Acta Chiropterologica, 15(1): 85–94, 2013
PL ISSN 1508-1109 © Museum and Institute of Zoology PAS
doi: 10.3161/150811013X667885
Distribution, abundance and roosts of the fruit bat Artibeus fraterculus
(Chiroptera: Phyllostomidae)
C. MIGUEL PINTO1, 2, 3, 4, 6, MARÍA R. MARCHÁN-RIVADENEIRA1, ELICIO E. TAPIA5, JUAN P. CARRERA1,
and ROBERT J. BAKER1
1Department
of Biological Sciences and Museum of Texas Tech University, Lubbock, TX 79409-3131, USA
Centro de Investigación en Enfermedades Infecciosas, Pontificia Universidad Católica del Ecuador, Quito, Ecuador
3
Department of Mammalogy and Sackler Institute for Comparative Genomics, American Museum of Natural History, New York,
NY 10024, USA
4
The Graduate Center, City University of New York, New York, NY 10016, USA
5Fundación Otonga, Apartado 17-03-1514A, Quito, Ecuador
6Corresponding author: E-mail: mpinto@amnh.org
2
Where does a species live? How common is it? Where does it spend its inactive periods? These are basic questions about the biology
of a species, which bring key information for application in conservation and management. Unfortunately, this information is
available for only a minimum fraction of all animal species. Using 1) ecological niche modeling with maximum entropy (Maxent),
2) relative abundance estimates using museum records, and 3) field surveys of roosting sites, we report the fraternal fruit-eating bat,
Artibeus fraterculus, as having a distribution limited to the Tumbesian ecoregion in Ecuador and west central Peru, being the
relatively most abundant bat species throughout its range, with healthy populations which are primarily sustained by cultivated and
introduced plants, and using human-made constructions as roost sites. Additionally, we described a large congregation of individuals
of this species in a single roost, representing the largest colony reported for the genus Artibeus. These results may indicate resilience
of A. fraterculus to human disturbance.
Key words: bat roost, ecological niche model, Tumbesian ecoregion
INTRODUCTION
The paucity in acquiring information on the biology of species greatly contrasts with the high rates
of habitat destruction and extinction. Basic biological questions (e.g., where a species lives? how common or rare is it? and, what structures it uses as
roosting sites?) remain largely unanswered for the
majority of species in the planet (Wilson, 1999).
Answers to these and other questions will help to fill
the gaps on the biology of species, which may be
used as base line information for further conservation initiatives (Schipper et al., 2008).
Members of the genus Artibeus are conspicuous
components of the Neotropical forests, and are fairly well studied (e.g., Handley et al., 1991; Emmons,
1999; Marques-Aguiar, 2008); however, Artibeus
fraterculus (the fraternal fruit-eating bat) is among
the less studied species in the group (Albuja, 1999;
Tirira, 2001, 2007). The published information on
the distribution and roost ecology of A. fraterculus is
general. It is only known that this species is distributed throughout the Tumbesian ecoregion, primarily
restricted to dry regions of the central and south
coast of Ecuador and northwest Peru from 0 to 1,600
meters (Patterson et al., 1992; Albuja, 1999; Marques-Aguiar, 2008), but newer information and approaches have not been implemented to better characterize its distribution. Colonies of A. fraterculus
use hollow trees and hollow river banks as diurnal
refuges (Albuja, 1999) as well as church buildings
in Lima Peru (Ortiz de la Puente, 1951); however,
there are no data on how resilient this species is
to human impact. Certainly, the current knowledge
about A. fraterculus does not allow a proper understanding of its biology necessary to implement a databased conservation assessment, and to design needed further research. For instance, this species has
been evaluated three times by IUCN initiatives, being placed in three disparate categories: vulnerable,
data deficient and least concern respectively (IUCN,
1996; Tirira, 2001; Molinari and Aguirre, 2008).
