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2009 SOUTHEASTERN NATURALIST 8(3):387–398
Luring Small Mammals: A Levels-of-organization Perspective
Luis R. Rodas1, Chad A. Jennison1, Daniel B. Hall2, and Gary W. Barrett1,*
Abstract - We compared prebaiting versus non-prebaiting of small mammal live
traps during autumn (i.e., when food resources were abundant) and during spring
(i.e., when food resources were scarce). Trapping was conducted within 10 experimental
grids (0.21-ha each) located in upland and bottomland (5 each) habitats. Four
species of small mammals were captured 10 or more times during this study: Peromyscus
leucopus (White-footed Mouse; 543 captures), Glaucomys volans (Southern
Flying Squirrel; 94 captures), Tamias striatus (Eastern Chipmunk; 53 captures),
and Ochrotomys nuttalli (Golden Mouse; 12 captures). The White-footed Mouse,
because of its abundance during both seasons, was the primary species of analysis.
White-footed Mice had a significantly higher probability of capture (1.29 times [or
29 percent]) in the prebaiting treatment than in the non-prebaited treatment. Prebaiting
did not have a significantly different effect on males compared to females or on
juveniles versus adult White-footed Mice. The practice of prebaiting, or luring small
mammals, is discussed across levels of organization .
Baiting is defined as a food, or some substitute, used to lure or entice
animals for entrapment or to stop for food during a journey (Webster’s Unabridged
Dictionary of the English Language 2001). Baits are used as a lure
in fishing, game management, and integrative pest management to increase
harvest, rates of capture, or for pest control. Prebaiting is the early placement
of food at a site of potential capture (e.g., live trap) or spread across an area
(e.g., grain or food distributed across a field or forest) to lure or acclimate
animals to this site or landscape patch to increase rate of capture or removal
once live-trapping techniques are used. The practice of prebaiting live traps to
increase the frequency of capturing small mammals by conditioning them to
trap presence goes back well over 70 yrs. Prebaiting was described as a fruitful
technique for increasing trapping efficiency, both for research (Moore 1936)
and pest eradication (Chitty 1942). Prebaiting has also been used as a means
to ensure equal probability of capture of new and marked individuals within a
study population (Chitty and Kempson 1949), as a technique to increase rates
of capture (Gentry et al. 1971), and to more accurately estimate population
densities (Tanton 1969). Chitty and Kempson (1949) remarked that when a
study demands a random catch of marked and unmarked animals on any one
day, it is essential that prebaiting be used. They suggest that certain small
mammals tend to avoid entering an unfamiliar object (e.g., a live trap); hence,
an increased rate of capture is predicted if the traps have been prebaited. They
observed higher capture success of Microtus agrestis L. (Field Vole) following
1Eugene P. Odum School of Ecology, University of Georgia, Athens, GA 30602.
2Department of Statistics, University of Georgia, Athens, GA 30602. *Corresponding
author - email@example.com.
388 Southeastern Naturalist Vol. 8, No. 3
prebaiting with oats. Moore (1936) also found that Microtus pennsylvanicus
Ord (Meadow Vole) was more efficiently captured if traps were baited, then
propped open for a day before being set for capture. The efficacy of prebaiting
or luring small mammals to live traps, however, awaits critical analysis.
Several early studies focused on how prebaiting affected population
estimates (Grodzinski et al. 1966, Tanaka and Kanamori 1969, Zejda and
Holisova 1971). Earlier mark-recapture studies assumed that prebaiting
would increase the rate of capture and provide a more robust estimate of
population abundance. Grodzinski et al. (1966), however, found that prebaiting
failed to homogenize removal rates between marked and unmarked
individuals, a result that skews regression estimates. Further, Buchalczyk
and Pucek (1968) found no evidence that prebaiting increased the rates of
removal of Microtus oeconomus Pallas (Tundra Vole), though total captures
were twice as high. Their finding was partially clarified by Zedja and Holisova
(1971) who showed that prebaiting within a grid lures animals whose
home ranges are not fully within the grid of study. Thus, prebaiting affects
spatial distribution and can contribute to infl ating density estimates.
