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ORIGINAL PAPER
‘Invasional meltdown’: evidence for unexpectedconsequences and cumulative impacts of multispeciesinvasions
W. Ian Montgomery • Mathieu G. Lundy •
Neil Reid
Received: 29 June 2011 / Accepted: 19 November 2011 / Published online: 1 December 2011
� Springer Science+Business Media B.V. 2011
Abstract Empirical support for ‘invasional melt-
down’, where the presence of one invading species
facilitates another and compounds negative impacts
on indigenous species, is equivocal with few convinc-
ing studies. In Ireland, the bank vole was introduced
80 years ago and now occupies a third of the island.
The greater white-toothed shrew arrived more recently
within the invasive range of the bank vole. We
surveyed the abundance of both invasive species and
two indigenous species, the wood mouse and pygmy
shrew, throughout their respective ranges. The nega-
tive effects of invasive on indigenous species were
strong and cumulative bringing about species replace-
ment. The greater white-toothed shrew, the second
invader, had a positive and synergistic effect on the
abundance of the bank vole, the first invader, but a
negative and compounding effect on the abundance of
the wood mouse and occurrence of the pygmy shrew.
The gradual replacement of the wood mouse by the
bank vole decreased with distance from the point of
the bank vole’s introduction whilst no pygmy shrews
were captured where both invasive species were
present. Such interactions may not be unique to
invasions but characteristic of all multispecies com-
munities. Small mammals are central in terrestrial
food webs and compositional changes to this
community in Ireland are likely to reverberate
throughout the ecosystem. Vegetation composition
and structure, invertebrate communities and the pro-
ductivity of avian and mammalian predators are likely
to be affected. Control of these invasive species may
only be effected through landscape and habitat
management.
Keywords Impacts � Interspecific competition �Island populations � Invasional meltdown � Multiple
invasions � Small mammal community
Introduction
‘Invasional meltdown’ (Simberloff and Von Holle
1999) describes the phenomenon where one non-
indigenous species facilitates the invasion of another
and compounds their independent impacts on native
species, communities and ecosystems. In reviewing
the concept of invasional meltdown, Simberloff
(2006) noted a lack of conclusive evidence and ‘‘a
particular dearth of proven instances in which two
invasive species enhance the impact and/or probability
of establishment and spread of the other’’. Where
systematic and experimental studies have been con-
ducted there is evidence of complex interactions
involving introduced and native predators. For exam-
ple, Adams et al. (2003) report enhanced invasion by
bullfrogs due to the presence of introduced fish which
W. I. Montgomery (&) � M. G. Lundy � N. Reid
School of Biological Sciences, Queen’s University
Belfast, Belfast BT9 7BL, Northern Ireland, UK
e-mail: [email protected]
123
Biol Invasions (2012) 14:1111–1125
DOI 10.1007/s10530-011-0142-4
increased tadpole survival due to predation on native
dragonfly nymphs.
Commensal rats and mice (Rodentia: Muridae) are
amongst the most common and detrimental of invasive
mammals, especially on islands (Courchamp et al.
2003; Borroto-Paez 2009; Harris 2009; Simberloff
2009). Non-commensal small mammals are less
frequently recorded as invaders (Courchamp et al.
2003; Borroto-Paez 2009; St Clair 2011). Moreover,
as non-commensal species are likely to be less
detectable than commensal species, the process of
invasion may only become apparent many years after
initial introduction.
We present data from Ireland on the invasion of two
non-commensal small mammal species where the
range of the more recent invader falls entirely within
that of the other. Hence, three geographical areas have
been formed: (1) indigenous species only, (2) indig-
enous plus one invading species and (3) indigenous
plus two invading species, allowing the investigation
of a potential invasional meltdown (Simberloff and
Von Holle 1999).
The bank vole Myodes glareolus (Schreber 1780)
was introduced into Ireland from Germany probably in
the late 1920s (Stuart et al. 2007), expanding its range
steadily to occupy roughly the south-western third of
the island. The greater white-toothed shrew Crocidura
russula (Hermann 1780) was first discovered in
Ireland during 2007 (Tosh et al. 2008). It has a limited
range within that of the bank vole and can occur at
high abundance and both species are now common
within the regurgitated pellets of birds of prey (Tosh
et al. 2008) indicating major changes have occurred in
the small mammal community recently. Due to the
size of its initial range it seems likely that the greater
white-toothed shrew was present in Ireland for more
than a decade prior to its discovery. In an Irish context,
it is particularly difficult to establish the status of
mammals that are perceived as ‘native’ due to
uncertainties and complications of (natural) reinva-
sion after the last glacial maximum (Yalden 1999;
Warren 2007; Searle 2008). It seems likely that the
wood mouse Apodemus sylvaticus (Linnaeus 1758)
and the pygmy shrew Sorex minutus (Linnaeus 1766)
arrived in Ireland during the same period as human
colonisation approximately 8,000 years before present
(Preece et al. 1986; McCormick 1999). Nevertheless,
species that colonised pre-1500 AD are generally
considered indigenous (Marnell et al. 2009) having
had sufficient time to integrate into the ecosystem and
become integral components, in this case, important
prey and predator species. All four species of small
mammal are habitat generalists and occupy field
boundaries the predominant habitat in lowland farm-
land (Harris and Yalden 2008).
Early ecological studies involving the bank vole
and wood mouse where they co-occur naturally e.g. in
Great Britain (Kikkawa 1964; Tanton 1969; Crawley
1970) and mainland continental Europe (Mermod
1969; Bergstedt 1965; Birkan 1968) as well as in
Ireland (Fairley and Jones 1976; Smal and Fairley
1981, 1982; Meehan 2005), give little consideration to
interactions between species. However, they indicate
interspecific differences in habitat associations (Evans
1942; Southern and Lowe 1968; De Jonge and Dienske
1979), trophic biology (Watts 1968; Hansson 1971;
Holisova and Obrtel 1980) and activity patterns
(Miller 1955; Kikkawa 1964; Greenwood 1978).
