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Caribbean
Naturalist
No. 19 2014
Small Indian Mongoose (Herpestes
auropunctatus) Population Abundance
and Effects of Habitat Features on
Trapping Success in Protected Areas
of Eastern Puerto Rico
Diana Guzmán-Colón and Gary J. Roloff
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Cover Photograph: View from the cloud forest in El Yunque National Forest. Photograph © Diana K
Guzman-Colon.
CARIBBEAN NATURALIST
The Caribbean Naturalist (ISSN # 2326-7119) is published by the Eagle Hill Institute, PO Box 9, 59 Eagle Hill Road, Steuben, ME
04680-0009. Phone 207-546-2821, FAX 207-546-3042. E-mail: office@eaglehill.us. Webpage: www.eaglehill.us/cana. Copyright
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Southeastern Naturalist (ISSN 1528-7092 [print], ISSN 1938-5412 [online]), and the Urban Naturalist (ISNN #2328-8965), journals
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eral ID # 010379899).
Board of Editors
James D. Ackerman, Department of Biology, University of Puerto Rico at Río Piedras, USA
Alfonso Aguilar-Perera, Department of Marine Biology, Universidad Autónoma de Yucatán, Mexico
Wayne J. Arendt, International Institute of Tropical Forestry, Luquillo, Puerto Rico, USA
Rüdiger Bieler, Field Museum of Natural History, Chicago, IL, USA
Christopher P. Bloch, Department of Biological Sciences, Bridgewater State University, Bridgewater, MA,
USA
William R. Buck, Institute of Systematic Botany, New York Botanical Garden, Bronx, NY, USA
Leo Douglas, Department of Geography/Geology, University of the West Indies, Mona, Jamaica
Robert Erdman, Department of Biological Sciences, Florida Gulf Coast University, Fort Myers, FL, USA
Keith Goldfarb, Eagle Hill Institute, Steuben, ME, USA ... Editor-in-Chief
Grizelle González, International Institute of Tropical Forestry, San Juan, Puerto Rico, USA
Gary R. Graves, Department of Vertebrate Zoology, Smithsonian Institution, Washington, DC, USA
S. Blair Hedges, Department of Biology, Pennsylvania State University, University Park, PA, USA
Julia A. Horrocks, Dept. of Biological and Chemical Sciences, Univ. of the West Indies, Cave Hill Campus,
Barbados
Scott Jones, Smithsonian Institution, Caribbean Coral Reef Ecosystems, Carrie Bow Cay, Belize
Heather Judkins, Department of Biological Sciences, University of South Florida, St. Petersburg, FL, USA
Craig A. Layman, Department of Biological Sciences,Florida International University, North Miami, FL,
USA
John Leavengood, Department of Entomology, University of Kentucky, Lexington, KY, USA
Antonio A. Mignucci-Giannoni, Manatee Conservation Center, Inter American University, Bayamón,
Puerto Rico, USA
Gregg Moore, Department of Biological Sciences, Jackson Estuarine Laboratory, University of New Hamp-
shire, Durham, NH, USA
James Pitts, Department of Biology, Utah State University, Logan, UT, USA
Robert Powell, Department of Biological Sciences, Avila University, Kansas City, MO, USA
Chris Rimmer, Vermont Center for Ecostudies, Norwich, VT, USA
Armando Rodríguez-Durán, Dean for Research, Inter American University, Bayamón, Puerto Rico, USA
Noris Salazar Allen, Smithsonian Tropical Research Institute, Panama
Inés Sastre de Jesus, Biology Department, University of Puerto Rico at Mayagüez, USA
J. Angel Soto-Centeno, American Museum of Natural History, Division of Mammalogy, New York, NY,
USA
Christopher Starr, Department of Life Sciences, University of the West Indies, St. Augustine, Trinidad and
Tobago
David W. Steadman, Florida Museum of Natural History, Gainesville, FL, USA
Kathleen Sullivan Sealey, Department of Biology, University of Miami, Coral Gables, FL, USA
Jarrod M. Thaxton, Department of Biology, University of Puerto at Mayagüez, USA
Jason M. Townsend, Department of Wildlife, Fish and Conservation Biology, University of California-
Davis, USA ... Managing Editor
Jill Weber, Eagle Hill Institute, Steuben, ME, USA ... Production Editor
Byron Wilson, Department of Life Sciences, University of the West Indies at Mona, Kingston, Jamaica
Graham A. J. Worthy, Department of Biology, University of Central Florida, Orlando, FL, USA
Joseph M. Wunderle, International Institute of Tropical Forestry, University of Puerto Rico at Río Píedras,
USA
Caribbean Naturalist
1
D. Guzmán-Colón and G.J. Roloff
2014 No. 19
CARIBBEAN NATURALIST
2014 No. 19:1–12
Small Indian Mongoose (Herpestes auropunctatus)
Population Abundance and Effects of Habitat Features on
Trapping Success in Protected Areas of Eastern Puerto Rico
Diana Guzmán-Colón1,* and Gary J. Roloff 1
Abstract - Herpestes auropunctatus (Small Asian Mongoose) was introduced in Caribbean
islands at the end of the 19th century and has triggered concern for natural resource managers
following declines in bird and herpetile populations subsequent to the mongoose introduc-
tions. We quantied mongoose abundance in protected areas of eastern Puerto Rico and
described how localized habitat features inuenced trapping success. We used mark–recap-
ture to estimate abundance and relate mongoose capture probabilities to habitat conditions.
