lable at ScienceDirect

Soil Biology & Biochemistry 43 (2011) 1482e1489

Contents lists avai

Soil Biology & Biochemistry

journal homepage: www.elsevier .com/locate/soi lbio

No ‘home’ versus ‘away’ effects of decomposition foundin a grasslandeforest reciprocal litter transplant study

Mark G. St. John a,*, Kate H. Orwin b, Ian A. Dickie a

a Landcare Research, PO Box 40, Lincoln 7640, New Zealandb Soil and Ecosystem Ecology Laboratory, Lancaster Environment Centre, Lancaster University, Lancaster LA1 4YQ, UK

a r t i c l e i n f o

Article history:Received 2 December 2010Received in revised form23 March 2011Accepted 25 March 2011Available online 12 April 2011

Keywords:BacteriaDecompositionFood webFungiHomeefield advantageLitterLitterbagMacrofaunaMicroarthropodsMites

* Corresponding author. Tel.: þ64 3 321 9860; fax:E-mail addresses: stjohnm@landcareresearch.co.n

lancaster.ac.uk (K.H. Orwin), dickiei@landcareresearch

0038-0717/$ e see front matter � 2011 Elsevier Ltd.doi:10.1016/j.soilbio.2011.03.022

a b s t r a c t

Plant litter often decomposes faster in the habitat from which it was derived (i.e. home) than whenplaced in foreign habitats (i.e. away), which has been called the homeefield advantage (HFA) of litterdecomposition. We tested whether the HFA of litter decomposition is driven by decomposer commu-nities being specialized at decomposing litter in their home habitat, by reciprocally transplanting litterfrom grassland to early-successional forest. Unexpectedly, we found an overall disadvantage for at-homedecomposition despite large differences in litter quality (lignin:N) between the two habitats. We foundmore evidence for habitat specialization among secondary decomposers (mites) than the primarydecomposers (bacteria and fungi), suggesting that soil animals may be important in driving HFA patternswhere they do exist. Grass litter decomposition in forest slowed down and became more fungal-based,while tree litter decomposition in grassland increased yet showed no shift to being bacterially-based,relative to ‘at home’ decomposition. This suggests a biological explanation for why a positive HFA wasnot observed. Our results highlight that both environmental context and soil biology can play animportant and sometimes counter-intuitive role in modifying decomposition. A better understanding ofthe interaction between all three primary drivers of decomposition (the environment, litter quality andsoil organisms) is necessary for reliable prediction of decomposition at global scales.

� 2011 Elsevier Ltd. All rights reserved.

1. Introduction

Decomposition is the secondmost important ecosystem functionmaintaining life on Earth, after primary production (Wilkinson,1998). It has been studied for decades (Swift et al., 1979) becauseof interest in nutrient cycling (Hunt et al., 1987; Parton et al., 2007)and carbon sequestration (Prescott, 2010; Wall et al., 2008).Decomposition is driven by three interacting factors: the physico-chemical environment (e.g. temperature, moisture), litter quality(e.g. lignin:N) and decomposer organisms (e.g. bacteria, fungi,invertebrates) (Swift et al.,1979). However, soil organisms are largelyignored in decomposition models because their activity is assumedto be predictably controlled by temperature, moisture and litterquality (Adair et al., 2008; Gholz et al., 2000; Parton et al., 2007;Trofymow et al., 2002; Zhang et al., 2008). While this approach caneffectively model decomposition at a local scale (e.g. Andrén andPaustian, 1987), w30% of the variance in global-scale predictions of

þ64 3 321 9998.z (M.G. St. John), k.orwin@.co.nz (I.A. Dickie).

All rights reserved.

decomposition remains unexplained (Adair et al., 2008; Gholz et al.,2000; Trofymow et al., 2002). This is a considerable source of errorfor modeling future climate scenarios and may be reduced witha better understanding of decomposer organisms.

It has recently been shown that litter tends to decompose morerapidly in the habitat fromwhich it was derived (i.e. home) than inother habitats (i.e. away), which has been termed the homeefieldadvantage (HFA) of litter decomposition (Ayres et al., 2006, 2009a,b;Gholz et al., 2000; Strickland et al., 2009a,b; Vivanco and Austin,2008). Thus litter quality may be relative to the habitat the litter issubjected to rather than being predictable by its chemical compo-sition. A possible reason for this is that decomposer organisms mayspecialize in decomposing litter derived from the plants above them(Ayres et al., 2009a). If so, decomposition models will be prone tomisleading results if they are parameterized with data from either‘away’ litters, standard substrates, or ex situ experiments. Thus weneed a better understanding of the drivers of HFA and howsoil biotaare involved in order to address this potential problem in how wemodel decomposition. Furthermore, the greatest HFAs of litterdecomposition recorded are for two studies (of three total)comparing grassland and forest systems (Hunt et al., 1988; Norriset al., 2001). From this Ayres et al. (2009a) speculated that larger

M.G. St. John et al. / Soil Biology & Biochemistry 43 (2011) 1482e1489 1483

disparities in litter quality may lead to greater HFAs of litterdecomposition. This is interesting as grassland-to-forest conversionis an important global change resulting from fire suppression, thespread of invasive trees and afforestation (Hibbard et al., 2001;Richardson and Rejmánek, 2004).

We studied litter decomposition in a subalpine grassland-to-forest successional system in New Zealand by reciprocally trans-planting litter between grassland and forest. Our objectives were tofirst determine if a large HFA of litter decomposition would beobserved for this transplant as predicted for large differences inlitter quality (Ayres et al., 2009a), and then to determine ifdecomposer organisms were responsible for the HFA of litterdecomposition. We would expect to see decomposer communitycomposition to be habitat specific, and less influenced by the typeof litter experimentally provided, if it is true that decomposerscommunities are specialized to decomposing litter from the plantsabove them. It also follows that if specialized decomposercommunities are responsible for HFA of litter decomposition, theyshould be at a disadvantage when presented with ‘away’ litter andtheir biomass should follow an HFA pattern similar to that of thelitter itself. We tested the following hypotheses to accomplish thesethree objectives:

(H1) there would be a large, positive HFA of litter decompositionin this system (because greater disparities in litter quality areexpected to generate larger HFA effects),(H2) decomposer community composition would be morestrongly driven by habitat than litter type (because specializa-tion of the decomposer community is a suspected mechanismdriving the HFA of litter decomposition), and(H3) there would be an HFA of decomposer productivity (i.e.biomass or abundance; because decomposers should performworse on foreign litter than on that which they are specialized todecompose).

