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1
LRH: Loveridge, Wearn, Vieira, Bernard and Ewers 2
RRH: Logging Facilitates Invasion of Small Mammals 3
4
5
6
Movement behaviour of native and invasive small mammals shows
logging may 7
facilitate invasion in a tropical rainforest 8
9
Authors: Robin Loveridge* (1) (2), Oliver R. Wearn (1)(3),
Marcus Vieira (4), Henry Bernard 10
(5) and Robert M. Ewers (1). 11
12
(1) Department of Life Sciences, Imperial College London,
Silwood Park Campus, Buckhurst 13
Road,
Ascot, Berkshire, SL5 7PY, UK 14
(2) BirdLife International Cambodia Programme, #2, Street 476,
Toul Tompung 1, 15
Chamkarmon, P.O. Box 2686, Phnom Penh, Cambodia 16
(3) Institute of Zoology, Zoological Society of London, Regent’s
Park, London, NW1 4RY, 17
UK 18
(4) Departamento de Ecologia, Instituto de Biologia,
Universidade Federal do Rio de Janeiro, 19
Caixa Postal 68020, 21941-902, Brazil 20
(5) Universiti Malaysia Sabah, Institute for Tropical Biology
and Conservation, Sabah, 21
Malaysia 22
23
24
* Corresponding author: Robin Loveridge
([email protected])
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Received ____; revision accepted ___ . 1
Abstract 2
Invasive species pose one of the greatest threats to
biodiversity. This study investigates the 3
extent to which human disturbance to natural ecosystems
facilitates the spread of non-native 4
species, focusing on a small mammal community in selectively
logged rainforest, Sabah, 5
Borneo. The microhabitat preferences of the invasive Rattus
rattus and three native species 6
of small mammal were examined in three-dimensional space by
combining the spool-and-line 7
technique with a novel method for quantifying fine-scale habitat
selection. These methods 8
allowed the detection of significant differences for each
species between the microhabitats 9
used compared with alternative, available microhabitats that
were avoided. Rattus rattus 10
showed the greatest preference for heavily disturbed habitats
and, in contrast to two native 11
small mammals of the genus Maxomys, R. rattus showed high levels
of arboreal behaviour, 12
frequently leaving the forest floor and travelling through the
under and mid-storey forest 13
strata. This behaviour may enable R. rattus to effectively
utilize the complex three-14
dimensional space of the lower strata in degraded forests, which
is characterized by dense 15
vegetation. The behavioural flexibility of R. rattus to operate
in both terrestrial and arboreal 16
space may facilitate its invasion into degraded forests. Human
activities that generate heavily 17
disturbed habitats preferred by R. rattus may promote the
establishment of this invasive 18
species in tropical forests in Borneo, and possibly elsewhere.
We present this as an example 19
of a synergistic effect, whereby forest disturbance directly
threatens biodiversity, and 20
indirectly increases the threat posed by invasive species,
creating habitat conditions that 21
facilitate the establishment of non-native fauna. 22
23
Key words: Invasion, synergistic effects, Rattus rattus,
selective logging, habitat preference, 24
arboreality. 25
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3
1
VAST AREAS OF THE REMAINING NATURAL FOREST IN SE ASIA EXIST IN A
LOGGED 2
AND DISTURBED STATE. In Borneo and Sumatra, for example, 46
percent and 72 percent of 3
natural forest is degraded, respectively (Margono et al. 2012,
Gaveau et al. 2014). Within the 4
Malaysian state of Sabah, Borneo, less than 2 percent of the
remaining lowland forests 5
remain undisturbed, mostly in just a few sites making up a total
of 700 km2 (Reynolds et al. 6
2011). With the vast majority of forests existing in an altered
state, it is essential for 7
conservation to understand the processes that drive community
change in modified 8
landscapes (Hansen et al. 2001, Meijard & Sheil 2007).
