Download introduced browsing mammals in new zealand natural forests

Ecological Monographs, 71(4), 2001, pp. 587–614
q 2001 by the Ecological Society of America
INTRODUCED BROWSING MAMMALS IN
NEW ZEALAND NATURAL FORESTS: ABOVEGROUND AND
BELOWGROUND CONSEQUENCES
DAVID A. WARDLE,1,5 GARY M. BARKER,2 GREGOR W. YEATES,3 KAREN I. BONNER,1
AND
ANWAR GHANI4
1Landcare
Research, P.O. Box 69, Lincoln 8152, New Zealand
Landcare Research, Private Bag 3127, Hamilton, New Zealand
Landcare Research, Private Bag 11052, Palmerston North, New Zealand
4AgResearch, Ruakura Agricultural Research Centre, Private Bag 3123, New Zealand
2
3
Abstract. Forest dwelling browsing mammals, notably feral goats and deer, have been
introduced to New Zealand over the past 220 years; prior to this such mammals were absent
from New Zealand. The New Zealand forested landscape, therefore, presents an almost
unique opportunity to determine the impacts of introduction of an entire functional group
of alien animals to a habitat from which that group was previously absent. We sampled 30
long-term fenced exclosure plots in indigenous forests throughout New Zealand to evaluate
community- and ecosystem-level impacts of introduced browsing mammals, emphasizing
the decomposer subsystem.
Browsing mammals often significantly altered plant community composition, reducing
palatable broad-leaved species and promoting other less palatable types. Vegetation density
in the browse layer was also usually reduced. Although there were some small but statistically significant effects of browsing on some measures of soil quality across the 30
locations, there were no consistent effects on components of the soil microfood web (comprising microflora and nematodes, and spanning three consumer trophic levels); while there
were clear multitrophic effects of browsing on this food web for several locations, comparable numbers of locations showed stimulation and inhibition of biomasses or populations
of food web components. In contrast, all microarthropod and macrofaunal groups were
consistently adversely affected by browsing, irrespective of trophic position. Across the
30 locations, the magnitude of response of the dominant soil biotic groups to browsing
mammals (and hence their resistance to browsers) was not correlated with the magnitude
of vegetation response to browsing but was often strongly related to a range of other
variables, including macroclimatic, soil nutrient, and tree stand properties.
There were often strong significant effects of browsing mammals on species composition
of the plant community, species composition of leaf litter in the litter layer, and composition
of various litter-dwelling faunal groups. Across the 30 locations, the magnitude of browsing
mammal effects on faunal community composition was often correlated with browser effects
on litter layer leaf species composition but never with browser effects on plant community
composition. Browsing mammals usually reduced browse layer plant diversity and often
also altered habitat diversity in the litter layer and diversity of various soil faunal groups.
Across the 30 locations, the magnitude of browser effects on diversity of only one faunal
group, humus-dwelling nematodes, was correlated with browser effects on plant diversity.
However, browser effects on diversity of diplopods and gastropods were correlated with
browser effects on habitat diversity of the litter layer. Reasons for the lack of unidirectional
relationships across locations between effects of browsers on vegetation community attributes and on soil invertebrate community attributes are discussed.
Browsing mammals generally did not have strong effects on C mineralization but did
significantly influence soil C and N storage on an areal basis for several locations. However
the direction of these effects was idiosyncratic and presumably reflects different mechanisms
by which browsers affect soil processes. While our study did not support hypotheses predicting
consistent negative effects of browsing mammals on the decomposer subsystem through
promotion of plant species with poorer litter quality, our results still show that the introduction
of these mammals to New Zealand has caused far-ranging effects at both the community and
ecosystem levels of resolution, with particularly adverse effects for indigenous plant communities and populations of most groups of litter-dwelling mesofauna and macrofauna.
Key words: alien organisms; browsing; decomposer food web; deer; goats; herbivory; macrofauna; mesofauna; microbial biomass; microfauna; New Zealand forests; plant litter.
Manuscript received 6 June 2000; revised 22 February 2001; accepted 23 February 2001; final version received 16 March 2001.
Present address: Department of Animal and Plant Sciences, University of Sheffield, Sheffield S10 2TN, UK.
E-mail: [email protected]
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DAVID A. WARDLE ET AL.
588
INTRODUCTION
In terrestrial ecosystems, browsing by herbivores has
important indirect effects on belowground properties
and processes, in particular the mineralization of soil
C and N (Holland et al. 1992, Molvar et al. 1993, Pastor
et al. 1993, Frank and Groffman 1998). Several mechanisms have been proposed to explain how herbivory
affects soil processes and the organisms that govern
these processes (Bardgett et al. 1998b), but three
emerge as being consistently important. First, animals
return organic matter and nutrients to the soil in relatively labile forms as dung and urine, which may stimulate soil activity (Ruess and McNaughton 1987,
Bardgett et al. 1998a, Mulder and Ruess 1998). Second,
herbivory can affect soil biota by inducing physiological changes at the whole-plant level, either by altering
the biomass and productivity of the browsed plant
(Ruess et al. 1998; but see McNaughton et al. 1998),
or by inducing the browsed plant to produce biomass,
and subsequently litter, of altered quality and decomposability (Seastedt et al. 1988, Tuomi et al. 1988,
Kielland et al. 1997, Kaitaniemi et al. 1998). Third, on
a longer temporal scale, browsing mammals preferentially feed upon plant species with a higher resource
quality (Coley et al. 1985, Grime et al. 1996), often
resulting in their replacement in the plant community
by species which are better defended but have poorer
resource quality (Augustine and McNaughton 1998,
Ritchie et al. 1998), ultimately causing retardation of
soil processes (Pastor et al. 1988, 1993; but see De
Mazancourt and Loreau 2000). The effects of herbivores on soil processes via the above mechanisms are
increasingly recognized as important in influencing
plant nutrition and plant growth, resulting in major
feedbacks between the aboveground and belowground
compartments of ecosystems (McNaughton et al. 1988,
De Mazancourt et al. 1998, 1999, Mulder and Ruess
1998).
While research on how herbivores affect soil processes is increasing, remarkably little is known about
how they influence the components of the soil food
web which ultimately regulate these processes. However, there is evidence that the effects of herbivory on
the microbial biomass can be positive (Ruess and Seagle 1994, Bardgett and Leemans 1995, Stark et al.
2000), negative (Pastor et al. 1988), or neutral (Wardle
and Barker 1997) depending on the system being considered. There is some evidence from the few studies
available that aboveground herbivory may also influence higher trophic levels of decomposer food webs,
for example microbe-feeding nematodes (Yeates 1976,
Seastedt et al. 1988, Merrill et al. 1994), microarthropods (Leetham and Milchunas 1985, Bardgett et al.
1993), litter-associated gastropods (Suominen 1999),
and various soil-associated macrofauna (Suominen et
al. 1999). Foliar herbivory can also alter the composition of specific groups of soil biota (Milchunas et al.
Ecological Monographs
Vol. 71, No. 4
1998, Suominen 1999, Suominen et al. 1999) although
Milchunas et al. (1998) concluded that these effects
tended to be small especially when compared with the
effects of herbivores on composition of aboveground
biota such as plants and birds.
The influence of herbivory on the diversity (including taxonomic richness) of consumer groups comprising the decomposer food web remains largely unexplored. Herbivory often increases plant diversity
(Zeevalking and Fresco 1977, Collins et al. 1998),
probably by reducing competitive exclusion (Grace and
Jutila 1999), although both positive and negative effects on diversity are possible depending on the mechanisms involved (Olff and Ritchie 1998, Proulx and
Mazumder 1998). The effects of plant diversity on decomposer diversity are poorly understood, although
reasons can be presented both for and against a relationship between decomposer diversity and plant diversity (Wardle et al. 1999, Hooper et al. 2000). Suomonen (1999) found gastropod diversity was consistently reduced by browsing while Leetham and Milchunas (1985) and Wall-Freckman and Huang (1998)
found no effect of browsing on the diversity of microarthropods and nematodes, respectively.
Despite the dearth of information, the potential effects of browsers on populations of soil organisms and
soil community structure may control ecosystem processes in the longer term (Milchunas et al. 1998). The
composition of the decomposer food web can operate
as a key regulator of mineralization processes (Ingham
et al. 1986, Bengtsson et al. 1996), plant nutrient acquisition (Setälä and Huhta 1991), and ultimately plant
growth (Alphei et al. 1996, Laakso and Setälä 1999).
The indirect influence of browsing on soil communities
is therefore likely to operate as a critical link in maintaining feedbacks between the soil subsystem and the
plant–herbivore subsystem (e.g., McNaughton et al.
1988, Pastor et al. 1988, De Mazancourt et al. 1998,
Mulder and Ruess 1998).
Several species of browsing mammals were liberated
in New Zealand between the 1770s and 1920s, including Capra hircus L. (feral goats) and deer (most notably
Cervus elaphus scoticus Lönnberg [red deer]); prior to
this, forest dwelling browsing mammals were absent
from New Zealand. Since their introduction, browsing
mammals have become widespread and abundant
throughout most of the forested landscape of New Zealand. Several studies have shown, mainly through the
use of fenced exclosures, that introduced browsing
mammals commonly reduce vegetation density in the
browse layer and alter vegetation composition by favoring unpalatable ferns and monocotyledonous species at the expense of faster-growing, palatable, broadleaved species (Conway 1949, Williams 1955, Wallis
and James 1972, Jane and Pracy 1974, Smale et al.
1995). New Zealand’s native megaherbivores, moas
(Aves: Dinornithiformes), became extinct through human hunting probably around or before AD 1400 (Hol-
BROWSING MAMMALS AND DECOMPOSERS
November 2001
daway and Jacomb 2000). While the ecological impact
of these browsers remains unclear, their browsing habits were probably very different from those of deer and
goats (Atkinson and Greenwood 1989, Caughley 1989)
and the effects of moa browsing on vegetation are believed to have been considerably less severe than those
of introduced browsing mammals (McGlone and Clarkson 1993).
There is increasing interest in understanding the ecological significance of alien organisms in new environments (Vitousek et al. 1997). The New Zealand forested landscape presents an almost unique opportunity
to determine the impacts of introducing an entire functional group of alien organisms (forest-dwelling browsing mammals) to an environment from which that group
was absent. In this context, we aimed to test the following four interrelated hypotheses so as to better understand the community- and ecosystem-level impacts
of introduced browsing mammals in New Zealand, with
emphasis on effects of browsers on the biotic components of the decomposer subsystem, through the use
of long term animal exclosure plots:
Hypothesis 1.—Browsing greatly reduces vegetation
density in the browse layer and shifts dominance to
unpalatable plant species; this, in turn, adversely affects soil chemical properties and various constituents
of the decomposer food web. This hypothesis is consistent with the findings of Pastor et al. (1988, 1993)
for boreal forests, and builds upon earlier studies in
New Zealand forests suggesting that browsing mammals induce dominance of certain plant functional
types above others (Wallis and James 1972, Jane and
Pracy 1974).