We address these hypotheses by measuring the bacterial, fungaland mite communities and mass loss in litterbags of grass and treelitter reciprocally transplanted between grassland and forest. Bytesting these hypotheses in combinationwe better resolve the leastunderstood driver of decomposition (i.e. soil biology) and improveour ability to predict it.

2. Materials and methods

2.1. Study site

Our study site was a 15 ha area on a river terrace in the Korowai/Torlesse Tussocklands Park, NewZealand (43�1104900 S,171�5204600 E).It was comprised of mono-dominant patches of Kunzea ericoides (A.Rich) Joy Thomps. trees (‘kanuka’) established into a matrix ofpreviously grazed (w55 years prior) grassland (Agrostis capillaris,Anthoxanthum odoratum, Festuca novae-zelandiae and Festuca rubra).SoilswereCassHill soils (Orthic BrownSoils/Dystrudepts) developedfrom loess parentmaterial overlaid onmoraine deposits. Soil pHwas5.34 � 0.02 (mean � 1 SE). Annual rainfall averages w1100 mmevenly distributed throughout year, and annual air temperaturesaverage 7.7 �C (min: �7.5 �C; max: 27.5 �C). We found 10 plots ingrassland areas that were at least 20 m from any kanuka trees andthen established a paired forest plot (with closed kanuka canopy)within 25e50 m of each grassland plot. Grassland plots weredominated by thick growth of the aforementioned grass species andaccumulated grass litter. Forest plot understorey vegetation includedthe occasional sparse patch of grasses alongwith amix of native andnon-native herbs; however, the dominant understorey feature wasbare, exposed mineral soil with little evidence of litter build up.

2.2. Litterbags

Grass and tree (kanuka) litter were collected in February 2008from a similar river terrace immediately adjacent to our study site.Abscised grass stems supported by current year’s growth werehand collected. Tree litter was collected by lightly shaking stems toencourage abscised, unfallen leaves and twigs onto tarps placedunderneath. Fifty grams (�1 g) of air-dried litter of each litter typewas placed individually into heat-sealed litterbags (200� 250mm)constructed of a top layer of 1.5 mm nylon mesh, an inner bottomlayer of 100 mm nylon mesh (to discourage physical mass loss ofsmall leaf material) and a bottom outer layer of 1.5 mm nylonmesh.In March 2008 two grass and two tree litterbags were affixed to thesurface of each plot directly on top of the previous year’s litter andunder a square meter section of 12-mm-mesh galvanized steelsecured by aluminum pegs. Three additional ‘traveler’ litterbags perlitter type were handled identically, but immediately collected intopolyethylene bags and returned to the lab to determine mass lossdue to handling. One set of litterbags was then collected after 9months and the last set after 12 months in the field. We chose tomeasure the decomposer community in litterbags at 9 months asa near-optimal point in time: close to when the majority decom-position would have occurred for the year (based on publisheddecomposition curves such as those in Coleman et al., 2004 andPrescott, 2010) and when the decomposers most responsible forthat mass loss would likely still have been abundant in the litter-bags (based on litterbag succession data presented in Anderson,1975). At 12 months the community of decomposers in litterbagswould more likely represent those adapted to later stages ofdecomposition and be less representative of the decompositionthat had occurred over the previous 12 months. Mass loss wascalculated as the difference between initial and final dry mass (at60 �C), correcting for losses during handling, and dividing by initialmass. An additional correction for allochthonous input of tree litterinto all litterbags placed into kanuka stands was determined bysubtracting the average mass of tree litter found in grass litterbags.

Litter quality (lignin:N) was determined by measuring percentlignin (by sulfuric acid digestion; Rowland and Roberts, 1994) andpercent nitrogen (N) (Leco CNS, Leco Laboratory Equipment Corp.,St Joseph, MI, USA) of both litter types from returned traveler bagsand from all bags collected at 9 months.

We used phospholipid fatty acid analysis (PLFA; Bardgett et al.,1996; Bligh and Dyer, 1959) on freeze-dried and ground litter tomeasure the broad structure of the microbial community that hadcolonized litterbags. Only known bacterial fatty acid markers (cy-17:0, cy-19:0, i-15:0, a-15:0, i-16:0, i-17:0, 16:1u9, and 17:0) wereusedwhenanalyzingbacterial biomass andcommunity composition.We calculated Shannon diversity (H0, henceforth ‘diversity’) of thebacterial PLFAmarkers according toMagurran (1988) and interpret itas an indicator of community composition. We avoid the issues ofusing diversity indices on PLFA data raised by Frostegård et al. (2011)as we only use this metric in combination with other communityanalyses, and not as a surrogate for species diversity. Ergosterol wasalso extracted from freeze-dried ground material, based on themethods described in Ruzicka et al. (1995) and Feeney et al. (2006) toobtain a measure of fungal biomass that is not potentiallyconfounded by the presence of plant fatty acids (i.e. PLFA 18:2u9,12).Basal respiration (BR) and substrate-induced respiration (SIR), rela-tive indicators of microbial activity and biomass respectively, werealso measured (Anderson and Domsch, 1978; Wardle, 1993).

Fungal communities were determined via T-RFLP peak-profileanalysis (Dickie and FitzJohn, 2007). DNA from 0.1 to 0.15 g oflitter was extracted using Soil DNA kits (MoBio Laboratories Inc.,Carlsbad, CA), with fungal DNA amplified using ITS1F-FAM andITS4-VIC primers (Dickie and FitzJohn, 2007). We cleaned positive

Forest Grassland Forest GrasslandGrass litter Tree litter

0

10

20

30

40

Perc

ent l

itter

mas

s lo

ss

Litter type: F1, 37 = 194.49, P < 0.001Habitat: F1, 37 = 168.62, P < 0.001Litter type X Habitat: NS

Fig. 1. Percent of original mass of grass and tree litter lost from litterbags after 12months either at ‘home’ (black bars) or ‘away’ (white bars). Bar heights are means � 1SE. Effects of litter type (grass, tree), habitat (grassland, forest) and their interactionwere determined by ANOVA. Significance of homeefield advantage (HFA) determinedby a two-sided, one-sample t-test.

