. Between sites, the 13C of litter sk offered to GP indicated no significant difference (Fig. 3b). Weak 13C signals in actinomycetes PLFAs were detected, but were also affected by sites and litter (P < 0.01). The trend was similar to that of GP bacteria (Fig. 3c). The 13C alteration PLFAs of other identified groups such as AMF and GN, however, showed consistence with the samples prior to incubation. Beyond the classified groups, 13C shifts in these detected “general” PLFAs indicated significant increases when the labeled litters had decomposed at “home” (Fig. 3d). Isotope carbon assimilation in PLFAs was derived from 2sources: labeled plant litter and organic matter in native soils. We calculated

Table 2 PLFA profiles of sampled soil in the 3 type sites. Microbial groups

Indicated PLFAs

Fungi Bacteria

18:2u6,9, 18:1u9c a15:0, i15:0, i16:0, i17:0, a17:0 16:1u7c, 18:1u7c, cy17:0and cy19:0 16:1u5c 10Me16:0

Study sites, nmol PLFA/g soil LC

AMF Actinomycetes Fungi/Bacteria Resource stress

GP GN

cy17:0/C16:1u7c

7.36 8.61 6.96 2.79 4.10 0.47 0.38

SK ± ± ± ± ± ± ±

0.37 0.23 0.34 0.14 0.18 0.012 0.011

6.76 7.69 6.22 2.54 3.30 0.49 0.36

AF ± ± ± ± ± ± ±

0.49 0.70 0.54 0.21 0.25 0.014 0.006

GP, GN and AMF represent gram positive bacteria, gram negative bacteria and arbuscular mycorrhizal fungi, respectively. Data are means ± SE.

7.36 7.18 9.86 2.54 3.86 0.44 0.35

± ± ± ± ± ± ±

0.79 0.89 0.92 0.26 0.23 0.02 0.013

W. Lu et al. / Soil Biology & Biochemistry 112 (2017) 248e257

Fig. 3.

13

253

C incorporation in groups of soil microbial community, including fungi (a), GP (b), actinomycetes (c) and others beyond the classified groups (d). Data are means ± SE.

Fig. 4. Incorporation of 13C in microbial groups. Over 70% 13C is incorporated to fungal PLFAs. Changes in actinomycetes are correlated to that of GP (R2 ¼ 0.81; P < 0.001). Of all transplanted litter, ar offers both the highest (12.19%) and lowest (1.28%) 13C to general PLFAs.

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carbon from both of them and showed that litter was able to provide more carbon to microorganisms when decomposed at “home” (Fig. 5a). Compared with ar and lc, the more recalcitrant sk litter increased the translocation of 13C from native SOM to microbial biomarkers (Fig. 5b). 3.4. HFA index calculation All the indices we measured were used to calculate the HFA index. Based on litter mass loss, the ADH of lc litter was higher than that of ar and sk litter. The index ADH of both lc and ar litter showed a positive ADH, while the ADH of sk was negatively 1.1478 (Table 3). When calculated using the C compounds fractions, the cellulose of ar and sk was much higher at home. However, the lignin in all tested litter presented an entirely different ADH: litter of ar exhibited a negative value, and was lower than both the litter of lc and sk. Our data also showed that C derived from the 3 types of litter to microbial groups had significant HFA. The estimations of 13 C-incorporation into microbial groups varied: 13C assimilated by gram-positive bacteria was reversed in sk at home, while ar showed disadvantages in fungal 13C assimilation. With respect to the 2 sources of microbial incorporated carbon, the litter supplied more carbon when decomposed at home as the ADH of the litter-derived carbon by 3species was positive. Conversely, when incubated at home, lc litter had an advantage in promoting 13C supplementation of native SOM to microbial PLFAs. As for sk and ar litter, the effect was negative. 4. Discussions 4.1. Litter and microbial community interaction under changing vegetation Previous research has found that plant litter as well as soil microbial biomass are major sources of SOM (Gentile et al., 2011). Soil microorganisms also work as decomposers in the fragmentation and chemical alteration of plant litter (Ayres et al., 2009; Ge et al., 2013; Sinsabaugh et al., 2013). However, grazing activities result in the occurrence of vegetation succession in grasslands, indirectly affecting both litter quality and decomposition (Bagchi and Ritchie, 2011). Through the reciprocal transplanting of 3 litter species, our study has highlighted the importance of the interaction between litter quality and decomposition sites.

