Linkages between plant litter decomposition, litter quality, and vegetation responses to herbivores

Functional Ecology

2002

16

, 585–595

© 2002 British Ecological Society

585

Blackwell Science, Ltd

Linkages between plant litter decomposition, litter quality, and vegetation responses to herbivores

D. A. WARDLE,*†§ K. I. BONNER† and G. M. BARKER‡

*

Department of Animal and Plant Sciences, University of Sheffield, Sheffield S10 2TN, UK,

†

Landcare Research, PO Box 69, Lincoln, New Zealand, and

‡

Landcare Research, Private Bag 3127, Hamilton, New Zealand

Summary

1.

There is increasing awareness that similar suites of plant traits may govern foliagepalatability and litter decomposability, but whether there is an association between theresponse of vegetation to herbivory and litter decomposition rates across plant speciesremains unexplored.

2.

We collected 141 samples of litter from 59 understorey and 18 canopy tree speciesfrom a total of 28 sites under natural forest throughout New Zealand. We assessedwhether variables related to decomposition and quality of litter of the understorey spe-cies showed a statistical relationship with the response of vegetation density (assessedusing a pole-intercept method) of the same species at the same locations to browsingby deer and goats. Decomposition and nutrient-loss data from litter were obtainedusing standardized laboratory bioassays.

3.

There was a significant positive correlation between litter decomposition rate andthe extent to which vegetation density was reduced by browsing mammals (

r =

0·488,

P

< 0·001). Further, decomposition rate and vegetation response to herbivory wereboth correlated with several of the same litter quality variables.

4.

The proportion of total initial phosphorus and nitrogen released from litter duringdecomposition was correlated with litter decomposition rate, but not with vegetationdensity response to browsing. This suggests that effects of browsers on vegetation com-position are more likely to influence ecosystem carbon flow than nitrogen or phosphorusflow.

5.

Litter-mixing experiments showed that good quality litters produced by plant spe-cies reduced by browsers tended to promote the decomposition of other litters. Mean-while, poor quality litters from species promoted by browsers tended to decomposemore rapidly when mixed with other litter types than when by themselves. However,these effects were weak and likely to be less important than the more direct effects ofbrowsing mammals on vegetation composition.

6.

The relationships between litter decomposition and effect of herbivory on vegeta-tion density were driven primarily by differences among the main plant functionalgroups, which showed the same decreasing rank order for both variables: large-leaveddicots, small-leaved dicots,

Nothofagus

, ferns, and monocots.

7.

The implications of these results for understanding how herbivores affect thedecomposer subsystem are considered. Because the results of this work are only par-tially consistent with those of an earlier study on how browsers affect decomposerorganisms and processes, conducted at the same 28 field sites, other mechanismsthrough which browser effects are manifested below-ground must often override thatinvestigated in this study.

Key-words

: Decomposition, deer, goats, herbivory, mineralization, litter quality, plant traits

Functional Ecology

(2002)

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, 585–595

§Author to whom correspondence should be addressed. E-mail: [email protected]

FEC_659.fm Page 585 Monday, September 9, 2002 10:05 AM

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© 2002 British Ecological Society,

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16

, 585–595

Introduction

Most of the carbon that plants fix and allocate to theirabove-ground tissues is eventually consumed by her-bivores or decomposer organisms. The nature of directlinkages between plants and above-ground herbivores,and those between plants and decomposers, has beenstudied extensively. There is an increasing recognitionthat important plant-mediated interactions also occurindirectly between above-ground herbivores and decom-posers. Decomposer activity influences plant nutrientacquisition, and this in turn affects the populationgrowth of invertebrate herbivores (Scheu, Theenhaus& Jones 1999). Further, foliar herbivory can exert avariety of effects on decomposer organisms and pro-cesses by influencing the quantity and quality of resourcesthat become available to decomposers (reviewed byBardgett, Wardle & Yeates 1998b; Wardle 2002).

Plant species that are preferentially browsed by her-bivores differ from those that are not with regard tokey ecophysiological traits (Coley, Bryant & Chapin1985; Grime 2001). These traits relate to the quality ofthe foliage and litter produced by the plant (Coley

et al

. 1985; Grime & Anderson 1986). If this is true,then foliage palatability should be positively correlatedwith litter decomposability across species. Evidencefor this comes from invertebrate herbivore feedingtests and litter decomposition bioassays (Cornelissen

et al

. 1999; Grime

et al

. 1996; Wardle

et al

. 1998).Herbivores influence plant community structure,

and may promote domination by either unpalatableor palatable species, depending upon whether theformer are suppressed (Bryant 1987; Pastor

et al

.1988) or promoted (Brown, Jepsen & Gibson 1988;McNaughton 1979) by herbivory. If foliage palatabil-ity, litter quality and decomposability are correlatedacross species, herbivore-induced changes in the rel-ative balance of palatable and unpalatable plant speciesshould be matched by changes in the net quality oflitter produced, and therefore in decomposer activity.Pastor

et al

. (1988, 1993) found browsing by moose(

Alces alces

L.) in boreal forest to induce replacementof deciduous palatable species by unpalatable spruce(

Picea

) species, and proposed that the correspondingdecline in several indicators of soil quality was due tothe poorer litter quality of spruce. However, no studyhas determined if this pattern is a general trend, orwhether there are predictable or consistent relation-ships across plant species between decomposability ofleaf litter and the response of density of above-groundvegetation to herbivory.