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C. M. Pinto, M. R. Marchán-Rivadeneira, E. E. Tapia, J. P. Carrera, and R. J. Baker
To provide a better understanding on the biology
of A. fraterculus that will benefit further conservation research and management practices, we assessed the distribution, abundance and roosting
habits of the poorly studied fruit-eating bat A. fraterculus (Chiroptera: Phyllostomidae). More specifically, we aimed to 1) predict the potential distribution of A. fraterculus through the generation of
a ecological niche model, 2) compare the relative
abundances of this species during bat surveys conducted in the Tumbesian ecoregion, and 3) report
roosting habits of this species in anthropogenic constructions.
MATERIALS AND METHODS
Niche-based Modelling of Potential Distribution
Ecological-niche model was produced to evaluate the suitable habitat for A. fraterculus and identify the environmental
variables that explain better the distribution of the species. This
model was constructed employing the maximum entropy machine learning algorithm in the software Maxent (Phillips et al.,
2006). Maxent estimates a target probability distribution based
on environmental information for the whole study area associated to presence-only data. The model generates a probability distribution that respects a set of constraints (expressed in terms of
environmental variables) derived from the occurrence data
(Phillips et al., 2006, 2008). Initially, we selected 49 unique occurrence points, which were tested for duplicated occurrence
data within the same 1 km2 grid cell using ENM tools (Warren
et al., 2008). This procedure allowed us to have only one point
per grid cell, and each remaining point was moved to the center
of its grid cell. We ended using 41 localities for developing the
Maxent model based on occurrence records of specimens collected in Ecuador and Peru (Appendix). Voucher specimens associated with the collection localities included in the analysis
were re-identified to validate their taxonomic classification.
A total of 19 bioclimatic variables were used in the model
(Table 1; WorldClim data set, from Hijmans et al., 2005). These
environmental variables have shown to be important on determining species distributions as they reflect aspects of seasonality, temperature, and precipitation (Hijmans et al., 2005). The
environmental data used were generated through interpolation
of average monthly climate data from weather stations on a 30
arc-second resolution grid (≈ 1 km2 resolution). The settings
used for running the model incorporated a β regularization parameter of 0.5. Random 25% of the sample was used for testing
the model. Maximum number of background points was fixed at
10,000. Twenty-five replicated run types were crossvalidated
and maximum iterations were fixed at 500. The average model
across all runs was selected. General accuracy of model was
evaluated by the Area Under the Curve (AUC) of Receiver
Operating Characteristic (ROC plots) as a measure of prediction
success (Fielding and Bell, 1997). Models providing AUC values in the range > 0.9 are considered highly accurate, between
0.7–0.9 useful, and lower than 0.7 poorly accurate (according to
Sweets, 1988). Additionally, jackknife test was used to evaluate
the rank of informative bioclimatic variables to generate
the models. Once the potential distribution was generated by
Maxent, the average potential area of distribution over the average minimum training value was calculated in km2.
Relative Abundances
Relative abundances were estimated to determine how common A. fraterculus is within the bat fauna of the Tumbesian
ecoregion. The definition used here for relative abundance is the
percentage that each species exhibits in a sample, being the sum
of all the relative abundances of the different species present in
the sample equals to 100% (e.g., Medellín et al., 2000). Two
approaches were used to obtain the data to estimate relative
abundances. 1) Using a relational database built for data on
mammalian museum specimens from Ecuador deposited in
World collections (26 natural history museums in total) (Carrera, 2007), the records of A. fraterculus were retrieved and
compared with the relative abundances of all the records of bats
from the same geographical region where A. fraterculus has
been collected (Ecuadorian provinces of El Oro, Guayas, Loja,
Los Rios and Manabí). 2) Data were retrieved from Peruvian
specimens (from the departments of Ancash, Amazonas, Cajamarca, La Libertad, Lambayeque, Lima, Piura and Tumbes) deposited in US museums with data available through on-line
databases, i.e., Field Museum of Natural History (FMNH) and
the Mammal Networked Information System (MaNIS) (Stein
and Wieczorek, 2004).