Small Asian Mongoose abundance was greater in the coastal forest type, but we found no
relationship between capture frequencies and habitat characteristics. This study provides
an initial assessment of Small Asian Mongoose population status in areas of eastern Puerto
Rico and offers baseline data for subsequent capture-recapture studies.
Introduction
Herpestes javanicus auropunctatus (Hodgson) (Small Asian Mongoose; hereaf-
ter Mongoose) is an opportunistic omnivore in the order Carnivora. Mongoose were
introduced to Caribbean and Pacic Islands with established sugar industries during
the late 1800s to control Rattus sp. (rat), which damaged sugar cane crops (Espeut
1882, Everard and Everard 1992). Mongoose failed to suppress rat populations and
were quickly recognized to be detrimental to native species (Hays and Conant 2007,
Philibosian and Ruibal 1971, Seaman and Randall 1962, Watari et al. 2008). Along
with other introduced mammalian predators like Felis catus L. (Domestic Cat) and
Canis lupus familiaris L. (Domestic Dog), Mongoose have likely contributed to
declines of terrestrial vertebrate populations in Hawaii and Puerto Rico (Engeman
et al. 2006, Hays 1999). Additionally, Mongoose are recognized as a reservoir and
vector for rabies, which has caused concern about disease transmission and spread
(Nadin-Davis et al. 2008, Pimentel 1955). Different management practices to con-
trol Mongoose populations have been implemented, but populations remain stable
range-wide (Quinn and Whisson 2005).
Mongoose occurrence on subtropical islands has exerted a strong pressure on
threatened species (Gorman 1975, Nellis and Everard 1983, Nellis and Small 1983,
Watari et al. 2008). In el Yunque National Forest (YNF), for example, Mongoose
occupy areas where Amazonia vittata B. (Puerto Rican parrot; IUCN Red List: Criti-
cally Endangered) has been reintroduced (Vilella 1998) and since 2000, six wild
parrots (3% of the remaining wild population) have been lost to Mongoose predation
1Department of Fisheries and Wildlife, Michigan State University, East Lansing, MI, 48824.
*Corresponding author - dguzmancolon@wisc.edu.
Manuscript Editor: J. Angel Soto-Centeno
Caribbean Naturalist
D. Guzmán-Colón and G.J. Roloff
2014 No. 19
2
(Engeman et al. 2006). Although Mongoose are not the primary predator of parrots
in YNF, a plan to simultaneously integrate Mongoose control into existing predator
management programs (i.e., rat control) could prove effective at reducing threats to
parrots, and other wildlife species. Analyses of stomach contents reveal that Mon-
goose prey mainly on macroinvertebrates, small reptiles, and amphibians (Gorman
1975, Nellis and Everard 1983, Pimentel 1955, Vilella 1998). These dietary prefer-
ences can potentially have a detrimental effect on some herpetile species.
In Puerto Rico and other Caribbean and Pacic islands, Mongoose presence is
more apparent in coastal habitats including dry forests, scrub areas, and pasturelands
(Pimentel 1955, Vilella 1998, Vilella and Zwank 1993). Prevalence of Mongoose
throughout YNF may be related to their adaptability to new environments and their
overall ecological generalist nature. Mongoose have a complex social structure,
diverse feeding habits, and high adaptability, with behavior differing depending
on locality (Vilella 1998). These characteristics likely make effective management
strategies location-specic. Management strategies involving population control,
data on demography, and spatial distribution are needed. Currently the population
size of Mongoose in YNF is unknown. In this paper, we aimed to provide an initial
estimate of Mongoose abundance in YNF by conducting a mark-recapture study in
a population assumed to be closed geographically. Ultimately, this type of informa-
tion can be used to inform Mongoose management plans.
The overall aim from our project is to contribute to a better understanding of
Mongoose abundance in YNF and an eastern coastal area of Puerto Rico, and de-
scribe how trapping success might be inuenced by localized habitat features. We
hypothesized that Mongoose population abundance in YNF is low compared to
coastal areas and that denser vegetation and woody debris will increase capture
probability. To test this hypothesis, we 1) compared Mongoose abundance between
YNF and adjacent coastal area, 2) compared habitat conditions among the dominant
forest types found in YNF and the coastal area sampled, and 3) evaluated the cor-
relation between the likelihood of capturing a Mongoose and habitat conditions in
the dominant forest types and the coastal area.