Despite this we still have only a 9
rudimentary mechanistic and theoretical understanding of why
these changes in biological 10
communities occur, and the possible role that invasive species
may play (Stokes et al. 2009). 11
In particular, synergistic effects between threat processes,
such as between logging and 12
biological invasion, or biological invasion and the spread of
disease (Wells et al. 2014a, 13
Wells et al. 2014b), have been poorly explored in tropical
forests thus far, but have the 14
potential to increase the extinction risk of native species
(Brook 2006). 15
16
Small mammals play a key role in biological communities, acting
as both seed 17
predators and dispersers (Asquith et al. 1997, Wells &
Bagchi 2005, Wells et al. 2009). 18
Small mammals are also important prey items for large avian and
mammalian predators 19
(Puan et al. 2011, Wilting et al. 2006). Changes in the
abundance of this functionally 20
important group in altered forests may cause cascading effects
on other trophic levels 21
(Grassman et al. 2005). Native rodent species may be
particularly threatened by the invasion 22
of the black rat, Rattus rattus (Stokes et al. 2009; Gibson et
al. 2013). Rattus rattus is now 23
spread over most of the world (Amori & Clout 2003), and when
it has invaded native habitats 24
on islands it has led to well-documented extinctions of native
bird fauna (Atkinson 1985, 25
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4
Barnett 2001), disruption to nutrient transport and soil
fertility (Fukami et al. 2006) and 1
carbon sequestration (Wardle et al. 2007). The multiple
ecological effects that cascade from 2
the invasion of R. rattus places a premium on understanding how
those invasions occur in 3
order to limit the future spread of this species. 4
5
In Borneo, R. rattus was traditionally thought to be restricted
to urban areas (Payne 6
and Francis 1985). However, R. rattus has been recently observed
in a small number of 7
primary and secondary tropical forests of northern Borneo (Wells
et al. 2006b, Cusack et al. 8
2014) and detected in the oil palm plantation matrix surrounding
the forests examined in this 9
study (Cusack 2011). Although this species has not been
systematically surveyed across 10
Borneo, the limited data available suggest it is not yet
ubiquitous in natural forest areas 11
(Nakagawa et al. 2007, Wells et al. 2007, Bernard et al. 2009,
Charles & Ang 2010). This 12
provides a unique opportunity to examine the niche overlap of R.
rattus with native species at 13
a relatively early stage in the invasion process. 14
15
Previous survey work has demonstrated that the occurrence of R.
rattus increases 16
along a gradient from undisturbed to heavily disturbed forest
(Cusack et al. 2014). Here, we 17
build on this work by examining whether logging facilitates the
invasion of R. rattus into 18
tropical forests by investigating their movement behaviour and
microhabitat selection at 19
small spatial scales. Our hypothesis is that the invasive R.
rattus has a stronger preference for 20
heavily disturbed forest microhabitat compared to native small
mammals, hence logging 21
disturbance creates favorable microhabitats for the
establishment of R. rattus in tropical 22
forests. 23
24
25
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5
We compare the habitat preferences of the invasive R. rattus
with three native species 1
of small mammals regarding (1) vertical space use, (2)
preference for more (or less) disturbed 2
forest microhabitats, and (3) preference for moving along and
through particular substrates 3
associated with forest disturbance. To effectively quantify a
species’ habitat preference, 4
habitat measurements must be made at the spatial scale at which
the species makes habitat 5
selection choices (Manly et al. 2002). We were able to study
fine-scale microhabitat 6
preference using the spool-and-line technique (Miles et al.
1981, Boonstra & Crane 1986), as 7
it allows even very subtle route choices to be quantified (Wells
et al. 2006, Harris et al. 8
2006). In addition, we employed a novel matching methodology to
establish actual preference 9
for microhabitats, comparing used vs. control microhabitats.