Roosting Sites
A survey of bats was conducted in El Oro, Loja and Zamora
Chinchipe provinces in southern Ecuador in January 2007.
We followed the road system and surveyed bats associated
with human constructions (e.g., houses, barns, mines, tunnels),
and few natural formations (e.g., outcrops, rock crevices). We
did not conduct a systematic survey (e.g., certain number of
TABLE 1. List of the 19 environmental variables from Hijmans
et al. (2005) used in the predictive distribution model in
Maxent. Variables are ordered by the percentage of contribution
to the distribution model
No.
Environmental variables
Contribution (%)
1 Mean temperature of driest quarter
35.9
2 Precipitation of wettest month
8.6
3 Mean diurnal range
8.2
4 Precipitation of driest month
7.8
5 Minimum temperature of coldest month
7.5
6 Precipitation seasonality
5.8
7 Mean temperature of coldest quarter
5.2
8 Precipitation of wettest quarter
4.3
9 Precipitation of coldest quarter
4.2
10 Maximum temperature of warmest month
2.6
11 Temperature seasonality
2.2
12 Precipitation of warmest quarter
2.0
13 Temperature annual range
1.5
14 Mean temperature of warmest quarter
1.4
15 Annual mean temperature
0.9
16 Isothermality
0.8
17 Mean temperature of wettest quarter
0.4
18 Precipitation of driest quarter
0.4
19 Annual precipitation
0.3
Biology of Artibeus fraterculus
constructions checked per town or grid), rather for maximization of results we asked local people where they have seen bats
in or around a particular settlement, and also we searched abandoned houses. Around 60 potential roosting sites were examined. When a roost site was found, direct counts of individuals
using the roost were performed without manipulation of the
bats. Also a descriptive physical characterization of the roost
was conducted, documenting the geographic coordinates, type
of construction were the roost was located, and the type of vegetation in the surroundings. Additionally, in May 2007, we identified diet items in the roost with the highest number of A. fraterculus. Based on appearance, we collected different seeds
from feces and fruit fragments from the floor of the roost. Seed
identification from faeces was conducted by comparison with
seeds from fruits of trees present in the surroundings of the
roost. Also, temperature measurements of this particularly hot
roost were taken.
RESULTS
Niche-based Modelling of Potential Distribution
Maxent results based on the average model across
25 runs showed that the area with highest environmental suitability of distribution for A. fraterculus is
restricted mainly to the central-south of Ecuador and
north of Peru (Fig. 1). The area over the 18% of probability of occurrence corresponds to the average
minimum training presence data across the models.
General average accuracy of the models evaluated by
the AUC was 0.8. The jacknife test analysis showed
that across runs the environmental variable with
highest gain when used in isolation was precipitation
of driest quarter, which therefore appeared to provide
the most useful information in the models. The environmental variable that decreases the gain the most
when it was omitted was temperature seasonality,
which therefore appeared to have the most information that was not present in the other variables. The
potential area of distribution of the species based on
the average predicted model over the 18% of probability of occurrence was 59,875.71 km2.
Relative Abundances
From a total of 6,167 museum records reported
for bats collected in the Tumbesian region, the most
commonly collected species was A. fraterculus with
963 records (15.6%). Among the majority of our
data partitionned by provinces and departments, the
trend of having A. fraterculus as the most abundant
bat species in the Tumbesian region holds, the only
exception is the department of Amazonas in Peru,
where this species is not a common component of
the bat fauna (ranking 3rd with 5.9%). The percentages of A. frateculus in the samples of Ecuador and
87
Peru are 14.1% and 17.3% respectively. Other common bats in the Tumbesian region were Glossophaga soricina, Sturnira erythromos, and Desmodus
rotundus (Table 2).
