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Small Indian mongoose (Herpestes auropunctatus) population abundance and effects of habitat features on trapping success in protected areas of eastern Puerto Rico

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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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,
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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,
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,
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,
Christopher Starr, Department of Life Sciences, University of the West Indies, St. Augustine, Trinidad and
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,
Caribbean Naturalist
D. Guzmán-Colón and G.J. Roloff
2014 No. 19
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 quantied mongoose abundance in protected areas of eastern Puerto Rico and
described how localized habitat features inuenced 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.
Herpestes javanicus auropunctatus (Hodgson) (Small Asian Mongoose; hereaf-
ter Mongoose) is an opportunistic omnivore in the order Carnivora. Mongoose were
introduced to Caribbean and Pacic 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 -
Manuscript Editor: J. Angel Soto-Centeno
Caribbean Naturalist
D. Guzmán-Colón and G.J. Roloff
2014 No. 19
(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 Pacic 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-specic. 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 inuenced 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 racemiora 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 Eln 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
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
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
Cyrilla racemiora L. (Swamp Titi),
Schefera morototoni (Aubl.) Maguire, Steyerm.
& Frodin (Morototo)
Palo Colorado Cyrilla racemiora 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
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.
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
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.
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 signicant 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 signicant differences in downed wood cover among the
four forest types (Fishers exact test; P < 0.001).
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
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-specic 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
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 identied, 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.
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
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 inuence 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 reect
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
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.
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.
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... [Nemoca Cimarrona]) that commonly experience wind- driven clouds ( Brokaw et al. 2012, Reagan andWaide 1996). Rodent sampling that occurred at sea level was outside the CNF but within the NEC, which is 1202 ha of undeveloped and protected land that includes 10.5 km of coastline; the NEC re- ceives 1500 mm of rainfall per year and is dominated by coastal forest-shrubs and scattered wetlands (Guzmán-Colón and Roloff 2014). Black Rats have been documented in the CNF in closed-canopy habitat of Tabo- nuco, Palo Colorado, and Palm forest; however, Norway Rats and House Mice have not been previously documented in the CNF despite rodent trapping ( Engeman et al. 2006, Weinbren et al. 1970, Willig and Gannon 1996 and tracking-plate assessment ( Engeman et al. 2006) in many of the same areas that we sampled in our study. ...
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Invasive rodents, particularly rats (Rattus spp.), occupy >80% of the world’s islands and are among the greatest threats to native biodiversity and agriculture on islands. At the time of their introduction in the 1500s, there was at least 1 native rat species in Puerto Rico. Today there are no native rodents remaining in Puerto Rico, but R. norvegicus (Norway Rat) may be found in urban settings, and R. rattus (Black Rat) are the most common rat across the island including within natural areas, and invasive Mus musculus (House Mouse) may also be found in urban and non-urban habitats. The Caribbean National Forest (CNF; locally El Yunque) in northeastern Puerto Rico has some native and endangered species vulnerable to rat predation. The objective of our study was to determine the presence and distribution of invasive rodents (rats and mice) across elevations and habitats within the CNF. We used 104 tracking tunnels, which are baited ink cards placed in tunnels so that foot prints of animal visitors could be identified, to determine presence of invasive rodent species. We placed 3 tracking tunnels at each 50-m elevation-gain (n = 66 total tunnels), on the edge of forest habitat from sea level to 1070 m at El Yunque peak along the main road (Highway 191) through the CNF. We established additional tracking tunnels (n = 38) in the major habitats in the CNF, including treefall and hurricane gaps, landslides, stream edges, and continuous forest. House Mice had not been previously reported in the CNF, and were found only at the forest edge along Highway 191 at elevations of 50–150 m and 300–1070 m, whereas rats (Rattus sp.) were found at all elevations and in all habitat types sampled. Logistic regressions revealed that mice and rat presence each increases with elevation (mice: P = 0.0352, rat: P = 0.0019), though total rodent presence did not. Knowledge of the habitat types and elevations that these invasive rodents occupy can inform management strategies for rodent control and native species protection.