Field-Site Description
El Yunque National Forest is located in the Luquillo Mountains in northeast
Puerto Rico (Fig. 1). Elevations of YNF range from 600 to 1080 m and the forest re-
ceives ~5000 mm of annual rainfall (Murphy and Stallard 2012). The YNF consists
of four forest types that are generally delineated by elevation and coarse vegetation
structure (Table 1). Dacryodes excelsa Vahl (Tabonuco) forest occurs on mountain
foothills with an elevation <600 m; Cyrilla racemiora L. (Palo Colorado) and
Prestoea acuminata var. montana (Graham) A.J. Hend. & Galeano (Sierran Palm)
forests occur between 600 m and 850 m; and the dwarf forest (or Eln woodlands)
occurs >850 m.
Some rivers and associated riparian zones from YNF ow north into the North-
eastern Ecological Corridor (NEC; Fig. 1). The NEC is a protected nature reserve
that encompasses 1202 ha of undeveloped land and includes 10.5 km of coastline.
Caribbean Naturalist
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D. Guzmán-Colón and G.J. Roloff
2014 No. 19
The NEC is composed of secondary forest and scattered wetlands, and receives an
average of 1500 mm of rain annually (Murphy and Stallard 2012). Coastal forests
tend to be drier and dominated by shrub vegetation.
Figure 1. Island of Puerto Rico (inset) and location of El Yunque Nationa Forest (YNF) and
the Northeast Ecological Rorridor (NEC) in eastern Puerto Rico. Map shows trap locations
along sereral roads and trails in YNF and NEC.
Caribbean Naturalist
D. Guzmán-Colón and G.J. Roloff
2014 No. 19
4
Methods
Mongoose capture and handling
We trapped Mongoose at each forest type in YNF and the coastal forest in the
NEC from May to July 2012. We used wire live traps (66 cm L x 22 cm W x 22 cm
H; Tomahawk Live Trap LCC, Hazelhurst, WI, USA), each with an easy-release
door and baited with canned tuna. Site locations for trapping were based on the oc-
currence of representative vegetation structure of each forest type. Because of the
rough terrain and accessibility in YNF, we placed traps near roads or trail network
to facilitate site access. At each trapping site, we deployed a 5 x 5 trap grid (25
traps) at 25-m spacing (125 x 125 m) and monitored the traps for ve days. Trap
locations were recorded with a handheld global positioning system (GPS) receiver
(Garmin International, Inc., Olathe, KS, USA).
Traps were opened and baited every morning before 0900 hr, checked, and
closed in the late afternoon. Captured individuals were immobilized by inject-
ing 1 cc of an intramuscular solution of xylazine. The solution was prepared by
Table 1. Forest types, coarse vegetation structure, and dominant plant species in El Yunque National
Forest (YNF), Puerto Rico (Quinn and Whisson 2005, Weaver 2008).
Forest type Dominant species Understory (dominant)
Tabonuco Dacryodes excelsa Diverse understory that varies with location:
High slopes
Cecropia schreberiana Miq. (Pumpwood)
Sloanea berteroana Chisy ex DC. (Bullwood)
Prestoea acuminata var. montana
Ridges
Cyrilla racemiora L. (Swamp Titi),
Schefera morototoni (Aubl.) Maguire, Steyerm.
& Frodin (Morototo)
Palo Colorado Cyrilla racemiora Dense patches of ornamental plants:
Prestoea acuminata var. Sanchezia speciosa Leonard (Firecracker)
montana Hamelia patens Jacq. (Coral)
Bambusa vulgaris Schrad. ex J.C. Wendl. (Com-
mon Bamboo)
Impatiens sp. (impatients)
Sierra Palm Prestoea acuminata var. Structure is similar to Palo Colorado forest.
montana Sierran Palm can be intertwined with Tabonuco
and Dwarf Forests.
Dwarf Forest Ocotea spathulata Mez Epiphytes, Bromeliads, and Fern species (Cyathea
(Nemoca Cimarrona) bryophylla (R. Tryon) Proctor and C.
Tabebuia rigida Urb. (Roble arborea (L.) Sm. [Helecho Gigante]). There is not
de Sierra) a distinction between understory and canopy veg-
Calyptranthes krugii Kiaersk. etation in this forest type. Prestoea acuminata var.
(Limoncillo) montana is also found.