In the present study, we sought explicitly to test forrelationships between measures of leaf litter quality,decomposability of leaf litter, and plant speciesresponses to herbivory in field conditions. This wasachieved by collecting litter from a range of plant spe-cies in several locations throughout New Zealand, andcomparing measures of litter decomposability andquality with the response of vegetation density of the

same plant species at the same location to long-termexclusion of browsing mammals. The ultimate goalwas to determine whether there are predictable effectsof foliar herbivory on the quality of litter produced,and to assess what the ecosystem-level implications ofthese might be.

Materials and methods

Wardle

et al

. (2001) reported the results of a study inwhich 30 fenced exclosure plots, mostly approximately20

×

20 m and established by the former New ZealandForest Service between 1961 and 1984, were sampled.These exclosures are located across most of New Zea-land’s major natural forest types, and were designed toexclude introduced browsing mammals [notably reddeer (

Cervus elaphus scoticus

Lönnberg) and feralgoats (

Capra hircus

L.)]. Measurements of variousabove- and below-ground variables, including vegeta-tion density of each plant species, were made insideand outside each exclosure. Each exclosure locationwas sampled once, between 26 September 1997 and 26May 1999. The present study focuses on 28 of theselocations (Appendix 1).

For each location, we selected up to six plant species(Appendix 1) which were abundant in the understoreybrowse layer (0–2 m vegetation height) according todata presented by Wardle

et al

. (2001). For each spe-cies fresh leaf litter was collected, usually off the forestfloor, or in some cases when still attached to the plantstem. Litter was also collected from up to three domi-nant canopy tree species at each location (Appendix1). Litter for the understorey (browse layer) specieswas used to answer questions about relationshipsbetween herbivore effects and decomposition vari-ables; that from the canopy species was collected forcomparative purposes. This litter was air-dried andstored until further use.

For each location, the response of vegetation den-sity of each of the selected browse layer species toherbivory by browsing mammals was determined usingthe densities of that species both inside and outside theexclosure plot (Wardle

et al

. 2001). These were was usedto derive an index,

V

(Wardle 1995), which ranges from

−

1 to +1 and becomes increasingly negative and positiveas the mammals have an increasingly positive or negativeeffect, respectively, on the browse layer vegetation densityof that species (a value of 0 indicates no effect).

Subsamples of each litter sample were analysed forthe concentration of several chemical components.Concentrations of phenolics and condensed tanninswere determined colorimetrically following extractionwith 50% acetone for 16 h; the procedure for phenolic


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Herbivory and litter decomposition


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measurements follows Price & Butler (1977); and thatfor condensed tannin measurements follows Broad-hurst & Jones (1978; see also Mole & Waterman 1994).Phenolic concentrations were determined as tannicacid equivalents and condensed tannins as catechinequivalents. Lignin, cellulose and fibre fractions weredetermined using the acid-detergent fibre–sulphuricacid procedure (Rowland & Roberts 1994). Briefly,acid-detergent fibre (hereafter called ‘fibre’) was deter-mined as the fraction remaining after treatment of thelitter with boiling acid detergent to hydrolyse protein.This fibre residue was then treated with 72% sulphuricacid to destroy the cellulose; cellulose is defined as thedifference between the initial and remaining fractions.Finally, the residue was ignited at 550

°

C to destroy allremaining organic matter, leaving only the inorganic(ash) fraction; acid-detergent lignin (hereafter called‘lignin’) is defined as the difference in this residuebetween pre- and post-ignition. Total nitrogen (N) andphosphorus (P) were determined using automated colori-metric methods (Technicon Instruments 1977) afterdigestion. Values of ratios of lignin to N, lignin to P,and N to P were derived from the above measurements.

The decomposability of each litter collected was assessedusing a standardized laboratory bioassay (Wardle

et al

. 1998). For each litter type, three 9 cm diameterPetri dishes were each two-thirds filled with a stand-ardized humus substrate (1·8% N, pH 3·9; collectedfrom a

Metrosideros umbellata

Cav.–

Weinmannia race-mosa

L. f. forest near Otira, New Zealand; 42

°

50

′

S,171

°

37

′

E) and amended to 250% moisture (dry weightbasis); a disc of nylon mesh with 1 mm holes wasplaced on the humus surface. Litter (1 g, oven-dried),cut into 5 mm fragments, was placed on the surface ofthe mesh of each Petri dish; the dish was then sealedwith tape to minimize water loss and incubated for92 days at

≈

22

°

C. In addition, to assess interactivelitter effects among species from each location whenmixed together, Petri dishes were set up in triplicate foreach of the possible two-way mixtures of litter for allthe species sampled from that location. These were setup as for the monospecific Petri dishes, but with eachdish containing 0·5 g of each of the two litter types.

Upon harvest, all remaining (undecomposed) litterwas removed from each Petri dish and rinsed. For thePetri dishes containing two species mixtures of litter,the remaining litter was visually sorted into the com-ponent species. All litter was then oven-dried (80

°

C,24 h), and its dry mass determined. For all the littersthat were decomposed in monoculture, N and P con-centrations of the remaining litter were determined asdescribed above.

Litter decomposition rate was determined as thepercentage mass lost during incubation. Loss of Nand P from the litter was calculated as the totalmass

×

nutrient concentration prior to incubation

minus that after incubation. The proportion of totalinitial N and P lost from the litter during decomposi-tion was calculated from these values. The percentagemass loss of each litter type in each two-way mixturewas compared with its percentage mass loss in mono-culture. These values were used to determine two datavalues for each litter type. First, the net effect of eachlitter type on the decomposition rate of all the other lit-ter types from that location was calculated as the meanenhancement of all other litter types by that species inmixture relative to their decomposition in monocul-ture. Second, the net response of decomposition rate ofeach litter type to all the other litter types from thesame location was calculated as the mean enhance-ment of decomposition rate of that species in all mix-tures in which it occurred relative to its decompositionrate in monoculture.