These studies lead to the hypothesis, that in Ireland,
there should be no interaction between invasive bank
voles and wood mice. However, Fasola and Canova
(2000) indicated that there was a population level,
negative asymmetry in the interaction between the
bank vole and wood mouse based on a removal
experiment designed to test the hypothesis that
interspecific competition occurs between these species
perhaps exposing a weakness of conventional, small-
scale, observational studies. There are few comparable
studies involving the greater white-toothed shrew and
pygmy shrew but the known biology of these primarily
insectivorous species (Fons 1972; Grainger and
Fairley 1978; Bever 1983; Meharg, Montgomery and
Dunwoody 1990), the former being approximately
three times larger than the latter (Harris and Yalden
2008), again gives little indication of any strong
interspecific interaction. Comparisons of allopatric
and sympatric populations of soricid shrews, however,
suggest differences consistent with interspecific com-
petition (Ellenbroek 1980). More pertinently, with
reference to invasional meltdown, the literature pro-
vides no indication whether the presence of the bank
vole and greater white-toothed shrew together should
have any greater impact on the wood mouse and/or
pygmy shrew than either in isolation. However,
Leisenjohann et al. (2011) presented evidence from
experimental manipulations in which the common
shrew Sorex araneus Linnaeus 1758 effected changes
in the behaviour of the bank vole through predation of
1112 W. I. Montgomery et al.
123
pups and competitive interference dependent on
environmental conditions.
We investigated to what extent the concurrent
invasions of Ireland by two small mammal species are
advantaged by the presence of the other and to what
extent their impacts on ‘indigenous’ species are
cumulative. In addition to focussing on interspecific
effects, we examine a range of habitat and landscape
parameters, controlling for variation in prevailing
environmental conditions, which permits conclusions
to be drawn with respect to the process and impacts of
invasion on a landscape scale. Specifically, we test the
hypotheses that (1) the presence of a second invading
species enhances the abundance and potential for
further invasion by another non-native species and (2)
the presence of a second invasive species is more
detrimental to indigenous species in terms of their
abundance than the presence of a single non-native
species. We demonstrate that the negative effects of
invasive species may be strong, even where no impact
was expected, and are cumulative with multiple
invasions resulting in native species replacement or
local extinction.
Methods
Species presence and relative abundance
Field work was conducted in the south-western third of
Ireland, principally in counties Offaly, Laois, Kil-
kenny, Waterford, Tipperary, Limerick and Cork
(Republic of Ireland) with some additional work in
county Down (Northern Ireland). Standard trap lines
comprised of two lethal, metal, snap traps (SelfSet
55 9 110 mm), baited with 0.5 g of soft cheese.
SelfSet traps are highly efficient in catching small
mammals (Phillips and East 1961; Grainger and
Fairley 1978) whilst soft cheese is a suitable bait for
omnivorous rodents and insectivores (Montgomery
and Montgomery 1989; Montgomery unpublished
data). The latter caught a January maximum of 24
pygmy shrews per 100 trap nights whilst Grainger and
Fairley (1978) recorded a winter peak of 34 pygmy
shrews per 100 trap nights using dead meal worms.
This difference may be due to habitat or year but it is
not thought to be important in the present context
where we do not estimate absolute population size.
Here, we calculate relative abundance to make
comparisons within species between areas with and
without invasive species. Each trap line consisted of
two traps at 10 sampling points separated by 10 m
intervals (i.e. 20 traps over 100 m). Traps lines were set
in the south-west 1 km square in each 10 km square
based on the standard Irish grid system. If grid squares
were inaccessible, the next available 1 km square with
road access within the same 10 km square was chosen.
Traps were left in situ for 24 h to cover one complete
cycle of diurnal and nocturnal activity. Trap lines
started adjacent to rural buildings and were set in
hedgerows of \2 m wide. Trap density was approxi-
mately 1 per 10 m2 presenting a trapping effort
substantially higher than that invested in most con-
ventional trapping grids (usually two traps per point on
a 10 9 10 m grid yielding a density of 1 per 50 m2).
All field work was conducted during late autumn and
winter 2010/2011 and was restricted to field bound-
aries, the most prevalent habitat available to all four
study species. Trapping methods were, therefore,
consistent between all three areas studied. Trap data
were expressed as the presence or absence and their
relative abundance i.e. numbers caught of each species.
Defining invasive species ranges
The initial objective was to establish the current range
of the bank vole and greater white-toothed shrew over
a large geographical area. Thus, a total of
165 9 10 km squares were surveyed in a grid strad-
dling the last known boundary of the bank vole range
established in 2002 (Telfer et al. 2005a) whilst also
including the last known boundary of the greater
white-toothed shrew range established in 2008 (Tosh
et al. 2008; Fig. 1a). The point of introduction for the
bank vole was taken as Foynes, Co. Limerick during
the late 1920s (Stuart et al. 2007). The distribution of
the bank vole west of the River Shannon (counties
Clare and Galway) was not investigated as this
represented a smaller part of the species’ range and
the River Shannon was deemed a significant barrier to
dispersal. Hence, expansion of the species in the west
constituted a disparate invasion which may be pro-
ceeding at a different rate from that over the majority
of the species’ range. Furthermore, there was no
evidence that the greater white-toothed shrew
occurred west of the River Shannon and hence this
area was not useful in testing the idea of ‘invasional’
meltdown.
Invasional meltdown in a small mammal community 1113
123
The ranges of both invasive species were defined
using a minimum convex polygon to enclose all
presence records determined by the Animal Move-
ments extension for Arcview 3.3 (ESRI, California,
USA). Due to the absence of data west of the River
Shannon during 2010, the north-western boundary was
interpolated by buffering the invasion front during
2002 by the mean distance which the range had
expanded by 2010 in the direction for which data were
available i.e. east and north-east. The area of the range
of each species was calculated in km2 using the Xtools
extension for Arcview 3.3.