10
11
METHODS 12
13
STUDY SITE AND SPECIES.- The study was conducted within the
Stability of Altered Forest 14
Ecosystems (SAFE) project site in Sabah, Malaysian Borneo (Ewers
et al. 2011). Small 15
mammal trapping was carried out in a 7200 ha area of
repeatedly-logged forest, with high 16
spatial variation in levels of forest disturbance. The
continuous forest of the SAFE project 17
area is connected to a large (> 1 million ha) area of similar
forest to the north, and is 18
otherwise surrounded by an oil palm plantation matrix. 19
20
The four study species belong to the Muridae family (rats and
mice). Native species 21
included the red spiny rat (Maxomys surifer), a widespread
generalist species with a 22
characteristic red pelage, Whitehead’s rat (Maxomys whiteheadi),
classified as Vulnerable on 23
the IUCN red list (IUCN 2014), and the long-tailed giant rat
(Leopoldamys sabanus). We 24
compared these species to the newly-invading black rat (Rattus
rattus). Ear tissue samples 25
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6
were taken from all individuals and stored in 95% alcohol. MtDNA
sequencing of the Rattus 1
species confirmed that it was a member of the Rattus rattus
species complex (sensu Aplin et 2
al. 2011, Pagès et al. 2010) based on both cytochrome b and CO1
gene sequences (M. Pagès, 3
pers. comm.). 4
TRAPPING AND TRACKING INDIVIDUALS.- Three trapping grids were
established at locations 5
that encompass a gradient of logging intensity and forest
modification. Grids were located 6
more than a kilometre from the forest edge and were all
connected by continuous forest. 7
Trapping was conducted for three months between May and July of
2012. Traps were 8
checked in the morning and captured individuals belonging to the
four study species were 9
anaesthetized using diethyl ether and a small fur clip was made
dorsally between the shoulder 10
blades. A spool was then attached to the under-fur using
acrylamide gel (Loctite). Spools 11
were made of nylon quilting cocoons and weighed between 1 and
2.5 g, extending over 12
distances of 100 to 200 m (Danfield Ltd). Spools were wrapped in
a thin layer of cling-film, 13
followed by a layer of electrical tape to prevent snagging on
vegetation. The weight of 14
spools was adjusted to less than five percent of the
individual’s body weight following the 15
ratio used in radio-tracking studies (Kenwood 2001). In
addition, all trapped target species 16
were injected with a unique passive induced transponder tag
(Francis Scientific Instruments, 17
Cambridge) to enable individual identification. Some individuals
that were re-captured were 18
spool-tracked multiple times. 19
20
HABITAT VARIABLES.- Habitat use was examined at two spatial
scales. The largest spatial 21
scale was the scale at which the availability of microhabitats
changed in the forest 22
environment and was standardized to intervals of 10 m along the
animal’s path. The smallest 23
spatial scale was the scale at which substrates (individual
fallen branches, leaf litter patches, 24
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7
open ground) changed along the animal’s path. This spatial scale
varied from approximately 1
0.5 to 5 m. 2
3
QUANTIFYING MICROHABITAT PREFERENCES.- The first ten meters of
each spool track were 4
discarded as a flight response (Harris et al. 2006), and the
first microhabitat measurements 5
were recorded a further ten meters from the starting point of
normal behaviour. Preliminary 6
trials were conducted to estimate the separation distance at
which repeated measures on the 7
spool track became independent from each other. The
autocorrelation between consecutive 8
10 m observations was assessed using the autocorrelation
function (ACF) in R (R 9
Development Core Team, 2014). Negligible correlation was found
at 10 m intervals 10
(correlation = 0.046), so this was subsequently used as the
spacing between repeated 11
microhabitat measurements. 12
13
Microhabitat was defined as the area within a 1 m radius of the
spool and nine 14
microhabitat variables were measured at 10 m intervals along the
animal’s track (a detailed 15
description of microhabitat variables is provided in Table 1 of
online supporting 16
information). All microhabitat variables were recorded by the
same researcher (R.L). The 17
density of vegetation in four layers of forest strata was
estimated visually for each 10 m 18
interval along the spool track following Puttker et al. (2008)
(near the ground 0-0.5 m, 19
understory 0.5-3.0 m, mid-story 3.0-20 m, and canopy > 20 m).
We assigned a score of 20
between one and four to each stratum to give an index of
vegetation density. Four further 21
variables indicating potential resource availability and
predation risk were also recorded 22
(total canopy closure, forest quality, tree basal area, habitat
concealment score). As covariates 23
that may influence the space use of individuals, we recorded
rainfall during the night and 24
lunar phase. Rainfall may influence small mammal movement by
masking the noise of travel 25
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8
across complex substrates (Vickery & Bider 1981; Browman et
al, 2000), and variation in 1
moonshine may influence the visibility of the microhabitats,
making some locations less 2
desirable when well lit by a full moon (Kotler et al. 1991).