M.G. St. John et al. / Soil Biology & Biochemistry 43 (2011) 1482e14891484

PCR products (ZR-96 DNA Kits; Zymo Research, Orange, CA),digested with HpyCH4IV (NEB, New England Biolab, Ipswich, MA)and BsuRI (Fermentas, Burlington, Canada) restriction enzymes,denatured with highly de-ionized formamide, and ran samplesthrough capillary electrophoresis with MapMaker 1000 standard(Bioventures Inc., Murfreesboro, TN). We used peak-profiles froma single channel to indicate total species richness and shifts infungal community composition. Peaks were binned using clusteranalysis in R (R Development Core Team, 2010) based on completelinkage clustering with a cut height of 2.5.

Microarthropods, mainly mites (Acari), were extracted usingTullgren funnels (Crossley and Blair, 1991) from approximately 10 g(dry wt.) subsamples of each litterbag. All mites within the Oriba-tida (except the Brachychthoniidae) were identified to morpho-species and all others to family (St. John et al., in press), thenassigned to functional groups according to Moore et al. (2005).

2.3. Data analysis

The homeefield-advantage index was calculated for eachgrasslandeforest plot pair as described by Ayres et al. (2009a).Briefly, this index is a measure of the percent change in decom-position of both litter types at home based on their relative percentmass losses within each habitat. This formulation controls forinherent differences in habitat that may affect decomposition (i.e.one habitat may simply be a better habitat than the other fordecomposition of most substrates) and produces a single HFA indexas the net for both litter types being considered. If we let ‘A’ and ‘B’represent litter of the two species under consideration and ‘a’ and‘b’ their respective habitats, then their relative mass losses withineach habitat are calculated as:

ARMLa ¼ Aa

Aa þ Ba

and the percent HFA for the pair is:

HFA index ¼�ARMLa þ BRMLb

ARMLb þ BRMLa

�� 100� 100

Note that this formulation specifically tests for the presence ofthe HFA phenomenon, not the individual HFA of each species in theanalysis. Calculating the HFA for individual species requires three ormore species in fully reciprocal transplants (Ayres et al., 2009b),which is beyond the scope of our study. We used a two-sided, one-sample t-test to determine if the HFA index was significant. Therelationship between response variables (e.g. mass loss) and littertype (grass vs. tree) and habitat type (grassland vs. forest) withinteraction was determined by ANOVA. Insignificant interactionterms were subsequently removed.

We ordinated bacterial (PLFA), fungal (T-RFLP) and arthropodcommunities using principal components analysis (PCA). Robust-ness of these ordinations was confirmed by comparing them withnon-metric multidimensional scaling plots (NMDS, k ¼ 2) gener-ated from the same data and finding highly similar patterns.Significance of the effects of litter type and habitat on communitycomposition was determined by non-parametric multiple analysisof variance (PERMANOVA; Anderson, 2001). A subsequent test fordifferences in between-sample distances (‘dispersion’; Anderson,2006) confirmed that significant effects were caused by differ-ences in community centroids (i.e. means) rather than communitydispersion (i.e. variability) in all cases.

All statistics and figures were generated with R v. 2.11.1(R Development Core Team, 2010). Response variables weretransformed prior to analysis as required to meet the assumptionsof normality. Differences are significant at a ¼ 0.05 unless stated

otherwise. All community data were converted to proportions foreach group and arcsin-square-root transformed prior to PCA(function rda of R package vegan), NMDS (function metaMDS of Rpackage vegan), PERMANOVA (function adonis of R package vegan)and analysis of multivariate community dispersions (functionbetadisper of R package vegan). We used Euclidean distances forbacterial and mite communities and Raup-Crick distances for thefungal community data (T-RFLP).

3. Results

3.1. Homeefield advantage of litter decomposition

Lignin:N of grass (10.5 � 0.4 [mean � 1 SE]) was significantlylower than tree litter (50.6 � 1.7) after 9 months of decomposition(data pooled across habitats, t38 ¼ �22.3, P < 0.001). There was noevidence of an HFA of litter decomposition (Fig. 1). Instead therewas a significant net disadvantage to at-home decomposition (HFAindex:�26.8� 3.1; t9¼�8.6994, P< 0.001). Mass loss at 12monthsranged from a low of 6.8 � 1.1% for tree litter at home to a high of33.7 � 0.7% for grass litter at home. The exceptionally poordecomposition of tree litter at home drove the negative HFA, whilegrass litter decomposed more quickly at home than away.

3.2. Decomposer community composition and diversity

Litter type was the strongest predictor of bacterial communitycomposition although communities on tree litter appeared to alsobe weakly sensitive to habitat (Table 1; Fig. 2a). Litter type wasa strong predictor of fungal community composition, with evidencefor an effect of habitat but only as aweak interactionwith litter type(Table 1; Fig. 2b). Mite community composition was stronglyrelated to habitat with no evidence for an influence of litter type(Table 1; Fig. 2c).

Bacterial PLFA diversity was higher in grassland than forest butdid not differ between litter types (Fig. 3a). Fungal richness (T-RFLP)was higher on grass than tree litter and did not differ by habitat(Fig. 3b). Mite richness was higher in forest than grassland for both

Table 1Significance of litter type (grass, tree) and habitat (grassland, forest) effectson community composition of bacteria (PLFA), fungi (T-RFLP) and mites (alltaxa combined) in litterbags after 9 months in the field, as determined by PERMA-NOVA. Boldface type indicates the greatest R2 for each taxa (row).

Litter Habitat Litter � Habitat

P (R2) P (R2) P (R2)

Bacteria 0.001 (0.44) 0.013 (0.09) NSFungi 0.001 (0.64) 0.497 (0.01) 0.002 (0.09)Mites 0.458 (0.01) 0.001 (0.41) NS

M.G. St. John et al. / Soil Biology & Biochemistry 43 (2011) 1482e1489 1485

nematode-feeding mites and oribatids regardless of litter type(Fig. 3c, d).