Fig. 5.

13

Changes in the vegetation type are associated with differences in litter types, which differed in their carbon qualities, including their concentrations of lignin, cellulose and hemicellulose. Cellulose, and lignin, are major carbon compounds within cell wall, differing in their persistence to decomposition, thus being the controller of decomposition (Glaser, 2005). In the selected patches, changes in the dominant species occurred from lc to sk, and then af, the carbon qualities of which possessed imparities. When the litter shifted from lc to sk, it becomes harder to be broken down because concentration of litter lignin increased. Low amount of labile leaf litter was possessed in ar, a kind of subshrub. Litter with lower recalcitrant compounds, like cellulose, typically decomposes faster €ttenschwiler and Jørgensen, 2010), and the decomposition of (Ha such litter will accelerate element cycling in the system. Our data revealed that cellulose occupied the greatest proportion of lost structural carbon in litter. For ar, it was relatively rich in accessible C compounds, such as soluble protein, fat and other non-structural compounds present in leaf litter (Zhang et al., 2015). Litter mass loss was higher in af at each site. We calculated the carbon quality loss rate, and discovered that cellulose, rather than lignin, was closely correlated to the total loss of mass for incubated litter (R2 ¼ 0.75). The correlation of cellulose and lignin with total loss of mass was closely associated with carbon translocation during decomposition. It is also consistent with previous conclusion that litter quality is a good predictor of carbon mineralization and immobilization (Fanin and Bertrand, 2016; Fanin et al., 2016). Within sites, negative effect on mass loss was observed in lignin, possibly because it requires more energy to be decomposed (Burns et al., 2013). Compounds in litter are distinct in their rate of decomposition and are utilized by decomposers at different stages. However, recent research characterizing the chemical structure and isotopic composition of SOC has revealed a low stability of litterderived lignin in soil (Gleixner, 2013). Soil decomposers have specialized roles in the breakdown of litters, which may be driven by the carbon strategies of the decomposers (Ayres et al., 2009; Sinsabaugh et al., 2013). Fungi and gram-negative bacteria (GN) are reported to utilize easily available substrates. Gram-positive bacteria may assimilate C more recalcitrant C sources from dead fungal or root biomass, not directly from rhizodeposits (Kramer and Gleixner, 2006). Actinomycetes, as well as certain fungal groups, can enter the complex decomposition process later (Fontaine et al., 2011; Marschner et al., 2011; Herman et al., 2012). Further, the metabolic products vary between

C derived from added litter (a) and native SOM (b). Data are means ± SE.

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Table 3 Home advantage index calculated by indices related to litter decomposition. Mass loss

