Download Similarities in perceived predation risk prevent temporal partitioning

Journal of Mammalogy, 97(2):483–489, 2016
DOI:10.1093/jmammal/gyv192
Published online December 26, 2015
Similarities in perceived predation risk prevent temporal
partitioning of food by rodents in an African grassland
Natalia Banasiak and Adrian M. Shrader*
School of Life Sciences, University of KwaZulu-Natal, Private Bag X01, Scottsville 3209, South Africa (NB, AMS)
* Correspondent: [email protected]
One way in which animals coexist is through temporal separation of feeding activities. This separation directly
reduces interference competition, but potentially not exploitive competition. To reduce exploitive competition,
coexisting species tend to utilize different microhabitats and/or achieve different feeding efforts across
microhabitats. However, 1 factor that has generally not been considered with regards to its impacts on competition,
and thus coexistence, is predation risk. As different predators are active during the day and at night, the location
of safe areas across the landscape can vary temporally. If so, then temporally separated prey species would likely
forage in different areas thus reducing exploitive competition. However, if predation risk across the landscape is
similar for nocturnal and diurnal species, then both could restrict their foraging to the same microhabitats, thus
increasing exploitive competition. To explore these alternative possibilities, we manipulated grass height in an
African grassland to create microhabitats that varied in predation risk. We then estimated perceived predation
risk of both nocturnal and diurnal rodents in these microhabitats by recording giving-up densities (GUDs) in
artificial resource patches. We found that despite differences in predators, both nocturnal and diurnal rodents
preferred feeding in the same microhabitats, and they achieved similar feeding efforts within these microhabitats.
This suggests that despite the prevention of interference competition through temporal partitioning, the spatial
similarities in perceived predation risk in relation to cover likely increase exploitive competition between these
rodents. However, as both nocturnal and diurnal rodents were present in the study area, it is likely that some other
mechanism (e.g., varied diets) allows them to coexist.
Key words: coexistence, competition, feeding effort, giving-up densities
© 2015 American Society of Mammalogists, www.mammalogy.org
Due to similarities in diet and/or habitat requirements, many
species have the potential to compete for key resources.
However, through differences in resource partitioning of their
diets (Kinahan and Pillay 2008; Symes et al. 2013), spatial
habitat selection (Abramsky et al. 1990; Morris 1996; Bramley
2014) and temporal separation of feeding activities (KronfeldSchor and Dayan 2003; Gutman and Dayan 2005), many
species reduce interspecific competition and are thus able to
coexist (Kotler and Brown 1988). For example, Symes et al.
(2013) found that 6 rodent and 2 shrew species coexisted in a
South African grassland–woodland mosaic by separating their
niches (i.e., reducing competition) through different combinations of diet, space, and time.
Competition, however, comes in 2 forms—interference and
exploitative competition (Nicholson 1954), which affect coexistence differently. Interference competition entails one species preventing another from accessing resources (e.g., food)
through direct confrontation (e.g., fights, chases—Case and
Gilpin 1974), or indirectly via one species avoiding certain
areas at certain times due to fear of injury from potential
aggressive encounters with another species (Ziv et al. 1993). In
contrast, exploitative competition (also called scramble competition) is when one species lowers food availability for other
species through feeding (Parker 2000) or by scaring prey eaten
by both species away (i.e., behavioral resource depression—
Charnov et al. 1976).
One way in which species can reduce interference competition is through temporal partitioning of feeding (Richards
2002; Kronfeld-Schor and Dayan 2003; Gutman and Dayan
2005). By foraging at different times, heterospecifics prevent
direct interactions. However, exploitative competition between
these species would still take place if they fed in the same
areas unless food was replenished in the period between visits
(Schoener 1974). A 2nd way in which exploitative competition could be reduced by temporal partitioning is if different
resources (e.g., prey species) are available at different times
(i.e., reduced resource overlap). For example, the availability
and presence of different insect species varies both spatially
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and temporally and thus insectivorous birds and bats potentially
reduce exploitative competition by foraging at different times
(Speakman et al. 2000). A 3rd way in which temporal partitioning could reduce exploitive competition, and thus promote
coexistence, would be if resource patches are renewed once a
day, and each species has a resource density at which it forages
more efficiently than its competitor/s (Brown 1989). For example, in the Negev Desert, Israel, 2 gerbil species coexist due, in
part, to differences in their feeding efficiencies. Specifically,
the gerbil (Gerbillus pyramidum) feeds more efficiently when
food availability is high, in contrast to the smaller G. allenbyi
that feeds more efficiently when food availability is low (Kotler
et al. 1993; Ziv et al. 1993).