3.3. Decomposer productivity

Therewas no evidence of an HFA of decomposer productivity forany of the groups measured. Bacterial biomass (PLFA) was greaterfor grass than tree litter, but did not respond to habitat (Fig. 4a).Bacterial biomass and activity as determined by SIR (mgCO2 gC�1)and BR (nmol g�1), respectively, displayed similar patterns as forbacterial PLFA biomass (SIR: grass litter in forest [176.3 � 10.0],grass litter in grassland [182.3 � 6.2], tree litter in forest[96.9 � 6.2], tree litter in grassland [86.1 � 8.5], litter type effectF1, 37 ¼ 123.84, P < 0.001, habitat effect NS, litter typeehabitatinteraction NS; BR: grass litter in forest [84.2 � 12.2], grass litter ingrassland [99.9 � 9.5], tree litter in forest [45.1 � 3.1], tree litter ingrassland [39.9 � 3.2], litter type effect F1, 37 ¼ 37.16, P < 0.001,habitat effect NS, litter typeehabitat interaction NS). Ergosterol (anestimate of fungal biomass) was significantly lower on grass litter athome than when in forest, while that on tree litter was similarregardless of habitat (Fig. 4b). Nematode-predatory mites weremore abundant on grass litter and there was a significant interac-tion with mites being more abundant at home vs. away (Fig. 4c);although, this was not significant when tested as an HFA. Oribatidmites tended to be more abundant in forest, especially on grasslitter, producing a significant interaction (Fig. 4d).

4. Discussion

4.1. Homeefield advantage of litter decomposition

Our results run counter to the globally dominant trend of an HFAof litter decomposition. We found no evidence for our hypothesis ofa large HFA of litter decomposition (H1) despite a five-fold differ-ence in lignin:N for the litters in our study. Instead, we found the

Fig. 2. Principal components analysis of bacterial (PLFA; a), fungal (T-RFLP; b) and mite (allsymbols) or ‘away’ (white symbols). Circle (grass litter) and square (tree litter) symbols are

largest negative HFA of litter decomposition seen in any litterbagstudy to date (Ayres et al., 2009a). The simplest interpretation ofthe observed pattern e that decomposition was positively relatedto litter quality (grass > tree) and habitat microclimate e seems tosupport the practice of modeling litter decomposition withoutinvoking soil biology. However, implicit in that approach is thateither decomposer organisms are widely dispersed (Anderson,1977; Fenchel and Finlay, 2004; Finlay and Fenchel, 2004;Hillebrand, 2004) thus finding their preferred food resources butperforming at a level regulated by the environment, or that soilorganisms are habitat specific (Anderson, 1977; Behan-Pelletieret al., 2008; Karasawa and Hijii, 2004; McGuire et al., 2010; Niel-sen et al., 2010) and perform at a level regulated by the quality oftheir resources. Our data on decomposer communities andproductivity proved illuminating in exploring these alternativesalong with the remaining hypotheses.

4.2. Decomposer community composition and diversity

We found little support amongst the primary decomposers(bacteria and fungi) for our hypothesis that decomposer commu-nity composition would be driven by habitat more so than littertype (H2; Table 1; Fig. 2a, b). This suggests that the lack of an HFA oflitter decomposition may have been caused by these importantdecomposer organisms exploiting their preferred substratesregardless of habitat, and fits with expectations of microscopicorganisms being highly vagile (Fenchel and Finlay, 2004; Finlay andFenchel, 2004; Hillebrand, 2004). However, the diversity of bacte-rial PLFA’s was consistently greater in grassland than forest, indi-cating these were different communities and demonstrating somelevel of habitat specificity among the primary decomposers. It ispossible that this pattern was driven by unsuitability of the foresthabitat for certain bacterial species (Nielsen et al., 2010); however,the use of diversity indices with PLFA data has recently beenquestioned (Frostegård et al., 2011) partly on the basis that PLFAmarkers are not analogous to species. For this reason we havetreated PLFA diversity as an indicator of community composition,but not of species per se. As noted by Frostegård et al. (2011), highdiversity does not indicate high naturalness, nor does diversityprovide an adequate indicator of the total data in PLFA. Nonethe-less, we feel the use of diversity indicies with PLFA data, as a part ofa more complete interpretation (i.e., along with additional metricsand multivariate analysis), remains a valid approach.

In contrast to the primary decomposers, we found that mites emainly oribatids (litter- and fungal-feeders) and predators ofnematodes e were predominantly habitat specific and litter typewas not related to their community composition (Table 1;

taxa combined; c) communities from litterbags after 9 months either at ‘home’ (blackcentroids � 1 SE for all litterbags within a treatment.

2.1

2.2

2.3Ba

cter

ial P

LFA

H'

FF

a

Litter type: F1, 21 = 3.60, P = 0.072Habitat: F1, 21 = 9.45, P = 0.006Litter type X Habitat: NS

0

5

10

15

Fung

alric

hnes

s (T

−RFL

P)

b

Litter type: F1, 35 = 20.70, P < 0.001Habitat: NSLitter type X Habitat: NS

Forest Grassland Forest GrasslandGrass litter Tree litterTT

0

1

2

3

Nem

atod

e−fe

edin

g m

ite

ffric

hnes

s c

Litter type: NSHabitat: F1, 37 = 7.30, P = 0.010Litter type X Habitat: NS

Forest Grassland Forest GrasslandGrass litter Tree litterTT

0

1

2

3O

ribat

id m

iteric

hnes

sd

Litter type: NSHabitat: F1, 37 = 24.15, P < 0.001Litter type X Habitat: NS

Fig. 3. Diversity of bacterial PLFA peaks (a), and taxon-richness of fungi (T-RFLP; b), nematode-feeding (c) and oribatid mites (d) from litterbags after 9 months either at ‘home’(black bars) or ‘away’ (white bars). Bar heights are means � 1 SE. Effects of litter type (grass, tree), habitat (grassland, forest) and their interaction were determined by ANOVA.

M.G. St. John et al. / Soil Biology & Biochemistry 43 (2011) 1482e14891486

Fig. 2c, d). These findings provide robust support for hypothesis H2and fit with expectations of limited dispersal and highmicrohabitatspecificity of microarthropods (Anderson, 1977; Behan-Pelletieret al., 2008; Karasawa and Hijii, 2004; Nielsen et al., 2010; St.John et al., 2002). The habitat specificity of mites suggests thatthese animals may play an important role in driving the HFA oflitter decompositionwhere this pattern is observed. It also supportsthe expectation that the exclusion of microarthropods, and that oflarger decomposers (e.g. earthworms and millipedes), by using finelitterbag mesh or in lab assays may produce erroneous estimates ofdecomposition in certain systems (Kampichler and Bruckner, 2009;Swift et al., 1979).