... Mongoose population density in the Caribbean ranges from 0.19 to 9.0 mongooses/ha (Pimentel 1955a,b;Hoagland et al. 1989;Corn and Conroy 1998;Vilella 1998;Horst et al. 2001;Quinn and Whisson 2005;Hudson 2010;Johnson et al. 2016). Horst et al. (2001) suggested that mongoose population density in Puerto Rico was lower in grasslands than semiwooded regions, Vilella (1998) found relatively low densities in montane humid and rainforest regions, but Guzmán-Colón and Roloff (2014) found no correlation between habitat type and population density. Population densities in Hawaii are estimated at 0.04 mongoose/ha in lowland wetlands to 3.0/ha in moist forests (Stone et al. 1994). ...
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The small Indian mongoose (Herpestes auropunctatus) is a diurnal opportunistic omnivore native to parts of the Middle East, India, and Asia (Corbet and Hill 1992; Lekagul and McNeely 1977; Veron et al. 2007). Much of what is known about the species comes from records of populations where they were introduced to control rodents on sugarcane plantations (predominantly the Caribbean Islands and Hawaii) rather than their native range (Horst et al. 2001). In published research, the introduced mongoose is alternately, and often synonymously, identied as H. auropunctatus or H. javanicus. However, research by Veron et al. (2007) suggests that H. auropunctatus and H. javanicus are distinct taxa with unique biogeographic ranges: H. auropunctatus from the Middle East to Myanmar and H. javanicus from Myanmar and east, throughout Southeast Asia. Myanmar represents the eastern and western limits of H. auropunctatus and H. javanicus, respectively (Veron et al. 2007). Given documentation by Espeut (1882) that the mongoose’s introduced to the Caribbean, and later Hawaii, originated from Calcutta, India, it is now generally accepted that the mongoose species introduced to North America is H. auropunctatus.
... Oral rabies vaccination strategies require knowledge of target species population density (Slate et al. 2008), which varies by habitat and season (Guzman-Colon & Roloff 2015;Johnson et al. 2016;Quinn & Whisson 2005), and may be higher in areas with anthropogenic resources (Quinn & Whisson 2005). Increased potential for human-mongoose and domestic animal-mongoose interactions in high population density areas underscore the need for mongoose management and vaccination programs. ...
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A wide array of sizes, ecosystems, cultures, and invasive wildlife are represented among inhabited islands. Here, six cases from the United States of America (US) are selected to illustrate the high diversity of invasive animal management issues and objectives. We outline the background, define the problems and management objectives. We identify the management approaches and discuss the results and influences as they specifically relate to inhabited islands. The examples are: (1) Gambian giant pouched rats on Grassy Key, Florida; (2) coqui frogs on Kaua’i, Hawai’i; (3) feral swine on Cayo Costa Island, Florida; (4) rodents and monitor lizards on Cocos Island, Guam; (5) black spiny-tailed iguanas (ctenosaurs) on Gasparilla Island, Florida; and (6) mongooses on Puerto Rico. The outcomes of the programs are discussed, particularly in relation to the impact of human habitation on success.
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In this chapter, the reader will notice that in the Puerto Rico Archipelago (PRA) – and probably elsewhere – we still lack information that would be valuable for the conservation and management of the vast majority of amphibians. For instance, we still have much to learn about the natural history, reproductive phenology, population biology, and dynamics of assemblages of species in a variety of environ- mental situations. We also lack information on the physiological responses of amphibians from the perspective of expected changes in climate, examples being shifts in elevational distribution and migration in response to sea-level rise and intrusion of salt water into coastal areas. Bridging the gap between herpetology and other disciplines (e.g. successional ecology, social sciences, and geographic information systems) is fundamental if we are to prioritize efforts towards the con- servation of amphibians and their ecosystems. Accordingly, we provide a brief description of land-use and changes in land-cover in PR and the VI through history, and summarize the anurans in the PRA. Note that whenever we use ‘VI’ as a stand-alone name in the text, we mean the USVI and BVI combined as a subset of islands in a geographical context. Finally, it is exciting that the earliest known fossil of an Eleutherodactylus (and the earliest fossil of any anuran in the Caribbean) – a humerus approximately 29 million years old – comes from PR. Even more exciting is our hope that this work will inspire current and future generations of herpetologists to conduct fruitful research on amphibians in the PRA and throughout the Caribbean.