Temporal separation as a mechanism leading to coexistence
(Schoener 1974) has been found in a wide range of animal species (e.g., Gutman and Dayan 2005; Leisnham et al. 2014; and
examples in Kronfeld-Schor and Dayan 2003). However, 1
thing that has not been extensively considered is how predation
risk affects microhabitat use and feeding effort of temporally
separated species and thus ultimately their coexistence. Jones
et al. (2001) studied 2 temporally separated spiny mice, with
Acomys cahirinus being nocturnal and A. russatus diurnal. In
winter, the 2 species easily coexisted, as they did not compete
for food. This was because their use of the different microhabitats (e.g., under and away from boulders) varied as did their
feeding effort within the microhabitats. However, in summer,
when snakes were active, both species of spiny mice fed more
in open areas away from boulders to avoid snakes. As a result,
this spatial shift in landscape use increased the overlap in the
use of more open microhabitats by the 2 spiny mice species.
However, as the feeding effort of the 2 species differed within
the habitats and they continued to use the available microhabitats to different degrees, the spiny mice were able to coexist
(Jones et al. 2001). Nevertheless, microhabitat selection may
not promote coexistence if the food resource (i.e., prey) moves
between the microhabitats, even if the competitors do not.
As different predators are active at different times, safe areas
across the landscape may vary temporally (Jacob and Brown
2000; Jones et al. 2001). For example, aerial predators (e.g.,
falcons and hawks) tend to be more active during the day, while
terrestrial predators (e.g., cats) tend to hunt more at night. In
response, prey species may consider areas under cover to be
safer during the day, as it can reduce detection by predators,
compared to at night when terrestrial ambush predators may use
cover to hide in (Mohr et al. 2003; Kotler et al. 2004). As spatial
differences in perceived predation risk can influence both largeand small-scale space use (i.e., a landscape of fear—Shrader
et al. 2008; Van Der Merwe and Brown 2008; Laundré et al.
2013), then under these circumstances temporally separated
prey species would likely forage in different areas. This spatial separation would reduce exploitative competition (Morris
1996), while temporal partitioning would prevent interference
competition (Kronfeld-Schor and Dayan 2003). This remains
true even if temporal partitioning is the result of previous interference between the prey species. As a result, under these circumstances, there are 2 mechanisms (i.e., spatial and temporal
separation) reducing competition and thus facilitating the coexistence of these species (Kotler and Brown 1988).
However, if nocturnal and diurnal species perceive landscape
features similarly with regards to predation risk (e.g., safety
under cover for rodents), then this perception could increase
exploitative competition as both species would restrict their
foraging to the same habitats and/or patches, albeit at different times of the day. If this was the case, it may be possible
that the benefits gained from reducing interference competition through temporal partitioning would be counteracted by
increased exploitive competition generated by similarities in
perceived predation risk.
To explore these alternative possibilities, we manipulated
grass height to alter perceived predation risk in an African
grassland utilized by both nocturnal and diurnal rodents.
Different predators were active at night compared to during
the day at our study area. Specifically, the majority of raptors
(e.g., long-crested eagles, Lophaetus occipitalis; jackal buzzards, Buteo rufofuscus; and black-shouldered kites, Elanus
caeruleus) were active during the day, compared to only 2 species of owls (barn owl, Tyto capensis; and spotted eagle owl,
Bubo africanus) that were active at night. In contrast, threats
from terrestrial predators were likely greater at night compared
to day, as many African mammalian predators of rodents are
nocturnal (e.g., white-tailed mongoose, Ichneumia albicauda;
genets, Genetta spp.—Skinner and Chimimba 2005). If nocturnal and diurnal rodents used the landscape differently with
regards to perceived predation risk, then we would expect that
they would feed in different microhabitats (e.g., open versus
closed cover) or their feeding effort would differ within the
same microhabitats, which would reduce exploitative competition. Alternatively, if perceived predation risk resulted in these
2 sets of rodents using microhabitats similarly, then, despite
temporal separation preventing interference competition, there
would be an increase in interspecific exploitative competition.