Cellulose

Lignin

13

13

C-fungi

C-GP

13

C-actinomycetes

13

13

C-other general

C-litter

13

C-SOM

lc

HDD ADD H ADH

21.46 5.05 6.81 9.60

15.95 12.20 27.42 0.73

3.93 0.09 2.47 1.55

1.96 0.79 2.34 0.41

0.098 0.101 0.013 0.016

0.153 0.149 0.013 0.010

0.129 0.695 0.817 0.007

1.99 1.53 3.43 0.09

0.10 0.03 0.01 0.06

sk

HDD ADD H ADH

52.18 57.85 6.81 1.15

11.12 52.62 27.42 14.08

4.52 1.25 2.47 0.81

1.11 4.53 2.34 1.08

0.351 0.383 0.013 0.019

0.211 0.233 0.013 0.010

0.356 0.802 0.817 0.341

1.39 6.58 3.43 1.76

0.18 0.25 0.01 0.08

ar

HDD ADD H ADH

44.35 31.72 6.81 5.81

50.01 0.98 27.42 21.61

3.52 4.47 2.47 1.52

3.83 0.17 2.34 1.33

0.279 0.139 0.013 0.128

0.084 0.047 0.013 0.024

1.149 0.465 0.817 0.796

6.25 0.12 3.43 2.70

0.26 0.20 0.01 0.07

microorganisms, and are important precursors that contribute to stable SOC fractions (Chapin et al., 2002; Tian et al., 2015). By incubating 13C labeled litters, our experiment provided evidence that microbial synthesis also plays a crucial role in carbon translocation compared with litter quality. Part of 13C was incorporated into the different decomposer groups. Fungal biomass and 13C incorporation were higher than other groups of microorganisms, suggesting that they are the major group active in regulating decomposition. Further important evidence is that fungalincorporated 13C was well correlated with litter derived 13C and mass loss of cellulose. This suggested that alteration of carbon quality of the litter, rather than the litter quantity, better explained the differences in C sequestration between sites. 4.2. Turnover of litter-derived C under changing vegetation Another ecological function of soil microorganisms during the litter decomposition process is C turnover. The rate of C flow from plants to SOM is eventually determined by the activity of soil microbial community and characteristics of litter. The development of soil microorganisms is related to the nutrient balance between resources and microorganisms (Sinsabaugh et al., 2013). Soil functional groups may alter stoichiometric relations with available resources and effect function, further influencing nutrients release within the system (Carrillo et al., 2016). When the vegetation changed, the C sequestration ability was also impacted by the C source and its turnover. Studies have proven that litter mass loss is largely a result of biodegradation driven by microorganisms surrounding the litter (Rubino et al., 2010). The substrates vary in their C quality and physical accessibility for decomposers resulting in different rates of decomposition. The pattern of microbial 13C incorporation can be regarded as the microbial activity in utilizing carbon substrates (Watzinger, 2015). Carbon flow from labeled plant litter to microbial groups was tracked using PLFA-SIP. At the different sites, 13C incorporation in PLFAs showed distinctions in community structure, but correlations were identified between loss of litter mass and cellulose, as well as 13C incorporated by fungi. Fungal assimilation of 13C was higher than for any other microbial group and more 13C was derived from litter to fungi at sites where the litter was the dominant species. Different groups of soil microorganisms prefer different C sources for their growth (Fontaine et al., 2011; Kramer and Gleixner, 2006). The process stimulates C turnover of the plant-soil system because carbon incorporated by soil microorganisms is from both exogenous litter and endogenous SOM (Gleixner, 2013). Systems with higher recalcitrant inputs are thought to result in a minor

organic loss due to the weak priming effect on native SOM (Bai et al., 2016). PLFA-SIP made it possible to partition measured microbial C from unlabeled native SOM. Our results implied that SOMderived PLFA-13C was negatively correlated with higher GP bacteria as well as relatively larger abundances of actinomycetes in PLFA. Most native SOM originates from recalcitrant compounds and microbial debris that can resist being decomposed for centuries (Gleixner, 2013). Mineralization of native SOM mirrors the richness of resource demanded by microbes; meanwhile, it also reflects the potential C loss from sequestered pools (Bai et al., 2016). However, the changes of 13C incorporation in both GP bacteria and actinomycetes show opposite trends compared with SOM-derived PLFAs. This can be explained by the carbon trade-off between mineralization and immobilization of these microbial components. GP bacteria and actinomycetes tend to allocate more SOM-derived carbon to catabolism (e.g. respiration), than to assimilation for their own growth. In contrast, readily decomposable substrates are favoured by the bacterial energy channel which is characterized by rapid growth, turnover of C and fast cycling of nutrients (Holtkamp et al., 2008; Ingwersen et al., 2008). 4.3. HFA revealed in the transplant experiment Veen et al. (2015) suggested that HFA is an unrecognized factor in explaining variability in litter decomposition, because it implies the affinity between plant litter and soil biota affects the decomposition process (Vivanco and Austin, 2008; Austin et al., 2014). Chemical and morphological properties of litter have been reported to determine the speed of decomposition and result in the functional adjustment of soil decomposers (Strickland et al., 2009; Manzoni et al., 2012). Ayres et al. (2009) reported that litter tends to decompose more quickly at the home sites than away and the HFA is actually a matter of interaction between litter biochemistry and decomposer biota (Perez et al., 2013). Soil decomposers may have developed abilities to allow “host” litter to start rapidly decomposing at “home”. In our study, the difference in the loss of litter mass at “home” compared to “away” was highly variable when the litters were incubated in the in situ transplant experiment. It ranged from 2.91% slower to 7.27% faster at “home” than “away”. When decomposed at a home site, additional decomposition (positive) was observed in lc and ar litter, while an opposite occurred in sk litter. Litter from sk is more recalcitrant to decomposition as it possess a higher lignin concentration. Therefore, we hypothesized that the lower quality of sk somehow impacted its “home advantage”. Recently, the functional breadth (FB) hypothesis stresses that decomposers from recalcitrant litter environments have a wider