Roosting Sites
A total of 38 roosting sites of at least 9 bat
species (e.g., A. fraterculus, Carollia perspicillata,
D. rotundus, Molossus molossus, and three species
of Myotis spp.) were found. Five roosts (10.9%)
were actively occupied by A. fraterculus; four were
located in human houses, and one in an active coal
mine.
The biggest conglomeration of A. fraterculus
(709 individuals) was found in an active coal mine
(35 m long with an approximate average height of
2.5 m) in El Naranjo Creek, along the trail Malacatos-El Tambo-Catamayo, Loja province, Ecuador
(-4°10’53.3994”, -79°17’39.8754”, 1,508 m). Inside
the mine, the individuals were not evenly distributed; 600 individuals were clustered in a vault at
8 m of the entrance, the remaining 109 bats were
located along the entire length of the mine in 11
groups composed by 2 to 28 individuals (9.91 mean;
± SD 8.35) (Fig. 2A). The temperature was 32°C in
the vault, and at 34°C in the posterior part of the
TABLE 2. Relative abundances calculated as the percentage of
records in museum collections of the most common four species
of bats in the Tumbesian ecoregion in Ecuador and Peru. Data
for Ecuador comes from the compilation of museum records
conducted by Carrera (2007) for the provinces of El Oro,
Guayas, Loja, Los Rios and Manabí. Records from Peru are
from FMNH and MaNIS for the departments of Ancash,
Amazonas, Cajamarca, La Libertad, Lambayeque, Lima, Piura
and Tumbes. Number refers to the total sum of specimens per
country. The ranges of the number of specimens are given per
each province or department surveyed in Ecuador and Peru,
respectively
Species
Ecuador
Artibeus fraterculus
Glossophaga soricina
Carollia perspicillata
Artibeus aequatorialis
Remaining 69 species
Total
Peru
Artibeus fraterculus
Glossophaga soricina
Sturnira erythromos
Desmodus rotundus
Remaining 99 species
Total
Number Range Relative abundance
460
486
320
202
1,793
3,261
47–224
6–297
1–160
4–110
14.1
14.9
9.8
6.2
55.0
100.0
503
248
226
103
1,826
2,906
2–163
1–142
1–79
1–26
17.3
8.5
7.8
3.5
62.8
100.0
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C. M. Pinto, M. R. Marchán-Rivadeneira, E. E. Tapia, J. P. Carrera, and R. J. Baker
FIG. 1. Map of Ecuador and Peru showing the Maxent model of the potential geographic distribution of A. fraterculus. The model
depicts occurrence probabilities from 18–100%, where the suitability is indicated by the intensity of the gray shading, where darker
tones indicate more suitable areas. Black dots indicate the localities used in generating the model. Inset: Map of South America
with a rectangle of the study area
Biology of Artibeus fraterculus
89
FIG. 2. Roosts of A. fraterculus in human constructions. A — partial colony in coal mine, El Naranjo creek, inset: entrance to the
mine; B — colony in inhabiting house ceiling, Chorrera Blanca, inset: house view from the front
90
C. M. Pinto, M. R. Marchán-Rivadeneira, E. E. Tapia, J. P. Carrera, and R. J. Baker
mine. Among the fruit fragments and seeds collected
on the floor of the coal mine were: guava Psidium
guajava (Myrtaceae), fig tree Ficus maxima (Moraceae), loquat Eriobotrya japonica (Rosaceae), Malabar plum Syzygium jambos (Myrtaceae), pungal
Solanum crinitipes (Solanaceae), and seeds of two
unidentified species. No other bat species were recorded inside the mine.
An abandoned house in Landangui (-4°12’
35.64”, -79°13’46.9194”, 1,539 m) contained 41
individuals. An inhabited house of two stories in
Chinguilamaca (-4°11’21.7674”, -79°19’39.684”,
1,358 m) harbored 10 individuals in the second floor
of the building. In a school building in Macará
(-4°22’59.9874”, -79°57’0”, 472 m) was found
a mother and her pup. In Chorrera Blanca
(-3°51’45.5754”, -79°33’51.4434”, 972 m) the second floor of an inhabited house served as roost of
28 individuals (Fig. 2B). Near all roosts dense vegetation and fruit trees were observed.