Materials and Methods
Study site.—We conducted our study from 11 April to
21 June 2012 (autumn into winter) in an 8 ha natural grassland located at the University of KwaZulu-Natal, Ukulinga
Research Farm in Pietermaritzburg, KwaZulu-Natal, South
Africa (30°24′S, 29°24′E). Grasslands within Africa provide a
good place to test the effects of temporal separation on coexistence. This is because they are inhabited by both nocturnal and
diurnal omnivorous rodent species (Taylor 1998; Skinner and
Chimimba 2005), food in the form of seed rain from grasses is
not pulsed and thus seeds fall throughout the 24 h cycle over a
number of months (Lyaruu 1999), and a range of nocturnal and
diurnal invertebrates are present that are also eaten by these
rodents (Samways et al. 1996).
Both aerial and terrestrial predators of rodents were present
at the study site. Daytime aerial predators observed included
long-crested eagles, jackal buzzards, and black-shouldered
kites, while nocturnal aerial predators comprised both barn and
spotted eagle owls. Terrestrial predators active during the day
BANASIAK AND SHRADER—PREDATION AND COEXISTENCE485
included slender mongoose (Galerella sanguinea) and secretary birds (Sagittarius serpentarius), while nocturnal terrestrial
predators included white-tailed mongoose, genets, feral cats
(Felis catus), serval (F. serval), and caracal (F. caracal). We
did not observe snakes (e.g., puff adders, Bitis arietans; brown
house snake, Lamprophis capensis; and rinkhals, Hemachatus
haemachatus) in the study area, but they may have been present. However, since we conducted our study during autumn and
winter, snakes were unlikely to have been very active.
Experimental design.—To determine the nocturnal and diurnal rodents’ use and feeding effort within the different grass
height microhabitats, we established four 3 × 3 m plots in 3
separate sites (N = 12 plots) in a grassland around a 20 × 10 m
woodland patch (Fig. 1). We selected the location of the sites
so that the ground at each site had similar slopes. Moreover,
we set up these sites so that all of the plots were 5 m from the
woodland patch in a straight line, with the sites separated from
each other by a minimum of 10 m to reduce the probability
of the same rodents utilizing more than 1 site. However, the
use of more than 1 site by some of the same individuals would
likely not alter the results of the study, as the habitat and foraging decisions of these few individuals would unlikely skew
the overall microhabitat use patterns of the whole rodent community. Within a site, individual 3 × 3 m plots were separated
by 1 m of uncut grass (> 150 cm high). For each 3 × 3 m plot,
we manipulated grass height by cutting the grass to either 5 cm,
20 cm, 40 cm, or leaving the grass uncut to act as a control (>
150 cm). The order of grass height plots was randomly assigned
at each site. We chose these heights as 5 cm provided no cover
for the rodents, 20 cm provided patchy cover as it included only
the fibrous parts of the grass tufts, at 40 cm the grass became
leafier providing cover, while the uncut (> 150 cm) grass offered
maximum cover at the study site.