Eugenia borinquensis Britton
(Guayabota de Sierra)
Henriettea squamulosum
(Cogn.) W.S. Judd (Jusillo)
Caribbean Naturalist
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D. Guzmán-Colón and G.J. Roloff
2014 No. 19
combining 0.5 ml of xylazine with 5 ml of distilled water in a sterilized blood-
collection tube. Each Mongoose was ear-tagged with a unique numbered metal tag,
sexed, and weighed. We also recorded the condition of the fur, tooth wear, and body
length (nose to base of tail) for each captured individual. After Mongoose recovered
from the anesthesia, they were released at the capture site. Forest Service personnel
trapped and handled all captured Mongoose. Hence, the project was deemed exempt
from the Institutional Animal Use and Care Committee requirements at Michigan
State University.
Habitat characteristics
We collected habitat data at each individual trap location on the day that the
trap grid was established. These data included visual estimates of understory cover
(%), canopy cover (%), and woody debris (%) within a 5-m radius plot centered on
the trap. Because of the nature of the data, we grouped cover estimates into four
categories (0%; 1–30%; 31–60%; 61–100%) and tabulated the number of plots
in each category as a measure of grid-level cover. We considered trees <60 cm in
height to be part of the understory. Woody debris ≥4 cm in diameter was included
in downed-wood estimates. The number of cover classes used in each analysis
differed because of low cell counts for some categories. In these instances, cover
classes were merged.
We used Fisher’s exact test (two-sided) to compare three classes of canopy cover
(0–30%, 31–60%, and 61–100%) among the ve forest types. We also used Fisher’s
exact test to compare the four cover categories for downed wood among the ve
forest types. Fisher’s exact test provides a more robust approximation than the
chi-squared test when expected cell counts are small. We used a chi-squared test to
compare three classes of understory cover (0%, 1–60%, and 61–100%) among the
ve forest types.
Mark-recapture
Mongoose home ranges vary between 2 to 8 ha, and individual home ranges
likely overlap (Hays 1999). Hence, we assumed that Mongoose home ranges over-
lapped our grids and that the population was closed during our 5-day sampling
event (i.e., there were no births, deaths, immigration, or emigration). We used the
RCapture package for R (R Development Core Team 2010) to t the mark–recap-
ture data to the closed-population models described by Otis et al. (1978). These
models are useful to derive abundance estimates and capture probabilities and to
identify sources of heterogeneity in the capture probabilities. We estimated Mon-
goose abundance for the tropical rainforests of YNF collectively and separately for
the coastal habitat of the NEC.
Capture frequency and habitat
To relate the likelihood of capturing a Mongoose to measured habitat char-
acteristics, we calculated average daily capture frequencies (based on a possible
125 traps per day) for each forest type. Traps that contained non-target species
or that were sprung were censored from the daily calculations. We also con-
Caribbean Naturalist
D. Guzmán-Colón and G.J. Roloff
2014 No. 19
6
verted cover estimates for canopy cover, understory cover, and woody debris to
binary data (i.e., present or absent) at each trap location. Subsequently, the num-
ber of plots with cover present in a forest type can be viewed as a patch-level
cover estimate.
Results
Habitat characteristics
Tabonuco forest consistently had the highest canopy cover (61–100% on 88% of
the vegetation plots) among the ve forest types. This nding indicated that canopy
cover was relatively contiguous in that forest type. Dwarf forest had the lowest
canopy cover (0–30% on 80% of the vegetation plot). Canopy cover in Palo Colo-
rado and Sierra Palm forests was generally dichotomous, i.e., plot locations either
had high or low canopy cover, which suggested a patchy distribution. Canopy cover
differed among forest types (P < 0.001), with coastal forest having the most diverse
cover among plots. These results indicate that we sampled a relatively complete
gradient of canopy-cover conditions during trapping.
Understory cover was highest (61–100% on 76% of the vegetation plots) in
dwarf forest and lowest (0% on 44% of the vegetation plots) in Sierra Palm. Under-
story cover in coastal, Palo Colorado, and Sierra Palm forests was variable among
plots, with intermixed patches of 0%, 1–60%, and 61–100% cover. The chi-squared
test for understory cover indicated signicant differences among forest types (=
30.57, P < 0.001).
Woody debris cover was generally low among the ve forest types we sampled,
with the majority of plots containing <61–100% cover. Palo Colorado and Sierra
Palm were the only forest types with some plots having high (61–100%) downed
wood cover. There were signicant differences in downed wood cover among the
four forest types (Fisher’s exact test; P < 0.001).
Mark–recapture
We trapped 34 Mongoose, with 30 individuals captured and 4 recaptures
(Table 2). The sex ratio differed between forest types, but across all grids was
1:1 (Table 2). On average, males were significantly heavier (mean = 2.60 kg,
SE = 0.07; t30 = -2.708, P = 0.01) than females (mean = 2.20 kg, SE = 0.10).