DISCUSSION
Limited Geographic Distribution
As other studies of mammalian distributions
using niche models have shown, it is possible to
characterize and delimit the distribution of a species
even in the absence of well populated datasets (e.g.,
Anderson and Martínez-Meyer, 2004; Helgen et al.,
2009). The potential geographic distribution of
A. fraterculus predicted in this study spans most of
the Tumbesian ecoregion, from sea level to middle
elevations in the Andes, including dry valleys of the
eastern slope of the Andes along the depression of
Huancabamba (Fig. 1). The lack of a continuous pattern of distribution along the west coast of Peru
might be associated to the few number of localities
included across this area, or a possible low tolerance
of the species for highly dry conditions of the
Sechura desert in northern Peru and the dry areas of
the coast (Rundel et al., 2007). Indeed, previous
studies showed that A. fraterculus is distributed
along the western north and central side of Peru
(Paterson et al., 1992; Pacheco et al., 2009) and
populations of A. fraterculus have been reported
from over 2,500 m near Huaylas, on the western
slope of the Andes of Peru through the lower Marañón valley. Our study did not include specimens
collected over 1,900 m and the potential distribution
predicted by Maxent showed that areas over this
elevation range were classified within 0 to 19%
of probability of occurrence. Additionally, the north
and south marginal areas included in the model
include regions where the species might not be abundant or none museum records have been reported.
Artibeus fraterculus shows an extent range of
distribution along the Tumbesian ecoregion and
parts of the dry Peruvian coast. Other endemic
mammals of these regions, e.g., Cabreramops aequatorianus, Eptesicus innoxious, Eumops wilsoni,
Lonchophylla hesperia, Lycalopex sechurae, Platalina genovessium, Proechimys decumanus, Rhogeessa velilla, Sigmodon peruanus, and Tomopeas
ravus, have apparently more restricted distributions.
This may indicate that A. fraterculus adapts to certain degree to different environments at the borders
of the Tumbesian ecoregion: the transition zone between the dry forests and the hyper humid environments of the Chocó forest, and the middle elevations
of the western slopes of the Andes (SánchezAzofeifa et al., 2005). In addition, other endemics
such as Aegialomys xanthaeolus, Amorphochilus
schnabli, and Sciurus stramineus could have very
similar distributions to A. fraterculus; however, this
merits more studies on these taxa that also have been
largely under studied (Tirira, 2007; Baird et al.,
2008; Gardner, 2008; Baker et al., 2009; Pacheco et
al., 2009). Interestingly, A. fraterculus is not distributed in the core of the humid Chocó forests, as some
bat species found in both the Chocó and Tumbesian
forests (e.g., Diaemus youngi and Lophostoma occidentalis — Pacheco et al., 2007; Pinto et al., 2007;
Velazco and Cadenillas, 2011). Perhaps, competitive
exclusion with other fruit-eating bats restricts
A. fraterculus to dry forests. For instance, the community of fruit-eating bats in the Tumbesian ecoregion is evidently less diverse than in the Chocó forest which harbours several species of small and
large Artibeus species (subgenera Artibeus and Dermanura) and others such as Mesophylla, Chiroderma, Vampyressa, and Vampyrodes among others
(Albuja, 1999; Tirira, 2007; Gardner, 2008). Additionally, a strong dry season with no dramatic
changes in temperature (as evidenced by the most
informative variables of the model: seasonality and
precipitation of driest quarter) may be influencing
the phenology of key alimentary resources for this
species, that may be absent outside the Tumbesian
ecoregion. These aspects should be studied in greater detail, since unfortunately little information exists
on Ecuadorian and Peruvian dry forests (SánchezAzofeifa et al., 2005).