3
4
An assessment of microhabitat preference requires a comparison
between the 5
microhabitats that are selected by a species with other
microhabitats that are available, but 6
not used. To compare observed vs. control microhabitat,
measurements taken every 10 m on 7
the spool track were paired with measurements at a spatially
matched location off the track. 8
The locations of these control measurements were determined by
walking 10 m in a straight 9
line on a bearing relative to the spool track of 45 °, 135 °,
225 °, or 315 °, with bearings 10
selected sequentially (Fig. 1). 11
12
QUANTIFYING SUBSTRATE PREFERENCES.- We broke spool tracks into a
series of discrete 13
steps, where a step was defined as a straight-line section of
track with no change of direction 14
greater than 20 °. For each step, we characterized the dominant
substrate into one of eight 15
categories following Wells et al. (2006), and the length of the
step (a detailed description of 16
the different substrate categories is provided in Table 1 of
online supporting information). 17
Species-specific step lengths were similar; M. surifer had the
longest mean step length at 2.0 18
m, and M. whiteheadi the shortest at 1.8 m. 19
20
As with the microhabitat variables, we recorded paired control
observations for each 21
step by noting the dominant substrate along a control step
located off the spool track. Control 22
steps were determined by walking the same distance as the
observed step on a bearing of 45 23
°, 135 °, 225 ° or 315 ° relative to the direction of the spool
step, with bearings selected 24
sequentially. 25
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1
STATISTICAL ANALYSIS.- Linear mixed effects models were used to
account for the nested 2
repeated measures taken on the same spool track from
individually-identified small 3
mammals. The R packages nlme and lme4 (Bates et al. 2011,
Pinheiro et al. 2011) were used 4
for these analyses. The categorical rain and lunar phase
variables were included as covariates 5
in all models but are not reported as they do not impinge on our
hypotheses. The significance 6
of fixed effects, including interaction terms, was determined
from likelihood ratio tests by 7
comparing models with and without the fixed effect or
interaction. 8
9
To test for vertical spatial segregation between species, we
used a binomial general 10
linear mixed effects model to compare repeated measures of the
height above ground at 10 m 11
intervals along the spool track across species. Height was
categorized into ground (< 0.5 m) 12
or above-ground (> 0.5 m) for analysis, and species, rain and
lunar phase were fitted as fixed 13
effects. The nested data structure was explicitly modelled by
nesting repeated measures taken 14
on the same spool track within individually-identified small
mammals. 15
The microhabitat variables used in this study examined different
layers of forest strata and 16
together provided a holistic measure of forest disturbance. The
values were highly 17
intercorrelated so we reduced the number of variables to a
smaller set of principal component 18
axes using the vegan package in R (Oksanen et al. 2011).
Variable standardization was 19
carried out by dividing the value of each variable by the
maximum values for that variable. 20
Much of the variation (35 %) was captured within the first
principle component (PC1), and 21
we therefore used this as the only variable in subsequent
modelling of species’ microhabitat 22
preference. This single composite variable provided a robust and
easy to interpret axis from 23
low forest disturbance (negative PC1 values) to high forest
disturbance (positive PC1 values). 24
Negative PC1 values were related to high forest quality scores,
high canopy and mid-storey 25
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10
density and high tree basal area. Positive PC1 scores were
associated with high understory 1
and high ground vegetation density. 2
3
To compare the strength of microhabitat preference between
species, a single 4
“microhabitat preference” response variable was generated for
each 10 m observation along 5
the spool track. This response variable was defined as the
difference in PC1 scores between 6
observed and paired control observations. This provided a
measure of the strength of 7
preference for more or less disturbed microhabitats in relation
to the immediate, surrounding 8
environment. A linear mixed effects model was used to compare
microhabitat preference 9
among species, retaining rain and lunar phase as additional
fixed effects and nesting repeated 10
measures of tracks within individually-identified small mammals
as random effects. 11
12
To compare the use of substrates across species, we first
calculated the ratio between 13
the number of times a substrate category was recorded in
observed versus matched control 14
steps per spool track. This ratio was then used to standardize
the observed frequency of 15
substrate use by the availability of the substrate in the
immediate vicinity of each spool track. 16
We log-transformed the ratio so that positive and negative
values scaled equally. Positive 17
values of this “substrate preference” score indicate preference
for that particular substrate and 18
negative values indicate avoidance of that particular substrate.