The approximate rate of range expansion of the
bank vole since introduction was the taken as the
maximum distance between Foynes and the furthest
record during 2010/2011 divided by 83.5 years (i.e.
assuming June 1927 as the date of introduction). The
point of introduction for the greater white-toothed
shrew was unknown (Tosh et al. 2008). Centroid
analysis was performed using the Animal Movements
extension to determine the centre of the greater white-
toothed shrew range, weighted by the density of all
known records (i.e. those in Tosh et al. 2008 plus the
current study). This was taken as its putative point of
introduction assuming a uniform rate of expansion
since establishment. However, as the date of intro-
duction was also not known there was insufficient data
available to allow a reliable estimate of range expan-
sion to be calculated.
Environmental parameters
A suite of potential confounding factors were col-
lected during trapping (Table 1) including altitude
(elevation above sea level) and the prevailing weather
conditions in the previous 12 h recorded on an ordinal
scale including temperature (very cold \ 0�C, cold
\ 5�C or mild [ 5�C), rainfall (heavy rain, light rain
or no rain), ground conditions (very wet, wet or damp)
and cloud cover (complete, partial or none). Data on
the percentage illumination of the moon’s disc were
acquired from http://aa.usno.navy.mil/data/docs/Moon
Fraction.php.
Habitat variables were also recorded (Table 1)
including estimated height of nearby trees, hedgerow
height and hedgerow width (±0.5 m). The time since
the last hedgerow cut was also estimated (at annual
intervals from 0 to 3 years). Hedgerow species
richness was estimated for both trees and ground flora
(species poor, average or species rich). Field bound-
aries were recorded as the presence or absence of a
bank or wall, verge or ditch.
Landscape variables (Table 1) were derived from
CORINE datasets (EEA 2000) to describe the prev-
alence of five common land cover types (Arable,
Bog, Broad-leaved woodland, Coniferous planta-
tions and Pasture). Each trap line was buffered to
250, 500, 750 m, 1 and 2 km and the percentage
cover of each landscape type estimated using
Fig. 1 a The bank vole
range (grey shading) during
2002 (Telfer et al. 2005a)
and the greater white-
toothed shrew range
(diagonal hatching) during
2008 (Tosh et al. 2008)
showing the placement of
1 km sample squares (opensquares) at the south-west
corner of each 10 km gridsquare within which traplines were set during winter
2010/2011. The point of
introduction for both species
is also shown (star symbols).
b The updated range
boundaries of both species
during 2010
1114 W. I. Montgomery et al.
123
the Patch Analyst 4 extension for Arcview 3.3.
Landscape structure (Table 1) was described at
the same five spatial scales in terms of habitat
‘patchiness’ using the density of habitat patch
edge boundaries, roughly analogous to hedgerow
density.
Table 1 Explanatory variables used to model small mammal relative abundance or occurrence
Variable type Variable name Units Description
Species Woodmouse N Relative abundance (i.e. numbers caught) of Apodemus sylvaticus
Pygmy shrew N Occurrence (presence and absence) and relative abundance (i.e. numbers caught)
of Sorex minutus
Bank vole N Relative abundance (i.e. numbers caught) of Myodes glareolus
GWTS N Relative abundance (i.e. numbers caught) of the greater white-toothed shrew
Crocidura russula
Confounding
variables
Altitude M Elevation above sea level derived from a Digital Elevation Model of Ireland
Dist from intro km Shortest distance in kilometres of each trapline from the point of introduction for
the bankvole (Foynes, Co. Clare) or greater white-toothed shrew (taken as
5 km north-east of Dundrum, Co. Tipperary)
% Moon % Percentage illumination of the moons disc
Weather Index A single Principal Component Axis accounted for 77.2% of variance in weather
patterns recorded during trap nights (Eigenvalue = 3.088) and was positively
correlated with temperature (r = 0.945), rainfall (0.857), ground conditions
(0.878) and cloud cover (0.831)
Habitat Hedgerow
maturity
Index Principal Component Axis #1 accounted for 33.8% of variance in habitat
variables collected in the field (Eigenvalue = 3.167) and was positively
correlated with tree height (r = 0.660), hedge height (0.874), hedge width
(0.868) and the estimated time since last hedgerow cut (0.875)
Verge spp.