However, the sexes did not differ in body length (t30 = -0.1666, P = 0.87); males
averaged 296 cm (SE = 0.36), whereas females averaged 293 cm (SE = 0.35).
Table 2. Mongoose trapping results by forest type in El Yunque National Forest (i.e., Palo Colorado,
Sierra Palm, and Dwarf) and coastal type in the Northeast Ecological Corridor, Puerto Rico, 2012.
Females Males
Forest Type n Recaptures n Recaptures Total
Palo Colorado 3 1 2 1 5
Sierra Palm 5 0 2 0 7
Dwarf 1 0 2 0 3
Coastal 8 0 11 2 19
Caribbean Naturalist
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D. Guzmán-Colón and G.J. Roloff
2014 No. 19
Also, Mongoose weight and body size did not vary by forest type (F3,33 = 0.75,
P = 0.53 and F3,33 = 1.13, P = 0.40, respectively; Table 3). Fifteen rats, 1 cat, and 4
Epilobocera sinuatifrons (A. Milne-Edwards) (Buruquena) freshwater crabs were
also trapped during the study. Mongoose were not captured on the Tabonuco for-
est site. Although there is a possibility of Mongoose being present on this site but
not detected, a closed-population model cannot account for non-detectability and
will not calculate abundance when there are no captures or recaptures. Therefore,
we excluded the Tabonuco forest from our analyses.
Our competing models for YNF included M0, Mh, and Mt. The top three models
included for NEC were Mt, Mb, and M0. These models (estimators) account for
different sources of variation in the capture probabilities. M0 assumes that every
animal in the population has the same capture probability for the study. Mh as-
sumes that each animal has a unique capture probability which remains constant
for all trapping occasions. Mb corrects for a change in capture probabilities due to
the animal’s response to trapping, although it assumes that the initial capture prob-
ability for all animals is the same. Mt (Schnabel) allows for time variation and as-
sumes that every individual in the population has the same capture probability for
a given sampling occasion, but these probabilities can vary at each sampling time.
Because our number of captures and recaptures were too small, we took caution in
choosing a model that suggested a time-specic or behavioral response. Our main
interest was to estimate abundance (N) and capture probabilities (p); thus, we based
our estimates on the M0 model with bias correction for small samples (Rivest and
Lévesque 2001). We estimated 41.9 (SE = 15.3) Mongoose with a capture prob-
ability of 0.08 for YNF and 83.9 (SE = 31.3) Mongoose with a capture probability
of 0.05 from the grids located in the coastal forest.
Table 3. Average mongoose weight (SE) and body size (SE) by forest type in El Yunque National For-
est (i.e., Palo Colorado, Sierra Palm, and dwarf forest) and coastal type in the Northeast Ecological
Corridor, Puerto Rico, 2012.
Habitat type Weight (kg) Body length (mm)
Palo Colorado 0.997 (0.03) 270 (23.4)
Sierra Palm 1.140 (0.09) 279 (20.9)
Dwarf 1.000 (0.05) 270 (46.7)
Coastal 1.100 (0.05) 308 (9.9)
Table 4. Average daily captures (SE) and percentage of canopy cover, understory cover, and downed
wood by forest type in El Yunque National Forest (i.e., Palo Colorado, Sierra Palm, and dwarf forest)
and coastal type in the Northeast Ecological Corridor, Puerto Rico, 2012.
Percent of coverage for all plots
Forest Mean daily captures (SE) Canopy cover Understory cover Downed wood
Coastal 0.17 (0.02) 72 76 0
Tabonuco 0.00 (0.00) 100 88 88
Palo Colorado 0.07 (0.02) 68 80 68
Sierra Palm 0.06 (0.02) 56 56 52
Dwarf Forest 0.02 (0.00) 44 80 0
Caribbean Naturalist
D. Guzmán-Colón and G.J. Roloff
2014 No. 19
8
Capture frequency and habitat
The highest Mongoose capture frequency (0.17 captures per day) was observed
in coastal forest, and the lowest capture frequency (0.00 captures per day) was in
Tabonuco (Table 4). No consistent patterns in daily capture frequency of Mongoose
and coarse measures of vegetation were identied, suggesting that patch-level
canopy cover, understory vegetation, or downed wood were not correlated with
trapping success. For example, canopy cover was highest in coastal and Tabonuco
forest types but the extremes of Mongoose capture frequency were observed in
these forest types (Table 4). Likewise, downed wood was absent from coastal and
dwarf forests, but capture frequencies were >8 times higher in coastal forest. The
presence of understory cover was consistently high among forest types (ranging
from 56% to 88% of the plots) yet capture frequencies of Mongoose varied consid-
erably (Table 4). In our study, patch-level vegetation structure did not consistently
relate to Mongoose capture frequency.