Hypothesis 2.—Browsing mammals alter plant community species composition, which, in turn, influences
the species composition and quality of litter, and therefore the composition of the main taxa of soil organisms.
This hypothesis predicts that the magnitude of effects
of browsing mammals on soil communities will be determined by the magnitude of effects of browsers on
plant community composition.
Hypothesis 3.—Browsing mammals may induce positive or negative changes in plant diversity, and these
effects are matched by corresponding predictable shifts
in the diversity of litter types entering the decomposer
subsystem, and ultimately in the diversity of various
components of the belowground biota.
Hypothesis 4.—Reductions in populations and biomasses of soil biota due to browsing will reduce belowground processes such as C mineralization, resulting in a greater storage of C and N on an areal basis
in the litter and humus layers of browsed forests.
METHODS
System and sampling strategy
Our study utilized a series of long-term, fenced,
browsing mammal exclosures. From the 1950s to the
589
1980s the former New Zealand Forest Service (NZFS)
established several hundred exclosures throughout
New Zealand to assess the impacts of introduced deer
and goats on vegetation in natural forests. With the
dissolution of the NZFS in the late 1980s, maintenance
of the vast majority of these exclosures was discontinued and many are no longer effective at excluding
browsing mammals, although it is likely that over 100
still remain in adequate condition. These exlosures
have the advantage of being scattered throughout most
of New Zealand’s forest types and climatic regions, and
are sufficiently distant from major tracks and routes to
reduce the incidence of human interference; many can
only be accessed by several hours walking or by helicopter or boat. They represent a unique resource for
addressing questions about how the introduction of a
whole functional group of alien animal species can alter
ecosystem properties.
For the present study, we selected 30 exclosures,
representing a wide geographic range and encompassing most of New Zealand’s major forest types (Fig. 1,
Table 1; all sites subsequently referred to by the codes
in the left hand column of Table 1). Only exclosures
that were at least 13 yr old were considered. The main
browsing mammal in most locations was C. elaphus,
with several locations supporting C. hircus, and with
the dominant browser in some areas being Dama dama
L. (fallow deer), Odocoileus virginianus Zimmerman
(white tailed deer), or Macropus eugenii Desmarest
(Dama wallaby). These exclosures do not exclude introduced arboreal browsing mammals such as Trichosurus vulpecula Kerr (brushtail possum), or introduced
rodents. Twenty nine of the exclosures were established
by the NZFS, while one (S21) was set up by the University of Canterbury’s School of Forestry. Most exclosures were ;400 m2 or 20 3 20 m (mean 6 1 SE
5 431 6 76 m2). Each exclosure was sampled once
between 25 September 1997 and 26 May 1999. While
we acknowledge that a one-time sampling cannot reflect temporal trends in our response variables, we restricted our sampling to the spring and autumn months
to avoid any extremes of temperature and moisture that
may have confounded the results.
The exclosures were not initially replicated, a problem that characterizes the vast majority of published
exclosure studies (see Stohlgren et al. 1999), particularly those that involve older exclosures. However, because most of the exclosures in our study were relatively large and because the focus was on belowground
properties effectively sampled over smaller spatial
scales, we employed a stratified sampling regime (cf.,
Stark et al. 2000). For each location we set up four
subplots (usually 4 3 4 m) per exclosure, with one
subplot in each corner, and each subplot usually at least
1.5 m away from the fence; adjacent subplots were at
least 8 m apart in the vast majority of cases. We also
set up four 4 3 4-m subplots outside the exclosure,
each paired with one of the inside-exclosure subplots
DAVID A. WARDLE ET AL.
590
FIG. 1.
Ecological Monographs
Vol. 71, No. 4
Distribution of the 30 locations that were sampled. Location codes are as for Table 1.
and located at least 3 m outside the fence. The four
pairs of subplots (each consisting of an inside-exclosure subplot and an outside-exclosure subplot) served
as the unit of replication for each location.
For each subplot at each location we measured both
browse-layer vegetation (0–2 m height layer) and
ground-layer vegetation (0–10 cm height layer). Density of browse-layer vegetation was measured using a
height frequency method (Scott 1965, Dickinson et al.
1992). A 2-m pole marked at 10-cm increments was
positioned vertically, and for each plant species the
presence of any vegetation intercepting a prescribed
cylinder (adjacent to the pole and indicated by horizontal circular guide rings attached to the pole) of diameter 5 cm was recorded for each of the twenty 10cm height classes. This pole was positioned twenty
November 2001
TABLE 1.
Site
code
S1
S2
S3
S4
S5
S6
S7
S8
S9
S10
S11
S12
S13
S14
S15
S16
S17
S18
S19
S20
S21
S22
S23
S24
S25
S26
S27
S28
S29
S30
BROWSING MAMMALS AND DECOMPOSERS
591
Characteristics of the 30 forest exclosure plots sampled in New Zealand.
Dominant tree species†
Aga. aus., Bei tar.
Bei. tar., Rho. sap., Cya. dea.
Kun. eri.
Aga. aus.
Mel. ram., Cya. med., Kni. exc.
Bei. taw.
Not. cli.
Dic. squ., Kun. eri., Mel. ram.
Cya. smi., Bei. taw.
Pod. hal., Gri. lit., Phy. alp.
Pod. hal., Cor. ban., Bra. rot.
Kun. eri.
Kun. eri.
Not. cli.
Several codominant
Myr. sal., Wei. rac., Not. fus.
Not. men., Not. fus., Wei. rac.
Not. sol.
Not. fus., Gri. lit., Car ser.
Not. fus., Not. men.
Not. cli.
Wei. rac., Lib. bid., Pod. tot.
Lib. bid., Pod. hal.
Mel. ram.
Not. cli.
Not. men.
Not. men.
Met. umb., Wei. rac.
Bra. rot., Dic. squ., Car. ser
Wei. rac., Dic. squ., Met. umb.
Mammals
excluded‡
January
Annual mean
Altitude rainfall temp.
(m. a.s.l.)§ (mm)
(8C)
Cap. hir.
Cap. hir.
Dam. dam.
Cap. hir.
Cer. ela., Mac. cug.
Cer. ela.
Cer. ela.
Cer. ela.
Cap. hir.
Cer. ela.
Cap.hir.
Cer. ela.
Cer. ela.
Cer. ela.
Cer. ela.
Cap. hir.
Cer. ela.
Cer. ela.
Cer. ela.
Cer. ela.
Cer. ela.
Cer. ela.
Cer. ela.
Cer. ela.
Cer. ela.
Cer. ela.
Cer. ela.
Odo. vir.
Odo. vir.
Odo. vir.
250
180
110
120
310
375
400
180
490
995
900
650
600
1090
590
340
600
800
560
710
1300
460
470
230
900
540
640
75
35
75
1974
2194
1377
2218
1739
1453
1476
2212
2536
2415
4742
1327
1901
1605
1708
1249
1616
1535
1615
1565
2594
3932
5896
2958
1832
1141
1127
1331
1329
1331
17.5
17.9
17.9
18.3
17.3
16.9
16.8
18.0
16.0
13.4
12.5
15.5
15.5
12.9
14.8
15.1
14.2
13.8
14.8
14.3
10.4
14.5
14.2
14.0
10.4
12.7
11.9
12.4
12.6
12.4
July
mean
temp.
(8C)
Year
exposure
established
9.9
10.5
9.6
8.8
7.0
6.0
5.9
7.4
7.3
3.1
4.7
5.0
5.2
2.8
5.2
7.2
4.5
2.9
3.2
2.3
21.0
3.8
3.6
4.0
0.6
2.4
2.3
5.4
5.6
5.4
1984
1984
1983
1983
1984
1961
1961
1968
1983
1985
1972
1982
1982
1983
1974
1978
1975
1963
1963
1963
1970
1966
1967
1968
1972
1964
1976
1979
1979
1979
Tree
spe- Tree
cies basal
rich- area
ness\ (m2/ha)
8
8
5
4
4
8
3
8
6
6
4
4
3
3
14
12
7
5
7
2
1
7
11
4
1
3
1
6
6
7
114
40
31
66
35
49
28
49
45
57
7
32
38
98
19
70
61
55
55
33
149
84
50
74
93
155
72
192
36
81
† Only tree species that constitute .10% of total basal area are included. Codes for tree species: Aga. aus. 5 Agathis
australis Salisb.; Bei. tar. 5 Beischmeidia tarairi (A. Cunn.) Benth & Hook. f. ex Kirk; Bei. taw. 5 B. tawa (A. Cunn.)
Benth. & Hook. f. ex. Kirk; Bra. rot. 5 Brachyglottis rotundifolia J. R. Forst. & G. Forst.; Car. ser. 5 Carpodetus serratus
J. R. Forst. & G. Forst.; Cor. ban. 5 Cordyline banksii Hook. f.; Cya. dea. 5 Cyathea dealbata (Forst. f.) Swartz; Cya. med.
5 C. medullaris (Forst. f.) Schwartz; Cya. smi. 5 C. smithii Hook. f.; Dic. squ. 5 Dicksonia squarrosa (Forst. f.) Swartz;
Gri. lit. 5 Griselinia littoralis Raoul; Kni. exc. 5 Knightia excelsa R. Br.; Kun. eri. 5 Kunzea ericoides (A. Ritch.) Joy
Thomps.; Lib. bid. 5 Librocedrus bidwillii Hook. f.; Mel. ram. 5 Melicytus ramiflorus I. R. Forst. & G. Forst.; Met. umb.
5 Metrosiderus umbellata Cav.; Myr. sal. 5 Myrsine salicina Hew. Ex. Hook. f.; Not. cli. 5 Northofagus solandri var.
clifforitioides (Hook. f.). Poole; Not. fus. 5 N. fusca (Hook. f.) Oerst.; Not. men. 5 N. menziesii (Hook. f.); Not. sol. 5 N.
solandri var. solandri (Hook. f.) Oerst; Phy. alp. 5 Phyllocladus alpinus Hook. f.; Pod. hal. 5 Podocarpus hallii Kirk; Pod.
tot. 5 P. totara G. Benn.; Rho. sap. 5 Rhopalostylis sapida H. Wendl. & Druce; Wei. rac. 5 Weinmannia racemosa L. f.