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Invasive species in the Southeast and Caribbean region include a wide variety of taxa and affect both terrestrial and aquatic systems. Wood-boring insect species, such as ambrosia beetles and their microbial associates and symbionts, are easily introduced in solid wood packing material; the warm, humid climate facilitates their establishment in southern forests. The climate is also very hospitable to the establishment of new invasive plants, which pose a threat not only through their own ecological effects but also via other organisms (e.g., insects and pathogens) they may harbor upon arrival through international plant trade. In both the terrestrial and aquatic systems of the Southeast, numerous invasive animal species, including birds, reptiles, amphibians, and fish have, been introduced via the commercial pet trade, for which Florida is a major center of activity. Compared to the continental Southeast, the ecosystems of the Caribbean islands of Puerto Rico and the US Virgin Islands, with their diverse sizes and respective levels of anthropogenic activities or land reserve statuses, experience unique environmental and economic effects of non-native invasive species.This chapter highlights invasive species issues of importance in the region, with separate coverage for the continental Southeast and the Caribbean islands.
The small Indian mongoose (Herpestes auropunctatus) is an invasive species and rabies reservoir in Puerto Rico. In the continental United States, terrestrial wildlife rabies is primarily managed by the National Rabies Management Program (NRMP) of the United States Department of Agriculture through oral rabies vaccination (ORV); the distribution of the vaccine baits is influenced by the population density of the target species. TheNRMPuses a density index for estimating raccoon (Procyon lotor) population density to guide bait distribution. In Puerto Rico, a wildlife rabies vaccination program does not exist and vaccination of domestic animals is limited and not compulsory. To acquire information on density and other population dynamics, we compared a mongoose density index (MDI) adapted from the NRMP raccoon density index (RDI) to 3 other methods (2 types of capture–mark–recapture [CAPTURE and MARK] and spatially explicit capture–recapture [SECR]) for estimating density that incorporate modeling procedures on detection probabilities, and examined the spatial distribution of mongooses within our study plots. We used the RDI trapping protocol modified for mongooses to livetrap mongooses in El Yunque National Forest (El Yunque) and Cabo Rojo National Wildlife Refuge (Cabo Rojo) in fall of 2011 and spring of 2012 resulting in 4 trapping sessions. The MDI estimates were consistently less than those from other methods for estimating mongoose densities. The MDI detected a greater mongoose density during the wet season (0.55 mongooses/ha) than the dry season (0.34 mongooses/ha) at Cabo Rojo, consistent with all 3 other density estimation methods. Overall, the correlation coefficient between MDI and the other calculation methods was
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Studied the biology of Herpestes auropunctatus where sympatric with the endangered ground-nesting Caprimulgus noctitherus in the Guanica Forest, Puerto Rico. Diet consisted primarily of orthopterans, coleopterans, and centipedes. A strong negative correlation was found between numbers of mongooses and singing Puerto Rican nightjars. Mongoose density was greatest <75m in coastal scrub forest. Nightjar density was greatest >75m in closed canopy dry limestone forest. Differences in habitat requirements of these two species may restrict range overlap, rather than predation by mongooses eliminating the nightjar from coastal areas and currently limiting the species to arid higher elevation areas. -from Authors
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A clear understanding of habitat associations of martens (Martes americana) is necessary to effectively manage and monitor populations. However, this information was lacking for martens in most of their southern range, particularly during the summer season. We studied the distribution and habitat correlates of martens from 2004 to 2006 in Rocky Mountain National Park (RMNP) across 3 spatial scales: site-specific, home-range, and landscape. We used remote-sensored cameras from early August through late October to inventory occurrence of martens and modeled occurrence as a function of habitat and landscape variables using binary response (BR) and binomial count (BC) logistic regression, and occupancy modeling (OM). We also assessed which was the most appropriate modeling technique for martens in RMNP. Of the 3 modeling techniques, OM appeared to be most appropriate given the explanatory power of derived models and its incorporation of detection probabilities, although the results from BR and BC provided corroborating evidence of important habitat correlates. Location of sites in the western portion of the park, riparian mixed-conifer stands, and mixed-conifer with aspen patches were most frequently positively correlated with occurrence of martens, whereas more xeric and open sites were avoided. Additionally, OM yielded unbiased occupancy values ranging from 91% to 100% and 20% to 30% for the western and eastern portions of RMNP, respectively.