To generate an index of available cover for rodents in the
different grass height treatments, we measured photosynthetically active radiation in µmol m−2 sec−1 using an AccuPAR
Fig. 1.—Layout of the experimental design indicating the location of
the 3 sites around the 20 × 10 m woodland patch (indicated by shaded
trees). Each site comprised four 3 × 3 m plots (indicated by open
squares), with each plot containing a randomly selected different grass
height treatment (5 cm, 20 cm, 40 cm, and >150 cm).
model LP-80 ceptometer (Decagon Devices, Inc., Pullman,
Washington). We took 4 light measurements from each 3 × 3 m
microhabitat plot by pushing the tip of the meter under the grass
along the ground from each corner toward the opposite corner. We then used the mean of these photosynthetically active
radiation measurements as the index of cover for the plot. We
repeated this for each of the plots in 2 sites. We omitted the 3rd
site, as shade from the trees partially covered some of the treatments. To ensure consistency, we took all the measurements on
a single cloudless day between 1100 h and 1300 h (i.e., solar
noon). Using the mean index values from all the plots, we were
able to estimate differences in cover between the grass height
treatments (i.e., microhabitats). Cover did not differ between
the 40 and > 150 cm treatments (Fig. 2).
We quantified utilization and feeding effort within the different grass height microhabitats by measuring giving-up densities (GUDs; i.e., the amount of food left in a patch once a
forager has finished eating—Brown 1988) in artificial patches.
Foraging in a patch is a trade-off between costs and benefits.
As a result, an animal should forage in a patch until its quitting
harvest rate (H) in the patch equals the sum of the metabolic
(C), predation risk (P), and missed opportunity costs (MOC)
of foraging in that patch (H = C + P + MOC—Brown 1988).
As harvest rate is dependent on the density of food within a
patch, GUDs can act as an index of quitting harvest (Schmidt
et al. 1998). Hence, animals show greater preference for a patch
through greater feeding effort, resulting in lower GUDs (Brown
1988).
We provided the rodents with food in artificial resource
patches comprised plastic circular trays (20 cm diameter × 2 cm
deep). To create diminishing returns to harvest rate and thus
making these artificial patches similar to natural food patches
(Kotler and Brown 1990), we filled the trays with a mixture of
80 g of whole sunflower seeds and approximately 700 g of filtered sand. By filling the artificial patches with sand, the rodents
would need to dig in the sand to obtain seeds in a similar manner to how they would forage for natural seeds (Kotler et al.
1994). In each grass height microhabitat (i.e., plot), we set up
a 3 × 3 grid of these artificial resource patches where each artificial patch was separated by 1 m. To maximize the perceived
predation risk within the microhabitats, we set up the grid in the
Fig. 2.—Photosynthetically active radiation (PAR; µmol m−2 sec−1) as
an index of the amount of cover provided by the different grass height
microhabitats. Error bars represent 95% confidence intervals.
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JOURNAL OF MAMMALOGY
middle of each 3 × 3 m plot. This resulted in the outer artificial
resource patches of the grid (N = 8 patches) being 50 cm from
the uncut grass at the edges of the plot.
Prior to data collection, we habituated the rodents to the artificial patches by initially filling the trays with only sunflower
seeds. We left these artificial resource patches out in the microhabitats over the 24 h cycle for 2 weeks. Each day, we checked
these artificial patches in the morning and late afternoon to
determine patch use and refilled any seeds that the rodents had
removed. After 2 weeks, we filled each artificial patch with the
sunflower seed and sand mixture. We then let the rodents forage in these artificial resource patches for an additional week
before we started collecting data.
To quantify differences in the nocturnal and diurnal rodents’
use of and feeding effort in the different microhabitats, we collected GUDs twice a day, at 0700 h and 1630 h, respectively. We
estimated GUDs by sifting and weighing the seeds left in the
artificial patches. We then reset these artificial resource patches
by mixing 80 g of seed into the 700 g of sifted sand. As all the
trays were set up in the same manner, we were able to compare
the GUDs from the different microhabitats (Kotler et al. 1994).
Once we had completed the feeding experiment, we used
Sherman livetraps to determine which rodent species fed
from the artificial resource patches. To do this, we placed a
2 × 2 grid of Sherman livetraps (each trap separated by 1 m)
into the middle of the grid of artificial patches in the different
microhabitats (N = 48 traps). We baited the traps with sunflower seeds mixed in peanut butter. In addition, we added a
piece of cotton wool into the traps for the rodents to use as
bedding material to help protect them against the cold. We
trapped over 7 days and nights (i.e., 336 trap days and nights),
checking the traps twice a day, at 0700 h and 1630 h, to determine the nocturnal and diurnal rodent species, respectively.