‡ Codes for mammal species: Cap. hir. 5 Capra hircus; Cer. ela. 5 Cervus elaphus scoticus; Dam. dam. 5 Dama dama;
Odo. vir. 5 Odocoileus virginianus; Mac. eug. 5 Macropus eugenii.
§ Meters above sea level.
\ Number of tree species of .5 cm diameter at 1.3 m height, on a plot of 400 m2.
times within each subplot (in a 4 3 5 grid), resulting
in a maximum possible score of 400 intercepts for each
species in the browse layer. Ground layer vegetation
was assessed in each subplot by using a point intercept
method (Goodall 1952). A frame with five points 20
cm apart was projected downwards and all plant species
intercepted by each point were recorded. This frame
was positioned twenty times in each subplot, resulting
in a maximum possible score of 100 intercepts for each
species.
Humus and litter samples were collected from each
subplot for chemical, microbial, and microfaunal analysis. Several square quadrats (usually 30 3 30 cm)
were placed in each subplot and litter and humus were
collected separately within these quadrats. In each sub-
plot, sufficient quadrats were sampled to provide
enough material for the required analyses and in most
cases at least three quadrats per subplot were sampled.
All litter was combined within each subplot, as was all
humus. A separate collection of litter from each subplot
was made specifically for the extraction of soil mesofauna and macrofauna. Here, litter was collected
from six circular areas of 34 cm diameter in each subplot; all litter was combined for each subplot.
Litter and humus analyses
Humus and litter sampled using the square quadrats
was weighed and the gravimetric moisture content
(808C, 24 h) measured to determine the total mass of
litter and humus present in each subplot on an areal
592
DAVID A. WARDLE ET AL.
basis. Each sample was then homogenized and a representative subsample used to determine C and N concentrations (using a Leco FP-2000 analyzer; Laboratories Equipment Corporation, St. Joseph, Michigan,
USA) and pH. Storage of C and N on an areal basis in
the litter and humus layers was determined from these
figures.
For each litter sample, a representative subsample
(;100 g wet mass) was hand sorted into leaf litter, twig
litter and amorphous material. All leaf litter was then
hand sorted into component species. Oven dry mass
(808C, 24 h) of all sorted material was then determined.
A subsample of each homogenized sample was selected for microbial measurements; all samples were
stored at 48C until the time of measurement. In the case
of humus, this material was sieved to 4 mm while the
litter layer material was cut into fragments of 1 cm
whenever necessary. Microbial basal respiration of
each subsample was determined as described by Wardle
(1993). This involved adjusting 3 g (dry mass) humus
or litter to 150% moisture content (dry mass basis),
placing it in a 130-mL airtight incubation vessel, and
incubating at 228C. CO2-C evolution between 1 h and
4 h of incubation was then determined by injecting 1mL subsamples of headspace gas into an infrared gas
analyzer. Substrate-induced respiration (SIR; a relative
measure of active microbial biomass) was determined
using the approach of Anderson and Domsch (1978),
as modified by West and Sparling (1986) and Wardle
(1993). This was performed as for basal respiration,
but with an amendment of 10 mg glucose/g material
at the beginning of the incubation.
Total microbial biomass C and N was determined for
each humus sample, using the fumigation–extraction
procedure described by Wardle and Ghani (1995), modified from Brookes et al. (1985) and Vance et al. (1987).
This technique cannot be reliably applied to litter, so
the litter samples were not analyzed using this approach. Briefly, duplicate subsamples (5 g dry mass)
of each humus sample were fumigated with chloroform
and a further two were left nonfumigated; these subsamples were extracted with 0.5 mol/L K2SO4 for 2 h
on an end-over-end shaker. These samples were then
centrifuged and filtered and stored at 48C until analysis
was complete. Total C in the fumigated and nonfumigated extracts was determined on a Shimadzu 500
TOC analyzer (Shimadzu Corporation, Kyoto, Japan;
Ghani et al. 1999). These extracts were also analyzed
for N using micro-Kjeldahl analysis. Microbial C and
N were determined by using the differences in C and
N between the fumigated and nonfumigated subsamples with transformation multipliers of 2.22 (Brookes
et al. 1985, Wu et al. 1990). Water soluble C concentrations were also determined for each humus sample
as described by Wardle and Ghani (1995) by extracting
10 g (dry mass; sieved to 4 mm) humus in 20 mL water
for 30 min using an end-over-end shaker at 208C.
Ecological Monographs
Vol. 71, No. 4
Amounts of total soluble C in these extracts were then
determined as described above.
A preweighed subsample (usually ;100 g wet mass)
of each homogenized humus and litter layer sample
was used for microfaunal and enchytraeid determination by using a tray variant of the Baermann method
(Southey 1986, Yeates et al. 1993b). Total nematodes,
rotifers, copepods, tardigrades, and enchytraeids were
counted under a stereomicroscope at 403 before being
killed and fixed by addition of an equal volume of
boiling 8% formaldehyde. Subsequently, a mean of 126
nematode specimens from each sample were identified
to nominal genus or family level and placed into six
functional groupings occupying three trophic levels,
following Yeates et al. (1993a, b). These trophic groupings (with component functional groups in brackets)
were: microbe feeders (bacterial feeders and fungal
feeders), predators (top predators and ‘‘omnivores’’,
i.e., predators that feed at more than one trophic level),
and herbivores (plant parasites and plant associates).
The leaf litter material collected from each subplot
for mesofaunal and macrofaunal assessments was extracted in its entirety by placing it in a Tullgren (modified Berlese) funnel for a period of 6–14 d depending
on the bulk and moisture content of the litter. Invertebrates were captured in ethylene glycol and stored in
70% ethanol prior to sorting and identification. Following Tullgren funnel extraction, the samples were
sieved and all material passing through a 5-mm mesh
was scanned using a binocular microscope for shells
of gastropod species not extracted in the funnels. The
groups of mesofauna enumerated included Collembola
and Acari (the latter separated into Oribatida, Astigmata, Mesostigmata, and Prostigmata). Main groups of
macrofauna counted included Coleoptera (identified to
family), Staphylinidae (Coleoptera; identified to subfamily), Stratiomyidae (Diptera) larvae, Gastropoda
(identified to species), Isopoda, Amphipoda, Diplopoda
(identified to family), Chilopoda, Araenida, Pseudoscorpionidea, and Opiliones.
Community-level assessments
For each group of taxa that we assessed (including
litter), we aimed to determine the effects of browsing
on community composition. These groups (and the taxonomic resolution to which they were identified) included plants in the browse layer (species level), plants
in the ground layer (species level), leaf litter in the
litter layer (species level), litter layer habitat composition (separated into twigs, amorphous material, and
leaf litter sorted into species), Nematoda in litter (family level), Nematoda in humus (family level), Gastropoda in litter (species level), Diplopoda in litter (family
level), Staphylinidae in litter (subfamily level), and Coleoptera in litter (family level). To determine the degree
of dissimilarity of community composition inside vs.
outside for each exclosure (cf. Milchunas and Lauenroth 1993, Milchunas et al. 1998) for each of these ten
November 2001
BROWSING MAMMALS AND DECOMPOSERS
groups, we quantified the dissimilarity between each
subplot inside the exclosure and the corresponding subplot outside the exclosure, using the community dissimilarity index of Whittaker (1952). This index increases with increasing dissimilarity of community
composition, and ranges from 0 (community composition identical between the two subplots) to 1 (community composition mutually exclusive between the
subplots).
To determine the effect of browsing on community
diversity, the Shannon-Weiner diversity index was calculated for each subplot for each of these ten groups;
the index based on the litter habitat composition of the
litter layer was used as a measure of microhabitat diversity (i.e., litter habitat diversity). Taxonomic richness, i.e., number of taxa noted for each subplot, was
also determined for each of the groups except for litter
layer habitat composition.
Statistical analyses
Our study enabled us to assess the effects of browsing mammals on response variables at two contrasting
scales: within each location and across all 30 locations.
At the within-location scale, the effect of browsing
mammals on each response variable was assessed by
paired t tests in which the four subplots inside each
exclosure were compared with the corresponding four
subplots outside it; data was transformed by log, square
root, or ranking whenever necessary to satisfy assumptions for parametric analysis. For the community
dissimilarity index data, it was not possible to test directly for statistical significance of exclosure effects
because each datum includes information from both
inside and outside the exclosure. Therefore, to test
whether community composition of each of the ten
groups of taxa mentioned earlier differed significantly
between inside and outside the exclosure for each location, Principal Components Analysis (PCA) was used
to derive principal components scores for each of the
eight subplots at that location which summarized the
overall community composition data for that group.
Paired t tests were then used to determine whether the
principal component scores for the main two axes, determined for each subplot, differed significantly between inside the exclosure and outside it, and therefore
whether the community composition of that group significantly differed inside vs. outside the exclosure (see
Wardle et al. 1999).
At the across-location scale, paired t tests were also
used for testing effects of browsing on the various response variables that we measured, but with each of
the 30 locations serving as a single unit of replication.
In addition, correlation and multiple stepwise regression were used to evaluate the possible influence of a
range of independent variables on the magnitude of
effect of browsing mammals on the populations (or
biomasses) of various groups of soil organisms (calculated as [population inside exclosure 2 population
593
outside exclosure]/[population inside exclosure]; see
Milchunas and Lauenroth 1993) across all 30 locations.
These independent variables included plant browse layer biomass and community characteristics, and litter
and humus chemical properties (and effects of browsers
on each of these variables), as well as such factors as
site macroclimate, forest stand properties, altitude, latitude, and age of exclosure. Macroclimatic variables
were determined for each location using climate-surface models (Leathwick and Stephens 1998) and included mean annual rainfall; mean July, January, and
annual air temperature; mean annual humidity; mean
solar radiation; and mean annual potential evapotranspiration. Forest stand properties included tree species
richness, diversity (Shannon-Weiner index), and basal
area for all trees with diameter .5 cm at 1.3 m height,
measured on a 400 m2 plot at each location. Correlation
and multiple stepwise regression analysis were also
used to determine whether community dissimilarity
(between inside and outside exclosure) of each soil
animal group (Nematoda, Staphylinidae, Coleoptera,
Diplopoda, Gastropoda) across the 30 locations was
more closely related to community dissimilarity of
browse layer plants and/or litter across these locations,
or was instead related to some of the independent variables mentioned above. Similar analyses were performed to determine whether effects of browsing on
diversity of these animal groups across locations were
related to browsing effects on plant, leaf litter, and litter
layer habitat diversity; or whether other variables instead emerged as being of importance.