A linear mixed effects model 19
was used to compare substrate preference among species and
substrate type, retaining rain 20
and lunar phase as additional fixed effects and nesting repeated
measures of tracks within 21
individually-identified small mammals as random effects. 22
23
RESULTS 24
25
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11
SPECIES’ SPATIAL BEHAVIOUR.- We attached 53 spools to 41
individuals, from which a total of 1
293 movement steps were recorded: 15 M. surifer individuals with
139 steps, 13 M. 2
whiteheadi individuals with 81 steps, nine L. sabanus
individuals with 41 steps and four R. 3
rattus individuals with 32 steps. The small number of R. rattus
reflects their relatively low 4
abundance in this habitat at what we believe is an early stage
in the invasion process. The 5
total spool track followed was 3.4 km with a mean spool length
of 64 m per individual (SE = 6
44.3 m). All species were captured on each of the three trapping
grids and individuals of 7
different species displayed a large amount of spatial overlap in
their terrestrial foraging 8
behaviour. Spool tracks of different species released on the
same night were occasionally 9
found to cross over each other, and individuals of different
species were recorded using the 10
same fallen log or dry riverbed. 11
12
Vertical segregation of space was observed between species (χ2 =
26.43, df = 3, p < 13
0.001). All observations of both Maxomys species were recorded
on the forest floor (< 0.5m 14
above the ground). However spool tracks of both R. rattus and L.
Sabanus were frequently 15
observed to pass along lianas (woody vines) that emanated from
the forest floor and 16
penetrated up into the under and mid-storey forest strata. 28
percent of R. rattus observations 17
(n = 32) and 27 percent of L. Sabanus observations (n = 41) were
recorded in the understory 18
(0.5 to 3 m) and a further nine percent of R. rattus
observations and 15 percent of L. sabanus 19
observations were recorded in the mid-storey of the forest (3 to
10 m). 20
21
MICROHABITAT AND SUBSTRATE PREFERENCE.- There were significant
differences among 22
species in their microhabitat preferences (Fig. 2) (χ2 = 17.91,
df = 3, p < 0.001). Across all 23
species, R. rattus had the strongest preference for the most
heavily disturbed forest 24
(preference = 0.31, SE = 0.06), followed by the two Maxomys
species that had weaker 25
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12
preferences for disturbed forest (M. whiteheadi: preference =
0.13, SE = 0.01; M. surifer: 1
preference = 0.10, SE = 0.01). Pairwise comparison between the
two Maxomys species 2
confirmed that M. whiteheadi showed the marginally stronger,
though non-significantly 3
different preference for more disturbed habitats (difference in
preference score =0.03, 4
SE = 0.04, df = 27, p = 0.45). Of the four species, only L.
sabanus had a preference for less 5
disturbed habitats (preference = -0.089, SE = 0.01). 6
7
The four species showed similar patterns of preference across
the substrate types (Fig. 8
3), with no significant differences among species (χ2 = 4.33, df
= 3, p = 0.228) and neither 9
was there a significant interaction effect between species and
substrate preference (χ2 = 10
24.60, df = 17, p = 0.104), despite an apparent preference for
R. rattus to prefer moving 11
through suspended leaf litter that the three native species
showed no preference for (Fig. 3). 12
Across species, however, there were strong preferences for some
substrates over others (χ2 = 13
88.97, df = 6, p < 0.001). Overall, small mammals showed the
strongest preference for fallen 14
wood (preference value = 0.85, SE = 0.17) and dry stream beds
(preference value = 0.83, SE 15
= 0.38), followed by rocky substrates (preference value = 0.53,
SE = 0.18). Species tended to 16
actively avoid leaf litter (preference value = -0.47, SE =
0.07), but were not strongly 17
influenced by suspended leaf litter (preference value = 0.32, SE
= 0.06), vines (preference 18
value = 0.25, SE = 0.06) or bare ground (preference value =
-0.06, SE = 0.01). Comparing the 19
two Maxomys species; M. surifer had the slightly stronger
preference for travelling along 20
vines, while M. whiteheadi had the stronger preference for
travelling over rocky terrain (Fig. 21
3). 22
23
DISCUSSION 24
25
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13
Our results emphasise how species make habitat selection choices
at multiple spatial scales 1
(Manly et al. 2002), and that small-scale processes can be used
to help explain large-scale 2
phenomena such as the invasion of R. rattus into modified
forests. We have confirmed 3
earlier survey work that demonstrated R. rattus is more likely
to be present in heavily 4
modified than unmodified tropical rainforest (Cusack et al.