For data analysis, each separate litter collection wasconsidered as a separate data point. This yielded 98points representing 51 different species in the under-storey (browse) layer and 43 points representing 18species in the tree canopy layer. Confounding prob-lems due to non-independence among samples areunlikely because, for the response variables measured,variability among species within locations was fre-quently as great as among locations (indicative of con-siderable phenotypic plasticity among species), andvariation across locations within species was often asgreat as among species. All variables were tested fornormality and transformed if necessary. Correlationanalysis was used to evaluate relationships for thebrowse layer species between decomposition variables,litter quality variables, and vegetation density re-sponse to browsing. Backward stepwise multipleregression was employed to determine, for the browselayer species, which combinations of litter qualityvariables served as best predictors of decompositionvariables and the response of vegetation density toherbivory. One-way

was used to test whetherthere were differences in litter quality and decomposi-tion variables among plant species with the greatestdensity outside and inside the exclosures.

The data were also used to compare different plantfunctional groups. All plant species were assigned toone of six groups (Appendix 1): ferns; gymnosperms;monocots; large-leaved dicots, leaf lamina width>6 mm (excluding

Nothofagus

); small-leaved dicots,leaf lamina width <6 mm; and members of

Notho-fagus

. Large-leaved dicots were distinguished fromsmall-leaved dicots because many of the small-leavedspecies have different growth forms (such as divarica-tion) to the large-leaved species, and have been pro-posed as having a stronger resistance to browsing(Greenwood & Atkinson 1977; McQueen 2000; butsee Howell, Kelly & Turnbull 2002).

Nothofagus

wasdistinguished from other large-leaved dicots because


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D. A. Wardle, K. I. Bonner & G. M. Barker


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Nothofagus

represents the only large-leaved ectomyc-orrhizal genus, and

Nothofagus

species form highlycompetitive, low-diversity (often monospecific) standsrelative to those dominated by other dicotyledonousspecies (Leathwick, Burns & Clarkson 1998). The

gymnosperm group was excluded from analysis on thebasis of too few data. One-way

was used toassess whether decomposition variables, litter qualityvariables and vegetation density response to browsingdiffered significantly among the five remaining groups.In addition, correlation and stepwise correlation ana-lyses were employed as described above, but to explorerelationships between decomposition variables, vege-tation response to browsing and litter quality variableswithin each of the five groups.

Results

When all understorey species

×

site combinations wereconsidered, there was a highly statistically significantrelationship between the rate of decomposition andthe response of vegetation density to browsing for thesame plant species (Fig. 1a). These two variables werecorrelated with several of the same resource qualityproperties – concentrations of condensed tannins, fibreand lignin, and ratios of lignin to N and of lignin toP (Table 1). The variables in the multiple regressionrelationship that explained the most variation for theresponse of vegetation density to herbivory, concen-tration of phenolics and of fibre, were also two of thefour variables that occurred in the regression relation-ship which best predicted litter decomposition rate(Table 2).

When the data were analysed so that each speciesrepresented a different data point (with the data fromeach species averaged across all locations in which itappeared), the nature of patterns identified remainedunchanged – there was still a significant relationshipbetween herbivore effect on vegetation and litterdecomposition rate (

r =

0·416,

P

= 0·002,

n

= 51).With this analysis, decomposition rate and herbivoreeffect both remained significantly correlated at

P

=0·05 with concentrations of condensed tannins andfibre, and with the lignin to N ratio; decompositionrate was also significantly related to lignin concentra-tion and with the lignin to P ratio. When the data wereanalysed so that each site was represented by a differ-ent data point (data were averaged for all specieswithin each location), the relationship between her-bivore effect and decomposition was still significant(

r =

0·173,

P

= 0·027,

n

= 28), meaning that sites thatshowed stronger overall negative effects of herbivoresalso, on average, produced litter that decomposedmore rapidly.

Despite vegetation response to browsing being cor-related with litter decomposition rate, there was norelationship between vegetation browsing responseand the proportion of either total N or total P lostfrom litter during decomposition [

r =

0·077 (

P =

0·219) and 0·114 (

P =

0·130), respectively]. Unlikedecomposition rate and vegetation response to her-bivory, litter N and P loss rates were not strongly cor-related with concentrations of condensed tannins, ligninor fibre; instead, the best predictors were the initial

Fig. 1. Relationships between relative litter decomposition rates for a range of plantspecies, and the relative responses of these species to herbivory by browsing mammals.Plant responses to herbivores are measured using the metric V (Wardle 1995; Wardleet al. 2001) which ranges from −1 to +1 and becomes increasingly negative and positiveas vegetation density in the browse layer is promoted and reduced, respectively, byherbivores (a value of 0 indicates no effect). The data set is based on 98 points (eachbased on decomposition rates of a given monospecific litter collection, and vegetationdensity inside vs outside a fenced exclosure plot for the same plant species and locationas that from which the litter was collected), representing 51 plant species and collectedfrom 28 locations. (a) Individual data points. × = Ferns; � = monocots; � = dicotswith leaf lamina width >6 mm; � = dicots with leaf lamina width <6 mm;� = Nothofagus spp. R = 0·488, P < 0·001, df = 96. (b) Means and 95% confidenceintervals for the estimate of plant group means for data in (a). The five groups differsignificantly at P < 0·001 with regard to both decomposition rate and vegetationresponse to herbivory (one-way ).