richness
Index Principal Component Axis #2 accounted for 16.3% of variance in habitat
variables collected in the field (Eigenvalue = 1.467) and was positively
correlated with the presence of a verge (r = 0.692) and the species richness of
ground flora (0.731) and trees (0.559)
Field boundary
type
Index Principal Component Axis #3 accounted for 13.1% of variance in habitat
variables collected in the field (Eigenvalue = 1.177) and was positively
correlated with the presence of banks and walls (r = 0.797) and negatively
correlated with the presence of ditches (-0.718)
Landscape
composition
Arable % Area of land defined as annual crops associated with permanent crops or non-
irrigated arable land expressed as a percentage of the total area within a buffer
surrounding each trapline at five different spatial scales: 250, 500, 750 m, 1
and 2 km
Bog % Area of land defined as peat bog, moor, heath or inland marsh expressed as a
percentage of the total area within a buffer surrounding each trapline at five
different spatial scales: 250, 500, 750 m, 1 and 2 km
Broad-leaved % Area of land defined as broad-leaved deciduous woodland expressed as a
percentage of the total area within a buffer surrounding each trapline at five
different spatial scales: 250, 500, 750 m, 1 and 2 km
Coniferous % Area of land defined as evergreen coniferous plantations expressed as a
percentage of the total area within a buffer surrounding each trapline at five
different spatial scales: 250, 500, 750, 1 and 2 km
Pasture % Area of land defined as pasture expressed as a percentage of the total area within
a buffer surrounding each trapline at five different spatial scales: 250, 500,
750 m, 1 and 2 km
Landscape
structure
Edge density m/ha The density of habitat patch boundaries within a buffer surrounding each trapline
at five different spatial scales: 250, 500, 750 m, 1 and 2 km calculated using
the ArcGIS extension Patch Analyst 4
Landscape variables were obtained from the CORINE land cover map 2000 (EEA 2000) using ArcGIS 10 (ESRI, California, USA)
Invasional meltdown in a small mammal community 1115
123
Trap out capture
To define the range of the invasive species, trapping
was restricted to a single night potentially biasing
estimates of relative abundance as the probability of
capture may have differed between species due to
variation in proportions of individuals in the popula-
tion that are more or less sedentary. A standard trap
line methodology was used as before but trapping
occurred over five consecutive nights with traps being
checked each morning. Twenty such trap lines were
set in each of the three geographical zones: (1)
indigenous species only, (2) indigenous plus one
invading species and (3) indigenous plus two invading
species. Replication was achieved by dividing the 20
standard trap lines equally into two 10 km squares at
two sites (North and South, respectively) within each
zone respectively: (a) Adare/Foynes, County Limerick
(R4549, R3841; R2933, R4345), (b) Cashel, County
Tipperary (R9297, R3840; S0913, S4553) and c)
Seaforde, County Down (J3739, J3338; J3739, J4045).
Removal data involving closed populations typi-
cally follow a negative exponential curve until all
animals are removed (Otis et al. 1978). Where
populations are open, as in the current study, they
comprise resident and non-resident animals. The latter
are generally transient animals that are dispersing
through a trap line or adjacent neighbours which were
previously resident elsewhere but expand their range
when the original residents of a trap line have been
removed. Such animals are hard to discriminate. For
the purposes of the current study we considered
individuals caught prior to the first day on which no
animals were caught as ‘resident’. Individuals caught
after the first day on which no animals were caught
were considered ‘transient’, representing dispersing
individuals or near neighbours moving into the trap
line. Estimates of the percentage of animals that were
considered resident and transient were subsequently
used to adjust the relative abundance data from the
165 9 1 km squares trapped previously so that the
total number of animals (both resident and transient)
could be estimated within the three zones of invasion.
Statistical analyses
Principal Components Analysis (PCA) was used to
summarise categorical variables describing related
variables into a reduced set of 4 axes (Table 1).
Variance in the relative abundance of the bank vole,
greater white-toothed shrew and wood mouse was
examined using separate Generalized Linear Models
(GLM) assuming a Poisson error distribution with a
logarithmic link function fitting the numbers of each
species caught as the dependent variable in each case.
Predictor variables included PCA derived variables,
habitat parameters and landscape composition and
structure (Table 1). The spatial scale at which each of
the landscape variables operated was selected by
building univariate models for each variable at each
spatial scale (Lundy and Montgomery 2010). The
single best explanatory scale for each variable was
taken as the model with the lowest Akaike Information
Criterion (AIC; Akaike 1983; Burnham and Anderson
2002). For both invasive species, the distance from
their respective points of introduction was also fitted
as a covariate. Only grid squares within the respective
ranges of each species were used for model construc-
tion. To test for interspecific effects, the relative
abundances of all other small mammal species were
also fitted as covariates. All two-way interaction
factors were included in models.
The pygmy shrew occurred at \10% of sites with
one individual per trap line, in all but one instance.
Thus, a GLM assuming a Binomial error distribution
with a logit link function was constructed where the
dependent variable was presence or absence of the
pygmy shrew. The pygmy shrew did not occur within
the range of the greater white-toothed shrew and,
therefore, could not exhibit any relationship with the
relative abundance of the latter per se but it was
evidently negatively affected by its presence. Thus,
the abundance of the greater white-toothed shrew was
excluded from the model and replaced with a two-
level factor (called GWTS range) which defined each
trap line as either within or outside the range of the
greater white-toothed shrew. All other variables were
fitted in the same manner as in the models for the other
species.
Prior to model fitting, all predictor variables that
occurred at \10% of trap lines were removed.
Remaining variables were tested for multicollinearity
using ordinary least squares regression to ensure that
all tolerance values were [0.1 and all variance
inflation factor values were\10.0 (Quinn and Keough
2002). Variables that were collinear were removed by
excluding one of a pair of bivariates (rs C 0.5) which
1116 W. I. Montgomery et al.
123
possessed the lowest correlation coefficient (rs) with
the dependent variable in each case (Booth et al.
1994). To allow the direct comparison of regression
coefficients, variables were standardized to have a �x ¼0 and a r = 1 prior to analysis. All possible model
permutations were created and ranked using AIC
values. The Akaike weight (wi) of each model was
calculated within the top set of N models, where the
value of delta AIC(Di) B 2 units (Burnham and
Anderson 2002). The Akaike weight of each model
is the relative likelihood of that model being the best
within a set of N models. To calculate the relative
importance of each variable relative to all other
variables, theP
wi of all models within the top set of
models that contained the variable of interest was
calculated and the variables ranked byP
wi
(McAlpine et al. 2006); the larger the value ofP
wi
(which varies between 0 and 1), the more important
the variable. Multimodel inference and model aver-
aging was used to determine effect sizes (b coefficient)
of each variable across the top set of models (Burnham
and Anderson 2002). Variables that had equalP
wi
values were ranked in order of the magnitude of their
model averaged regression coefficients.
The relative abundance of each species was exam-
ined over five consecutive trap nights using a Repeated
Measures Mixed Model assuming an autoregressive
error structure at a lag of 1 night (AR1) fitted using the
Residual Maximum Likelihood (REML) procedure.