2014), and confirmed our 5
hypothesis that this pattern appears to arise from specific,
small-scale alterations to 6
microhabitat structure that R. rattus actively prefers to move
in. 7
8
VERTICAL SPATIAL SEGREGATION.- This study represents one of the
only efforts to quantify 9
the extent of arboreal space use by R. rattus (Key and Woods
1996), and how this ability may 10
facilitate invasion in logged tropical forests. Neither Maxomys
species showed arboreal 11
behaviour, however both L. sabanus and R. rattus showed
significantly different vertical 12
space use compared to these terrestrial species, utilizing
higher layers of the forest strata. 13
Indeed, the foot morphology of the two species is very similar,
both having broad feet and 14
prominent plantar pads, adaptations known to indicate
arboreality in murid rodents (Aplin et 15
al. 2003). Moreover, the long tails of both species, up to 120
percent of body length for R. 16
rattus and 135 percent of body length for L. sabanus, help with
balance and may well be 17
adaptions for climbing (Boonsong et al. 1988). Therefore R.
rattus is well-adapted to fully 18
exploit the three-dimensional complexity of forest habitat. This
is of particular concern as 19
nest predation by this introduced omnivore may negatively impact
the survival success of 20
native bird species, as has been the case on other tropical
islands such as Hawaii 21
(Amarasekare 1993). 22
23
The behavioural flexibility of R. rattus to utilise both
terrestrial and arboreal space 24
may significantly increase the species’ invasion capability into
the complex three 25
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14
dimensional forest environment. Indeed, invasive species are
more frequently habitat 1
generalists than specialists (Olden et al. 2004, Whitney &
Gabler 2008). When entering a 2
new forest habitat R. rattus can potentially access both
terrestrial and arboreal foraging 3
resources and a greater extent of niche space than an
obligately-terrestrial, or obligately-4
arboreal species. Additionally, in Sabah, arboreal murid rodent
communities are relatively 5
species poor compared to terrestrial small mammals (Wells et al.
2004). Therefore the 6
arboreal adaptive zone could have more space for invasion. In
addition, it has also been 7
suggested that arboreal behaviour may reduce exposure to
terrestrial predators, and present 8
physical barriers for aerial predators (Montogomery &
Gurnell 1985, Buesching et al. 2008). 9
10
MICROHABITAT PREFERENCE.- Both Maxomys species and R. rattus
showed significant 11
preference for more disturbed microhabitats, corroborating the
results of a previous study 12
using trapping data at the same study site (Cusack et al. 2014).
Here, however, we have 13
demonstrated at a smaller spatial scale that these three species
choose to move through more 14
disturbed habitats than less disturbed, alternative habitats in
the immediate surrounding 15
environment. Disturbed habitats were characterized by a low
presence of large trees, 16
allowing the growth of dense ground and under-storey vegetation
layers. This provides 17
excellent cover from predators. Heavily-disturbed habitats may
maximize both predator 18
avoidance and resource availability, making these habitats
desirable for small mammals. The 19
greater abundance of these habitats after human disturbance may
also explain why it has been 20
observed that small mammal populations tend to increase after
logging activity (Adler and 21
Levins 1994, Pardini 2004). Among the three species, R. rattus
showed the strongest 22
preference for more disturbed habitat. This suggests that
heavily-disturbed forest habitat is a 23
more strongly preferred habitat for R. rattus than it is for the
native Maxomys species. 24
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15
Heavily disturbed forest habitat may therefore facilitate the
invasion of this species into 1
logged forests in Borneo (Stokes et al. 2009, Cusack et al.