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concentrations of the N and P being lost and the ratiosof these nutrients to lignin and each other (Tables 1and 2).

With regard to the litter-mixing measurements, theeffect of a given litter on decomposition rates of all theother litters collected from the same site was weaklypositively related to the decomposition rate of its ownlitter (

r =

0·284,

P

= 0·003), as well as the responseof vegetation density of that species to browsing(

r =

0·137,

P

= 0·099). This effect was weakly signific-antly correlated with litter fibre and lignin concentra-tions (Table 1), and was best predicted by a four-variablemultiple regression that included these variables(Table 2). The net response of decomposition rate of agiven litter to being mixed with other litters from thesame site was negatively correlated with both the rateof decomposition of that litter (

r =

−

0·456,

P

< 0·001)and response of vegetation density of that species tobrowsing (

r =

−

0·195,

P

= 0·034). This variable wassignificantly correlated with most of the same litterquality attributes that were correlated with litter

decomposition rate: concentrations of fibre, celluloseand lignin, and ratios of lignin to N and N to P.

When the data were analysed by placing all littertypes in three categories (litter from understorey spe-cies with a greater vegetation density inside the exclos-ure and outside the exclosure, and litter from canopytree species), there were large differences with regard toseveral litter quality variables (Table 3). Those specieswith greater density outside the exclosure produced lit-ter with greater concentrations of phenolics, con-densed tannins, fibre and lignin, and greater ratios oflignin to N and lignin to P, than those with a greaterdensity inside the exclosure. However, litter from can-opy tree species had higher values for most of thesevariables than litter from plants in either of the twounderstorey categories. Understorey species that werereduced by browsing produced litter that decomposedmore rapidly than that produced by plants in the othertwo categories. However, there were no significant dif-ferences among categories for the proportion of total Nor P lost from the litter, or for variables based on litter-mixing effects (Table 3). When differences occurred fora given variable between plant species favoured insideand outside exclosures, these differences generallybecame larger when data analysis was restricted toonly those plant species for which the exclosure effectwas significant at

P

= 0·05 (data not presented).When plant species were assigned to functional

categories, there were highly significant differencesamong groups with regard to both decomposition rate(

F

4,93

= 15·6,

P

< 0·001) and vegetation density re-sponse to browsing (

F

4,93

= 5·42,

P

< 0·001) (Fig. 1b).There was a distinct relationship at the functionalgroup level between litter decomposition rate andresponse of vegetation density to browsing, with large-leaved dicots having the highest values for both variables,and ferns and monocots having the lowest (Fig. 1b).These results were reasonably consistent with differ-ences among functional groups with regard to litterquality; functional groups differed overall at

P

= 0·05

Table 1. Pearson’s correlation coefficients between concentrations of chemical components of litter, and variables relating to litter decomposition andresponse of vegetation density to mammal browsing, for a range of plant species growing in the vegetation browse layer (0–2 m height)

Phenolics‡Condensed tannins‡ Fibre Cellulose Lignin

Nitrogen (N)

Phosphorus (P)‡

Lignin to N ratio‡

Lignin to P ratio‡

N to P ratio

Decomposition rate 0·000 −0·274* −0·760*** −0·525*** −0·464*** 0·201* 0·334** −0·379*** −0·573*** −0·434***Relative N release§ −0·145 −0·157† −0·069 0·114 −0·197† 0·600*** 0·000 −0·590*** 0·126 0·395***Relative P release§ 0·158 0·092 −0·173 −0·148 −0·154 0·036 0·639*** −0·141 −0·550** −0·419***Litter mixing effect¶ −0·000 0·055 0·243* 0·051 0·250* 0·173† 0·038 0·000 0·061 −0·135Litter mixing response¶ 0·172† −0·133 −0·633*** −0·413*** −0·342*** 0·080 0·136 −0·380*** −0·251* −0·380***Response to browsing†† −0·130 −0·319** −0·474*** −0·196† −0·314** 0·115 0·191 −0·217* −0·308** −0·152

Data from 98 litter collections, each representing a unique species × location combination, from a total of 51 species and 28 locations.†, *, **, *** = correlation coefficient significantly different to 0 at P = 0·100, 0·050, 0·010 and 0·001, respectively. All values that are listed as significant at P = 0·001 remain significant at P = 0·05 when a Bonferroni correction is applied.‡Log-transformed variable.§Proportion of total initial N or P lost from litter during decomposition.¶Mean effect of litter of species on decomposition rates of litter from all other species at that site, and mean response of decomposition rate of that species to all other species from that site, in litter-mixing bioassays.††Value of index V which is related to the relative density of vegetation of a given plant species inside vs outside fenced browsing mammal exclosure plot.

Table 2.

Stepwise multiple regression relationships relating variables for decomposi-tion and response of vegetation density to mammal browsing to concentrations of chemicalcomponents of litter

Dependent variable Independent variables in relationship*

R

2

Decomposition rate ln(PH) (–); FIB (–); LIG (–); NP (–) 0·693Relative nitrogen release N (+); ln(LIGN) (–); NP (+) 0·540Relative phosphorus release ln(PHOS) (+) 0·418Litter-mixing effect FIB (+); LIG (+); ln(P) (–); ln(LIGP) (–) 0·259Litter-mixing response FIB (–); NP (–) 0·421Response to browsing ln(PH) (–); FIB (–) 0·297

The data set used, and dependent and independent variables, are the same as for Table 1. Only those terms that explain a statistically significant proportion of the variation of the response variable at

P =

0·05 are included.