Abundance through its Range
The data on the relative abundances showed that
A. fraterculus is the most frequently collected bat in
Biology of Artibeus fraterculus
the Tumbesian ecoregion (Table 2), and may be the
most abundant bat of the area. In previous surveys
along the Tumbesian ecoregion, A. fraterculus was
a common component of the bat fauna. In a study in
Lima, Peru, A. fraterculus was the second more frequently captured species after G. soricina (Mena
and Williams de Castro, 2002). In an intensive survey of bats across the coast of Ecuador, A. fraterculus was the most common bat captured (Carrera et
al., 2010). In a survey in Piura, Peru, A. fraterculus
was among the most abundant species (Pacheco et
al., 2007). In Guayas province, Salas (2008) determined that the most abundant species was A. fraterculus. These data show clear evidence that in the
Tumbesian ecoregion, A. fraterculus might be at
least as abundant as two of the most common bats
in other areas of the Neotropical region, the bats
C. perspicillata and A. jamaicensis (e.g., Fleming,
1988; Gardner et al., 1991; Medellín et al., 2000).
During our survey of museum databases, A. fraterculus was abundant in all provinces and departments
surveyed, except in the departments of Ancash and
La Libertad in Peru where data of very few collected species are available (i.e., five records in total). In
the Peruvian department of Amazonas, A. fraterculus was the third most abundant bat species, which
is not surprising because in addition to contain part
of the semiarid Huancabamba deflection and the
Marañón valley which are suitable habitats for this
species (Patterson et al., 1992), it also has large
extensions of unsuitable habitat (e.g., rainforests of
the eastern versant of the Andes).
It might be argued that museum records are biased because some bats are easier to catch than
others (e.g., Larsen et al., 2007), or because errors in
identifications and data acquisition, and bias in sampling due the non-standardized nature of museum
collection efforts (Graham et al., 2004). None the
less, museum data are highly valuable due to the
large amounts of records across vast temporal and
spatial periods (Graham et al., 2004). In this particular case, specimens of A. fraterculus are easy to indentify in the field for the white markings in the face
characteristic of Artibeus, and the smaller body size
and paler coloration than the other sympatric congeners A. aequatorialis and A. lituratus (e.g., forearm length in A. fraterculus ranges from 52–59 mm
versus 57–68 in A. aequatorialis, versus 65–78 mm
in A. lituratus) (Tirira, 2007; Larsen et al., 2010).
Moreover, in the original description of A. fraterculus, Anthony (1924: 6) mentions “A. fraterculus is
so obviously smaller than true jamaicensis that the
distinction may be noted upon immediate superficial
91
inspection.” Thus, field identifications for different
collectors are reliable, and misidentifications should
be uncommon. It is unlikely that a small amount of
misidentifications would drive an overrepresentation bias.
Resilience to Human Impact
The dry forests of southwestern Ecuador and
northwestern Peru have been facing high human
pressures ranging from deforestation, and desertification to mining activities and subsequent water
contamination (e.g., Dobson and Gentry, 1991; Sierra et al., 2002). However, the use of human structures as roosting sites, and eating exotic and cultivated plant species (i.e., P. guajava, E. japonica, and
S. jambos) suggest that A. fraterculus tolerates disturbed environments and the presence of humans.
The availability of human structures and the abundance of fruit crops may be determining factors for
the high abundance of A. fraterculus in disturbed
environments. A similar pattern has been found in
other neotropical bats such as C. perspicillata and
A. jamaicensis that also are frequently found occupying human-made constructions as roosting sites
(Morrison and Handley, 1991; Cloutier and Thomas,
1992). Even, A. fraterculus could be used as a species indicator of habitat quality, where high abundances would equal to habitat disturbance, like with
the vampire bat D. rotundus (Medellín et al., 2000).
But first, more studies are required to contrast the
relative abundances of A. fraterculus between human-modified and undisturbed environments to determine if this species is less abundant in pristine
forests. Whether the disturbed environments are
population sink habitats for A. fraterculus requires
further research (e.g., Sauvajot et al., 1998). It is
possible, as hypothesized by Tirira (2001), that pesticides applied to the fruit crops and chemicals produced by the mining industry could be threatening
this species; however, no studies have investigated
this possibility.