RESULTS
Plant responses
Plant density in the browse layer (i.e., pole intercept
frequency) was greater inside than outside the exclosures for 25 of the 30 locations, and these effects were
significant at P 5 0.05 for 13 locations (Fig. 2). Further,
when the data for all 30 locations were pooled, plant
density in the browse layer was significantly greater
inside than outside the exclosures (Fig. 3). In contrast,
for the 16 locations in which some ground layer vegetation was present, there were several instances in
which density in the ground layer was greater outside
than inside the exclosure, and these effects were significant at P 5 0.05 for five locations (Fig. 2). There
were no overall significant differences in the vegetation
density of the ground layer between inside and outside
exclosures when data were pooled for all locations (Fig.
3).
Browsing mammals affected the relative importance
of different plant species in the browse layer, and there
were clear differences in composition inside vs. outside
for several exclosures (Fig. 4). At 12 locations, several
larger leafed plant species were very abundant inside
the exclosure and effectively absent outside it. Species
that were frequently severely reduced by browsers in-
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DAVID A. WARDLE ET AL.
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Vol. 71, No. 4
FIG. 2. Plant density and soil chemical properties inside and outside of 30 browsing mammal exclosure plots. I, inside
exclosure; O, outside exclosure. For each panel, locations are arranged in order of decreasing effect of browsers on the
density of plants in the browse layer (calculated as [density inside exclosure 2 density outside exclosure]/[density inside
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BROWSING MAMMALS AND DECOMPOSERS
cluded Geniostoma rupestre J. R. Forst. & G. Forst.,
Astelia spp., Griselinia littoralis Raoul, and Coprosma
spp. (especially C. grandifolia Hook. f.). However,
there were instances in which some plant species were
clearly promoted by browsing, and these tended to include smaller-leaved shrubs [i.e., Cyathodes juniperina
J. R. Forst. and G. Forst., Leucopogon fasciculatus (G.
Forst.) A. Rich], and some fern species [e.g., Blechnum
spp., Polystichum vestitum (Forst. F.)]. Browsing mammals also induced large changes in the vegetation composition of the ground layer (Fig. 5); browsing significantly enhanced the cover of sedges (Uncinia spp.) at
five sites and the grass Microlaena avenacea (Raoul)
Hook. f. and filmy ferns (Hymenophyllum spp.) at two
sites.
Humus and litter chemical properties
In nearly all of the 30 locations there was no significant effect of browsing mammals on either N concentration or C to N ratio of the litter layer (data not
presented), although when the data were averaged
across all 30 locations, the C to N ratio was marginally
significantly lower inside (50.0) than outside (53.6) the
exclosures (t 5 2.08, P 5 0.043; Fig. 3). Seven locations showed significant effects of browsers on humus N concentration although the direction of this response varied among locations (Fig. 2); only four
showed significant effects on humus C to N ratio (data
not presented) and there were no significant effects
when data were averaged across all 30 locations (Fig.
6). Ten and 11 locations showed significant effects of
browsers on pH in the litter and humus layers, respectively, roughly equal numbers of locations showed
stimulation and reduction of pH by browsers, and when
the data were averaged across all 30 locations there
were no significant differences inside vs. outside exclosures (Figs. 3 and 6). Over a quarter of the locations
also showed significant effects of browsers on humus
soluble organic C concentrations (Fig. 2), and, averaged across the 30 locations, concentrations were significantly greater inside (422 mg C/g humus) than outside (351 mg C/g humus) exclosures (t 5 2.16, P 5
0.040; Fig. 6).
For many of the 30 locations, browsing mammals
significantly affected C and N storage on an areal basis
in the humus and (to a lesser extent) litter layers (Fig.
7). Despite the strength of these effects in several cases,
the direction of browser effects was highly idiosyncratic, with browsers significantly promoting sequestration of C and N in some cases and having the reverse
effect in others. When averaged across all 30 locations
595
there were no overall effects of browsing mammals on
C or N storage in litter or humus, and the magnitude
of the effect of browsers on C and N storage was not
significantly correlated with the magnitude of effect of
browsers on either vegetation density or vegetation
composition (dissimilarity index data) across sites.
Components of the soil microfood web
Our measurements enabled us to assess the effects
of browsing mammals on the soil microfood web,
which includes the microflora and microfauna, and
which spans at least three consumer trophic levels (Fig.
8). The soil microbial biomass responded significantly
to browsers at several locations, whether measured by
fumigation–extraction or SIR (Fig. 8). There were also
several instances of significant effects of browsers on
the C to N ratio of the microbial biomass (Fig. 8).
Microbial basal respiration, indicative of C mineralization rate, was less strongly influenced by browsing
mammals, with five and four locations showing significant responses in the litter and humus layers respectively (data not presented).
Analysis of the within-exclosure data across the 30
locations revealed that microbial biomass in the humus
was most closely correlated with substrate N concentration (for both the SIR and fumigation–extraction
data) while microbial biomass in the litter layer was
most closely related to substrate pH (Table 2). Microbial biomass showed little consistent relationship with
most climatic or forest stand properties across locations
(Table 2 and data not presented). Further, all microbial
parameters showed idiosyncratic responses to browsers, with both strong positive and negative effects being
detected, and with no net effect of browsers on any
microbial variable when the data from all 30 locations
were averaged (Figs. 3 and 6). The magnitude of effects
of browsing mammals on the microflora was not significantly related to the magnitude of effects of browsers on vegetation density or composition (quantified
using dissimilarity indices), or age of exclosures,
across locations. However, the response of microbial
biomass (fumigation–extraction) to browsers was highly positively correlated with the effects of browsers on
humus N concentration across the 30 sites (R2 5 0.323,
P 5 0.003).
The effects of browsing mammals on the soil microfood web were clearly multitrophic in nature for
several locations; populations of microbe-feeding and
predaceous nematodes were significantly affected by
browsers in both the humus and litter layers in nearly
half the sites (Fig. 8). There were also frequent sig-
←
exclosure]). For each location in each panel, the shaded bar is the larger of the two. Location codes correspond to Table 1.
The symbols 1, *, **, and *** indicate that the inside and outside values differ at P 5 0.10, 0.05, 0.01, and 0.001, respectively.
NA 5 statistical test not performed because samples for all replicates needed to be combined to provide sufficient humus
for analysis; ND 5 not determined.
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DAVID A. WARDLE ET AL.
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Vol. 71, No. 4
FIG. 3. Box-and-whisker plots summarizing data for the response to browsing mammals of autotrophs and components
of the decomposer food web in the litter layer for all 30 locations. The index V (Wardle 1995), determined for each response
variable for each location, becomes increasingly negative if the value is increasingly greater outside the exclosure relative
to inside it, and increasingly positive if it becomes increasingly greater inside the exclosure than outside it; the index ranges
from 21 to 11, with 0 indicating no difference. For each variable, the box encompasses the middle half of the data (values
of V) between the first and third quartiles, the bisecting line is at the value of the median, and the horizontal line outside
the box represents the typical range of data values. Asterisks indicate outlier values. P values are for paired t tests comparing
the significance of the difference between the value of the variable inside the exclosure and that outside the exclosure across
the 30 locations. For each variable, locations with values of or very close to 0 both inside and outside the exclosure are not
included.
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BROWSING MAMMALS AND DECOMPOSERS
597
FIG. 4. Density of plant species in the browse layer inside and outside of 30 browsing mammal exclosure plots. All units
are mean numbers of intercepts per 400 points (see Methods: System and sampling strategy). Only plant species with a mean
score of three intercepts either inside or outside the exclosure are included. I, inside exclosure; O, outside exclosure. For
each location in each panel, the shaded bar is the larger of the two. Location codes correspond to Table 1. The symbols 1,
*, **, and *** indicate that the inside and outside values differ at P 5 0.10, 0.05, 0.01, and 0.001, respectively. Species
abbreviations are as for Table 1 and additional ones are as follows: Ack. ros. 5 Ackama rosifolia A. Cunn.; Asp. bul. 5
Asplenium bulbiferum Forst. f.; Ast. tri. 5 Astelia trivervia Kirk; Ast. sp. 5 Astelia sp.; Ble. dis. 5 Blechnum discolor (Forst.
f.) Keys; Ble. fra. 5 B. fraseri (Cunn.) Luerssen; Ble. mon. 5 B. montanum Chambers and Farrant; Ble. nov. 5 B. novaezealandiae Chambers and Farrant; Bra. rep. 5 Brachyglottis repanda J. R. Forst. and G. Forst.; Car. arb. 5 Carmichaelia
arborea (G. Forst.) Druce; Cop. arb. 5 Coprosma arborea Kirk; Cop. cil. 5 C. ciliata Hook. f.; Cop. foe. 5 C. foetidissima
J. R. Forst and G. Forst; Cop. gra. 5 C. grandifolia Hook. f.; Cop. lin. 5 C. linariifolia Hook. f.; Cop. luc. 5 C. lucida J.
R. et G. Forst.; Cop. mic. 5 C. microcarpa Hook. f.; Cop. par. 5 C. parviflora Forst f.; Cop. pro. 5 C. propinqua A. Cunn.;
Cop. rha. 5 C. rhamnoides A. Cunn.; Cop. rot. 5 C. rotundifolia A. Cunn.; Cop. s. t. 5 Coprosma sp. (t) as in Eagle, A.;
Cop. ten. 5 C. tenuifolia Cheeseman; Cya. jun. 5 Cyathodes juniperina (J. R. Forst. and G. Forst.) Druce; Fre. bau. 5
Freycinetia baueriana Endl.; Gah. pau. 5 Gahnia pauciflora Kirk; Gen. rup. 5 Geniostoma rupestre J. R. Forst. and G.