The practice of luring small mammals to specifically established habitat
sites has also been used for decades at the ecosystem and landscape levels
to: (1) attract and poison, or remove, small mammals considered to be crop
depredators or vectors of disease to humans (Chitty 1942), (2) insure that
mark-recapture methods of estimating population densities are valid and
accurate (Smith et al. 1975), and (3) increase frequency of capture (Gentry
et al. 1971). The question remains unanswered, however, whether or not the
prebaiting or luring practices are worthy of the time and resources necessary
to continue this practice, or if prebaiting efficacy is species specific. To test
these questions, we designed a replicated, seasonal (fall and spring) study
to quantify the effects of prebaiting at the population and community levels.
Though other species were frequently captured in prebaited traps, we selected
P. leucopus Rafinesque (White-footed Mouse) as the primary focus of
our analysis because of its abundance and frequency of capture. Specifically,
we addressed questions, such as whether behavioral response of P. leucopus
to prebaiting changes with season and whether prebaiting affects the probability
of recapture of marked individuals.
Study area and research design
The study site was the HorseShoe Bend Ecological Research Site
(HSB) located in Clarke County near Athens, GA (33º57'N, 83º23'W).
HSB is located in a 14.2-ha riverine peninsula formed by a meander of the
North Oconee River. Upland and bottomland deciduous forest characterize
the peninsula. Though the bottomland is susceptible to flooding, no
flooding occurred during our investigation. Both habitats are dominated by
Smilax spp. (greenbrier), Lonicera mackii (Rupr.) Herder (Honeysuckle),
Ligustrum sinense Lour. (Chinese Privet), Quercus nigra L. (Water Oak),
and Liquidambar styraciflua L. (Sweet Gum). Quercus alba L. (White
2009 L.R. Rodas, C.A. Jennison, D.B. Hall, and G.W. Barrett 389
Oak) and Fagus grandifolia Ehrh. (American Beech) are also abundant in
the upland, whereas Betula nigra L. (River Birch) and Liriodendron tulipifera
L. (Tulip Poplar) are common in the bottomland (Christopher and
Barrett 2006, Klee et al. 2004).
We established five experimental grids in each of the bottomland and upland
habitats. Each grid was approximately 0.21 ha, including a 10-m border
around each grid, consisted of 12 trapping stations spaced approximately
10 m apart along two parallel transects of six stations each (see Christopher
and Barrett  for an aerial photograph of the research site including a
design of trapping stations). Each station consisted of one Sherman live trap
(7.6 x 7.6 x 25.4 cm; H.B. Sherman Traps, Tallahassee, FL) situated on a
wooden platform 1.5 m high on the trunk of a tree. Thus, we used a total of
120 live traps for this study.
The possibility that newly-situated live traps might serve as novel
stimuli, thus decreasing initial rates of capture of small mammals, can be
eliminated (1) by using a continuous or daily trapping regime, including
use of a population abundance estimator, such as the Schnabel method
(Schnabel 1938), or (2) by maintaining live traps in the same place on
a seasonal or yearly basis (Boonstra and Krebs 2006). To eliminate the
foreign stimulus concern, we followed a research design that maintained
Sherman live traps left in place on wooden platforms for six consecutive
years (see Christopher and Barrett  and Klee et al.  for details
regarding research design).
Live trapping was conducted weekly from 4 September–22 November
2005, and from 21 February–9 May 2006. We randomly selected one of the
two transects within each grid to be prebaited. Prebaiting consisted of placing
black oil sunfl ower seeds in open traps during a 24-hr prebaiting period;
nonprebaited traps within each grid were left open, but not baited. At the
end of the 24-hr prebaiting period, all traps were baited with black oil sunfl
ower seeds, set overnight, and checked the following morning. Seeds from
both prebaited and non-prebaited traps were removed from each trap when
we checked for captured individuals. Date, location of capture, and species
of small mammal livetrapped were recorded. Each captured individual was
marked with a sequentially numbered ear tag (Scott Roestenburg, Neway
Products, Murray, Utah) for identification. We determined sex, weight to
the nearest gram, reproductive condition (open or closed vaginal orifice,
abdominal or scrotal testes, pregnant, and/or lactating), and examined for
general health of each captured animal. Captured individuals were released
at the site of capture immediately following examination. Animals were
handled in accordance with the guidelines provided by the American Society
of Mammalogists (ASM Animal Care and Use Committee 1998) and approved
by The University of Georgia Animal Care and Use Committee (AUP
We considered as categorical measurements taken on each of 120 traps,
half (60 traps) of which were prebaited and half (60 traps) not prebaited.