2014). 2
3
It is interesting to note that this same preference for
disturbed habitat was not 4
replicated by L. sabanus, which showed a preference for less
disturbed habitat. One 5
explanation for this reverse trend is that the semi-arboreal L.
sabanus benefits from exploiting 6
resources present in the more intact canopy of less disturbed
forest. This species also has a 7
relatively larger body size, making it more mobile. This,
combined with semi-arboreal 8
behaviour, may make this species less susceptible to predation
(Montogomery & Gurnell 9
1985) and therefore more able to exploit the microhabitats that
lack the dense vegetation 10
layer associated with disturbed forest sites. 11
12
SUBSTRATE PREFERENCE.- All study species showed a clear
preference for moving along 13
fallen wood (Fig. 3). Woody debris contains high concentrations
of invertebrates, a key 14
resource for small mammals (Emmons 2000). Larger pieces of woody
debris may also be 15
used as cover in order to reduce visual detection by predators
(Browman et al. 2000). This is 16
supported by the observation that individuals in this study
sometimes travelled parallel to 17
fallen wood, close against the side. Travelling on top of woody
debris has also been 18
hypothesized to provide a simple substrate to allow for faster,
more efficient travel and to 19
allow small mammals to scan more effectively for predators
whilst moving (Shadbolt & 20
Ragai 2010). Therefore, in terms of foraging and predation risk,
fallen wood may be an 21
important microhabitat feature for maintaining populations of
small mammals. 22
23
Small mammals tended to avoid moving through leaf litter, a
pattern that may be 24
explained by the complexity of this substrate inducing slow,
noisy travel with greater risk of 25
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16
predation (Shadbolt & Ragai 2010). By contrast, the
preference for sunken, dry river beds 1
may be explained by the more enclosed nature of this substrate,
reducing visibility to 2
predators. 3
4
Using trap-level habitat data, Cusack et al. (2014) found that
the occurrence of L. 5
sabanus could be predicted by the presence of fallen wood and
low levels of leaf litter. 6
However these were not significant predictors of occurrence for
either Maxomys species or R. 7
rattus (Cusack et al. 2014). By contrast, we found that all
study species showed a significant 8
preference for fallen wood and an avoidance of leaf litter. The
slight contrast in the findings 9
between the two studies likely arises from differences in
methodologies. Cusack et al. (2014) 10
used microhabitat variables associated with individual trap
sites, representing point locations 11
where individual small mammals were captured, whereas we used
more finely detailed 12
information on the movement tracks of individuals through the
habitat. This apparent contrast 13
in results therefore reinforces the importance of measuring
habitat preference at the spatial 14
scale at which the species makes habitat selection choices in
order to accurately discern 15
patterns of behaviour (Manly et al. 2002). 16
17
IMPLICATIONS FOR IMPROVED MANAGEMENT OF LOGGED FOREST SYSTEMS.-
The microhabitat 18
data presented demonstrates how one of the major threats to
biodiversity in the tropics, 19
namely habitat degradation and modification (Brown & Brown
1992), may multiply the 20
likely impact of a second major threat, invasive species (Kot et
al. 1996). Specifically, we 21
found that habitat degradation may generate habitat that is more
suitable for R. rattus, so 22
promoting the spread of this invasive species, which may in turn
threaten the persistence of 23
native fauna. Species potentially impacted by the invasion of R.
rattus into tropical 24
rainforests include under and mid-storey nesting birds, which
are often vulnerable to nest 25
-
17
predation by rodents, and other small mammals through direct
competition. In addition, the 1
threat of R. rattus to native fauna may be further magnified by
the species potentially acting 2
as a conduit for the introduction of novel diseases into native
small mammal communities 3
(Wells et al. 2014b). 4
5
The findings of this study agree with those of Cusack et al.