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ability to decompose a wider range of litters than those from richer environments (Fanin et al., 2016). The negative advantage of sk in our study also supports the FB hypothesis. SK is a more recalcitrant environment than LC and AR, because the dominant sk possesses a higher lignin concentration. Thus SK would potentially benefit the breakdown of lc and ar. As a result, the reduction of mass loss rate of the “guest litter” in SK was minimized to support the mechanism identified in the FB hypothesis. In contrast, sk had only a minor advantage when decomposed at the habitat from where it was derived. Across highly contrasting ecosystems, interactions between litter and decomposer community are discussed (Strickland et al., 2009; Vivanco and Austin, 2008; Fanin and Bertrand, 2016). Positive effects are explained by the specialization of the decomposer to the particular substrate (Ayres et al., 2009). However, in our study, litters and sites were patches in a single grassland ecosystem. The mass decomposition data indicate that only the litter of lc and ar had a positive HFA. This could be explained by a greater difference in their litter quality compared with that of incubated sites. For the selected patches, the community dominated by sk constituted a stage between LC and AR communities. Importance values indicated that S. krylovii is a vital companion species both in earlier successional stage (LC) and later successional stage (AR). Therefore, in terms of sk litter, the microbial specialization in LC and AR may be weaker when S. krylovii is present. In the other words, the incubated sk litter has more similarities to the surrounding host litter. Based on forest-grassland transplant experiment, Freschet et al. (2012) concluded that high quality litter disappears faster than expected when placed in a high quality litter matrix, but decomposes slower in a matrix of poor quality. The substrate qualityematrix quality interaction (SMI) hypothesis highlighted that HFA is positively related to the magnitude of the difference between the litters involved. With the exception of mass loss rate, indices such as N loss, respiration and soil inorganic N were introduced into the estimations of the interactions between litter and decomposer communities (Freschet et al., 2012; Ayres et al., 2009). Evidence shows that litter chemistry and associated ecological processes change more quickly during decomposition when decomposed in a home environment (Wallenstein et al., 2013). In our study, the decomposition rate of cellulose and lignin, as well as alteration of isotope carbon derived from both litter and native SOM, was used to evaluate HFA. Comparing the HFA index calculated by them, the potential relations were revealed. For example, the positive value of the ADH calculated by cellulose mass loss, 13C -fungi and 13C-litter increased from lc to sk, and then to ar. Alternatively, HFA calculated by GP bacteria and actinomycetes indicated a negative value only in lc, while 13C-SOM showed a positive value. The opposite results were achieved when estimated by sk and ar. This indicated that when it is beneficial for GP bacteria and actinomycetes to incorporate carbon, less 13C is obtained from native SOM. In other words, when the litter of sk and ar are decomposed at their “home site”, a lower magnitude of soil priming exists in comparison with lc. 5. Conclusions Overall, our reciprocal transplant litter experiment by incubating 13C-labeled litter provides new insight to effects of litter type and decomposition sites on decomposition rates and the fate of litter-derived C. During decomposition, it exhibited higher decomposition rate of cellulose and more 13C incorporation in fungi, when each type of litter was incubated in its dominated sites. HFA index presented positive values that illustrate dominant litter had advantage in mediating decomposition process. These results provide evidences for revealing the mechanisms of leaf litteresoil