Discussion
We found that the coastal forest of eastern Puerto Rico supported a greater
abundance of Mongoose than the forest types of YNF combined. Among the four
forest types sampled in YNF, Mongoose were most frequently captured in the mid-
elevation Palo Colorado and Sierra Palm types. Visitor facilities on the northern
slopes of YNF are concentrated in these forest types. Further, our results suggest
that vegetation structures associated with forest types on YNF are not related to
Mongoose captures and hence, other factors such as resource availability should be
considered. We caution that our observations of Mongoose abundance and captures
may not represent broad-scale patterns across YNF because this study was spatially
(5 sites) and temporally (1 summer) restricted. We recommend a more spatially and
temporally extensive trapping effort to further clarify these relationships.
In Puerto Rico, high-quality Mongoose habitats tend to occur in dry and scrub
areas (Pimentel 1955, Vilella and Zwank 1993). Our ndings were consistent with
these studies in that tropical forests of YNF supported fewer Mongoose than the
drier, scrubbier coastal habitat of eastern Puerto Rico. Other studies have also
found that Mongoose have a general tendency to avoid rainy areas in the islands of
St. Croix, Trinidad, and St. John’s (Coblentz and Coblentz 1985, Nellis and Everard
1983). The mechanism causing this pattern is unclear. Pimentel (1955) suggested
that Mongoose occur at lower abundances in forested areas because prey and shel-
ter are less available; however, this assertion was not directly tested in that study.
Although we did not document marked Mongoose moving among trapping grids
in our study, coastal habitats and YNF are connected both by natural structures such
as riparian corridors as well as a number of major roads. Mongoose are known to
favor roadside habitats; hence, population control measures for YNF need to ac-
knowledge the possibility of having constant movement of individuals from adjacent
forest habitats and those moving from the coastal forest along roadside habitats.
To improve trapping success or increase sightings, forest habitat characteristics
are commonly used to predict occupancy of an area by organisms (Baldwin and
Caribbean Naturalist
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D. Guzmán-Colón and G.J. Roloff
2014 No. 19
Bender 2008, Erwin 2011, Hoffman 2010, Wiebe et al. 2013). In this study, Mon-
goose capture frequency was not related to the habitat elements that we thought
would correlate with Mongoose habitat selection (i.e., canopy cover, understory
cover, and woody debris). The Sierra Palm and Palo Colorado sites were closer
to recreational areas, and these forest types had the highest Mongoose capture
frequencies in YNF. Those results suggest that Mongoose abundance in the park is
more closely associated with human activity (e.g., around trails and trash) as op-
posed to vegetation structure.
It has been proposed that Mongoose use recreation areas when human activity
within YNF increases, potentially exploiting food or prey made available by poor
sanitation practices (Quinn et al. 2006). Improvements in trash management have
resulted in fewer Mongoose sightings in YNF parks (L. Rivera, Plant Biologist,
USFS, Puerto Rico, pers. comm). Mongoose do not necessarily come into direct
contact with humans in these areas, but rather use recreational sites when human
activity is low. Indeed, Quinn et al. (2006) and Leighton et al. (2008) found that
Mongoose tended to avoid direct human contact unless infected with the rabies
virus. Consistent with these observations from Puerto Rico, Hussain et al. (2011)
found that Mongoose populations in Pakistan were higher in areas located close to
villages compared to wild areas and croplands. Hussain et al. (2011) inferred that
Mongoose occurred in proximity to villages because of high rodent populations in
the area. It is plausible that Mongoose in YNF may also be attracted to recreation
areas because prey may occur at higher densities in areas frequented by humans. To
further understand the relationship between Mongoose and recreationists on YNF,
future research should explore how food left over by visitors inuence Mongoose
prey (e.g., insects, rats and other vertebrates) and its relationship to augmenting
localized Mongoose populations.
We recognize several limitations to our study. The study occurred over a single
season (summer 2012), and so our Mongoose population estimates do not reect
uctuations related to seasonal variations. A low number of recaptures precluded
the use of more sophisticated population-estimation approaches, and hence we
were unable to include the effects of individual animal covariates such as age,
reproductive status, or sex on capture success. The M0 model underestimates
population size because it does not take into account animal heterogeneity or trap
response (Pollock 1981). Additionally, we only surveyed areas of YNF that were
accessible via trails, which do not represent a random sample of habitats. There-
fore, Mongoose population status in less-visited areas of the park, such as release
sites for the Puerto Rican parrot, remains to be studied. Nevertheless, this assess-
ment provides the rst published study using marked and released Mongoose on
YNF and thus offers a baseline data for subsequent capture–recapture studies.