Roosting Habits and a Record in Roosting
Conglomeration
The roosts and fruit fragments described here increase the knowledge on the type of roosts used by
A. fraterculus and its diet. Yet, it becomes necessary
to know in deeper detail the characteristics of the
roost sites in human-modified and undisturbed environments following standardized procedures (e.g.,
Boyles, 2007). The coal mine with the unusual
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C. M. Pinto, M. R. Marchán-Rivadeneira, E. E. Tapia, J. P. Carrera, and R. J. Baker
concentration of 709 A. fraterculus individuals in
a single roosting site is the highest reported for any
species of Artibeus. The high number of individual
in a single roost site could be explained for the high
temperatures (32°C and 34°C) of the coal mine
while compared with the exterior mean temperature
of 24°C. It is known that some tropical and subtropical bat species prefer hot roosting sites, and it has
been explained as a mechanism for saving energy
expenditure (e.g., Dechmann et al., 2004; Law and
Chidel, 2007). It is possible that this mine could be
a unique hot spot in the area, attracting A. fraterculus from the surroundings. As opposite to these findings, A. jamaicensis has being reported using mostly cool caves (< 27°C) with temperatures similar to
the outside environment (Arita and Vargas, 1995;
Rodríguez-Durán, 1998). The closest number for
a concentration of Artibeus was reported for Arita
and Vargas (1995), estimating the presence of more
than 500 individuals of A. jamaicensis in Murciélagos Cave, Yucatán, México; within the same cave,
Ortega and Arita (1999) re-estimated the total number of A. jamaicensis as ca. 250 individuals.
Conclusions
Here A. fraterculus is reported as: i) having a relatively limited geographic distribution, ii) being
the most abundant bat species through its range, iii)
resilient to human disturbance by eating cultivated
and introduced plants, and using human-made constructions as roost sites, and iv) roosting in a great
congregation larger than previous reports for other
species of Artibeus. These results may indicate that
A. fraterculus plays an important role providing ecological services as a seed disperser in the dry forests
of southern Ecuador and northern Peru. In addition,
we recommend A. fraterculus as a representative
species for studies focused on the conservation of
the Tumbesian ecoregion, which has been heavily
influenced by human activities (Dobson and Gentry,
1991). With the information gathered in this study
(e.g., distribution, roost information, relative abundances) it is corroborated that the IUCN category
of least concern is appropriate for this species
(Molinari and Aguirre, 2008); also, it would be possible to design studies for monitoring the effect of
human activities on A.fraterculus populations. For
example, it would be possible to track bioaccumulation of pesticides used in fruit crops and chemicals
used in gold mining and to determine if these activities are negatively impacting the population of this
species.
ACKNOWLEDGEMENTS
We are grateful to J. C. Cokendolpher, K. M. Helgen, P.
Iturralde-Pólit, P. Jarrín-V., R. W. Kays, T. Kingston, H. Mantilla-Meluk, P. M. Velazco, and four anonymous reviewers for