P

< 0.001 for each regression.(+) and (–) after each variable indicate a positive or negative relationship between the independent and dependent variable.*Abbreviations: PH = phenolics; FIB = fibre; LIG = lignin; N = nitrogen; P = phosphorus; LIGN = lignin to N ratio; LIGP = lignin to P ratio; NP = N to P ratio.


590D. A. Wardle, K. I. Bonner & G. M. Barker

© 2002 British Ecological Society, Functional Ecology, 16, 585–595

for all litter quality variables except P concentration.Small-leaved dicots and Nothofagus had the highestconcentrations of condensed tannins and phenols;ferns and monocots had the highest concentrations ofcellulose and fibre; and ferns and Nothofagus had thehighest concentrations of lignin (Table 4). Litter nutri-ent concentrations were generally highest for the fernsand the large-leaved and small-leaved dicots (Table 4).Functional groups did not differ significantly overallwith regard to the proportional loss during decompo-sition of either N (F4,93 = 1·41, P = 0·237) or P(F4,93 = 0·88, P = 0·447). However, in the litter-mixing

experiment, the net effect of a given litter on all otherlitters collected from the same site differed amongfunctional groups (F4,93 = 3·00, P = 0·022), with large-leaved dicots having the greatest effect and ferns andNothofagus having the least. The net response of agiven litter to all other litter types from the same sitewas strongly influenced by functional group effects(F4,93 = 7·61, P < 0·001); this response was greatest forthe ferns and monocots.

Within functional groups, only ferns and Nothofa-gus demonstrated statistically significant relationshipsbetween decomposition rate and vegetation density

Table 3. Litter quality and decomposition variables for litter of forest understorey plant species reduced by browsing mammals(vegetation density higher inside exclosure); understorey species promoted by browsing mammals (vegetation density greateroutside exclosure); and canopy tree species

Litter variableReducedspecies (R)*

Enhanced species (E)

Canopy species P (all data)‡ P (R vs E)‡

Phenolics (%) 1·41 2·61 4·15 <0·001 <0·001Condensed tannins (%) 0·212 0·862 1·557 <0·001 <0·001Fibre (%) 42·9 52·8 52·8 <0·001 0·001Cellulose (%) 21·0 23·1 20·9 0·229 0·180Lignin (%) 20·0 25·3 30·5 <0·001 0·016Nitrogen (N) (%) 1·31 1·26 1·16 0·392 0·616Phosphorus (P) (%) 0·177 0·119 0·108 0·205 0·174Lignin to N ratio 20·6 25·1 36·5 <0·001 0·147Lignin to P ratio 254·7 377·1 653·6 <0·001 0·028N to P ratio 14·1 15·5 17·5 0·025 0·447Decomposition rate (% day−1) 31·8 19·5 19·6 0·003 < 0·001Release of N from litter (% day−1) 50·2 48·6 42·0 0·243 0·751Release of P from litter (% day−1) 32·9 28·8 23·6 0·221 0·463Litter-mixing effect (%)† 8·57 3·73 5·26 0·427 0·217Litter-mixing response (%)† 4·60 9·76 3·95 0·463 0·308Number of observations (n) 59 39 43

Data analysed using one-way . Litter variables, and the data for the understorey species, are as for Table 1.*Reduced = understorey species × location combinations for which vegetation density of species was greater inside than outside fenced exclosure plot; enhanced = combinations for which density was greater outside than inside exclosure.†Mixing effect = mean percentage enhancement by a given litter on the decomposition rates of litter from all other species collected from the same site when in mixture relative to monoculture; mixing response = mean percentage enhancement of decomposition rate of a given litter by all the other litters collected from the same site when in mixture relative to monoculture.‡All P values <0·004 remain significant at P = 0·05 when a Bonferroni correction is applied.

Table 4. Litter quality variables (mean ± SD) of all subcanopy litter collections for each of five plant groupings

Plant grouping

P*Litter variable Ferns Monocots Dicots (large leaf)† Dicots (small leaf) Nothofagus

Phenolics (%) 1·65 ± 2·41 0·77 ± 1·45 1·56 ± 1·26 3·78 ± 2·91 2·23 ± 0·73 <0·001Condensed tannins (%) 0·323 ± 0·325 0·181 ± 0·183 0·315 ± 0·531 1·31 ± 1·887 0·522 ± 0·330 0·025Fibre (%) 60·3 ± 14·8 57·3 ± 5·2 37·9 ± 9·6 40·2 ± 14·2 52·6 ± 8·9 <0·001Cellulose (%) 25·4 ± 4·2 32·6 ± 7·3 18·3 ± 5·8 19·2 ± 7·0 19·9 ± 2·2 <0·001Lignin (%) 29·2 ± 9·2 13·9 ± 5·3 19·3 ± 9·1 20·8 ± 11·7 30·8 ± 9·3 <0·001Nitrogen (N) (%) 1·36 ± 0·42 0·90 ± 0·39 1·26 ± 0·50 1·57 ± 0·48 1·20 ± 0·52 0·010Phosphorus (P) (%) 0·134 ± 0·123 0·048 ± 0·029 0·194 ± 0·244 0·190 ± 0·290 0·084 ± 0·181 0·115Lignin to N ratio 27·0 ± 22·1 21·4 ± 18·9 21·8 ± 21·3 15·2 ± 10·4 28·4 ± 8·2 0·040Lignin to P ratio 363 ± 261 509 ± 489 227 ± 342 239 ± 204 362 ± 60 0·007N to P ratio 16·1 ± 8·8 22·1 ± 7·7 12·1 ± 8·5 14·7 ± 9·6 13·7 ± 4·1 0·013Number of observations (N ) 20 11 40 16 10

*Derived using one-way among the five plant types.†Large leaf = leaf lamina width >6 mm; small leaf = leaf lamina width <6 mm.