feedbacks in grassland, including the return of carbon (C) to the soil through litter decomposition and fraction in functional microbial groups. Moreover, these findings indicated that grassland with a higher biodiversity will benefit the litter decomposition within the ecosystem. Once such litter-soil feedbacks process is considered, vegetation management in grassland will contribute to carbon cycle, formation of soil organic matter in ecosystem. Acknowledgements We are grateful to the Duolun Restoration Ecology Station of the Institute of Botany of the Chinese Academy of Sciences for providing the research sites and the support and technical assistance from the people who work there. The research was supported by the earmarked fund for the National Natural Science Foundation of China (31501995), the 973 project (2014CB138805), and Young Elite Scientist Sponsorship Program(YESS)by CAST (2015QNRC001). References Austin, A.T., Vivanco, L., Gonzalez-Arzac, A., Perez, L.I., 2014. There's no place like home? An exploration of the mechanisms behind plant litter- decomposer affinity in terrestrial ecosystems. New Phytologist 204, 307e314. Ayres, E., Steltzer, H., Simmons, B.L., Simpson, R.T., Steinweg, J.M., Wallenstein, M.D., Mellor, N., Parton, W.J., Moore, J.C., Wall, D.H., 2009. Home-field advantage accelerates leaf litter decomposition in forests. Soil Biology and Biochemistry 41, 606e610. Bagchi, S., Ritchie, M.E., 2011. Herbivory and plant tolerance: experimental tests of alternative hypotheses involving non-substitutable resources. Oikos 120, 119e127. , S., Huygens, D., Boeckx, P., 2016. Phospholipid 13C stable Bai, Z., Liang, C., Bode isotopic probing during decomposition of wheat residues. Applied Soil Ecology 98, 65e74. Balasooriya, W., Denef, K., Huygens, D., Boeckx, P., 2014. Translocation and turnover of rhizodeposit carbon within soil microbial communities of an extensive grassland ecosystem. Plant and Soil 376, 61e73. Barger, N.N., Ojima, D.S., Belnap, J., Wang, S.P., Wang, Y.F., Chen, Z.Z., 2004. Changes in plant functional groups, litter quality, and soil carbon and nitrogen mineralization with sheep grazing in an Inner Mongolian Grassland. Journal of Range Management 57, 613e619. Berg, B., McClaugherty, C., 2008. Plant Litter: Decomposition, Humus Formation, Carbon Sequestration, second ed. Blaud, A., Lerch, T.Z., Chevallier, T., Nunan, N., Chenu, C., Brauman, A., 2012. Dynamics of bacterial communities in relation to soil aggregate formation during the decomposition of C-13-labelled rice straw. Applied Soil Ecology 53, 1e9. Boschker, H.T.S., Nold, S.C., Wellsbury, P., Bos, D., de Graaf, W., Pel, R., Parkes, R.J., Cappenberg, T.E., 1998. Direct linking of microbial populations to specific biogeochemical processes by C-13-labelling of biomarkers. Nature 392, 801e805. Bradford, M.A., Berg, B., Maynard, D.S., Wieder, W.R., Wood, S.A., 2015. Understanding the dominant controls on litter decomposition. Journal of Ecology 229e238. Burns, R.G., DeForest, J.L., Marxsen, J., Sinsabaugh, R.L., Stromberger, M.E., Wallenstein, M.D., Weintraub, M.N., Zoppini, A., 2013. Soil enzymes in a changing environment: current knowledge and future directions. Soil Biology & Biochemistry 58, 216e234. Carrillo, Y., Ball, B.A., Molina, M., 2016. Stoichiometric linkages between plant litter, trophic interactions and nitrogen mineralization across the litteresoil interface. Soil Biology and Biochemistry 92, 102e110. Chapin III, F.S., Matson, P.A., Mooney, H.A., Chapin III, F.S., Matson, P.A., Mooney, H.A., 2002. Principles of Terrestrial Ecosystem Ecology. Cleveland, C.C., Reed, S.C., Keller, A.B., Nemergut, D.R., O'Neill, S.P., Ostertag, R., Vitousek, P.M., 2014. Litter quality versus soil microbial community controls over decomposition: a quantitative analysis. Oecologia 174, 283e294. Cornwell, W.K., Cornelissen, J.H.C., Amatangelo, K., Dorrepaal, E., Eviner, V.T., Godoy, O., Hobbie, S.E., Hoorens, B., Kurokawa, H., Perez-Harguindeguy, N., Quested, H.M., Santiago, L.S., Wardle, D.A., Wright, I.J., Aerts, R., Allison, S.D., van Bodegom, P., Brovkin, V., Chatain, A., Callaghan, T.V., Diaz, S., Garnier, E., Gurvich, D.E., Kazakou, E., Klein, J.A., Read, J., Reich, P.B., Soudzilovskaia, N.A., Victoria Vaieretti, M., Westoby, M., 2008. Plant species traits are the predominant control on litter decomposition rates within biomes worldwide. Ecology Letters 11, 1065e1071. Cowie, B.R., Greenberg, B.M., Slater, G.F., 2010. Determination of microbial carbon sources and cycling during remediation of petroleum hydrocarbon impacted soil using natural abundance C-14 analysis of PLFA. Environmental Science & Technology 44, 2322e2327. Denef, K., Six, J., 2006. Contributions of incorporated residue and living roots to aggregate-associated and microbial carbon in two soils with different clay mineralogy. European Journal of Soil Science 57, 774e786.