Management implications
Species invasions in ecosystems have ecological, social, and economic impli-
cations (Esler et al. 2010). Mongoose impacts on ecological, social, and economic
factors has been well-documented (Barun et al. 2010, Coblentz and Coblentz
Caribbean Naturalist
D. Guzmán-Colón and G.J. Roloff
2014 No. 19
10
1985, Fukasawa et al. 2013, Nellis and Small 1983, Watari et al. 2008). The
primary management goal for Mongoose in YNF is to reduce threats to humans
and animals by avoiding further rabies transmission and predation on other vul-
nerable wildlife. Our local study showed that areas in Palo Colorado and Sierra
Palm forest had the highest number of individuals in YNF, but that population
abundance was higher in the adjacent coastal forest (NEC). Thus, effective Mon-
goose management likely extends beyond the YNF boundary where the Forest
Service does not have jurisdiction. For Mongoose management, it is important to
consider seasonality, Mongoose dispersal, and breeding patterns during control
programs. For example, Mongoose trapping success declines during rainy days
and when females are nursing because they use smaller home ranges during that
time (Barun et al. 2010, Hays and Conant 2007). Additionally, trap success will
likely be highest during the end of the dry season when Mongoose populations
are highest and known to be dispersing for breeding (Hays 1999). Furthermore,
Mongooses in YNF presumably use consistent travel routes (Quinn and Whisson
2005). For further research in YNF regarding Mongoose invasions, information
regarding the source and preferred dispersal routes, as well as the degree to which
populations are connected, can assist managers with their goals, whether that be
reducing the numbers of Mongoose or eradicating them from some areas.
Acknowledgments
We thank Felipe Cano, Pedro Ríos, Benjamín Fuentes, and Anastacio Gómez from the
USDA Forest Service for eld assistance and advice. Pedro Quiñones and Kurt Vercauteren
from APHIS provided suggestions on methodology. Two anonymous reviewers provided
helpful comments on early versions of this manuscript. Funding for this project was
provided by the Michigan State/University of Puerto Rico Partnership in Environmental
Conservation and the Forest Service.
Literature Cited
Baldwin, R.A., and L.C. Bender. 2008. Distribution, occupancy, and habitat correlates of
American Martens (Martes americana) in Rocky Mountain National Park, Colorado.
Journal of Mammalogy 89(2):419–427.
Barun, A., C.C. Hanson, K.J. Campbell, and D. Simberloff. 2010. A review of Small Indian
Mongoose management and eradications on islands. International Conference on Island
Invasives: Eradication and Management. Auckland, New Zealand, IUCN 12:17–25.
Coblentz, B.E., and B.A. Coblentz. 1985. Control of the Indian Mongoose, Herpestes
auropunctatus, on St-John, United States Virgin Islands. Biological Conservation
33(3):281–288.
Engeman, R., D. Whisson, J. Quinn, F. Cano, P. Quinones, and T.H. White. 2006. Monitor-
ing invasive mammalian predator populations sharing habitat with the critically endan-
gered Puerto Rican Parrot, Amazona vittata. Oryx 40(1):95–102.
Erwin, M.D. 2011. Population characteristics and habitat selection of Muskrats (Ondatra
zibethicus) in response to water level management at the Summerberry Marsh Complex,
The Pas, Manitoba, Canada. M.Sc. Thesis. Iowa State University, Ames, IA, USA.
Esler, K.J., H. Prozesky, G.P. Sharma, and M. McGeoch. 2010. How wide is the “know-
ing–doing” gap in invasion biology? Biological Invasions 12(12):4065–4075.
Caribbean Naturalist
11
D. Guzmán-Colón and G.J. Roloff
2014 No. 19
Espeut, W.B. 1882. On the acclimatization of the Indian Mongoose in Jamaica. Proceedings
of the Zoological Society of London 1882:712–714.
Everard, C.O.R., and J.D. Everard. 1992. Mongoose rabies in the Caribbean. Annals of the
New York Academy of Sciences 653:356–366.
Fukasawa, K., T. Hashimoto, M. Tatara, and S. Abe. 2013. Reconstruction and prediction of
invasive mongoose population dynamics from history of introduction and management:
A Bayesian state-space modelling approach. Journal of Applied Ecology 50(2):469–478.
Gorman, M.L. 1975. The diet of feral Herpestes auropunctatus (Carnivora:Viverridae) in
the Fijian Islands. Journal of Zoology 175(2):273–278.
Hays, W.S.T. 1999. Annual dispersal cycle of the Small Indian Mongoose (Herpestes auro-
punctatus) (Carnivora: Herpestidae) in Hawai’i. Pacic Science 53(3):252–252.
Hays, W.S.T., and S. Conant. 2007. Biology and impacts of Pacic Island invasive species.
1. A worldwide review of effects of the Small Indian Mongoose, Herpestes javanicus
(Carnivora: Herpestidae). Pacic Science 61(1):3–16.