The total numbers of each species were fitted as the
dependent variables in each case and for the wood
mouse the estimated numbers of residents and tran-
sients. Replicate area (North and South) and trap line
ID (1–10) were fitted as random factors. The three
invasion zones: (1) indigenous species only, (2)
indigenous plus one invading species and iii) indig-
enous plus two invading species (Area), trap night
(1–5) and their interaction (Area*Trap night) were
fitted as fixed factors. Non-significant interactions
were subsequently removed.
Variance in the adjusted estimates of total numbers
and numbers of residents and transients for wood
mouse was examined using a GLM assuming a
Poisson error distribution with a logarithmic link
function.
All statistical analyses were performed using
GenStat v10 and SPSS v 18.
Results
A total of 286 bank voles, 18 greater white-toothed
shrews, 215 wood mice and 16 pygmy shrews were
captured during the first survey. The mean number of
animals caught per trap line per night was 3.28 animals
(range 0–11). This left approximately 16 (80%) traps
unoccupied at each trap line ensuring that differential
activity patterns between the species did not result in
trapping bias where one species might have entered
the traps non-randomly thus occupying them and
denying access to others (Liu and Yip 2003; Pascal
et al. 2009).
The range of the bank vole was estimated to cover
approximately 32,700 km2 during winter 2010/2011,
accounting for 38.7% of Ireland (Fig. 1b). The max-
imum distance between the point of introduction and
the furthest record during 2010/2011 was 148 km.
Given a putative introduction date during the late
1920s (Stuart et al. 2007), the mean rate of range
expansion was estimated at 1.79 km-year. The range of
the greater white-toothed shrew was estimated to
cover approximately 1,000 km2 during 2007/08 (Tosh
et al. 2008). We estimated the species range to cover
approximately 2,300 km2 during winter 2010/2011,
accounting for 3.3% of the total land area of the island
(Fig. 1b). Centroid analysis suggested a putative point
of introduction 5 km north-east of Dundrum, North
Tipperary (Fig. 1b), assuming constant rate of radial
dispersal from a single introduction.
The relative abundance of the bank vole was
associated negatively with that of wood mouse, pygmy
shrew and, most notably, their interaction (Fig. 2a).
Conversely, the relative abundance of the greater
white-toothed shrew was associated positively with
relative abundance of wood mouse (Fig. 2b). The
relative abundance of the wood mouse was associated
negatively with numbers of bank vole (Fig. 2c). The
presence of the pygmy shrew was associated nega-
tively with the presence of the greater white-toothed
shrew and bank vole (Fig. 2d). No pygmy shrews were
caught within the range of the greater white-toothed
shrew but 16 were caught outside its range predom-
inantly along or beyond the margins of the distribution
of the bank vole. This is reflected in the percentage
occurrence of the pygmy shrew in the three geograph-
ical areas studied (Fig. 3a). Most notably, the
Invasional meltdown in a small mammal community 1117
123
occurrence of the bank vole was elevated significantly
in the presence of the greater white-toothed shrew
(Fig. 3a). Moreover, the relative abundance of the
bank vole was negatively associated with distance
from its introduction point (Fig. 2a). Specifically, its
relative abundance was greatest within 90 km of the
point of introduction with about 2–3 animals caught
per trap line but declined steadily toward the invasion
front where \0.5 animals were caught per trap line
(Fig. 3b). Wood mouse numbers were lowest in close
proximity to the point of bank vole introduction with
on average 0.5 animals per trap line but increased
rapidly, near and beyond, the bank vole invasion front
to [ 3 animals per trap line (Figs. 2a, 3b) representing
a six fold reduction in the relative abundance of the
wood mice in areas where there had been prolonged
contact with the bank vole. Moreover, the percentage
occurrence of the wood mouse was greatest in the area
of indigenous species only; significantly lower in the
area of indigenous plus one invading species; and,
significantly lower again in the area of indigenous plus
two invading species (Fig. 3a).
The relative abundance of the bank vole and
occurrence of the pygmy shrew were associated
positively with field boundary type (PC3), specifically
the presence of banks and walls and the absence of
GWTSWeather PC1
AltitudeBroad-leaved (2km)
Vegetation PC2Bankvole*Pygmy shrew
% moonPygmy shrew
Vegetation PC1Edge density (250m)
Arable (2km)Pasture (2km)
Vegetation PC3Coniferous (2km)
Bog (750m)Bankvole
-0.304 ± 0.116**
-0.326 ± 0.111***
-0.278 ± 0.120**-0.160 ± 0.073*
-0.225 ± 0.118*
-0.166 ± 0.084
0.149 ± 0.0780.133 ± 0.074
-0.135 ± 0.2130.085 ± 0.075
-0.265 ± 0.266
-0.028 ± 0.096
0.073 ± 0.075
-0.036 ± 0.079
0.037 ± 0.077
0.034 ± 0.077
∑wi
Edge density (2km)Weather PC1
Coniferous (2km)GWTS
Bog (2km)Altitude
Arable (500m)Vegetation PC2
Woodmouse*GWTSVegetation PC1Vegetation PC3