591Herbivory and litter decomposition


response to browsing (Table 5). Litter decompositionrates for all functional groups except monocots, andvegetation density responses to browsing for all groupsexcept ferns and Nothofagus, could be related to atleast some litter quality variables in multiple regressionrelationships (Table 5). Despite this, within functionalgroups, the variables that best explained decomposi-tion rates in these relationships were never the same asthose that best explained vegetation density responsesto browsing (Table 5).

Discussion

The present study extends the findings of previousstudies (Cornelissen et al. 1999; Grime et al. 1996;Wardle et al. 1998) by demonstrating an across-speciesrelationship between plant litter decomposability andthe response of vegetation density to herbivory. Thisprovides support for the hypothesis of Pastor et al.(1988, 1993) that plant species which produce goodquality litter are disadvantaged by browsing, and thatherbivory by browsing mammals therefore switchesthe competitive balance towards plant species withpoor litter quality. Such an outcome is possible only ifpalatable plant species are not promoted by browsing(cf. McNaughton 1979, 1985), and in our study therewas a clear pattern of such plants being only negativelyaffected by herbivores. With regard to New Zealandforest understorey species, at least, it appears probablethat decomposability of litter and vegetation responsesto herbivory are governed by the same or similar suitesof traits, and this is reinforced by Tables 1 and 2 whichdemonstrate that both response variables were relatedto concentrations of secondary metabolites and struc-tural carbohydrates in plant-derived tissues.

While litter mass loss (indicative of C mineraliza-tion) showed a distinct relationship with vegetation

density response to herbivory, loss rates of N and Pfrom the litter did not. It is apparent from Table 1 that,whereas litter decomposition rate was related to bothconcentrations of C constituents (secondary meta-bolites and structural carbohydrates) and concentrationsof major nutrients (N and P), release rates of N andP were related only to concentrations of nutrients,while the response of vegetation density to browsingwas related only to concentrations of C constituents.This suggests that, across species, vegetation densityresponse to herbivory is driven by some of the samefactors that influence litter C mineralization, but not Nor P mineralization. This is consistent with the sugges-tion that browsing mammals preferentially browsevegetation on the basis of C chemistry and not nutrientstatus (Bryant, Chapin & Coley 1983), and indicatesthat browsers therefore selectively remove plant spe-cies that promote C mineralization, but not necessarilythat of major nutrients. This means that browser-induced vegetation changes are likely to have astronger influence on the ecosystem dynamics of Cthan on the dynamics of N or P.

Interactive effects among litters from different plantspecies may be ecologically important (Blair, Parmelee& Beare 1990; McTiernan, Ineson & Coward 1997;Wardle, Bonner & Nicholson 1997). Seastedt (1984)proposed that litter of better quality should acceleratethe decomposition of associated poor quality litterand, conversely, poor quality litter should retarddecomposition of good quality litter. If so, litter fromspecies reduced by browsing in our study should pro-mote the decomposition of associated litters when inmixture, while litter from species encouraged by brows-ing should retard decomposition of associated litters.Our results provide some evidence for this, but theeffects are weak. Litter from species with faster decom-position rates did promote greater decomposition

Table 5. Stepwise multiple regression relationships relating litter decomposition rates and response of vegetation density tomammal browsing to concentrations of chemical components of litter, for each of the five plant groupings shown in Table 4

Plant grouping

Independent variables serving as predictors ofR2 (decomposition vs browsing)‡Decomposition rate R2 Response to browsing R2

Ferns ln(LIGN) (–); ln(LIGP) (–); ln(CT) (–)

0·725*** None NS 0·281*

Monocots None NS ln(P) (+) 0·556* 0·188 (NS)Dicots (large-leaved)† ln(PH) (–); FIB (–) 0·451*** LIG (–) 0·254** 0·089 (NS)Dicots (small-leaved) ln(CT) (–); FIB (–); ln(LIGN) (–) 0·824*** N (+) 0·328* 0·071 (NS)Nothofagus NP (–) 0·515* None NS 0·570**

The data set and independent variables used are the same as for Table 1. Only those terms that explain a statistically significant proportion of the variation of the response variable at P = 0·05 are included.NS, *, **, ***, indicate that R2 is not significantly different to 0, and significantly different to 0 at P = 0·05, 0·01 and 0·001, respectively.Abbreviations: CT = condensed tannins; PH = phenolics; LIG = lignin; FIB = fibre; N = nitrogen; P = phosphorus; LIGN = lignin to N ratio; LIGP = lignin to P ratio; NP = N to P ratio.†Large-leaved = leaf lamina width >6·0 mm; small-leaved = leaf lamina width <6·0 mm.‡Relationship between plant litter decomposition rate, and response of vegetation of the same species at the same location, to mammal browsing.




of associated litters and, although there was apositive relationship across species between vegetationresponse to browsing and net effect of litter on asso-ciated litters, it was significant only at P = 0·10. Thoseplants that produced litter of the lowest quality werealso those whose decomposition rates were moststrongly promoted by associated species, although therelationship between vegetation response to herbivoryand response of litter decomposition to mixing withother litters was only marginally significant at P =0·05. These results suggest that browsing mammalsmay reduce vegetation density of plant species that notonly decompose more rapidly but also accelerate thedecomposition of associated, more recalcitrant, littertypes. However, the indirect effect of browsing mam-mals on interspecific litter interactions is small, andlikely to be of only secondary importance for overalldecomposition rates when compared with the moredirect effects of browsing mammals removing plantspecies that produce faster decomposing litter.