Rodents were identified to species level using Taylor (1998)
and then released where they were caught. We did not mark
the rodents, as we were only interested in species’ presence
and not abundance.
The research on the live animals followed guidelines of
the American Society of Mammalogists (Sikes et al. 2011)
and the University of KwaZulu-Natal animal ethic protocols. The University of KwaZulu-Natal animal ethics committee approved all experimental procedures under reference
number 012/12/Animal. No animals were harmed during the
study.
Data analysis.—As the data were not normally distributed,
we used a Friedman Test, which is the non-parametric alternative to a repeated measures analysis of variance, to compare
the feeding effort (i.e., GUDs) within the different grass height
microhabitats (5 cm, 20 cm, 40 cm, >150 cm) and time of day
(day, night). We used the Friedman Test, as the GUDs recorded
in the each of the different sites were likely from the same
individuals over the 2 weeks. We then used Wilcoxon Signed
Ranks tests with a Bonferroni correction for the a posteriori
analyses. This resulted in the significance level being adjusted
to P = 0.0017 to account for all combinations required. All
analyses were conducted in SPSS 19.0.
Results
Rodent species livetrapped within our study site included the
nocturnal Natal multimammate mouse (Mastomys natalensis;
N = 5 individuals), African pygmy mouse (Mus minutoides;
N = 1 individual), and the diurnal four-striped grass mouse
(Rhabdomys pumilio; N = 15 individuals—Taylor 1998).
Despite being classified as diurnal, the four-striped grass mouse
sometimes also forages at night (Perrin and Kotler 2005; Abu
Baker and Brown 2010). However, we did not capture fourstriped mice during the night. Moreover, nocturnal foraging of
this mouse is limited to times when night time temperatures
are above 5°C (Perrin and Kotler 2005). As temperatures during our study were below 5°C each night, it is unlikely that the
four-striped grass mice foraged nocturnally.
Rodent feeding activity differed significantly between
the grass height microhabitats (Friedman test: χ2 = 713.09,
P < 0.0005; Fig. 3). In contrast to expectations, we found that
the nocturnal and diurnal rodent communities had the same
microhabitat utilization pattern and achieved similar GUDs (i.e.,
feeding effort) in the different microhabitats (all P > 0.0017;
Fig. 3). Specifically, both sets of rodents achieved greater feeding effort (i.e., achieved lower GUDs) when grass height was
≥ 40 cm compared to when it was ≤ 20 cm (all P < 0.0005). In
addition, feeding effort (i.e., GUDs) did not differ significantly
between the 40 and > 150 cm microhabitats (day: P = 0.623,
night: P = 0.173) nor between the 5 and 20 cm microhabitats
(day: P = 0.487, night: P = 0.777; Fig. 2). Finally, in the more
open microhabitats where grass height was < 20 cm, the rodents
only fed in the artificial patches around the edges of the grids
(i.e., those closest to the > 150 cm high uncut grass) and never
in the central patch.
Discussion
Temporal partitioning of feeding times is one way in which
animals can reduce interference competition and thus coexist
(Kronfeld-Schor and Dayan 2003). However, if these temporally separated species utilize microhabitats to the same extent,
they could still experience exploitative competition through the
reduction of food availability. Despite differences in cover and
Fig. 3.—Mean giving-up densities (GUDs) of the rodent community
at 4 different grass heights for both day (□) and night (▲) foraging.
Error bars represent 95% confidence intervals.
BANASIAK AND SHRADER—PREDATION AND COEXISTENCE487
the predators that were active during night and day, we found
that both nocturnal and diurnal rodents had the same pattern
of microhabitat utilization. Moreover, both sets of rodents
showed the same feeding effort in each of the different microhabitats, and achieved greater feeding effort (i.e., lower GUDs)
in patches where the grass height was ≥ 40 cm. This suggests
that, despite the prevention of interference competition through
temporal partitioning, the spatial similarities in perceived predation risk in relation to cover likely increase exploitive competition between these rodents. As a result, temporal partitioning
of feeding activity alone is not a sufficient mechanism to allow
for coexistence between these rodent species.