Forst.; Heb. str. 5 Hebe stricta (Benth.); Hed. arb. 5 Hedycarya arborea J. R. Forst. and G. Forst.; His. inc. 5 Histiopteris
incisa (Thunb). J. Smith; Leu. fas. 5 Leucopogon fasciculatus (G. Forst.) A. Rich; Lyc. deu. 5 Lycopodium deuterodensum
Herter; Lyc. vul. 5 L. volubile Forst. f.; Myr. aus. 5 Myrsine australis (A. Rich.) Allan; Neo. ped. 5 Neomyrtus pedunculata
(Hook. f.); Ole. ran. 5 Olearia rani A. Cunn.; Phy. tri. 5 Phyllocladus trichomanoides D. Don; Pim. sp. 5 Pimelia sp.; Pit.
ten. 5 Pittosporum tenuifolium Sol. Ex. Gaertn.; Pol. ves. 5 Polystichum vestitum (Forst. f.); Pse. axi. 5 Pseudowintera
axillaris (J. R. et. G. Forst.); Pse. col. 5 P. colorata (Raoul) Dandy; Pse. les. 5 Pseudopanax lessonii (D. C.) C. Koch; Pse.
sim. 5 P. simplex (G. Forst.) Philipson; Rip. sca. 5 Ripogonum scandens J. R. & G. Forst.; Rub. cis. 5 Rubus cissoides A.
Cunn.; Sch. dig. 5 Schefflera digitata J. R. and G. Forst.
nificant effects of browsers on the ratio of bacterial
feeding to fungal feeding nematodes, and therefore on
the relative importance of the bacterial vs. fungal energy channels. Again the effects of browsing mammals
on all nematode variables were idiosyncratic, with no
overall significant effect of browsers on nematode populations across the 30 locations (Figs. 3 and 6). Similar
patterns were also noted for other, less numerous, soil
microfood web components, i.e., tardigrades, copepods, and rotifers (Figs. 3 and 6).
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DAVID A. WARDLE ET AL.
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FIG. 5. Density of plant species in the ground layer inside and outside of the 16 browsing mammal exclosure plots in
which a ground layer vegetation was present. All units are mean total numbers of intercepts per 100 points (see Methods:
System and sampling strategy). Only plant species with a mean score of two intercepts either inside or outside the exclosure
are included. I, inside exclosure; O, outside exclosure. For each location in each panel, the shaded bar is the larger of the
two. Location codes correspond to Table 1. The symbols 1, *, **, and *** indicate that the inside and outside values differ
at P 5 0.10, 0.05, 0.01, and 0.001, respectively. Species abbreviations are as for Table 1 and Fig. 4; additional ones are as
follows: Ble. cha. 5 Blechnum chambersii; Ble. fil. 5 B. filiforme (Cunn.) Ettingsh; Ble. flu. 5 B. fluviatile (R. Br.) Salomon;
Hym. dem. 5 Hymenophyllum demissum (Forst. f.) Swartz; Hym. dil. 5 H. dilatatum (Forst. f.) Swartz; Hym. mul. 5 H.
multifidum (Forst. f.) Swartz; Hym. san. 5 H. sanguinolentum (Forst. f.) Swartz; Hym. sp. 5 Hymenophyllum sp.; Lyc. vol.
5 Lycopodium volubile Forst. f.; Met. rob. 5 Metrosideros robusta A. Cunn.; Mic. ave. 5 Microlaena avenacea (Raoul)
Hook. f.; Phy. pus. 5 Phymatosorus pustulus (Forst. f.) Large, Braggins and Green; Unc. cla. 5 Uncinia clarata Kük; Unc.
sp. 5 Uncinia sp.; Unc. unc. 5 U. uncinata (L. f.) Kük.
Analysis of the within-exclosure data across the 30
locations found that nematode populations often
showed significant relationships with soil chemical
properties (e.g., substrate pH, N concentration, and soil
C on an areal basis), and in the case of microbe-feeding
nematodes, total annual precipitation (Table 2). However, there was no relationship between the magnitude
of effects of browsers on nematode populations and the
magnitude of effects of browsers on vegetation density,
vegetation composition, or age of exclosure across the
30 locations. However, multiple stepwise regression
analysis revealed that a significant proportion of the
total variation across the 30 locations for the effects of
browsers on nematode abundance could be explained
in terms of several other independent variables including substrate properties, tree stand characteristics and
effects of browsers on organisms of lower trophic levels (Table 3). This was especially apparent for microbefeeding nematodes in litter and predaceous nematodes
in humus, for which 50% and 64% of the total variation
could be explained, respectively.
Mesofaunal and macrofaunal responses
Browsing did not affect the abundance of enchytraeids within locations (data not presented), and across
the 30 locations there was no significant overall effect
of browsers on enchytraeid abundance (Fig. 3). However, the other groups of mesofauna (all microarthropods) showed consistent and very clear responses to
browsers (Fig. 9), regardless of trophic position. Effects of browsers on abundances of microarthropods
were negative for all but one of the 63 instances in
which a significant effect at P 5 0.05 was detected
(Fig. 9). Across the 30 locations for the within-exclosure data, all mesofaunal groups except the Mesostigmata showed significant relationships with some substrate and macroclimatic variables (Table 2), but not
with forest stand variables (data not presented). Further,
when the results were averaged over all 30 locations
the effects of browsers on microarthropod populations
were highly significant for all groups (Fig. 3). The magnitude of effects of browsers on microarthropod populations did not reflect the magnitude of effects of
November 2001
BROWSING MAMMALS AND DECOMPOSERS
599
FIG. 6. Box-and-whisker plots summarizing data for the response to browsing of components of the decomposer food
web in the humus layer, and autotrophs, for all 30 locations. See Fig. 3 legend for further explanation of plot.
browsers on vegetation density, vegetation composition, or age of exclosure across the 30 locations. However, multiple stepwise regression analysis showed that
significant amounts of variation across the 30 sites in
the effects of browsers on various microarthropod
groups could be effectively explained by macroclimatic
variables, density of browse layer vegetation inside the
exclosure, and the effects of browsers on soil chemical
properties including soil storage of C and N (Table 3).
Responses in abundance of macrofauna to browsing
mammals were similar to those of mesofauna, and
again there were consistent, and often very strong, reductions of all the dominant macrofaunal groups by
browsers (Fig. 10); all but one of the 138 effects depicted in Fig. 10 which were significant at P 5 0.05
involved reductions of abundance by browsers. For the
within-exclosure data across the 30 locations, populations of five of the eight macrofaunal groups were
significantly correlated with mean January temperature, and some also showed significant relationships
with substrate quality variables (Table 2); there were,
however, few relationships with forest stand variables
across locations. When averaged across all 30 locations, populations of all 13 macrofaunal groups tested
were significantly reduced by browsing mammals (Fig.
3), irrespective of trophic position. The magnitude of
macrofaunal population response to browsers across
the 30 locations was generally not significantly related
to the effect of browsers on browse-layer vegetation
density or composition, nor to age of exclosure. However, for eight of the most abundant macrofaunal groups
a statistically significant proportion of the variation
across the 30 locations with regard to their population
response to browsing could be explained by combinations of variables reflecting soil chemical, litter compositional, forest stand, and macroclimatic properties.
(Table 3). For the Gastropoda, Diplopoda, and Amphipoda, over 50% of the variation across locations in
terms of response to browsers could be explained by
combinations of variables such as litter properties,
browser effects on areal storage of C and N, and location altitude (Table 3).
Community dissimilarity
The community dissimilarity analyses revealed that
community structure differed significantly between inside and outside of the exclosure plots for several locations, and for five groups of organisms (plants in the
browse layer, nematodes in humus, nematodes in litter,
diplopods, and gastropods) at least 60% of all sites
showed significant differences between inside and outside the exclosure (Fig. 11). Across the 30 locations,
there were no animal groups for which community dissimilarity was significantly related to plant community
dissimilarity (Table 4). Further, dissimilarity measures
for litter species composition were not significantly re-
DAVID A. WARDLE ET AL.
600
Ecological Monographs
Vol. 71, No. 4
FIG. 7. Storage of C and N on an areal basis in the humus and litter layers inside and outside of 30 browsing mammal
exclosure plots. Symbols and legend are as for Fig. 2, and locations are arranged in the same rank order for each panel as
for Fig. 2.
lated to those for plants. However, dissimilarity indices
for litter nematodes, gastropods, and diplopods were
all significantly related to dissimilarity indices for species composition of litter across the 30 sites, and litter
nematode dissimilarity was very strongly correlated
with litter habitat dissimilarity (Table 4). Over 60% of
variation across locations with regard to dissimilarity
indices for litter could be explained by stepwise multiple regression relationships incorporating various site
variables including tree diversity at the site (Table 5).
Stepwise multiple regression relationships could also
explain .40% of the total variation across sites for
community dissimilarity for three of the faunal groups
(litter nematodes, gastropods, and diplopods) in terms
of combinations of independent variables such as litter
dissimilarity indices, soil chemical properties, tree basal area, and macroclimatic properties (Table 5).
Community diversity
In most locations browsing mammals reduced plant
diversity (Shannon-Weiner index) in the browse layer;
diversity was greater inside the exclosure than outside
for all but three locations and for half the locations the
effects were significant at P 5 0.05 (Fig. 12). However,
this trend did not occur for the ground layer vegetation
and in the majority of instances diversity in this layer
was greater outside the exclosure. Averaged across all
30 locations, diversity indices were significantly reduced by browsers for vegetation in the browse layer
but not in the ground layer (Table 5). Diversity indices
calculated for litter species, litter habitat, nematodes,
diplopods, and gastropods were also often affected by
browsers but these effects were idiosyncratic with
roughly equal numbers of cases of stimulation and reduction by browsing (Fig. 12); diversity indices were
not significantly influenced by browsing mammals for
these groups when averaged across all 30 locations
(Table 6). However, diversity indices calculated for coleopteran families and staphylinid subfamilies were,
when significantly influenced by browsers, usually
greater outside the exclosure (Fig. 12). Averaged across
all 30 locations, there was a significant increase in diversity of both these groups by browsers (Table 6).
Plant species richness responses to browsers generally
paralleled those for plant diversity indices, with a mean
reduction by browsers of species richness across all
locations of 38% in the browse layer (Table 6). Diplopod family richness was only significantly affected
by browsers for two locations (data not presented) but
when the data were averaged across locations there was
a statistically significant, although small, reduction in
richness (Table 6). Gastropod species richness was sig-
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BROWSING MAMMALS AND DECOMPOSERS
601
FIG. 8. Properties of litter and humus microfood web components (microflora and nematodes) inside and outside of 30
browsing mammal exclosure plots. FE 5 fumigation–extraction method; SIR 5 substrate induced respiration; mf 5 microbe
feeders; bf 5 bacterial feeders; ff 5 fungal feeders. Other symbols and legend are as for Fig. 2, and locations are arranged
in the same rank order for each panel as for Fig. 2.
nificantly reduced by browsers in nine locations (and
no significant positive effects of browsers were found;
data not presented), and when the data were averaged
across locations species richness was significantly re-
duced by a mean of 13% by browsing, corresponding
to a loss of 2.4 species per location (Table 6).