390 Southeastern Naturalist Vol. 8, No. 3
Measurements were taken weekly over 12 weeks during each of two seasons
(Fall 2005 and Spring 2006). Each measurement corresponded to a trapping
outcome that was categorical, with possible values: female, male, juvenile, or
empty. The response can be treated as a multinomial random variable; we used
a multinomial regression model as the basis of statistical analysis. A generalized
logit model (Agresti 1990) was used in which the log odds (or logit) of a
capture of a particular sex type (female, male, or juvenile) versus no capture
(empty) was modeled as a linear function of explanatory variables including
whether or not the trap was prebaited, the season, and time of capture within
each season. The model involved three log odds specifications as follows:
π F ijkl
π E ijkl
= μF ij + γ F jweekk + δF jweekk
π E ijkl
= μMij + γ Mjweekk + δMjweekk
π J ijkl
π E ijkl
μJi2 +γ J 2weekk +δ J 2weekk 2
μJ i1 ⎧⎨ ⎪
Here πFijkl represents the probability of capturing a female in the lth trap (l =
1…60), during the kth week (k = 1…12), during the jth season ( j = 1,2, corresponding
to Fall 2005 and Spring 2006, respectively), under the ith treatment
( i = 1,2, corresponding to no prebaiting and prebaiting, respectively).
Probabilities πMijkl, πJijkl, πEijkl of capturing, respectively, a male, juvenile, or
no animal (E = empty trap) are defined similarly.
The three lines in model (1.1) represent sub-models for the log odds of
a female capture versus no capture, male capture versus no capture, and
juvenile capture versus no capture, respectively. The first two of these logits
(for female and male capture odds) were each modeled in terms of a linear
predictor involving constant terms (means on the log odds scale) for each
treatment by seasons combination (the μ*ij terms), and quadratic functions
of time (γ*j weekk + δ*j weekk) that differed across seasons. Because only
one juvenile animal was captured in fall 2005, it was necessary to assume
a much simpler constant log odds model for juvenile captures in season 1
(j = 1). In season 2 (spring 2006), the log odds of a juvenile capture were
modeled similarly to those of females and males. Model parameters were
allowed to differ across the three logits (F = female, M = male, and J = juvenile)
subscripts to allow a comparison of the treatment effect of the odds of
female capture to differ from the treatment effect of the odds of a male being
captured. A quadratic effect of time was chosen based upon initial plots of
capture, which indicated non-constant rates of capture over time. Note that
weekk in (1.1) has been centered in the ith treatment, jth season after averaging
over each 12-week time period.
if j = 1 (fall)
if j = 2 (spring)
2009 L.R. Rodas, C.A. Jennison, D.B. Hall, and G.W. Barrett 391
Model (1.1) allows tests to be conducted to detect treatment effects (i) for
any particular animal type (female, male, or juvenile); (ii) for at least one of
the three animal types; or (iii) for all animal types (aggregated). Season and
time effects were similarly investigated.
We tested the following hypotheses:
A. There was no treatment (prebaiting) effect for any mouse type. This hypothesis
states that the odds of capturing a female, male, or juvenile versus
capturing no animal are equal between the two treatments for all three
B. Assuming that treatment effects were equal for all three mouse types,
there was no effect on the overall capture rate of mice regardless of gender/
maturity. This hypothesis states that the odds of captures across all
three animal types are the same across treatments.
C. The treatment effect on the capture rate for females was no different than
that for males. This hypothesis specifies that the odds of a female versus
male capture are the same in the prebaiting condition as in the non-prebaiting
D. During spring 2005, the treatment effect on the capture rate for juveniles
was no different from that of adults. This hypothesis specifies that the
odds of a juvenile capture versus adult capture are the same in the prebaiting
condition as in the non-prebaiting condition.
In addition, to justify averaging across seasons and animal types when
assessing treatment effects, we tested for a two-way interaction between
treatment and season and a three-way interaction between treatment, season,
and animal type.