Thus these data demonstrate habitat specificity for significantportions of the decomposer communities (a pre-requisite forhypothesis H2 as a mechanism for HFA patterns) despite the closeproximity of our paired plots (w50 m). Similarly, there was norelationship between the magnitude of the HFA response anddistance between forest habitats involved in reciprocal transplantsfrom prior HFA of litter decomposition studies (F1, 33 ¼ 1.50,P ¼ 0.230) (Barlow et al., 2007; Bocock et al., 1960; Castanho and deOliveira, 2008; González et al., 2003; Hobbie et al., 2006;McClaugherty et al., 1985; Prescott et al., 2000; Rothstein et al.,

2004; Vivanco and Austin, 2008). At least half of these HFA studiesused similar plot spacing as ours, thus the negative HFA pattern ofthe current study was unlikely to be due to proximity of plots.

4.3. Decomposer productivity

We found no support for our hypothesis that there would beHFA patterns in decomposer organism productivity (H3; Fig. 4),which is unsurprising given there was no HFA of litter decompo-sition (H1) in our study. Grass litter decomposition slowed downand became more fungal-based in forest (Fig. 4b, d). This shift tofungal decomposition in forests fits with expectations thatdecomposition in grasslands is relatively bacterially-based, withhigher abundances of nematodes and their predators, while that inforests is fungally-based, with higher abundances of oribatid mitesand other fungal-feeders (Wallwork, 1976; Wardle, 2002). Incontrast, tree-litter decomposition increased, yet showed no shiftto bacterially-based decomposition when in grassland, relative towhen in forest (Fig. 4a, c). This asymmetrical response is likelyindicative of a biological explanation for why a positive HFAwas notobserved. That is, it appears tree litter decomposition benefitedfrom the presence of surrounding grass litter (i.e. litter mixing)

0

5

10

15

20

25

30

35To

tal b

acte

rial P

LFA

(nm

ol g

−1)

a

Litter type: F1, 21 = 25.90, P < 0.001Habitat: NSLitter type X Habitat: NS

0

10

20

30

40

50

60

70

Ergo

ster

ol (µ

g g−1

)

b

Litter type: F1, 20 = 3.66, P = 0.070Habitat: F1, 20 = 6.77, P = 0.017Litter type X Habitat: F1, 20 = 9.04, P = 0.007

Forest Grassland Forest GrasslandGrass litter Tree litter

0

20

40

60

80

Nem

atod

e−fe

edin

g m

ites

(10

g−1) c

Litter type: F1, 36 = 30.75, P < 0.001Habitat: F1, 36 = 10.69, P = 0.002Litter type X Habitat: F1, 36 = 13.61, P < 0.001

Forest Grassland Forest GrasslandGrass litter Tree litter

0

20

40

60

80O

ribat

id m

ites

(10

g−1)

d

Litter type: F1, 36 = 3.81, P = 0.059Habitat: F1, 36 = 53.87, P < 0.001Litter type X Habitat: F1, 36 = 7.47, P = 0.010

Fig. 4. Biomass of bacteria as estimated by PLFA analysis (a) and fungi, as estimated by ergosterol content (b), and abundance of nematode-feeding (c) and oribatid mites (d) fromlitterbags after 9 months either at ‘home’ (black bars) or ‘away’ (white bars). Bar heights are means � 1 SE. Effects of litter type (grass, tree), habitat (grassland, forest) and theirinteraction were determined by ANOVA.

M.G. St. John et al. / Soil Biology & Biochemistry 43 (2011) 1482e1489 1487

while it was the forest decomposer community that benefited fromthe addition of the labile grass substrate. The contrast between thegrass plots, which had thick grass and litter cover (i.e. abundant,labile fuel for decomposition) versus the sparsely vegetated,predominately bare-soil understorey of the forest plots (i.e. poor inboth litter quantity and quality) supports this mechanism asa possibility.

Some studies have demonstrated that mixing of litter typesstimulates decomposer biomass and diversity, and decomposition(Fyles and Fyles, 1993; Hansen and Coleman, 1998; Hansen, 2000;McTiernan et al., 1997; Rustad and Cronan, 1988; Taylor et al.,1989; Wardle, 2006); although, a few studies have shown neutraland negative effects on decomposition (Klemmedson,1992; Prescottet al., 2000; Rustad and Cronan, 1988; Thomas, 1968). Presumably,stimulation is a consequence of litter trait complementarity: highquality substrates may provide fuel to assist the decomposition ofmore recalcitrant litter, while the latter may provide greater struc-ture or refuges and therefore access for a greater abundance ordiversity of decomposers (Hansen and Coleman, 1998; Hansen,2000; Wardle, 2006). Bacterial and fungal decomposition isa ‘hopeful act’whereby they exude extracellular enzymes that break

organicmatter down into ingestiblemolecules, with no guarantee ofa return on investment (Prescott, 2010; Schimel and Bennett, 2004).It is likely that the decomposition of tree litter in grassland wassubsidized by the decomposition of the surrounding grass litterthrough a constant immigration of bacterial cells and their digestiveenzymes even though tree litter, having a high lignin:N ratio, wasunlikely to independently support bacterial growth and succession(Schimel and Bennett, 2004). The divergent bacterial communityassociatedwith tree litter in grassland relative to in forest is evidencein support of this effect (Figs. 2a and 3a; Table 1). Conversely, thefungal-based decomposer community of the forest habitat was ableto thrive on the grass substrate as evidenced by the significantincrease of fungal biomass andoribatid abundance ongrass in forestsrelative to grassland (Fig. 4b, d).

Evidence from previous reciprocal litter transplant studiessupports our interpretation. We reclassified the 35 foresteforestreciprocal litter transplant studies reviewed in Ayres et al. (2009a)based on whether or not home litter was cleared prior to place-ment of litterbags. HFA values were both positive in 11 of the 12studies where the home litter was cleared (Bocock et al., 1960;Castanho and de Oliveira, 2008; Vivanco and Austin, 2008) and

M.G. St. John et al. / Soil Biology & Biochemistry 43 (2011) 1482e14891488

significantly higher than in the 23 studieswhere home litterwas leftintact (t33 ¼ �2.72, P ¼ 0.010) (Barlow et al., 2007; González et al.,2003; Hobbie et al., 2006; McClaugherty et al., 1985; Prescottet al., 2000; Rothstein et al., 2004). Our interpretation is that theeffect of surrounding litter is analogous to inertia. Decomposition ofa small amount of low-quality litter may be swept along partially asan indirect consequence of decomposer activity (rather than directconsumption of the low-quality litter) when placed in an environ-ment with large amounts of high quality litter; whereas, an envi-ronment with low litter quantity or quality will have lessdecompositional inertia to act upon experimentally providedsubstrates. An implicit assumption in the hypothesis that decom-poser organisms drive the HFA of litter decomposition is that theiraction on the litter is direct; they either are, or are not, pre-adaptedto consuming their home litter.We suggest thatfinding a lack of HFAof litter decomposition says little about the degree to whichdecomposer communities are pre-adaptated to decompose homelitter due to the potential for overwhelming indirect effects on theexperimental litter when abundant alternative litter sources areavailable.