Pasture (2km)Pygmy shrewWoodmouse
Broad-leaved (2km)Dist from intro
% moonWoodmouse*Pygmy shrew
-0.356 ± 0.072***-0.643 ± 0.223**
-0.242 ± 0.069***-0.234 ± 0.089**-0.230 ± 0.080**
0.205 ± 0.072**-0.099 ± 0.118
0.125 ± 0.063*0.121 ± 0.069
-0.080 ± 0.087-0.057 ± 0.066
-0.067 ± 0.107
-0.058 ± 0.084-0.036 ± 0.080
0.025 ± 0.056
-0.032 ± 0.136
-0.015 ± 0.0950.009 ± 0.063 Edge density (750m)
Coniferous (2km)
Weather (PC1)
Altitude
Bankvole
Arable (500m)
Vegetation PC1
Pasture (250m)
Dist from Intro
Vegetation PC2
Woodmouse
Bog (250m)
Broad-leaved (2km)
Vegetation PC3
% moon
-0.531 ± 0.291
-0.607 ± 0.407*
-0.851 ± 0.501
-0.736 ± 0.655
0.499 ± 0.233*
0.146 ± 0.349
-0.044 ± 0.426
1.680 ± 1.140
0.688 ± 0.578
0.341 ± 0.829
0.184 ± 0.466
-0.420 ± 0.608
0.026 ± 0.4780.127 ± 0.403
0.356 ± 0.528
0.0 0.2 0.4 0.6 0.8 1.0
0.0 0.2 0.4 0.6 0.8 1.0 0.0 0.2 0.4 0.6 0.8 1.0
0.0 0.2 0.4 0.6 0.8 1.0
Vegetation PC1
Weather PC1
Broad-leaved (2km)
Vegetation PC2
Woodmouse
Bog (2km)
Pasture (250m)
% moon
Altitude
Edge density (2km)
Bankvole
Vegetation PC3
Arable (250m)
Coniferous (1km)
GWTS range
-5.990 ± 3.070
Factorial
-0.797 ± 0.270**
0.758 ± 0.218***
-0.648 ± 0.257*
0.586 ± 0.197*
0.405 ± 0.218-0.266 ± 0.160
0.225 ± 0.286
-0.184 ± 0.218
0.038 ± 0.179
-0.083 ± 0.190
0.132 ± 0.195
0.011 ± 0.107
0.014 ± 0.175
∑wi
(a)Bank vole relative abundance (n=133) (b) Greater white-toothed shrew abundance (n=27)
(c)Wood mouse relative abundance (n=165) (d) Pygmy shrew occurrence (n=165)
Fig. 2 Relative importance of explanatory variables in explain-
ing variation in the relative abundance of a bank voles, b greater
white-toothed shrews (GWTS) and c wood mouse and d the
occurrence of pygmy shrews. Variables are ranked in order of
the sum of their Akaike weights (P
wi) within the top set of
models i.e. models with DAIC B 2. Black bars indicate those
variables that were retained in the best single approximating
model (i.e. that with the lowest AIC value) and grey barsindicate variables included in all other models within the top set
1118 W. I. Montgomery et al.
123
ditches, whereas the relative abundances of the greater
white-toothed shrew and the wood mouse were asso-
ciated negatively with the same feature (Fig. 2a–d).
Overall, landscape variables at the larger spatial scales
were generally more important in explaining variation
in the relative abundance and occurrence of small
mammals than ground-truthed habitat parameters. The
relative abundance of the bank vole was associated
positively with the area of pasture within a 2 km buffer
(Fig. 2a) whereas the relative abundance of the wood
mouse and occurrence of the pygmy shrew were
negatively associated with the same feature and the
area of arable within a 2 km buffer (Fig. 2c, d). Both
indigenous species were associated positively with
habitat patch edge density and associated negatively
with landscapes dominated by coniferous plantations
(Fig. 2c, d). The relative abundance of the wood
mouse was significantly lower in areas where bog was
prevalent within a buffer of 750 m (Fig. 2c). Weather
conditions had little effect on the capture of any
species but the illumination of the moon had a strong
negative effect on the numbers of both invasive
species caught (Fig. 2a, b).
The total numbers of bank vole and wood mice
caught differed significantly over a period of five trap
nights (Table 2) with greatest numbers being caught
on night one with a subsequent decline (Fig. 4). There
was no significant change in the total numbers of
greater white-toothed shrew caught over the 5 trap
nights. For the wood mouse only, the number of animals
determined as resident and transient, also differed
significantly over the 5 trap nights and between the
three geographical areas (Fig. 4) as demonstrated by
the significant interaction of Area*Trap night
(Table 2). In general, numbers of transient wood mice
increased over the five trap nights (Fig. 4) and there
was a significantly greater proportion of transients
caught in the area of indigenous species plus one
invasive species i.e. bank vole only than in either the
indigenous species only or indigenous species plus
two invasive species i.e. bank vole plus greater white-
toothed shrew (Table 3). There was no significant
difference in the number of bank voles caught between
either area in which it occurred (Table 2; Fig. 4).
There were no patterns in the timing of captures of the
pygmy shrew but overall numbers were significantly
reduced in areas with invasive species, being com-
pletely absent from areas with two invasive species
(Table 2; Fig. 4). Invasive species had a significant
negative and cumulative effect on the estimate of
the total numbers of wood mice (Fd.f=2,162 = 8.29,
P \ 0.001), and a negative effect on numbers of
residents (Fd.f=2,162 = 7.25, P \ 0.001; Fig. 5). Num-
bers of transient wood mice were significantly
greater in the presence of bank vole than where
there were no invasive species or where there were two
(Fd.f=2,162 = 8.65, P \ 0.001; Fig. 5).
(a)
(b)
Species
Bank v
ole
GWTS
Woo
d m
ouse
Pygm
y shr
ew
% o
ccu
rren
ce ±
s.e
.