(2014) in demonstrating 6
that R. rattus shows strong preference for heavily disturbed
habitats. We therefore 7
recommend that the best practical defence against the invasion
of R. rattus into tropical 8
forests is to preserve forest habitats that are less suitable
for the species (Bernard et al. 2009). 9
This may be achieved through reduced impact logging techniques
that are designed to 10
minimise levels of habitat disturbance and degradation (Gerwing
& Uhl 2002, Putz et al. 11
2008). 12
13
Our results also point towards specific new methods for
minimising the likelihood of 14
R. rattus invasion based on the fine-scale habitat preferences
of the species for particular 15
forest structural elements. It is a common logging practice to
undertake some crude shaping 16
of felled wood extracted from the forest prior to transportation
in order to reduce the weight 17
and cost of transporting the wood. This contributes to large
quantities of wood fragments 18
being discarded within logged forest stands, at the sides of
logging roads and along the forest 19
edge. Recent research by Pfeifer et al. (2015) has shown that
the volume of deadwood within 20
a logged tropical forest increases with greater forest
disturbance. We have demonstrated that 21
fallen wood is especially preferred by R. rattus. Therefore
reducing the availability of this 22
favoured microhabitat type along the forest edge may be one
means of reducing the 23
likelihood of R. rattus invading logged forest stands. This
could be achieved by 24
implementing logging practices that promote extraction
efficiency. For example improving 25
-
18
tree selection to only log the most suitable tall, straight
trees would minimise the amount of 1
wood discarded. Improved disposal of waste wood could also be
explored. 2
3
Furthermore, cutting back mid-storey vegetation, such as lianas
and knocking 4
suspended leaf litter to the ground may reduce the ability of
invasive small mammals to 5
penetrate the non-terrestrial layers of forest strata. Before
committing to such an action 6
however, it will be important to ensure that this approach will
not inadvertently compromise 7
the movement corridors of other native small mammal species,
such as scansorial mice in the 8
genera Chiropodomys and Haeromys that may exploit lianas. Our
data, nonetheless, provide 9
initial support for the use of liana cutting as an important
component of enrichment planting 10
practices aimed at rehabilitating the structure and composition
of degraded forests (Kettle 11
2010, Ansell et al. 2011). 12
13
14
15
ACKNOWLEDGEMENTS 16
We thank the Royal Society’s South East Asia Rainforest Research
Programme for logistical 17
support, and Yayasan Sabah, Maliau Basin Management Committee,
the State Secretary, 18
Sabah Chief Minister’s Departments and the Sabah Biodiversity
Council for permission to 19
conduct research. This work was funded by the Sime Darby
Foundation. RME was 20
supported by European Research Council Project number 281986. We
are grateful for the 21
comments of T. Coulson, and A. M. Valenzuela. 22
23
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1
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28
1
10m A
BCobs
CDobs
BCcont
CDcont
AB
DEobs EFobs
DEcont
EFcont
2
Fig. 1. An example spool track of a male M. surifer illustrating
the spool track the animal 3
moved along (continuous black line) with observation locations
(filled circles) and the 4
spatially matched control routes (dotted lines) with control
locations (open circles). A= 5
release point; AB= first 10 m route of spool track that was
discarded as a flight response; 6
BCobs= observed 10 m route of spool track; BCcont= spatially
matched 10 m control route for 7
segment BC. 8
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29
LS MS MW RR
-1.0
-0.5
0.0
0.5
1.0
Species
Mic
roh
ab
itat
pre
fere
nce
1
Fig. 2. Microhabitat preferences of three native (white) and one
introduced species (grey) of 2
small mammals. Positive values of the habitat preference score
indicate a preference for 3
selecting more disturbed habitats over less disturbed habitats,
and negative values indicate the 4
reverse. LS = Leopoldamys sabanus, MS = Maxomys surifer, MW =
Maxomys whiteheadi, 5
RR = Rattus rattus. 6
-
30
BG FW LL RK SLL ST V
-2-1
01
2
Substrate
Su
bstr
ate
pre
fere
nce
va
lue
a
BG FW LL RK SLL ST V
-2-1
01
2
Substrate
Su
bstr
ate
pre
fere
nce
va
lue
b
BG FW LL RK SLL ST V
-2-1
01
2
Substrate
Su
bstr
ate
pre
fere
nce
va
lue
c
BG FW LL RK SLL ST V
-2-1
01
2
Substrate
Su
bstr
ate
pre
fere
nce
va
lue
d
1
Fig. 3. Substrate preference values of Leopoldamys sabanus (A),
Maxomys surifer (B), 2
Maxomys whiteheadi (C) and Rattus rattus (D) for bare ground
(BG), fallen wood (FW), leaf 3
litter (LL), rocky substrates (RK), suspended leaf litter (SLL),
dry stream beds (ST) and vines 4
(V). Positive preference values indicate substrates that are
preferred and negative values 5
indicate substrates that are avoided. 6