When the within-exclosure data for the 30 locations
was considered, diversity indices of most groups were
Ecological Monographs
Vol. 71, No. 4
DAVID A. WARDLE ET AL.
602
TABLE 2. Pearson’s correlation coefficients between soil organism biomasses (microbial data) or populations (faunal data)
and selected soil chemical and macroclimatic variables, for n 5 30 locations.
Size class
Microflora‡
Microfauna
Mesofauna
Macrofauna
Organism group
Storage
Substrate N of C in
concentra- litter (areal
Substrate pH
tion
basis)
Microbial biomass (SIR; humus)
0.148
Microbial biomass (SIR; litter)
0.437*
Microbial biomass (FE; humus)
0.282*
0.104
Microbe-feeding Nematoda
(humus)
0.433*
Microbe-feeding Nematoda
(litter)\
Predaceous Nematoda (humus) 20.536**
Predaceous Nematoda (litter)
0.164
Collembola
0.402*
Oribatida
0.333†
Mesostigmata
0.109
Protostigmata
0.419*
Gastropoda
0.327†
Isopoda
0.339†
Diplopoda
0.207
Amphipoda
0.392*
Staphylinidae (predaceous)
0.197
Araenida
0.426*
Opiliones
0.488**
Chilopoda
0.432*
0.364*
0.313†
0.662**
0.461**
0.104
20.031
20.158
20.158
0.495**
20.353*
0.279
0.541**
0.317†
0.241
0.031
0.308†
0.420*
0.134
0.161
0.380*
0.236
0.330†
0.342†
0.134
0.233
20.346*
20.427*
20.313†
0.031
20.151
20.288
20.256
20.309†
20.362*
20.100
20.256
0.248
20.371*
Mean
annual
rainfall\
20.083
20.167
0.438*
0.367*
Mean
Mean annual
January
solar
temperature radiation
20.291
20.244
0.151
0.236
0.588*** 20.045
20.242
0.205
20.126
20.137
0.077
20.167
20.154
20.122
20.104
0.187
20.262
0.031
0.000
0.054
20.430*
20.216
0.521**
0.470**
0.000
0.328†
0.408*
0.546**
0.527**
0.400*
0.242
0.482*
0.070
0.282
20.158
20.148
0.194
20.428*
0.089
20.440*
20.194
0.520**
0.459**
0.130
0.420*
0.189
0.158
0.339†
0.200
0.228
0.204
0.154
0.161
Note: Only inside-exclosure data were included in analyses.
†, *, **, *** Correlation coefficient statistically significant to 0 at P 5 0.10, 0.05, 0.01, and 0.001, respectively.
‡ SIR 5 substrate induced respiration method; FE 5 fumigation–extraction method.
\ Log-transformed variable.
TABLE 3. Results of stepwise multiple regression analysis relating the magnitude of browsing effects on soil faunal populations to external environmental factors, for n 5 30 locations.
Size class
Reduction by browsing of:†
Microfauna
Microbe-feeding Nematoda (humus)
Microbe-feeding Nematoda (litter)
Predaceous Nematoda (humus)
Predaceous Nematoda (litter)
Collembola
Oribatida
Mesostigmata
Prostigmata
Gastropoda
Isopoda
Diplopoda
Amphipoda
Staphylinidae (predaceous)
Araenida
Opiliones
Chilopoda
Mesofauna
Macrofauna
Independent variables in relationship‡
ln(ASIRH) (2)
TSH (2); DDOC (1); NOR (1)
NLI (2); TNSP (2); DMF (1)
DMIC (1); ln(RP) (2)
DNAREA (1); JULT (1); PCOV (1)
ACAREA (2); JULT (1); PCOV (1)
DNAREA (1); APHH (2)
SOLRAD (2)
DNAREA (1); ÏALTIT (2); CNLI (2)
STAREA (1); ÏALTIT ( 2)
PHHI (1); LDIS (1); ln(ANL) (2)
DCAREA (1); CNLI (2); ÏALTIT ( 2)
NHI (1); PDIS (1)
DNAREA (1); LDIS (1)
PHLI (1); SOLRAD (2)
STAREA (1); APCOV (2)
R2
P
0.236
0.504
0.641
0.348
0.463
0.445
0.541
0.323
0.596
0.458
0.522
0.596
0.262
0.345
0.358
0.422
0.006
,0.001
,0.001
0.007
0.001
20.002
,0.001
0.001
,0.001
,0.001
,0.001
,0.001
0.017
0.005
0.003
,0.001
Note: Only terms that explain a statistically significant proportion of the variation of the response variable at P 5 0.05
are included in each relationship.
† Expressed as ([population inside exclosure] 2 [population outside exclosure])/(population inside exclosure).
‡ (1) or (2) after a variable indicates a positive or negative relationship between the independent variable and the response
variable. Abbreviations are as follows: ACAREA, ANL, APCOV, APHH, ASIRH 5 absolute value of proportional reduction
by browsing, i.e., ([value inside exclosure] 2 [value outside exclosure])/[value inside exclosure] of humus C storage per
unit area, N concentration of litter, density of browse layer vegetation, humus pH, and humus SIR, respectively; ALTIT 5
altitude (meters above sea level), CNLI 5 C-to-N ratio of litter inside exclosure; DDOC, DCAREA, DMF, DMIC, DNAREA
5 proportional reduction by browsing of humus soluble C, humus C storage on an areal basis, populations of microbefeeding nematodes, humus microbial biomass (fumigation–extraction), and humus N storage on an areal basis; JULT 5 mean
July temperature (8C); LDIS 5 dissimilarity index D for plant litter species composition (inside vs. outside exclosure); NHI,
NLI 5 concentration of N (%) inside exclosure for litter and humus, respectively; NOR 5 northing (relative scale based on
latitude of site); PDIS 5 dissimilarity index D for plant species composition of browse layer (inside vs. outside exclosure);
PCOV 5 density of browse layer vegetation inside exclosure (intercepts per 200 points); PHHI, PHLI 5 pH inside exclosure
of humus and litter, respectively; RP 5 ratio of rainfall to potential evapotranspiration; SOLRAD 5 solar radiation
(mJ·m22·d21); STAREA 5 tree stem density (no./ha); TNSP 5 tree species richness per 400 m2 ; TSH 5 tree species diversity
(Shannon-Weiner diversity index).
November 2001
BROWSING MAMMALS AND DECOMPOSERS
603
FIG. 9. Populations of microarthropod groups in litter inside and outside of 30 browsing mammal exclosure plots. Symbols
and legend are as for Fig. 2, and locations are arranged in the same rank order for each panel as for Fig. 2.
significantly related to few forest stand or substrate
variables, but diversity of several groups was significantly correlated with mean January temperature (i.e.,
the Shannon-Weiner diversity values for litter species
[R2 5 0.151, P 5 0.042], staphylinid beetles [R2 5
0.257, P 5 0.005], humus nematodes [R2 5 0.144, P
5 0.033], and litter nematodes [R2 5 0.244, P 5 0.006],
and species richness for gastropods [R2 5 0.257, P ,
0.001]). Across the locations, the effects of browsers
on diversity of humus nematodes, but not of any other
faunal group, was significantly related to the response
of browse layer vegetation diversity to browsers (Table
7). Meanwhile, the effect of browsers on gastropod
diversity was significantly related to the effect of
browsers on leaf species diversity in the litter layer,
and browser effect on diplopod diversity was significantly related to browser effect on litter layer habitat
diversity (Table 7). With one exception there were no
significant correlations between the effects of browsers
on any two groups of animal taxa (Table 7). Stepwise
multiple regression revealed few relationships between
browser effects on diversity of faunal groups and independent site variables across the 30 locations. However, the magnitude of browser effects on gastropod
diversity across sites was significantly related to site
humidity (R2 5 0.339, P , 0.001), and browser effects
on coleopteran and staphylinid diversity were both significantly related to the effects of browsers on humus
C storage on an areal basis (R2 5 0.279, P 5 0.003
and R2 5 0.191, P 5 0.017, respectively). The magnitude of response of diplopod diversity to browsers
was best predicted by a multiple regression relationship
incorporating mean January temperature and the effect
of browsers on habitat diversity in the litter layer (R2
5 0.550, P , 0.001).
DISCUSSION
Plant and soil food web responses
The response of the plant community to browsing
was generally consistent with our first hypothesis;
browsing usually reduced vegetation density and often
severely reduced palatable, larger-leaved (notophyllous, sensu Raunkiaer [1934], Webb [1956]) species
causing domination by unpalatable small-leaved (nanophyllous and leptophyllous, sensu Raunkiaer [1934])
species, ferns, and ground layer monocotyledonous
plants. This is consistent with studies showing shifts
in the relative abundance of different plant functional
types following browsing in New Zealand forests (Wallis and James 1972, Jane and Pracy 1974) and elsewhere (Augustine and McNaughton 1998, Virtanen
1998). The increases in abundance of unpalatable species often observed outside the exclosures was presumably due to release from competition with palatable
species, as well as improved light levels at the ground
layer (Ritchie et al. 1998, Huisman et al. 1999, Suominen et al. 1999). Plant species with larger leaves and
604
DAVID A. WARDLE ET AL.
Ecological Monographs
Vol. 71, No. 4
FIG. 10. Populations of macrofaunal groups in litter inside and outside of 30 browsing mammal exclosure plots. Symbols
and legend are as for Fig. 2, and locations are arranged in the same rank order for each panel are as for Fig. 2.
November 2001
BROWSING MAMMALS AND DECOMPOSERS
specific leaf areas are often less well defended and have
higher nutrient concentrations when compared with
species that produce smaller, longer lived, leaves (see
Grime 1979, Coley et al. 1985, Cornelissen et al. 1999),
meaning that these larger leaved species are both more
likely to be palatable to herbivores and produce litter
of superior quality for decomposers (Cornelissen et al.
1999). The significantly lower litter layer C to N ratio
and higher humus soluble C content inside exclosures
across all 30 locations is consistent both with this trend
and with our first hypothesis, and is presumably due
to superior litter quality of those plant species dominating inside the exclosure (see Grime et al. 1996).
This effect is, however, relatively small and may therefore be insufficient to exert detectable effects on the
soil biota.