0
20
40
60
80
100
* * **
Fig. 3 a Percentage occurrence ± s.e. of each small mammal
species within the ranges of (i) indigenous species only (whitebars), (ii) indigenous plus one invasive species (light grey bars)
and (iii) indigenous plus two invasive species (dark grey bars)
where stars represent total absence and b the relationship
between the mean relative abundance (numbers caught) ± s.e.
of bank vole and wood mouse against distance from the point of
introduction for the bank vole (divided into ten discrete distance
categories of equal width)
Invasional meltdown in a small mammal community 1119
123
Discussion
This study provides convincing evidence of invasional
meltdown (Simberloff and Von Holle 1999). We show
that the negative effects of invasive species can be
very strong, even where no impact was expected, due
to interspecific differences in ecology and behaviour
(Evans 1942, Miller 1955, Watts 1968), and are
cumulative bringing about species replacement and
local extinction. In this case, species replacement was
slow and incomplete with respect to the effect of the
bank vole on the wood mouse but rapid and complete
with respect to the combined effect of the bank vole
and the greater white-toothed shrew on the pygmy
shrew. Most notably, the greater white-toothed shrew,
being the second invader, had a positive and syner-
gistic effect on the abundance of the first invader i.e.
the bank vole, but a negative and compounding effect
on the abundance of the wood mouse and occurrence
of the pygmy shrew. Such interactions conform to the
invasional meltdown model. However, the presence of
both negative and positive interspecific effects sug-
gests that such interactions may not be characteristic
of invasions alone but of all multispecies communi-
ties. For example, similar landscape and habitat effects
(e.g. Andrews and O’Brien 2000; Orrock et al. 2000;
Panzacchi et al. 2010) and negative interspecific
interactions (e.g. Fox and Fox 2000; Eccard and
Ylonen 2003; Morris 2005) have been revealed in well
established small mammal communities.
Confining the current study to one habitat (farmland
hedgerows) during a single period in the annual
population cycle within 1 year avoided confounding
influences in the interpretation of the results, but
leaves open the issue of whether gradual species
replacement will continue and eventually be complete
across the full range of habitats occupied by both
indigenous species. The wood mouse and pygmy
shrew occupy, not only farmland, but also woodland,
rough grassland, dry and wet heath and uplands \1,000 m above sea level (Harris and Yalden 2008).
Whilst field margins of enclosed farmland in Ireland
comprise[80% of the land area (EEA 2000) and is the
most prevalent habitat available to small mammals,
the contribution of the wider landscape to abundance
(Huitu et al. 2003; Nupp and Swihart 2000; Panzacchi
et al. 2010) makes it difficult to predict the effects of
invasion in other habitats which may be more or less
favourable depending on species preferences. Com-
plete replacement may never be effected if the
invading species either do not invade less prevalent
habitats or if the outcome of species interactions is
Table 2 Generalized estimating equation of small mammal
relative abundance (total numbers caught) on five consecutive
trap nights (a–d) with area (indigenous species only,
indigenous plus one invasive species and indigenous plus two
invasive species) and trap night fitted as fixed factors
Model Variables Wald v2 df P
(a) Bank vole Area 0.13 1,194 0.724
Trap night 23.02 4,194 \0.001
(b) GWTSa Trap night 0.58 4,94 0.680
(c) Wood mouse Area 35.19 2,285 \0.001
Trap night 6.63 4,285 \0.001
Area*Trap night 4.75 8,285 \0.001
(i) Residents Area 26.57 2,285 \0.001
Trap night 23.08 4,285 \0.001
Area*Trap night 9.73 8,285 \0.001
(ii) Transients Area 7.99 2,285 \0.001
Trap night 6.65 4,285 \0.001
Area*Trap night 3.71 8.285 \0.001
(d) Pygmy shrew Area 9.12 2.247 \0.001
Trap night 1.00 4.45 0.418
Wood mouse (c) was also split between those that were determined as (i) resident or (ii) transienta The GWTS was restricted to only one species range; thus range was not fitted for this species
1120 W. I. Montgomery et al.
123
habitat specific (Kelt et al. 1995; Fox and Fox 2000;
Smith and Quinn 1996). Further research is needed
to resolve the impact of the bank vole and greater
white-toothed shrew in other habitats. There was no
indication that there was any more propensity for
commensalism among greater white toothed shrews
(Harris and Yalden 2008) than other species in the
current study perhaps reflecting differences in den-
sity or rural buildings in Ireland compared to
continental Europe.
The gradual replacement of the wood mouse by the
bank vole decreased with distance from the point of
introduction and the disparate habitats supporting the
former have not halted the protracted process of
replacement. Trapping over a period of five nights
suggested that the replacement of the wood mouse was
equivocal: overall numbers were not significantly
different between areas with indigenous species only
and those areas with the bank vole but not the greater
white-toothed shrew. Whilst resident wood mice were
Rel
ativ
e ab
un
dan
ce ±
s.e
.
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
Rel
ativ
e ab
un
dan
ce ±
s.e
.
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
Rel
ativ
e ab
un
dan
ce ±
s.e
.
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
0.0
0.1
0.2
0.3
0.4
0.5
0.6
1 2 3 4 5 1 2 3 4 5
1 2 3 4 5
1 2 3 4 5 1 2 3 4 5
1 2 3 4 50.0
0.2
0.4
0.6
0.8
1.0
1.2
(a) Bank vole (b) Greater white-toothed shrew
(c) Wood mouse (d) Pygmy shrew
(e) Wood mouse i) Residents ii) Transients
Fig. 4 Mean relative abundance of small mammals (total
numbers caught) ± s.e. on five consecutive trap nights a–d with
wood mouse; e split between those that were determined as
(i) resident or (ii) transient. Ranges are defined as (i) indigenous
species only (black circles), (ii) indigenous plus one invasive
species (light grey triangles) and (iii) indigenous plus two
invasive species (dark grey squares)
Invasional meltdown in a small mammal community 1121
123
impacted negatively, the percentage of transient
individuals in the overall population increased where
the bank vole was present. Thus, the wood mouse may
have changed its behaviour in the presence of the bank
vole which may affect survival and hence population
dynamics indirectly (Adler and Levins 1994; Boinski
et al. 2005; Vibe-Petersen et al. 2006). Nevertheless,
overall landscape factors may prevent the complete
replacement of the wood mouse in the presence of the
bank vole where the greater white-toothed shrew has
yet to colonise.