Vegetation structure that creates cover is a key component
that reduces perceived predation risk of rodents (Hughes and
Ward 1993; Kotler and Blaustein 1995; Mohr et al. 2003; Abu
Baker and Brown 2010). This is due to a lower probability of
detection and capture by both aerial and ambush predators.
In contrast, open areas provide opportunities to spot potential
predators at greater distances but do not provide concealment
from predators. Species such as fox squirrels (Sciurus niger),
thirteen-lined ground squirrels (Ictidomys tridecemlineatus),
degus (Octodon degus), southern African ground squirrels
(Xerus inauris), and the nocturnal Allenby’s gerbil (Gerbillus
andersoni allenbyi) rely heavily on vision as a means to detect
predators (Thorson et al. 1998; Ebensperger and Hurtado 2005;
Edwards and Waterman 2011; Embar et al. 2011). However,
the lower feeding effort showed by gerbils in open habitats
suggests that open sightlines aid predators more to locate prey
than it helps prey to detect approaching predators (Embar et al.
2011). The fact that the rodents in our study preferred to feed
in microhabitats with high cover suggests that they do not rely
on long-range visual detection of approaching predators to
reduce predation risk and their preferred antipredator strategy
is concealment.
The preference for microhabitats with greater cover suggests
that both the nocturnal and diurnal rodents in our study perceived the open microhabitats to be more dangerous. This could
be an attempt to reduce predation risk from pursuing predators (e.g., birds of prey, mongoose), as grass height can influence predator hunting success (Janes 1985; Kotler et al. 2004;
Embar et al. 2011). This may also explain why when both sets
of rodents fed in the open microhabitats (i.e., 5 and 20 cm), they
restricted their feeding to the artificial patches on the periphery
of the 3 × 3 grid. By feeding in these patches, they were closer
to the uncut >150 cm tall grass surrounding the plot compared
to the resource patch in the middle of the grid. Thus, if chased
they would be able to get within the sounding tall grass quicker,
thus reducing predation risk, than if they were feeding in the
middle of the grid. For example, Simmons (2000) found that
the success of African marsh harrier (Circus ranivorus) hunting
on rodents was lowest in tall vegetation. In addition, owls tend
to be more cautious and less maneuverable when hunting in
dense vegetation (Longland and Price 1991; Rohner and Krebs
1996). However, antipredator behaviors may be altered or combined in multipredator systems, such that by sticking to cover
rodents also escape detection from both aerial and terrestrial
predators (Lima 1998; Stankowich and Blumstein 2005).
In contrast to Jones et al. (2001), both the nocturnal and
diurnal rodents in our study used the same microhabitats. As
GUDs provide an index into the feeding effort within the different microhabitats (Jones et al. 2001), our results suggest that,
despite a reduction in interference competition, there is potential for a high degree of exploitive competition between these
nocturnal and diurnal rodents. However, the presence of both
sets of species indicates that, even if there was extensive competition between the species, there must be some other mechanism that allows them to coexist (Kotler and Brown 1988).
One way in which these species could coexist is through
the partitioning of their diets (Kotler and Brown 1988; Jones
et al. 2001). All three of the species in our study were omnivorous, dividing their diets between seeds, vegetation, and insects
(Skinner and Chimimba 2005). As we only provided seeds as
a food source in our artificial patches, it is possible that under
unmanipulated conditions these rodents could reduce exploitive competition within the microhabitats by feeding on different food types. However, the similar feeding effort on the
seeds within the different microhabitats suggests that, despite
the potential to reduce exploitive competition, these species
still compete to some degree. For example, Kronfeld-Schor
and Dayan (1999) found that 2 species of spiny mice reduced
interference competition as they were temporally separated.
Nevertheless, an extensive overlap in food preferences by the 2
species suggested that if food were limiting, then the temporal
separation would not reduce exploitive competition. However,
potential differences in arthropods ingested by the 2 spiny
mice, either through different arthropods being active at different times (i.e., food availability) or different preferences for
specific arthropods by the 2 species (i.e., resource partitioning),
may have reduced exploitive competition thus enabling their
coexistence (Kronfeld-Schor and Dayan 1999).