The relationship between decomposability andvegetation response to herbivory was driven to a largeextent by differences between plant functional groups;it is significant that the five groups we identifiedshowed identical ranking with regard to both variables(Fig. 1b). It is apparent that the favourability of tissuesfrom large-leaved dicots to herbivores and decompos-ers is because of the low concentrations of secondarymetabolites and structural carbohydrates in thesetissues, while the unfavourability of fern, monocotand Nothofagus tissues is due largely to high concen-trations of structural carbohydrates.

The fact that small-leaved dicots were significantlyless adversely affected by browsing than were large-leaved dicots (F1,54 = 6·12, P = 0·016), but did not pro-duce litter that decomposed significantly more slowly(F1,54 = 0·71, P = 0·403), would suggest that the plantsin this group have a greater resistance to herbivorythan would be expected based on the decompositiondata. Many species in this group show a divaricatinggrowth habit, and our data provide some evidence forthe view that this growth form may serve as a structuraldefence against herbivores (Greenwood & Atkinson1977; but see Howell et al. 2002; McGlone & Clarkson1993). In this light it is relevant that this habit has beenproposed as having arisen through selection pressurefrom browsing by the recently extinct moas (Aves:Dinornithiformes; Greenwood & Atkinson 1977).

Our results provide evidence that foliar herbivoreshave the capacity to retard below-ground processesthrough causing a switch from understorey commu-nity domination by plants that produce good qualitylitter (which decomposes rapidly) to those that pro-duce poor quality litter. However, it is important tonote that this is only one of several mechanisms bywhich herbivores can influence the decomposer sub-system. First, such a mechanism will operate only ifherbivores adversely affect only palatable species, andnot if palatable species are optimized by herbivory

(Davidson 1993; McNaughton 1979). Second, herbiv-ores can also affect decomposer processes and organ-isms (either positively or negatively) through thereturn of dung and urine to the soil (Bardgett et al.1998a), inducing physiological changes and shifts inlitter quality of browsed plants (Kielland, Bryant &Ruess 1997), and affecting ecosystem productivity(Belovsky & Slade 2000). These mechanisms all oper-ate simultaneously, and it is the balance of the mech-anisms that helps determine the magnitude anddirection of overall effects of foliar herbivory on thedecomposer subsystem. In the study of Wardle et al.(2001), which utilized the same sites as the presentstudy, decomposer organisms and processes wereadversely affected by browsing mammals on somesites, and positively affected on others. It is likely thatdiminished quality of litter input through herbivore-induced vegetation changes was a driving factor inmany of those sites in which adverse effects of her-bivory on decomposers was detected. However, thismechanism must have been overridden by other mech-anisms for those sites in that study where herbivoreshad positive effects on decomposers.

Acknowledgements

We thank Gaye Rattray for technical assistance in set-ting up the decomposition bioassays, Kate Dorling(University of Western Australia) for the nutrient ana-lyses, and the Palmerston North Chemistry Labor-atory, Landcare Research for measurements of lignin,phenolics and related compounds. Marie-CharlotteNilsson made helpful comments on an earlier versionof the manuscript. This work was supported by theNew Zealand Marsden Fund and the Foundation ofResearch, Science and Technology (New Zealand).

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Received 8 January 2002; revised 4 April 2002; accepted 19April 2002




Appendix 1

Species for which litter was sampled from each of the 28 sites (site codes correspond to Table 1 of Wardle et al. 2001)

Site code

Plant species in understorey

Greater inside exclosure† Greater outside exclosure Canopy tree species

S1 Freycinetia baueriana Endl. [M]‡ NS¶ Blechnum fraseri (Cunn.) Luerssen [F] NS Agathis australis Salisb. [G]Beilschmeidia tarairi (A. Cunn.) [L]

S2 Coprosma arborea Kirk [L] NS B. tarairi [L]F. baueriana [M]* Geniostoma rupestre J. R. Forst. & G. Forst. [L] NS

S3 Coprosma rhamniodes A. Cunn [S] NS Pseudopanax lessonii (D. C.) C. Koch [L] NS Kunzea ericioides (A. Ritch) Joy Thomps [S]

Melicytus ramiflorus J. R. Forst. & G. Forst. [L]*S4 Gahnia pauciflora Kirk [M] NS A. australis [G]* A. australis [G]

Astelia trinervia Kirk [M] NSS5 M. ramiflorus [L]** Cyathea dealbata (Forst. F.) Swartz [F] NS Knightia excelsa R. Br. [L]

M. ramiflorus [L]S6 Coprosma grandifolia Hook. F. [L]** C. dealbata [F]* Beilschmeidia tawa (A. Cunn)

Benth. & Hook. F. ex. Kirk [L]Hymenophyllum demissum (Forst. f.) Schwarz [F]** Uncinia sp. [M]