Our first hypothesis was not supported when the
components of the belowground microfood web were
considered; for each of the three consumer trophic levels (microbes, microbe-feeders, predators), as many locations showed reduction as showed stimulation by
browsers (Fig. 8). This means that, while browsing
mammals had mostly unidirectional effects aboveground, these were not necessarily matched belowground. The idiosyncratic response of microbes and
microflora to browsing mammals presumably reflects
the range of mechanisms through which browsers can
affect belowground biota and which sometimes have
directly opposite consequences (Bardgett et al. 1998b);
it is the relative balance of these mechanisms which
determines the observed response of belowground organisms. For example, dung and urine return by browsers could positively affect the belowground biota (see
Ruess and McNaughton 1987, Mulder and Ruess 1998),
while plant compositional changes (as per our hypothesis) may have the reverse effect. It is also apparent
that the effects of browsers on the soil microfood web
are tritrophic; frequently the highest trophic level (i.e.,
the predatory nematodes which occupy the tertiary consumer trophic level) responded (either positively or
negatively) to browsers when the lower ones did not,
and vice versa. This is consistent with earlier experimental and theoretical work suggesting that different
components of the soil microfood web are affected differentially by top-down vs. bottom-up forces following
manipulation of the resource base (Wardle and Yeates
1993, De Ruiter et al. 1995, Mikola and Setälä 1998).
Browsing mammals also changed the composition of
individual trophic levels within the microfood web;
frequently significant (although idiosyncratic) effects
were noted both for the microbial C to N ratio and for
the ratio of fungal feeding to bacterial feeding nematodes. This latter result indicates that browsers can induce important shifts between the bacterial-based and
fungal-based energy channels in soil food webs (see
Moore and Hunt 1988, Bardgett et al. 1998b).
All mesofaunal groups (except Enchytraeidae) and
all macrofaunal groups were consistently reduced by
605
browsing mammals. Although the direction of these
results is consistent with our first hypothesis, this is
unlikely to reflect changes in litter quality by browsers;
the soil microfood web components, which are far more
intimately associated with the resource than are most
of these organisms, did not show a unidirectional response. Further, reduction of mesofaunal and macrofaunal groups occurred even for those locations in
which browsers increased the quality of the resource
base (e.g., sites S3, S5, and S9). The consistently adverse effects of browsing mammals on these organisms
is therefore more likely to reflect the physical effects
of browsers, for example disturbance caused by trampling and scuffing. The intensity of scuffing and treading (and resultant disturbance, compaction, and reduced substrate porosity) caused by hoof pressure from
deer and goats can be considerable, and is likely much
more severe than that caused by the extinct species of
browsing moas (Duncan and Holdaway 1989). In this
context, it is significant that, when data were pooled
across all 30 locations (Fig. 3), browsers had no overall
effect on any of those faunal groups that occupy the
aqueous component of the litter layer and which are
intimately associated with the leaf substrate, and had
adverse overall effects on all free living faunal groups
that are more exposed to external environmental factors. This is consistent with studies showing that larger,
free-living, soil animals are less resistant than smaller
ones to exogenous disturbances (Wardle 1995). At
some sites, reduction of mesofaunal and macrofaunal
groups may have also resulted from effects of browsers
on plant properties allowing increased light incidence
at the ground layer (Suominen et al. 1999) and unfavorable microclimatic changes (Kielland and Bryant
1998). However, this was clearly not the case in all
instances, because some locations that demonstrated
strong responses to browsers of several faunal groups
(e.g., sites S1, S4, and S29) showed no detectable effect
of browsing on vegetation density or composition.
Across the 30 locations, we failed to find significant
relationships between the magnitude of effect of browsers on browse layer vegetation density or composition
(dissimilarity index data), and the magnitude of effect
of browsers on the abundance of any group of soil biota.
This is inconsistent with our first hypothesis. Our multiple regression analyses (Table 3) suggest that the resistance of soil biota to browsers is instead determined
by a suite of other factors. For many faunal groups,
over half of the across-location variation for the effects
of browsers on their densities could be explained by
combinations of other site-based factors such as belowground nutrient status, macroclimate, forest stand
properties, and the responses of lower trophic levels
and nutrients to browsers. This is consistent with previous studies indicating that habitat characteristics
(e.g., nutrient status of the system, C availability, macroclimate) can determine the resistance, and other components of stability, of populations and biomasses of
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BROWSING MAMMALS AND DECOMPOSERS
organisms in a wide range of ecological communities
(McNaughton 1985, De Angelis 1992, Closs and Lake
1994, Wardle 1998, McCauley et al. 1999).
Community dissimilarity
Browsing mammals strongly affected the dissimilarity of communities inside vs. outside exclosures for
several locations and for all groups of organisms considered. However, there was no evidence that the community dissimilarity of any faunal group was significantly related to plant community dissimilarity across
the 30 locations, in direct contrast to the predictions
of our second hypothesis. Dissimilarity indices for
three litter-dwelling animal groups were instead significantly correlated with dissimilarity indices for litter
composition across the locations, suggesting that
browsing mammals can alter community composition
of some faunal groups through altering community
composition of litter in the litter layer. This implies a
level of specificity of resources for the component organisms of these three groups. All three faunal groups
that showed this relationship are mainly either microbefeeders or microbidetritivores. Different types of litter
support different communities of microorganisms
(Widden 1986, Carreiro and Koske 1992) and litterdwelling fauna which feed on microbes (in particular
fungi) show distinct feeding specificity (Visser and
Whittaker 1977, Klironomas et al. 1992). Further, as
was the case for the belowground faunal population
data, community dissimilarity inside vs. outside exclosures for these three groups was highly significantly
related to combinations of various site variables (Table
5), indicating that site factors also govern resistance of
belowground animals to browsing mammals at the
community level.
The second hypothesis did not hold because, while
browser effects on community structure of some belowground faunal groups were related to browser effects on the composition of their habitat in the litter
layer across the 30 locations, the magnitude of browser
effects on litter species composition clearly did not
reflect the magnitude of browser effects on plant community composition. The effect of browsers on litter
compositional dissimilarity inside vs. outside exclosures was instead strongly related to other, independent
site variables (Table 5). Browsing mammals clearly induced changes in the community composition of dead
leaves in the litter layer, and these effects must have
ultimately resulted from changes in the composition of
607
aboveground vegetation; the absence of a link between
the two with regard to the magnitude of dissimilarity
across locations can only be explained by the magnitude of browsing-induced effects either on aboveground production (and hence litterfall), or on litter
quality and associated decomposition rates of resident
litter, also differing across locations.
Community diversity
There were large shifts in plant diversity due to
browsing mammals, consistent with our third hypothesis. These effects were usually negative, although a
small subset of locations did show significant increases
in plant diversity in the ground layer. Several earlier
studies have detected enhanced plant diversity due to
aboveground mammalian herbivory, particularly in
grasslands (Zeevalking and Fresco 1977, Collins et al.
1998) probably through a reduction in competitive exclusion (Grace and Jutila 1999), an increased incidence
of inedible plant species (Milchunas et al. 1988), and
disturbance effects (Olff and Ritchie 1998). However,
in nutrient-poor ecosystems, diversity may reduce grazing because limited resources prevents vegetation regrowth after grazing (Pandey and Singh 1991, Proulx
and Mazumder 1998). Our exclosure sites were probably quite nutrient poor in relation to those used for
most other comparable studies (for our 30 locations,
C-to-N ratios in the litter layer ranged from 30 to 108
and in the humus layer from 16 to 46), and may be
within the range for which browsing would be expected
to reduce diversity (Proulx and Mazumder 1998). Further, unlike other exclosure studies, New Zealand forests did not evolve in the presence of the browsing
mammals being investigated, and the extinct megaherbivores (moas) would not have exerted effects of
comparable intensity (McGlone and Clarkson 1993).
Plant species of New Zealand’s forests may therefore
not have evolved to thrive under high mammalian
browsing pressure, such as is the case for other floras
(Westoby 1989).
We found that the magnitude of effect of browsing
mammals on diversity of only one animal group, humus-dwelling nematodes, was significantly correlated
with the magnitude of effect of browsers on browselayer vegetation diversity across the 30 locations. Reduction of browse-layer plant species richness was
matched by reduced richness of gastropod species and
diplopod families across all 30 sites, but the magnitude
of reduction of richness of these animal groups was
←
FIG. 11. Community dissimilarity indices for various groups of organisms (including litter), indicating degree of dissimilarity of community structure inside vs. outside browsing mammal exclosure plots. For each panel, locations are arranged
in order of decreasing dissimilarity between inside and outside exclosure for plant species in the browse layer. Location
codes correspond to Table 1. The symbols 1, *, **, and *** indicate that community structure differs significantly between
inside and outside the exclosure at P 5 0.10, 0.05, 0.01, and 0.001, respectively, as determined by paired t tests on principal
axes derived by Principal Components Analysis (see Methods: Statistical analyses). ND 5 not determined; N 5 no ground
layer vegetation present.
Ecological Monographs
Vol. 71, No. 4
DAVID A. WARDLE ET AL.
608
TABLE 4. Pearson’s correlation coefficients between different groups of taxa (including plant litter) with regard to the
community dissimilarity index D calculated for inside vs. outside exclosures, across n 5 30 locations.
Dissimilarity index (inside vs. outside exclosure) for:
Dissimilarity
index (inside
vs. outside
exclosure) for:
Plants
(browse
layer)
Litter
(leaf
species)
Litter (leaf species)
Litter (habitat diversity)
Nematoda (humus)
Nematoda (litter)
Gastropoda
Diplopoda
Staphylinidae
Coleoptera
20.270
0.047
0.152
0.223
0.058
0.050
20.093
0.037
ND†
0.110
0.398*
0.401*
0.371*
0.161
0.162
Litter
(habitat
diversity)
Nematoda Nematoda
Staphylini(humus)
(litter) Gastropoda Diplopoda
dae
20.021
0.570***
0.236
0.148
0.183
0.290
0.116
0.160
0.077
0.344
0.224
0.148
0.094
0.157
0.148
0.442*
0.601***
0.460*
0.167
0.178
0.870***
Note: Dissimilarity indices were calculated using families for Nematoda, Diplopoda, and Coleoptera; subfamilies for
Staphylinidae; and species for Gastropoda.
*, **, *** Correlation coefficient is significantly different from 0 at P 5 0.05, 0.01, and 0.001, respectively.