Model (1.1) was fit using maximum likelihood estimation with the SAS
procedure NLMIXED (Version 9.1 of the SAS System for Windows, Copyright
© 2002–2003 by SAS Institute, Cary, NC). All hypotheses were tested
using Wald test statistics, which have asymptotic Chi-square distributions
(Agresti 1990, section 4.2.4). The goodness-of-fit of model (1.1) to these
data were assessed via a deviance goodness-of-fit test (Agresti 1990, section
4.1.4) to insure the validity of inferences derived from the model.
We captured four species of small mammals at least 10 times during
this study: Peromyscus leucopus Rafinesque (White-footed Mouse; 543
captures), Glaucomys volans L. (Southern Flying Squirrel; 94 captures),
Tamias striatus L. (Eastern Chipmunk; 53 captures), and Ochrotomys
nuttalli Harlan (Golden Mouse; 12 captures). P. leucopus was selected
for detailed analysis because of their abundance during both the fall and
spring trapping sessions.
We conducted a deviance goodness-of-fit test to support the use of model
(1.1) as the basis of inference. The resulting test statistic χ2
123 = 129.6, P =
0.32 confirmed that there was no significant evidence for lack of fit. Test
statistics for hypotheses A–D are summarized in Table 1. The three-way
interaction between treatment, season, and animal type, the two-way interaction
between treatment and season, and the two-way interaction between
392 Southeastern Naturalist Vol. 8, No. 3
Table 1. Primary hypotheses A-D showing odds ratio (ORs) estimates for significant effects. F = females, M = males, and J = juveniles.
Hypothesis Test (95% confidence
description statistic P-value interval) Interpretation
A No prebaiting effect for χ3
2 = 7.92 <0.05 F: 1.46 (0.90, 2.02); Odds of capture are significantly higher under prebaiting treatment
any mouse type. M: 1.35 (0.97, 1.73); than control treatment for at least one mouse type (gender/maturity
J: 1.08 (0.80, 1.37) level).*
B No treatment effect for all χ1
2 = 6.92 <0.01 1.29 (1.05, 1.53) Odds of capture (all mice) are significantly higher in the prebaiting
mouse types combined. treatment than in the control condition.
C No gender by treatment χ1
2 = 0.11 0.74 Insufficient evidence to conclude that prebaiting has different effects
interaction. on males than on females.
D No juvenile/adult by χ1
2 = 0.06 0.81 Insufficient evidence to conclude that prebaiting has different
treatment interaction in effects on juveniles than on matures.
*Note that 95 percent confidence intervals on the odds ratios (ORs) are separate intervals for individual ORs, and are not based on a simultaneous confidence
region for all three ORs. This explains why no intervals cover 1, but the result that at least one OR is different than 1 is significant at P = 0.05.
2009 L.R. Rodas, C.A. Jennison, D.B. Hall, and G.W. Barrett 393
treatment and animal type were nonsignificant (χ2
2 = 1.46, P = 0.48; χ2
0.24, P = 0.62; χ2
2 = 2.14, P = 0.34; respectively), justifying the inferences
presented in Table 1.
Prebaiting resulted in significantly higher odds of capture for
White-footed Mice than the nonprebaiting treatment. Because the
treatment by mouse-type interaction was nonsignificant, the test and
corresponding odds ratio (ORs) for all mice types combined provided the
most appropriate summary of this result. White-footed Mice had odds of
capture 1.29 times (or 29%) higher in the prebaiting treatment than in
the control treatment. Prebaiting had no significantly different effect on
males compared to females or on juveniles compared to mature animals.
Our finding suggests that prebaiting does increase frequency of capture of
the White-footed Mouse. Therefore, this practice may be viewed as an efficacious
methodology for this species.
Perhaps the main reason for prebaiting is to increase the initial probability
of capture by conditioning animals to the trapping station. Prebaiting
techniques have been practiced for decades to lure animals to a site or area
for termination by poisoning (Chitty 1942), and to increase probability of
capture (Gentry et al. 1971). There is a paucity of information, however,
with which to evaluate this technique where prebaited and nonprebaited
treatments are established in a replicated research design. There also exists
the need to discuss how baiting and prebaiting practices relate to potential
changes in abundance across levels of organization.