contributing valuable comments on the paper. G. S. Acosta and
M. Granda provided help during the field work. Funding was
provided to CMP by a Latin American Student Field Research
Award from the American Society of Mammalogists, and two
J. Knox Jones Scholarships from Texas Tech University.
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Received 29 December 2012, accepted 28 February 2013
APPENDIX
Forty-one unique georeferenced localities of A. fraterculus included in Maxent analysis (Fig. 1)
Ecuador — Azuay: Challcapac (-3°13’59.8794”, -79°12’);
Santa Isabel (-3°16’0.12”, -79°19’0.1194”); El Oro: Palmales,
Reserva Militar Arenillas (-3°40’27.4008”, -80°6’19.9794”);
14.5 km S Zaruma (-3°40’59.88”, -79°37’0.1194”); Cerro
Chiche, limit between Portovelo and Piñas (-3°46’3.2988”,
-79°38’50.8986”); El Cubo, Reserva Militar Arenillas
(-3°38’48.9012”, -80°9’40.788”); Portovelo, near El Tablón –
Quinta Palomares (-3°44’11.598”, -79°35’41.1”); Punta Brava,
Reserva Militar Arenillas (-3°28’13.998”, -80°7’3.1794”);
Puyango, Bosque Petrificado – near Quebrada de los Sábalos
(-3°52’46.2”, -80°5’34.299”); Quebrada Seca, Fuerte Militar
Arenillas, 7.1 km W and 12.5 km S of the base (-3°39’24.0978”,
-80°10’56.1966”); Santa Rosa (-3°27’, -79°58’0.0012”);
Zaruma, El Faique (-3°42’7.1994”, -79°37’18.3966”);
Zaruma, Mine 2, neighborhood La Colón (-3°41’23.1174”,
-79°35’43.6992”); Guayas: Bosque Protector Cerro Blanco,
Canoa trail (-2°25’38.1972”, -80°1’17.6988”); Durán (-2°12’,
-79°49’59.8794”); Hacienda El Refugio, 5 km E Manglar Alto
(-1°49’59.9874”, -80°42’59.9976”); Manglares Churute, Cerro
Cimalón (-2°25’36.3174”, -79°33’40.518”); Manglares Churute, Cerro Pancho Diablo, Ismael Acero’s farm (-2°25’15.1998”,
-79°37’52.9968”); near Cusumbotopo (-2°9’18.1974”,
-80°1’42.7794”); El Triunfo, El Piedrero (-2°19’0.0006”,
-80°24’); Loja: 24 km N Catacocha (-4°1’, -79°37’); Alamor
(-4°1’59.8794”, -80°1’59.8794”); Hacienda Almenital, 10 km
W of Catacocha (-4°4’60”, -79°47’60”); Hacienda Casanga,
10 km W Catacocha, near Casanga (-4°1’0.0006, -79°45’);
Malacatos (-4°13’59.8794”, -79°16’59.8794”); Mangahurquillo, bosque Quebrada Achiotes (-4°10’0.1194”, -80°25’59.88”);
Puyango, Bosque Petrificado – near Las Pailas, Quebrada de los
Chirimoyos (-3°53’48.498”, -80°4’35.1978”); Zapotillo, Quebrada Las Lajas (-4°22’59.88”, -80°15’); 3 km N from Vilcabamba (-4°12’59.9976”, -79°15’); Los Ríos: Cerezo (Abras De
Mantequilla), ca. 12 km NE Vinces (-1°33’, -79°15’); Puebloviejo,7 km SW, El Papayo near San Juan (-1°33’, -79°31’60”);
Vinces (-1°33’, -79°43’59.8794”); Manabí: Cabo Pasado,
17 km N near San Vicente-Pedernales (0°4’59.9982”,
-80°2’59.9994”).
Perú — Cajamarca: Santa Cruz, Catache, R Saña, 2 km N
Monte Seco (-6°50’59.9994”, -79°4’1.1994”); Lambayeque:
Chiclayo, Oyotún, Molino El Collao (-6°51’54”, -79°19’22”);
Olmos, ca 12 km NW Olmos (-5°53’33.648”, -79°46’55.92”);
Lima: El Agustinín, Cerro El Agustino (-12°2’34.692”,
-76°59’46.7514”); Piura: Hacienda El Bigote (-5°18’56.1594”,
-79°47’3.1194”); Huancabamba, San Miguel del Faique,
15 road km E. Canchaque (-5°22’44.58”, -79°33’53.9994”);
Tumbes: Pampas de Hospital, Quebrada Faical, E El Caucho
24 km SE (-3°49’20.8554”, -80°19’59.52”); Zurumilla, Matapalo (-3°25’45.1914”, -80°14’52.8”).