† Not determined on the basis of representing a spurious correlation.
not correlated with the magnitude of reduction of plant
species richness across locations. The level of reduction of gastropod species richness by browsers was
comparable to that observed by Suominen (1999) for
a series of browsing mammal exclosures in Scandinavia. Our finding that the magnitude of response to
browsing of gastropod and diplopod diversity was correlated with the magnitude of browser effects on leaf
litter species diversity or litter layer habitat diversity
across all exclosures is consistent with earlier studies
showing microarthropod diversity to be influenced by
microhabitat diversity (Anderson 1978, Sulkava and
Huhta 1998). Even though browsing mammals reduced
vegetation diversity in the browse layer across all 30
locations, diversity of both coleopteran subfamilies and
staphylinid subfamilies was enhanced by browsers (Table 6). Given that taxonomic richness of these groups
was not affected by browsers, this means that browsers
consistently reduced the population sizes of some taxa
in these groups more than others. In most instances,
our third hypothesis was not supported because the
magnitude of effects of browsers on vegetation diversity across the 30 locations did not correlate with the
magnitude of browser effects on soil animal diversity.
This is probably in part because effects of browsers on
plant diversity did not cause corresponding predictable
shifts in habitat diversity. These results are consistent
with the findings of Wardle et al. (1999) that loss of
plant species from a plant community can either cause
increases or decreases in the diversity of soil organisms, depending on the plant species removed, and suggests that different plant species may have substantially
different effects on overall belowground habitat diversity (Hooper et al. 2000).
Soil processes
In contrast to our fourth hypothesis, browsing mammals did not consistently reduce C mineralization (litter
TABLE 5. Multiple regression relationships relating values of the dissimilarity index D (calculated for determining dissimilarities of community structures inside vs. outside exclosures)
for various taxa (including plant litter) to external environmental variables, across n 5 30
locations.
Dependent variables
Independent variables in relationship†
R2
P
Litter (leaf species)
Litter (habitat)
Humus Nematoda (families)
Litter Nematoda (families)
Gastropoda (species)
Diplopoda (families)
TSH (1); CNHI (2); PCOV (1)
TSH (1); ÏALTIT ( 2); BASAR (2)
SIR (2)
ln(RP) (2); ACNL (2); LDISH (1)
ln(RAIN) (2); SOLRAD (2); LDIS (1)
DCLAREA (1); BASAR (2)
0.650
0.621
0.210
0.575
0.531
0.407
,0.001
,0.001
0.014
,0.001
,0.001
0.001
Notes: Only terms that explain a statistically significant proportion of the variation of the
response variable at P 5 0.05 are included in each relationship. Coleopteran and Staphylinid
relationships are not presented because no relationships were significant at P 5 0.05.
† (1) or (2) after a variable indicates a positive or negative relationship between the independent variable and the response variable. Abbreviations are as for Table 3; additional ones
include: ACNL 5 absolute value of proportional reduction by browsing of litter CN ratio;
BASAR 5 tree basal area (m2/ha); CNHI 5 C-to-N ratio of humus inside exclosure; DCLAREA
5 proportional reduction by browsing of litter C storage on an areal basis; LDIS, LDISH 5
dissimilarity index (inside vs. outside exclosure) for litter leaf species community structure
and litter habitat, respectively; RAIN 5 mean annual precipitation (mm); SIR 5 humus SIR
inside exclosure.
November 2001
BROWSING MAMMALS AND DECOMPOSERS
609
FIG. 12. Diversity indices for various groups of organisms (including litter) inside and outside of 30 browsing mammal
exclosure plots. Symbols and legend are as for Fig. 2, but, for each panel, locations are arranged in order of decreasing
effect of browsers on the diversity of plants in the browse layer (calculated as [(diversity inside exclosure) 2 (diversity
outside exclosure)]/[diversity inside exclosure]).
TABLE 6.
Ecological Monographs
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DAVID A. WARDLE ET AL.
610
Diversity of plants, litter, and soil biota inside and outside exclosure plots, averaged across all 30 locations.
Shannon-Weiner diversity index
Richness
Biota
Inside
Outside
t value
P
Inside
Outside
t value
P
Plant species (browse layer)
Plant species (ground layer)
Leaf litter species
Litter habitat diversity
Nematode families (humus)
Nematode families (litter)
Gastropod species (litter)
Diplopod families (litter)
Staphylinid subfamilies (litter)
Coleopteran families (litter)
1.97
0.89
1.89
1.29
2.16
2.12
2.58
1.32
2.26
2.35
1.29
0.88
1.80
1.19
2.14
2.05
2.56
1.33
2.47
2.58
5.92
0.08
1.50
1.45
0.47
1.16
0.45
0.22
4.33
4.12
,0.001
0.935
0.144
0.145
0.643
0.254
0.653
0.824
,0.001
,0.001
6.45
2.36
5.46
ND
15.3
14.4
19.0
5.11
8.04
12.4
3.99
2.36
5.51
ND
14.9
13.8
16.6
4.80
7.98
12.4
5.77
0.01
0.18
ND
0.86
1.58
5.47
2.97
0.56
0.20
,0.001
0.989
0.861
ND
0.396
0.125
,0.001
0.006
0.581
0.841
Notes: The t values were determined using paired t tests with n 5 30 locations (i.e., 29 df) except for the plant species
(ground layer) in which only the 14 locations with a vegetated ground layer present were used. ND 5 not determined.
and humus respiration); indeed, relatively few locations
showed significant effects and the overall effect of
browsers across the 30 locations was not significant.
Earlier studies have shown that browsing effects on C
and N mineralization can be negative (e.g., Pastor et
al. 1988, 1993; see also Ritchie et al. 1998), positive
(e.g., McNaughton et al. 1988, Kielland et al. 1997),
or neutral (e.g., Molvar et al. 1993, Burke et al. 1999),
probably because of the varied ways in which browsers
may affect soil organisms, especially those in the soil
microfood web (Bardgett et al. 1998b and this study).
In this light, we also found no consistent effect of
browsing mammals on litter or humus C and N storage
on an areal basis. Although there were strong statistically significant effects at several locations, these effects were idiosyncratic, again pointing to a range of
mechanisms with opposing effects on net soil C and N
sequestration. These mechanisms involve the effects of
browsers on both soil biological properties and plant
species composition. There is evidence that forest plant
species can differ tremendously in their effects on belowground soil C and N storage (Binkley and Giardina
1998, Finzi et al. 1998) and it is conceivable that dif-
ferent plant species which are eaten out by deer and
goats across sites vary in their effects on storage of C
and N.
Conclusions
Our study failed to entirely support any of our four
hypotheses, indicating that while the mechanisms proposed by Pastor et al. (1988, 1993) may have applied
in some locations they clearly did not in others, and
when the data was averaged across all 30 locations
there was little support for these hypotheses at least
with regard to belowground processes and mechanisms.
Although browsing mammals had generally predictable
effects aboveground, browser effects on the soil microfood web and soil processes were idiosyncratic, and
the directions of effects were presumably governed by
the balance of different mechanisms by which browsers
can potentially influence the belowground system (see
Bardgett et al. 1998b). The unidirectional response of
the litter mesofauna and macrofauna to browsing, although consistent with our hypotheses, is more likely
to reflect physical effects of browsers than browsinginduced shifts in resource quality.
TABLE 7. Pearson’s correlation coefficients between taxa (including plant litter) with regard to browsing effects on the
Shannon-Weiner diversity index, across n 5 30 locations.
Effect of browsing on diversity index of:
Effect of browsing on
diversity index of:
Litter (leaf species)
Litter (habitat diversity)
Nematoda (humus)
Nematoda (litter)
Gastropoda
Diplopoda
Staphylinidae
Coleoptera
Plants
(browse
layer)
20.055
0.245
0.466**
0.120
0.167
20.061
20.127
0.050
Litter
(leaf
species)
ND†
0.153
0.042
0.369*
20.071
0.028
20.100
Litter
(habitat Nematoda Nematoda
Staphylinidiversity) (humus)
(litter)
Gastropoda Diplopoda
dae
20.255
0.190
0.250
20.574***
20.088
20.033
0.004
0.185
0.279
0.187
0.079
20.052
20.120
0.127
0.205
0.087
0.169
20.162
0.183
20.129
0.511**
Notes: For each taxonomic group the data are expressed as ([diversity index inside exclosure] 2 [diversity index outside
exclosure])/[diversity index inside exclosure]. Diversity indices were calculated using families for Nematoda, Diplopoda,
and Coleoptera; subfamilies for Staphylinidae; and species for Gastropoda.
*, **, *** Correlation coefficient is significantly different from 0 at P 5 0.05, 0.01, and 0.001, respectively.
† Not determined on the basis of representing a spurious correlation.
November 2001
BROWSING MAMMALS AND DECOMPOSERS
Finally, our study enabled us to evaluate the effects
of an introduced functional group of organisms on the
structure and function of indigenous communities in
which that group was previously absent. Only a handful
of studies have considered how alien organisms affect
key properties of indigenous communities and ecosystems (i.e., invasive plants, Vitousek and Walker 1989;
invasive invertebrates, Beggs and Rees 1999, Carroll
and Hoffmann 2000). As a result of its very recent
colonization by humans, New Zealand presents an opportunity, unparalleled in most parts of the world, for
investigating ecological consequences of introduced
alien organisms. Our results demonstrate that the introduction of deer and goats to New Zealand forests
has caused far-ranging but often unpredictable effects
at both the community- and ecosystem-level of resolution, with particularly adverse effects for indigenous
plant communities and populations of most groups of
litter-dwelling mesofauna and macrofauna.
ACKNOWLEDGMENTS
We thank the following people for information enabling us
to relocate exclosure plots, for accompanying us on some of
our field trips, or for help in sampling and backpacking soil
and litter from the field: Peter Abbott, Phil Alley, Nils Anthes,
Bruce Burns, Larry Burrows, David Byers, Alison Evans,
John Gow, Sean Husheer, Merilyn Merrett, Juha Mikola,
Claire Newell, Marcy and Rory Rowe, Bianca Ryburn, Karl
Schasching, Mark Smale, Cam Speedy, and John von Tunzelman. John Leathwick provided the macroclimate data for
the thirty locations and Bianca Ryburn, Moira Dexter, and
Kate Orwin provided laboratory assistance. Anouk Wanrooy
prepared the illustrations and Peter Bellingham, Bruce Burns,
and Claire Newell assisted with plant identifications. The
New Zealand Department of Conservation is acknowledged
for providing permits for us to sample most of these exclosures and for providing accommodation in several instances.
The Rakiura Maori Land Trust gave us permission to sample
the Stewart Island exclosures. Rob Allen, Peter Bellingham,
Claire de Mazancourt, Christa Mulder, Duane Peltzer, J. M.
Blair, and two anonymous reviewers provided helpful comments on earlier versions of this manuscript. This work was
supported by the New Zealand Marsden Fund and the National Foundation for Research, Science, and Technology.
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