This imbalancee that tree litter decomposition in grassland wasa passive consequence of grassland decomposer activity accessingtheir preferred substrates while grass litter decomposition in forestwas an active consequence of a decomposer community beingpresented with a novel, higher quality substrate e has criticalimplications for the interpretation of HFA studies and the design ofdecomposition experiments. Studies where this imbalance is notimportant (i.e. decompositional inertia is low) are more likely togenerate in situ HFA values representative of the decomposercommunities’ abilities for home and away litters regardless ofwhether litter is removed from the area of the litterbag. In contrast,studies where decomposers lacked concurrent access to theirpreferred resources, because ‘home’ litter was either physicallyremoved from plots (e.g. Bocock et al., 1960; Castanho and deOliveira, 2008; Hunt et al., 1988; Vivanco and Austin, 2008) or thedecomposers were removed from their home environments (e.g.Ayres et al., 2009b; Strickland et al., 2009a), may havemeasured thedecomposer community’s ability to decompose a given litter (andhence a biological mechanism for the HFA of litter decomposition),but not necessarily the decomposition (or HFA) that would haveoccurred in situ (i.e. in the presence of decomposer inertia generatedfrom surrounding litter). Furthermore, the imbalance demonstratesthat whether or not litter is cleared before placing litterbags in thefield is not necessarily equivalent to the effect of experimentallymixing litters within litterbags, as the latter would lack inertia.Finally, it follows that biologically-driven HFAs of litter decompo-sition are more likely to be detected in field studies of comparisonswithin ecosystem types (e.g. either forests or grasslands; fungal-based or bacterial-based) than between vastly differing ecosystemtypes (e.g. forests versus grasslands; fungal-based versus bacterial-based) due to there being potentially fewer confounding factors.Whether or not local litter should be removed prior to placement oflitterbags in HFA studies is dependent on the question being asked.It is prudent to leave litter intact if one intends to test for an HFA orobtain decomposition rates representative of natural rates. Littershould be removed if one intends to reveal the potential of thedecomposer community to drive theHFAphenomenon; however, indoing someasured decomposition ratesmay be unrepresentative ofnatural rates. Alternatively, an experiment that manipulates thequantity of litter proximal to litterbags in each environmentincluded in the reciprocal transplant would test our explanation ofthe patterns observed in HFA studies and capture both of the aboveresearch questions.

It is increasingly apparent from the growing number of litterdecomposition studies that soil biology can play an important, and

sometimes counter-intuitive, role in modifying decompositionbeyond what can be expected based on litter quality and climate.For example, biotic controls may interact with and overwhelm theeffects of both litter quality and climate in some systems (McGuireet al., 2010; Wall et al., 2008). That an HFA of litter decompositionexists, generally, seems clear (Ayres et al., 2009a; Gholz et al.,2000). Whether or not adaptation to home litter by decomposercommunities drives this phenomenon remains unclear. We foundno evidence for an HFA of litter decomposition in our study andhencewere unable to test whether soil organisms are drivers of thisphenomenon where it does occur. However, we did find soilanimals to be more habitat specific than primary decomposers, aswell as ample evidence for inertial effects to obscure the trueperformance of decomposers on a litter type in isolation e both ofwhich could modify interpretation of previous decompositionstudies. Our data suggest that the understanding of decompositioncan be greatly improved through research on the interactionbetween litter quality and decomposer organisms, and a next steptowards improving our ability to model decomposition globallywould be to investigate the conditions that do and do not lead toHFAs of litter decomposition.

Acknowledgements

We thank Nicola Bolstridge, Karen Bonner, Morgan Coleman andChris Morse for assistance with data collection and Christine Bezarfor editing our manuscript. We thank Ed Ayres for kindly providingaccess to supporting data. We also thank our anonymous reviewersfor their insightful suggestions, which improved this paper. Fund-ing was provided by the New Zealand Foundation for Research,Science, and Technology (Ecosystem Resilience OBI) and theLandcare Research Capability Fund.

References

Adair, E.C., Parton, W.J., Del Grosso, S.J., Silver, W.L., Harmon, M.E., Hall, S.A.,Burke, I.C., Hart, S.C., 2008. Simple three-pool model accurately describespatterns of long-term litter decomposition in diverse climates. Global ChangeBiology 14, 2636e2660.

Anderson, J.M., 1975. Succession, diversity and trophic relationships of some soilanimals in decomposing leaf litter. Journal of Animal Ecology 44, 475e494.

Anderson, J.P.E., Domsch, K.H., 1978. Physiological method for quantitative measure-ment of microbial biomass in soils. Soil Biology & Biochemistry 10, 215e221.

Anderson, J., 1977. The organization of soil animal communities. Ecological Bulletins25, 15e23.

Anderson, M.J., 2001. A new method for non-parametric multivariate analysis ofvariance. Austral Ecology 26, 32e46.

Anderson, M.J., 2006. Distance-based tests for homogeneity of multivariatedispersions. Biometrics 62, 245e253.

Andrén, O., Paustian, K., 1987. Barley straw decomposition in the field ea comparison of models. Ecology 68, 1190e1200.

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., 2009a. Home-field advantageaccelerates leaf litter decomposition in forests. Soil Biology & Biochemistry 41,606e610.

Ayres, E., Dromph, K.M., Bardgett, R., 2006. Do plant species encourage soil biotathat specialise in the rapid decomposition of their litter? Soil Biology &Biochemistry 38, 183e186.

Ayres, E., Steltzer, H., Berg, S., Wall, D., 2009b. Soil biota accelerate decomposition inhigh-elevation forests by specializing in the breakdown of litter produced bythe plant species above them. Journal of Ecology 97, 901e912.