W. Lu et al. / Soil Biology & Biochemistry 112 (2017) 248e257 Fanin, N., Bertrand, I., 2016. Aboveground litter quality is a better predictor than belowground microbial communities when estimating carbon mineralization along a land-use gradient. Soil Biology and Biochemistry 94, 48e60. Fanin, N., Fromin, N., Bertrand, I., 2016. Functional breadth and home-field advantage generate functional differences among soil microbial decomposers. Ecology 97, 1023e1037. Fontaine, S., Henault, C., Aamor, A., Bdioui, N., Bloor, J.M.G., Maire, V., Mary, B., Revaillot, S., Maron, P.A., 2011. Fungi mediate long term sequestration of carbon and nitrogen in soil through their priming effect. Soil Biology & Biochemistry 43, 86e96. Freschet, G.T., Aerts, R., Cornelissen, J.H.C., 2012. Multiple mechanisms for trait effects on litter decomposition: moving beyond home-field advantage with a new hypothesis. Journal of Ecology 100, 619e630. Frostegård, A., Bååth, E., 1996. The use of phospholipid fatty acid analysis to estimate bacterial and fungal biomass in soil. Biology and Fertility of Soils 22, 59e65. Ge, T., Chen, X., Yuan, H., Li, B., Zhu, H., Peng, P., Li, K., Jones, D.L., Wu, J., 2013. Microbial biomass, activity, and community structure in horticultural soils under conventional and organic management strategies. European Journal of Soil Biology 58, 122e128. Gentile, R., Vanlauwe, B., Six, J., 2011. Litter quality impacts short- but not long-term soil carbon dynamics in soil aggregate fractions. Ecological Applications 21, 695e703. Glaser, B., 2005. Compound-specific stable-isotope (delta C-13) analysis in soil science. Journal of Plant Nutrition and Soil Science 168, 633e648. Gleixner, G., 2013. Soil organic matter dynamics: a biological perspective derived from the use of compound-specific isotopes studies. Ecological Research 28, 683e695. €ttenschwiler, S., Jørgensen, H.B., 2010. Carbon quality rather than stoichiometry Ha controls litter decomposition in a tropical rain forest. Journal of Ecology 98, 754e763. Herman, D.J., Firestone, M.K., Nuccio, E., Hodge, A., 2012. Interactions between an arbuscular mycorrhizal fungus and a soil microbial community mediating litter decomposition. FEMS Microbiology Ecology 80, 236e247. Holland, E.A., Coleman, D.C., 1987. Litter placement effects on microbial and organic-matter dynamics in an agroecosystem. Ecology 68, 425e433. Holtkamp, R., Kardol, P., van der Wal, A., Dekker, S.C., van der Putten, W.H., de Ruiter, P.C., 2008. Soil food web structure during ecosystem development after land abandonment. Applied Soil Ecology 39, 23e34. Ingwersen, J., Poll, C., Streck, T., Kandeler, E., 2008. Micro-scale modelling of carbon turnover driven by microbial succession at a biogeochemical interface. Soil Biology & Biochemistry 40, 864e878. Kramer, C., Gleixner, G., 2006. Variable use of plant- and soil-derived carbon by microorganisms in agricultural soils. Soil Biology & Biochemistry 38, 3267e3278. Li, Y., 1994. Research on the grazing decgration model of the main steppe rangeland in Inner Mongolia and some considerations for the establishment of a computerized rangeland monitoring system. Acta Phytoecologica Sinica 68e79. Liski, J., Perruchoud, D., Karjalainen, T., 2002. Increasing carbon stocks in the forest soils of western Europe. Forest Ecology and Management 169, 159e175. Manzoni, S., Taylor, P., Richter, A., Porporato, A., Agren, G.I., 2012. Environmental