A potential concern that could be directed toward our study
is that the limited number of species that we recorded in the
grassland may not be a true reflection of the rodent community.
However, as the grassland was far from water and human dwellings, the number of rodent species that could potentially live
within this grassland is limited (Taylor 1998). In fact, the species that we caught make up the 3 most common rodent species
living in the grasslands of KwaZulu-Natal, South Africa (Taylor
1998). The only other rodent species that may have been present is the Angoni vlei rat (Otomys angoniensis). However, as
we did not come across any of its distinctive runways through
or around our plots, it is unlikely that these solitary, purely herbivorous rodents (Bronner and Meester 1988) were in the section of the grassland where we conducted the study. However,
if they were present, the fact that they have a completely different diet means that they would not directly compete with the
other species for food and thus would be able to coexist. As a
result, our results reflect the general rodent community within
KwaZulu-Natal grasslands and thus likely provide insight into
the coexistence of these rodents across the province.
Up to this point, we have focused on competition as a way
to discuss our observations. However, it is possible that food
was not limiting in the grassland and hence the rodents were
not competing for resources. If this were the case, then it is
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JOURNAL OF MAMMALOGY
not surprising that both the nocturnal and diurnal rodents displayed similar feeding efforts within the same microhabitats.
Therefore, our results would simply reflect the rodents’ microhabitat use in relation to perceived predation risk.
However, density dependence generally governs rodent population size (e.g., Saitoh et al. 2008; Previtali et al. 2009; Letnic
et al. 2011). Thus, if food availability were high, we would
expect that rodent populations would increase rapidly, due to
their high reproductive outputs, to a point where they were
at equilibrium with available resources. As a result, it would
be unlikely that these larger rodent populations would have
access to excess food. Additionally, rainfall on the farm in 2011
was below average (708 mm) compared to a 32-year mean of
790 mm (Kirkman et al. 2014). As grass growth is determined
by rainfall, it is unlikely that the below-average rainfall would
have resulted in an excessive seed set. Thus, exploitive competition for food between the rodent species seems the most likely
outcome.
Competition, however, may not be limited to differences
between the rodent species. It is also possible that other seedeating taxa such as birds and insects may compete for food
within the grassland. A number of seed-eating birds have been
observed on the farm including bronze mannikin (Spermestes
cucullatus), red-collared widow (Euplectes ardens), and longtailed widow (E. progne; A.M. Shrader, University of KwaZuluNatal, pers. comm.). However, as these species move over large
areas (i.e., locally migratory in winter—Hockey et al. 2005)
and are thus not restricted to the grassland where we conducted
our study, the total impact they could have on food availability is unlikely to be great. In contrast, harvester ants (Messor
capensis), which feed extensively on seeds, could reduce food
availability for other species in areas surrounding their colonies. However, Milton and Dean (1993) found that harvester
ants only removed between 10% and 18% of the annual seed
biomass produced by plants. As a result, these ants may reduce
the availability of seeds, but the extent is unlikely to result in
heavy exploitive competition with rodents.
Ultimately, our results highlight the potential role that predation risk can have on competition between species and thus
their coexistence. Similarities in perceived predation risk can
result in temporally separated species utilizing microhabitats
to the same extent, thus decreasing the effectiveness of temporal partitioning in reducing exploitive competition. Moreover,
as predators can remain or move in and out of areas, changes
in predation risk can vary over temporal scales. As a result,
through influences on the competitive interactions between
species, predation risk could potentially alter community composition and dynamics.
Acknowledgments
Natalia Banasiak thanks the University of KwaZulu-Natal
G. Langmuir bursary for financial support. AMS thanks the
National Research Foundation (NRF) for financial support.
B. Kotler, J. Wilson, C. Pavey, J. Merritt, and N. Hagenah provided valuable comments on the manuscript.
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Submitted 23 April 2015. Accepted 20 November 2015.
Associate Editor was Chris R. Pavey.