Procedures used when live-trapping small mammals vary with the length
of the trapping regime. For example, some investigators prebait small mammal
live traps for a 2-day (Getz et al. 2006, Suazo and DeLong 2007) or even
a 1-week period of time (Boonstra and Krebs 2006). Some researchers place
closed live traps on grids a minimum of 3 days before sampling to allow small
mammals to acclimatize to their presence before trapping begins (e.g., Wiewel
et al. 2007), whereas more typically, traps are set in a particular grid pattern,
baited with peanut butter, oats, cracked corn, or sunfl ower seeds, then checked
the following morning. Trapping is frequently conducted for 2–3 consecutive
days (e.g., Christopher and Barrett 2006, Pauli et al. 2006).
Prebaiting procedures and acclimation practices are typically affiliated
with mark-recapture estimates of small-mammal population abundance and
related parameters (e.g., Hammond and Anthony 2006, Wiewel et al. 2007).
Numerous factors may affect capture probabilities. These include social
status, sex, age, patterns of activity, and location of traps in relation to centers
of animal activity; quality of habitat; live traps previously occupied by
other species (Boonstra et al. 1982, Hammond and Anthony 2006); or traps
previously occupied by conspecifics, especially those of the opposite sex
(Christopher and Barrett 2007, Drickamer 1984, Mazdzer et al. 1976).
Disadvantages of prebaiting include the probable attraction of animals
on the edge of the sampling area resulting in infl ated density estimates
394 Southeastern Naturalist Vol. 8, No. 3
(Zedja and Holisova 1971), including a disruption of the spatial and social
organization of the small-mammal populations (Gentry et al. 1971). It is
recommended to avoid prebaiting in studies investigating social organizaton
based on live-trapping results, unless these data are needed for calculation
of edge effect. Summerlin and Wolfe (1973), for example, have shown that
older and higher social ranking Sigmodon hispidus Say and Ord (Hispid
Cotton Rat) tend to be caught first and more frequently than younger, lower
ranking individuals. Further, prebaiting adds additional food resources that
may affect population dynamics. Additional time and monetary expenses are
also associated with prebaiting. To date, the behavioral and economic effects
of prebaiting on White-footed Mice have not been quantified.
We next provide a perspective on the effects of prebaiting and luring on
small-mammal dynamics across levels of organization (population, community,
ecosystem, and landscape).
In our study, we found significantly greater probability of capture of
White-footed Mice in prebaited traps compared to those traps that were
baited once a trapping regime was initiated. Prebaiting had no significant effect
on males compared to females or on juveniles when compared to adults.
We suggest that prebaiting is species specific at the population level and
likely related to the type of bait used, quality of habitat, and season when
prebaiting was used. For example, Grodzinski et al. (1966) suggest that food
availability would infl uence trap response of small mammals. To test this
hypothesis, Smith and Blessing (1969) demonstrated that food availability
reduced the number of live trap captures of Peromyscus polionotus Wagner
(Old-field Mouse) when wild birdseed was dispersed to one-half of an oldfield community. We suggest that addition of grain, such as wild birdseed, is
a form of prebaiting at the population level if the type of bait used is targeted
at a particular species, such as Old-field Mice.
Although we focused on White-footed Mice in the current study based
on a robust sample size (n = 543 captures), numerous other small mammals
likely will be attracted to the baiting site, thus providing valuable information
at the community level. For example, four species of small mammals
(Old-field Mouse, Southern Flying Squirrel, Eastern Chipmunk, and Golden
Mouse) were captured at least ten (10) times during our prebaiting/baiting
Prebaiting may alter food availability, and should decrease movement of
small mammals near the supplemental food, thus invalidating any comparisons
of home-range size. It may also shift the focal point of species activity
into the grid or site from the surrounding border zone. Thus, species or individuals
responding to the site of prebaiting would appear to be part of the
resident population (Zejda and Holisova 1971). This response to prebaiting
would alter not only home-range size but, perhaps, small-mammal species
interactions at the community level. These interactions, plus factors such
2009 L.R. Rodas, C.A. Jennison, D.B. Hall, and G.W. Barrett 395
as bait used, weather, and habitat quality must be taken into account when
deciding to prebait traps or add bait to a particular community type.