S7 Coprosma lucida J. R. et. G. Forst. [L]** Cyathodes juniperina (J. R. Forst. & G. Forst.) [S]* K. excelsa [L]Astelia sp. [M]* Leucopogon fasciculata (G. Forst.) A. Rich. [S]* Nothofagus solandri var.

cliffortioides (Hook. F.) Poole [N]S8 C. grandifolia [L]** Brachyglottis repanda J. R. Forst. & G. Forst. K. ericioides [S]

[L] NSMicrolaena avenacea (Rauol) Hook. F. [M] K. excelsa [L]Uncinia uncinata (L. f.) Kük [M]**

S9 Asplenium bulbiferum Forst. F. [F]** M. avenacea [M]** B. tawa [L]Cyathea smithii Hook. F. [F] NSSchleffera digitata (J. R. & G. Forst.) [L]**

S11 Brachyglottis rotundifolia J. R. Forst. & G. Forst. [L]* Blechnum montanum Chambers & Farrant [F]* B. rotundifolia [L]Carmichaelia arborea (G. Forst.) Druce [S]*C. grandifolia [L] NSHebe stricta [Benth] [L]*

S12 Carpodetus serratus J. R. Forst. & G. Forst. [L]** L. fasciculatus [S]* K. ericioides [S]Uncinia sp. [M]*

S13 Astelia sp. [M]** C. juniperina [S]* K. ericioides [S]C. lucida [L]**Griselinia littoralis Raoul [L] NS

S14 Coprosma ciliata Hook. F. [S] NS N. solandri var. cliffortioides [N]Coprosma sp. [S]*G. littoralis [L]**N. solandri var. cliffortioides [N]*Pseudowintera colorata (Raoul) Dandy [L] NS

S16 Blechnum discolor (Forst. F.) [F] NS Myrsine salicina Hew. Ex. Hook. F. [L]

C. grandifolia [L]** Weinmannia racemosa L. f. [L]Pseudowintera axillaris (J. R. et G. Forst.) [L]*

S17 Coprosma microcarpa Hook. F. [S]** C. juniperinus [S] NS N. fusca [N]N. menziesii (Hook. F.) [N]

G. littoralis [L]*Nothofagus fusca (Hook. F.) Oerst [N] NSPimelia sp. [L] NS

S18 Coprosma linariifolia Hook. F. [S] NS N. solandri var. solandri [N]G. littoralis [L] NSNothofagus solandri var. solandri (Oerst) [N] NS

S19 C. serratus [L] NS N. fusca [N] NS K. ericioides [S]N. fusca [N]

S20 N. fusca [N] NS N. fusca [N]N. menziesii [N]* N. menziesii [N]

S21 N. solandri var. cliffortioides [N] NS C. rhamnoides [S] NS N. solandri var. cliffortioides [N]S22 Coprosma foetidissima J. R. Forst. & G. Forst. [L]* Neomyrtus pedunculatus (Hook. F.) [S] NS Librocedrus bidwillii Hook. f. [G]

C. lucida [L]*G. littoralis [L]**Pseudopanax simplex (G. Forst.) Philipson [L]**P. colorata [L] NS




S23 A. bulbiferum [F] NS Coprosma rotundifolia A. Cunn. [S] NS G. littoralis [L]S. digitata [L]** Polystichum vestitum (Forst. F.) [F]** L. bidwillii [G]

S24 Pittosporum tenuifolium Sol. Ex. Gaertn. [L]** C. rotundifolia [L]* M. ramiflorus [L]S25 N. solandri var. cliffortioides [N] NS Hymenophyllum multifidum (Forst. F.) [F] NS N. solandri var. cliffortioides [N]

Hymenophyllum sanguinolentum (Forst. F.) [F] NSS26 Blechnum fluviatile (R. Br.) Salomon [F] NS H. sanguilentum [F]** N. menziesii [N]

C. serratus [L] NS N. menziesii [N]**Coprosma parviflora Forst. f. [S]** N. solandri var. cliffortioides [N] NS

P. vestitum [F] NSS27 Coprosma s. t. as in Eagle, A. [S]** B. discolor [F]* N. menziesii [N]

G. littoralis [L]** Pseudowintera colorata [L]*Pseudopanax sp. [L]*

S28 B. discolor [F] NS C. foetidissima [L] NS Dacrydium cupressinum Lamb. [G]Metrosideros umbellata Cav. [L]W. racemosa [L]

S29 Histiopteris incisa (Thunb.) J. Smith [F] NS B. discolor [F] NS B. rotundifolia [L]B. rotundifolia [L]* C. serrata [L]

Dicksonia squarrosa (Forst. f.)Swartz [F]

S30 C. foetidissima [L]** B. discolor [F] NS D. squarrosa [F]D. squarrosa [F]* M. umbellata [L]

W. racemosa [L]

†Greater inside exclosure and greater outside exclosure = measured vegetation density of that species is higher inside the exclosure, and outside the exclosure, respectively.‡Letters in square brackets represent plant type; codings: F = ferns; G = gymnosperms; L = large-leaved dicots (leaf lamina width >6 mm); M = monocots; N = Nothofagus; S = small-leaved dicots (leaf lamina width <6 mm).¶Statistical significance: NS, * and ** indicate that the difference in vegetation density inside vs outside the exclosure plot of that species is not significantly different, is different at P = 0·05, or is different at P = 0·01, respectively (derived from Wardle et al. 2001).

Site code

Plant species in understorey

Greater inside exclosure† Greater outside exclosure Canopy tree species

Appendix 1 Continued


Documents

Linkages between plant litter decomposition, litter quality, and vegetation responses to herbivores