Hoffman, J.N. 2010. Habitat characteristics affecting Allegheny Woodrat (Neotoma ma-
gister) populations on the Chestnut Ridge in Southwestern Pennsylvania. M.Sc. Thesis.
Indiana University of Pennsylvania, Indiana, PA, USA
Hussain, I., T. Mahmood, and M.S. Nadeem. 2011. Population estimates, habitat prefer-
ence, and the diet of Small Indian Mongoose (Herpestes javanicus) in Potohar Plateau,
Pakistan. Pakistan Journal of Zoology 43(1):103–111.
Leighton, P.A., J.A. Horrocks, B.H. Krueger, J.A. Beggs, and D.L. Kramer. 2008. Predict-
ing species interactions from edge responses: Mongoose predation on Hawksbill Sea
Turtle nests in fragmented beach habitat. Proceedings of the Royal Society Biological
Sciences 275(1650):2465–2472.
Murphy, S.F., and R.F. Stallard. 2012. Water quality and landscape processes of four wa-
tersheds in eastern Puerto Rico. United States Geological Survey, Professional Paper
1789:292.
Nadin-Davis, S.A., J. Velez, C. Malaga, and A.I. Wandeler. 2008. A molecular epidemio-
logical study of rabies in Puerto Rico. Virus Research 131(1):8–15.
Nellis, D.W., and C.O.R. Everard 1983. The biology of the mongoose in the Caribbean.
Studies of the fauna of Curacao and other Caribbean islands 64:1–162.
Nellis, D.W., and V. Small 1983. Mongoose predation on sea turtle eggs and nests. Biotro-
pica 15(2):159–160.
Otis, D.L., K.P. Burnham, G.C. White, and D.R. Anderson. 1978. Statistical-inference from
capture data on closed animal populations. Wildlife Monographs(62):7–135.
Philibosian, R., and R. Ruibal. 1971. Conservation of the lizard Ameiva polops in the Virgin
Islands. Herpetologica 27(4):450–454.
Pimentel, D. 1955. Biology of the Indian Mongoose in Puerto Rico. Journal of Mammalogy
36(1):62–68.
Pollock, K.H. 1981. Capture-Recapture models: A review of current methods, assumptions,
and experimental design. Pp. 426–435, In C.J. Ralph and J.M. Scott. (Eds.). Estimating
Numbers of Terrestrial Birds, Studies in Avian Biology, Cooper Ornithological Society,
Camarillo, CA, USA.
Quinn, J.H., and D.A. Whisson. 2005. The effects of anthropogenic food on the spatial
behaviour of Small Indian Mongooses (Herpestes javanicus) in a subtropical rainforest.
Journal of Zoology 267:339–350.
Quinn, J.H., D.A. Whisson, and F. Cano. 2006. Managing the Small Indian Mongoose (Her-
pestes javanicus) in the midst of human recreation: What is the optimal approach? Pp.
393–398, In R.M. Timm and J.M. O’Brien (Eds.). Proceedings of the 22nd Vertebrate
Pest Conference. University of California, Davis, CA, USA.
Caribbean Naturalist
D. Guzmán-Colón and G.J. Roloff
2014 No. 19
12
R Development Core Team. 2010. R: A language and environment for statistical computing.
R Foundation for Statistical Computing, Vienna, Austria.
Rivest, L.-P., and T. Lévesque. 2001. Improved log-linear model estimators of abundance in
capture-recapture experiments. Canadian Journal of Statistics 29(4):555–572.
Seaman, G.A., and J.E. Randall. 1962. The mongoose as a predator in the Virgin Islands.
Journal of Mammalogy 43(4):544–546.
Vilella, F.J. 1998. Biology of the mongoose (Herpestes javanicus) in a rain forest of Puerto
Rico. Biotropica 30(1):120–125.
Vilella, F.J., and P.J. Zwank. 1993. Ecology of the Small Indian Mongoose in a coastal dry
forest of Puerto Rico where sympatric with the Puerto Rican Nightjar. Caribbean Journal
of Science 29(1–2):24–29.
Watari, Y., S. Takatsuki, and T. Miyashita. 2008. Effects of exotic mongoose (Herpestes
javanicus) on the native fauna of Amami-Oshima Island, southern Japan, estimated by
distribution patterns along the historical gradient of mongoose invasion. Biological
Invasions 10(1):7–17.
Weaver, P.R.L. 2008. Dwarf forest recovery after disturbances in the Luquillo mountains of
Puerto Rico. Caribbean Journal of Science 44(2):150–163.
Wiebe, P.A., J.M. Fryxell, I.D. Thompson, L. Borger, and J.A. Baker. 2013. Do trappers
understand Marten habitat? Journal of Wildlife Management 77(2):379–391.