Whereas, prebaiting and baiting studies involving small mammals
traditionally have focused on specific species and feeding sites (e.g., live
traps or feeding stations; Chitty and Kempson 1949, Grodzinski et al. 1966,
Gurnell 1980), several approaches have focused on the ecosystem level,
such as grain addition or food enrichment (Bendell 1959, Cole and Batzli
1978, Fordham 1971, Hansen and Batzli 1979). For example, supplemental
food has been added to old-field and riparian ecosystems to quantify the
population dynamics response of Old-field Mice (Smith and Blessing 1969),
Meadow Vole (Desy and Thompson 1983), Hispid Cotton Rat (Doonan and
Slade 1995), Microtus ochrogaster Wagner (Prairie Vole) (Slade et al. 1997),
and Zapus hudsonius Zimmermann (Jumping Mouse) (Trainor et al. 2007).
See reviews by Boutin (1990) and Adams (2001) regarding the response of
small mammals to supplemental food resources.
Landscape ecology focuses on elements such as patches, corridors, and
matrices. At the landscape scale, patches and corridors are frequently managed
for conservation purposes. Plant communities, agroecosystems, and
landscapes are frequently modified or structured by special plantings or corridors
to lure or effect movement of select species of small mammals to and
within these patch types (Danielson and Hubbard 2000, Mabry and Barrett
2002, Mabry et al. 2003). High-quality corridors are frequently used to lure or
funnel small mammals to other patches of high-quality habitat (LaPolla and
Barrett 1993, Mabry and Barrett 2002). Small mammals frequently benefit
from this landscape conservation and management strategy (Mech and Hallett
2001, Wolff and Barrett 2008). However, there are exceptions to this strategy
(e.g., Bowne et al. 1999, Haddad et al. 2003). Small mammals lured into, or
making use of, landscape corridors frequently are preyed upon by an array of
predators. For example, Barrett et al. (2001) documented five events of predation
on the Hispid Cotton Rat by snakes and owls in an experimental landscape
investigation at the Savannah River Site (SRS) in Aiken County, SC.
This luring/patch-quality management strategy has been practiced
for well over 70 years. For example, Stoddard (1931) described feed
patches, established to attract and provide grain-producing plant species
for Colinus virgianus L. (Bobwhite Quail). Plant species, such as Lespedeza
striata Thunb. (Japanese Clover), Panicum ramosum L. (Brown-top
Millet), and Panicum miliaceum L. (German Millet) are planted as food
for quail. These plant species are also excellent food sources for small
mammals (Barrett 1968, Miller and Miller 1999). Stoddard (1931) describes
how high-quality landscape patches are beneficial to hunters in
locating coveys of quail, as well as in increasing population growth and
survivorship of this game species. Interestingly small mammals, such as
cotton rats, also benefit from this increased food source and vegetative
cover. Consequently, population densities of cotton rats were frequently
396 Southeastern Naturalist Vol. 8, No. 3
controlled on these established landscape patches by poisoned baits and
prescribed burning (Stoddard 1931:428).
In summary, we suggest the practice of prebaiting or luring small mammals
occurs across levels of organization and at differing temporal/spatial
scales. Responses to prebaiting likely differ at increased temporal/
spatial scales, responses are species specific depending on habitat quality and
the nature of the bait or lure used, and effects on abundance or biodiversity
differ depending on trophic-level dynamics (Haddad et al. 2003). Future investigations
need to be designed at the ecosystem or landscape scales to better
understand small-mammal population and community dynamics in an integrative
manner when prebaiting is an experimental component of the research
design. Currently, luring and prebaiting are recognized as management and
conservation practices. Much as Seddon et al. (2007) describe the science of
“reintroduction biology,” we suggest there exists the need to develop the science
of “luring biology” across levels of integration.
We thank M. Adams, D. Crawford, T. Gancos, L. Gibbes, H. Korngold, and T.
Luhring for field assistance during 2005 and 2006. M.T. Mengak, guest editor, S.B.
Castleberry, and an anonymous reviewer provided valuable comments on an earlier
draft of this manuscript. Appreciation for editorial comments and final preparation
of this manuscript are extended to T.L. Barrett. This study was partially supported by
the Eugene P. Odum Endowed Chair held by G.W. Barrett.
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