257

and stoichiometric controls on microbial carbon-use efficiency in soils. New Phytologist 196, 79e91. Marschner, P., Umar, S., Baumann, K., 2011. The microbial community composition changes rapidly in the early stages of decomposition of wheat residue. Soil Biology & Biochemistry 43, 445e451. Perez, G., Aubert, M., Decaens, T., Trap, J., Chauvat, M., 2013. Home-Field Advantage: a matter of interaction between litter biochemistry and decomposer biota. Soil Biology & Biochemistry 67, 245e254. Rinnan, R., Baath, E., 2009. Differential utilization of carbon substrates by bacteria and fungi in tundra soil. Applied and Environmental Microbiology 75, 3611e3620. Rubino, M., Dungait, J.A.J., Evershed, R.P., Bertolini, T., De Angelis, P., D'Onofrio, A., Lagomarsino, A., Lubritto, C., Merola, A., Terrasi, F., Cotrufo, M.F., 2010. Carbon input belowground is the major C flux contributing to leaf litter mass loss: evidences from a 13C labelled-leaf litter experiment. Soil Biology and Biochemistry 42, 1009e1016. Schuman, G.E., Janzen, H.H., Herrick, J.E., 2002. Soil carbon dynamics and potential carbon sequestration by rangelands. Environmental Pollution 116, 391e396. Sinsabaugh, R.L., Manzoni, S., Moorhead, D.L., Richter, A., 2013. Carbon use efficiency of microbial communities: stoichiometry, methodology and modelling. Ecology Letters 930e939. St John, M.G., Orwin, K.H., Dickie, I.A., 2011. No 'home' versus 'away' effects of decomposition found in a grassland-forest reciprocal litter transplant study. Soil Biology & Biochemistry 43, 1482e1489. Stevenson, F.J., 1994. Humus Chemistry: Genesis, Composition, Reactions. Strickland, M.S., Osburn, E., Lauber, C., Fierer, N., Bradford, M.A., 2009. Litter quality is in the eye of the beholder: initial decomposition rates as a function of inoculum characteristics. Functional Ecology 23, 627e636. Tian, J., McCormack, L., Wang, J., Guo, D., Wang, Q., Zhang, X., Yu, G., Blagodatskaya, E., Kuzyakov, Y., 2015. Linkages between the soil organic matter fractions and the microbial metabolic functional diversity within a broadleaved Korean pine forest. European Journal of Soil Biology 66, 57e64. Veen, G.F., Freschet, G.T., Ordonez, A., Wardle, D.A., 2015. Litter quality and environmental controls of home-field advantage effects on litter decomposition. Oikos 124, 187e195. Vivanco, L., Austin, A.T., 2008. Tree species identity alters forest litter decomposition through long-term plant and soil interactions in Patagonia, Argentina. Journal of Ecology 96, 727e736. Wallenstein, M.D., Haddix, M.L., Ayres, E., Steltzer, H., Magrini-Bair, K.A., Paul, E.A., 2013. Litter chemistry changes more rapidly when decomposed at home but converges during decomposition-transformation. Soil Biology & Biochemistry 57, 311e319. Watzinger, A., 2015. Microbial phospholipid biomarkers and stable isotope methods help reveal soil functions. Soil Biology and Biochemistry 86, 98e107. Yang, G., Liu, N., Lu, W., Wang, S., Kan, H., Zhang, Y., Xu, L., Chen, Y., 2014. The interaction between arbuscular mycorrhizal fungi and soil phosphorus availability influences plant community productivity and ecosystem stability. Journal of Ecology 102, 1072e1082. Zhang, Y., Tang, S., Liu, K., Li, X., Huang, D., Wang, K., 2015. The allelopathic effect of Potentilla acaulis on the changes of plant community in grassland, northern China. Ecological Research 30, 41e47.