Dwarf forest in Puerto Rico's Luquillo Mountains varies according to substrate and topography with very short, dense forest growing on exposed, rocky sites. High elevation level sites suffered consider-able damage during past hurricanes whereas the trees on certain lower slopes were protected by ridges or spurs. Post-disturbance recovery of dwarf forest on two types of sample plots near East Peak was slow. Nearly 37 years after a 1968 airplane crash, Cyathea bryophila (R. Tryon) Proctor and Eugenia borinquensis Britton accounted for 71% of the 25.3 t ha −1 total aboveground dry weight biomass (hereafter biomass) on 780 m 2 of the crash site. This is only 30% of the 80 t ha −1 average biomass of the surrounding dwarf forest prior to Hurricane Hugo of 1989. Also, six 250 m 2 permanent plots (stratified by topography with sites on ridges, slopes, and ravines) showed delayed post-hurricane mortality, declining in mean stem numbers from 2,956 stems ha −1 in 1990 to 2,268 stems ha −1 in 2005. Average plot biomass decreased from 72.8 t ha −1 in 1990 to 61.6 t ha −1 in 2000, increasing slightly to 62.9 t ha −1 in 2005. Recovery on all sites was characterized by an immediate invasion of grass cover along with an influx of ferns, followed by dicotyledonous seedlings and saplings, and finally small trees. More than one-half of the arborescent species growing in dwarf forest are endemic to Puerto Rico where they play a prominent role in post disturbance recovery; moreover, 85% of the trees do not exceed 15 m in height anywhere in the Luquillo Mountains.
An understanding of the underlying processes and comprehensive history of invasive species is necessary to assess the long-term effectiveness of invasive species management. However, continuous, long-term labour-intensive population surveys on invasive species are often not feasible. Thus, it is important to learn about their dynamics through management action and its consequences. Amami Island, Japan, has an ongoing large-scale and long-term eradication programme of invasive small Indian mongooses. To estimate the long-term pattern of population size and the parameters determining the dynamics, including anthropogenic removal, we applied a surplus-production model within a Bayesian state-space formulation incorporating the initial population size, number of captures and capture effort. Using the estimated process model directly, we conducted stochastic simulations to evaluate the feasibility of eradication. Estimated 32-year annual capture probability of mongooses has increased since their introduction. The population size started to decline in 2001; mean population size in 2000 was 6141 (95% CI: 54156817), and declined to 169 (95% CI: 42408) by 2011. Parameter estimates of a Weibull catchability model indicated that there was large individual heterogeneity in the probability of being captured, and per-effort capture probability declined with an increase in annual capture effort. The simulation study indicated that the eradication feasibility in 2023 would be over 90% if the same annual capture effort is upheld as in 2010 (2075760 corrected trap-days). However, increasing annual capture effort would have little effect on shortening the time to eradication. Synthesis and applications. A hierarchical model that incorporates multiple types of data to reveal long-term population dynamics has the potential to be updated with the outcomes of control efforts, and will enhance adaptive management of invasive species. This approach will offer valuable information about trade-offs between time to eradication success and effort per unit time in a long-term eradication project, and the length of time needed to continue management actions to achieve eradication success.
Hydroelectric developments have significantly altered the hydrology and the historical wetland cycle in the Saskatchewan River Delta (SRD) by reducing both long term and within year flood frequency. This research details the responses of SRD wetlands to water level manipulation and links it to the habitats selected by muskrats thus highlighting the conditions that should be the focus of wetland management. Following the partial drawdown (PD) in the fall of 2007, muskrat densities derived from mark recapture surveys did not differ between PD and full supply level (FSL) wetlands. On a per flooded area basis, PD wetlands supported residual muskrat population at similar densities as FSL wetlands during the years of the drawdown. The partial drawdown resulted in increased amounts of senescent vegetation in PD wetlands in 2008 and 2009, mainly affecting Carex and Typha vegetation classes. The result of habitat selection modeling was generally consistent with other studies of muskrats, although it was complicated by the habitat structure of these northern wetlands. Muskrats selected for rooted Typha with greater frequency than any other habitat, followed by rooted Equisetum. Ducks Unlimited Canada's records from 1979 to 1990 show that water level drawdowns were successful at increasing muskrat house densities in SRD wetlands. In the years after a drawdown muskrat house densities generally increased and peaked three years after a drawdown, however the ten year densities were unaffected. Low muskrat densities, and low recruitment in SMC wetlands compared to other northern deltas are likely due to degenerating wetland habitat conditions created by prolonged water level stabilization. Small scale water level manipulation efforts by various managers, most notably Ducks Unlimited Canada, have produced increases in muskrat populations. Although expensive and logistically difficult the results I have presented suggest that a large scale drawdown and refill would stimulate muskrat populations in the SRD.