The mechanisms whereby invasive species impact
or replace indigenous species are many and varied and
the outcome may be subtle (King et al. 2011). There
may be direct interspecific competition for limited
resources or interference competition (Probert and
Litvaitis 1996, Bohn et al. 2008, Stokes et al. 2009;
Leisenjohann et al. 2011). For example, it is possible
that similarity in diet provides a basis for competition
for food resources between the bank vole and wood
mouse, and the greater white-toothed shrew and
pygmy shrew (Watts 1968; Hansson 1971; Fons
1972; Grainger and Fairley 1978; Holisova and Obrtel
1980; Bever 1983; Meharg et al. 1990). Indeed, such is
the dependency of both rodent species on inverte-
brates, especially arthropods during the summer, that
diffuse competition (Pianka 1974) amongst all four
species may play a role in determining species
interactions. Disease and parasites have also been
implicated in species replacements including those
involving rodents (Rushton et al. 2000; Torchin et al.
2003; Telfer et al. 2005a; Bell et al. 2009). This may
well be relevant with respect to the bank vole and
wood mouse as both share pathogens that may
undermine host survival and reproduction (Telfer
et al. 2002; Telfer et al. 2005b). It is possible that the
introduction of the bank vole may also expose naive
wood mice to one or more novel pathogens not
previously found in Ireland (Stuart and Sleeman
2006).
Our findings have much wider implications for
ecosystem change than compositional shifts in small
mammal communities alone (Wardles et al. 2011).
Rodents and insectivores are central in grassland and
woodland food webs. They consume fungi, flowers,
seeds and seedlings and prey upon invertebrates whilst
they are, in turn, the main food source for generalist
and specialist avian and mammalian predators.
Although there is overlap in trophic biology of the
four species studied, they are not ecological equiva-
lents. For example, the bank vole feeds more on green
plant material than the wood mouse whilst it is
considerably more active during diurnal periods. The
greater white-toothed shrew has a body mass approx-
imately three times larger than the pygmy shrew
making them poor ecological equivalents. Hence, the
gradual replacement of the indigenous Irish species
may have major consequences at the ecosystem level.
The introduction of the bank vole and greater
white-toothed shrew into Ireland has led to concurrent,
Table 3 Summary of the capture success for wood mouse
over a period of five consecutive trap nights in each of three
areas: (i) indigenous species only, (ii) indigenous plus one
invasive species and (iii) indigenous plus two invasive species
Range % of Residents
caught on night
1 ± SD (n)
% of Total
captures that
were transients
± SD (n)
(i) Indigenous
species only
71.3 ± 28.7 (20) 33.2 ± 25.8 (20)
(ii) Indigenous
plus one invading
species
56.7 ± 40.4 (3) 78.3 ± 36.9 (10)
(iii) Indigenous
plus two invading
species
53.7 ± 9.1 (12) 37.0 ± 46.0 (17)
Total Residents Transients
Ad
just
ed a
bu
nd
ance
± s
.e.
0
1
2
3
4
5
6
a
b bb
aa
a
a
b
Fig. 5 Mean abundance ± s.e. for the total, resident and
transient numbers of wood mice per standard trap line for trap
night 1 adjusted by the total cumulative number caught over trap
nights 1–5 within the ranges of (i) indigenous species only
(white bars), (ii) indigenous plus one invasive species (light greybars) and (iii) indigenous plus two invasive species (dark greybars). Significant differences within each category and species
(total, resident and transient) are shown using different
superscript letters
1122 W. I. Montgomery et al.
123
overlapping invasions on a geographical scale that
have resulted in a major reduction in relative abun-
dance of the wood mouse and the local extinction of
pygmy shrew where both invasive species occurred
together. Furthermore, the synergistic relationship of
two invading species compounds their impacts on
indigenous communities supporting the invasional
meltdown model. Invasive mammals are already
affecting the unique assemblage of endemic lineages
that comprise the Irish mammal fauna (Reid and
Montgomery 2007; Reid 2010). In contrast to the
impact of invasive species such as muntjac deer or
grey squirrel which have more constrained habitats
such as woodland, the ongoing invasion of the bank
vole and greater white-toothed shrew in Ireland is
likely to be widespread as agricultural land mostly
with hedgerows as field boundaries comprises 80% of
the land area. Often, the ecological impacts and
economic costs of introduced species, especially those
on islands, become apparent only after many decades
and remain hidden until it is too late to address their
adverse effects adequately (e.g. White and Harris
2002). Eradication of rodents on islands has been
demonstrably successful in recent years (Veitch and
Clout 2002) but widely established, smaller mammal
species on larger islands may prove more difficult than
controlled interventions for larger and less abundant
invasive species with more restricted distributions e.g.
muskrat in Ireland (Fairley 1982) or coypu in Britain
(Gosling and Baker 1987). Control of invasive small
mammals and their impacts may only be effected
through long-term landscape and habitat management
wherein habitats which support native species are
preferentially enhanced to provide suitable refugia
from the interspecific impact of invaders. It is
important that this means of mitigation is implemented
as soon as possible in the process of invasion and that
management prescriptions are applied in areas not yet
invaded.
Acknowledgments Dr. Neil Reid was supported by the
Natural Heritage Research Partnership (NHRP) between the
Northern Ireland Environment Agency (NIEA) and Quercus,
Queen’s University Belfast (QUB). Dr. Mathieu Lundy was
supported by The National Parks and Wildlife Service,
Department of Arts, Heritage and the Gaeltacht (Republic of
Ireland). Licences to trap pygmy shrews (a protected species)
were issued by the National Parks and Wildlife Service,
Department of Arts, Heritage and the Gaeltacht (Republic of
Ireland) and the Northern Ireland Environment Agency,
Department of Environment (United Kingdom). We are
grateful to Dr. Sally Montgomery who provided invaluable
assistance in the field, whilst thanks also go to the farmers and
landowners of Ireland for their goodwill, interest and
hospitality. We are also grateful to Derek Yalden for
comments on an early draft of the manuscript and to two
anonymous referees for their contributions in improving the
final publication.
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