Bardgett, R.D., Hobbs, P.J., Frostegård, A., 1996. Changes in soil fungal:Bacterialbiomass ratios following reductions in the intensity of management of anupland grassland. Biology and Fertility of Soils 22, 261e264.

Barlow, J., Gardner, T.A., Ferreira, L.V., Peres, C.A., 2007. Litter fall and decompositionin primary, secondary and plantation forests in the Brazilian Amazon. ForestEcology and Management 247, 91e97.

Behan-Pelletier, V.M., St. John, M.G., Winchester, N., 2008. Canopy Oribatida: treespecific or microhabitat specific? European Journal of Soil Biology 44, 220.

Bligh, E.G., Dyer, W.J., 1959. A rapid method of total lipid extraction and purification.Canadian Journal of Biochemistry and Physiology 37, 911e917.

Bocock, K.L., Gilbert, O., Capstick, C.K., Twinn, D.C., Waid, J.S., Woodman, M.J., 1960.Changes in leaf litter when placed on the surface of soils with contrastinghumus types. Journal of Soil Science 11, 1e9.

M.G. St. John et al. / Soil Biology & Biochemistry 43 (2011) 1482e1489 1489

Castanho, C.d.T., de Oliveira, A.A., 2008. Relative effect of litter quality, forest typeand their interaction on leaf decomposition in south-east Brazilian forests.Journal of Tropical Ecology 24, 149e156.

Coleman, D.C., Crossley Jr., D.A., Hendrix, P.F., 2004. Fundamentals of Soil Ecology.Academic Press, New York.

Crossley, D.A., Blair, J.M., 1991. A high-efficiency, low-technology Tullgren-typeextractor for soil microarthropods. Agriculture Ecosystems & Environment 34,187e192.

Dickie, I.A., FitzJohn, R.G., 2007. Using terminal restriction fragment length poly-morphism (T-RFLP) to identify mycorrhizal fungi: a methods review. Mycor-rhiza 17, 259e270.

Feeney, D.S., Crawford, J.W., Daniell, T., Hallett, P.D., Nunan, N., Ritz, K., Rivers, M.,Young, I.M., 2006. Three-dimensional microorganization of the soil: root-microbe system. Microbial Ecology 52, 151e158.

Fenchel, T., Finlay, B.J., 2004. The ubiquity of small species: patterns of local andglobal diversity. Bioscience 54, 777e784.

Finlay, B.J., Fenchel, T., 2004. Cosmopolitan metapopulations of free-living microbialeukaryotes. Protist 155, 237e244.

Frostegård, Å, Tunlid, A., Bååth, E., 2011. Use and misuse of PLFA measurements insoils. Soil Biology & Biochemistry, 1e5. doi:10.1016/j.soilbio.2010.11.021.

Fyles, J.W., Fyles, I.H., 1993. Interaction of douglas-fir with red alder and salal foliagelitter during decomposition. Canadian Journal of Forest Research 23, 358e361.

Gholz, H.L., Wedin, D.A., Smitherman, S.M., Harmon, M.E., Parton, W.J., 2000. Long-term dynamics of pine and hardwood litter in contrasting environments:toward a global model of decomposition. Global Change Biology 6, 751e765.

González, G., Seastedt, T.R., Donato, Z., 2003. Earthworms, arthropods and plantlitter decomposition in aspen (Populus tremuloides) and lodgepole pine (Pinuscontorta) forests in Colorado, USA. Pedobiologia 47, 863e869.

Hansen, R.A., Coleman, D.C., 1998. Litter complexity and composition are determi-nants of the diversity and species composition of oribatid mites (Acari: Ori-batida) in litterbags. Applied Soil Ecology 9, 17e23.

Hansen, R.A., 2000. Effects of habitat complexity and composition on a diverse littermicroarthropod assemblage. Ecology 81, 1120e1132.

Hibbard, K.A., Archer, S., Schimel, D.S., Valentine, D.W., 2001. Biogeochemicalchanges accompanying woody plant encroachment in a subtropical savanna.Ecology 82, 1999e2011.

Hillebrand, H., 2004. On the generality of the latitudinal diversity gradient. Amer-ican Naturalist 163, 192e211.

Hobbie, S., Reich, P., Oleksyn, J., Ogdahl, M., Zytkowiak, R., Hale, C., Karolewski, P.,2006. Tree species effects on decomposition and forest floor dynamics ina common garden. Ecology 87, 2288e2297.

Hunt, H.W., Coleman, D.C., Ingham, E.R., Ingham, R.E., Elliott, E.T., Moore, J.C.,Rose, S.L., Reid, C.P.P., Morley, C.R., 1987. The detrital food web in a shortgrassprairie. Biology and Fertility of Soils 3, 57e68.

Hunt, H.W., Ingham, E.R., Coleman, D.C., Elliott, E.T., Reid, C.P.P., 1988. Nitrogenlimitation of production and decomposition in prairie, mountain meadow, andpine forest. Ecology 69, 1009e1016.

Kampichler, C., Bruckner, A., 2009. The role of microarthropods in terrestrialdecomposition: a meta-analysis of 40 years of litterbag studies. BiologicalReviews 84, 375e389.

Karasawa, S., Hijii, N., 2004. Effects of microhabitat diversity and geographicalisolation on oribatid mite (Acari: Oribatida) communities in mangrove forests.Pedobiologia 48, 245e255.

Klemmedson, J.O., 1992. Decomposition and nutrient release from mixtures ofGambel oak and ponderosa pine leaf litter. Forest Ecology and Management 47,349e361.

Magurran, A.E., 1988. Ecological Diversity and Its Measurement. University Press,Cambridge.

McClaugherty, C.A., Pastor, J., Aber, J.D., Melillo, J.M., 1985. Forest litter decompo-sition in relation to soilenitrogen dynamics and litter quality. Ecology 66,266e275.

McGuire, K., Zak, D., Edwards, I., Blackwood, C., Upchurch, R., 2010. Sloweddecomposition is biotically mediated in an ectomycorrhizal, tropical rain forest.Oecologia 164, 785e795.

McTiernan, K.B., Ineson, P., Coward, P.A., 1997. Respiration and nutrient release fromtree leaf litter mixtures. Oikos 78, 527e538.

Moore, J.C., Mccann, K., De Ruiter, P.C., 2005. Modeling trophic pathways, nutrientcycling, and dynamic stability in soils. Pedobiologia 49, 499e510.

Nielsen, U.N., Osler, G.H.R., Campbell, C.D., Burslem, D.F.R.P., van der Wal, R., 2010.The influence of vegetation type, soil properties and precipitation on thecomposition of soil mite and microbial communities at the landscape scale.Journal of Biogeography 37, 1317e1328.

Norris, M.D., Blair, J.M., Johnson, L.C., 2001. Land cover change in eastern Kansas:litter dynamics of closed-canopy eastern redcedar forests in tallgrass prairie.Canadian Journal of Botany 79, 214e222.

Parton, W., Silver, W.L., Burke, I.C., Grassens, L., Harmon, M.E., Currie, W.S., King, J.Y.,Adair, E.C., Brandt, L.A., Hart, S.C., Fasth, B., 2007. Global-scale similarities innitrogen release patterns during long-termdecomposition. Science 315, 361e364.

Prescott, C.E., Zabek, L.M., Staley, C.L., Kabzems, R., 2000. Decomposition ofbroadleaf and needle litter in forests of British Columbia: influences of littertype, forest type, and litter mixtures. Canadian Journal of Forest Research 30,1742e1750.

Prescott, C.E., 2010. Litter decomposition: what controls it and how can we alter itto sequester more carbon in forest soils? Biogeochemistry. doi:10.1007/s10533-010-9439-0.

R Development Core Team, 2010. R: A Language and Environment for StatisticalComputing. R Foundation for Statistical Computing, Vienna, Austria.

Richardson, D.M., Rejmánek, M., 2004. Conifers as invasive aliens: a global surveyand predictive framework. Diversity and Distributions 10, 321e331.

Rothstein, D.E., Vitousek, P.M., Simmons, B.L., 2004. An exotic tree alters decom-position and nutrient cycling in a Hawaiian montane forest. Ecosystems 7,805e814.

Rowland, A.P., Roberts, J.D., 1994. Lignin and cellulose fractionation in decomposi-tion studies using acidedetergent fibre methods. Communications in SoilScience and Plant Analysis 25, 269e277.

Rustad, L.E., Cronan, C.S., 1988. Element loss and retention during litter decay ina red spruce stand in Maine. Canadian Journal of Forest Research 18, 947e953.

Ruzicka, S., Norman, M.D.P., Harris, J.A., 1995. Rapid ultrasonication method todetermine ergosterol concentration in soil. Soil Biology & Biochemistry 27,1215e1217.

Schimel, J.P., Bennett, J., 2004. Nitrogen mineralization: challenges of a changingparadigm. Ecology 85, 591e602.

St. John, M.G., Bagatto, G., Behan-Pelletier, V., Lindquist, E.E., Shorthouse, J.D.,Smith, I.M., 2002. Mite (Acari) colonization of vegetated mine tailings nearSudbury, Ontario, Canada. Plant and Soil 245, 295e305.

St. John, M.G., Crossley, D.A.Jr., Coleman, D.C. Microarthropods. In: Huang, P.M., Li,Y.C., Sumner, M.E. (Eds.), Handbook of Soil Sciences, vol. 1, second ed. Taylor andFrancis, Boca Raton, FL, in press.

Strickland, M.S., Osburn, E., Lauber, C., Fierer, N., Bradford, M.A., 2009a. Litter qualityis in the eye of the beholder: initial decomposition rates as a function ofinoculum characteristics. Functional Ecology 23, 627e636.

Strickland, M.S., Lauber, C., Fierer, N., Bradford, M.A., 2009b. Testing the functionalsignificance of microbial community composition. Ecology 90, 441e451.

Swift, M.J., Heal, O.W., Anderson, J.M., 1979. Decomposition in Terrestrial Ecosys-tems. Blackwell Scientific Publications, London.

Taylor, B.R., Parsons, W.F.J., Parkinson, D., 1989. Decomposition of Populus trem-uloides leaf litter accelerated by addition of Alnus crispa litter. Canadian Journalof Forest Research 19, 674e679.

Thomas, W.A., 1968. Decomposition of loblolly pine needles with and withoutaddition of dogwood leaves. Ecology 49, 568e571.

Trofymow, J., Moore, T.R., Titus, B., Prescott, C., Morrison, I., Siltanen, M., Smith, S.,Fyles, J., Wein, R., Camiré, C., Duschene, L., Kozak, L., Kranabetter, M., Visser, S.,2002. Rates of litter decomposition over 6 years in Canadian forests: influenceof litter quality and climate. Canadian Journal of Forest Research 32, 789e804.

Vivanco, L., Austin, A.T., 2008. Tree species identity alters forest litter decompositionthrough long-term plant and soil interactions in Patagonia, Argentina. Journalof Ecology 96, 727e736.

Wall, D.H., Bradford, M.A., St. John, M.G., Trofymow, J.A., Behan-Pelletier, V.,Bignell, D.D.E., Dangerfield, J.M., Parton, W.J., Rusek, J., Voigt, W., Wolters, V.,Gardel, H.Z., Ayuke, F.O., Bashford, R., Beljakova, O.I., Bohlen, P.J., Brauman, A.,Flemming, S., Henschel, J.R., Johnson, D.L., Jones, T.H., Kovarova, M.,Kranabetter, J.M., Kutny, L., Lin, K.C., Maryati, M., Masse, D., Pokarzhevskii, A.,Rahman, H., Sabara, M.G., Salamon, J.A., Swift, M.J., Varela, A., Vasconcelos, H.L.,White, D., Zou, X.M., 2008. Global decomposition experiment shows soil animalimpacts on decomposition are climate-dependent. Global Change Biology 14,2661e2677.

Wallwork, J.A., 1976. The Distribution and Diversity of Soil Fauna. Academic Press,New York.

Wardle, D.A., 1993. Changes in the microbial biomass and metabolic quotient duringleaf-litter succession in some New Zealand forest and scrubland ecosystems.Functional Ecology 7, 346e355.

Wardle, D.A., 2002. Communities and Ecosystems: Linking the Aboveground andBelowground Components. Princeton University Press, Princeton.

Wardle, D.A., 2006. The influence of biotic interactions on soil biodiversity. EcologyLetters 9, 870e886.

Wilkinson, D.M., 1998. Fragments of an entangled bank: do ecologists study most ofecology? Oikos 82, 393e394.

Zhang, D., Hui, D., Luo, Y., Zhou, G., 2008. Rates of litter decomposition in terrestrialecosystems: global patterns and controlling factors. Journal of Plant Ecology 1,85e93.