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Oecologia Australis
21(4): 422-430, 2017
10.4257/oeco.201 7.2104.06
FACTORS AFFECTING MAMMALIAN ENCOUNTER RATES
IN TRANSECT SURVEYS: A CASE STUDY IN ILHA GRANDE STATE PARK,
STATE OF RIO DE JANEIRO, BRAZIL
Bruno Cascardo Pereira1, Átilla Colombo Ferreguetti2* & Helena Godoy Bergallo2
1 Instituto Chico Mendes de Conservação da Biodiversidade (ICMBio). Parque Nacional Serra das Lontras, Ilhéus, BA, Brasil. CEP:
45 653-970
2 Universidade do Estado do Rio de Janeiro (UERJ), Instituto de Biologia Roberto Alcantara Gomes, Departamento de Ecologia. Rua São
Francisco Xavier, 524, PHLC 220, Maracanã, Rio de Janeiro, RJ, Brasil. CEP: 20559-900
E-mails: bruno.pereira@ ib ama.gov.br, atilla.ferreguetti@g mail.com, nena.bergallo@gmail.com
ABSTRACT
Distance sampling is a widely used technique. However, the influence of several factors on the observations when
using this technique, such as speed of the observers, microhabitat, weather, and method of detection, are still
unknown. We aimed to evaluate the effect of various factors in the encounter rates and frequency of detection of
mammalian species using the distance sampling technique with transects in an Atlantic Forest area, Ilha Grande,
state of Rio de Janeiro, Brazil. We evaluated the effects of the forms of detection, sighting time, and the climate
conditions on mammals samplings. Between December 2003 and May 2005, 128 transects were undertaken by a single
observer, totalling 401.3 km and 382 hours. We recorded 163 individuals of nine species of mammals. Several factors
affected our study using the distance sampling by linear transects, which include the animal activity period (i.e.,
object of study), followed by climate conditions, and transect location. We also found lower encounter rates in
transects located in the north part of the island, because of the interference of tourists and the poaching pressure,
which must be associated with the higher human densities in the north of the island that would inhibit the presence
of certain species. This study highlights the importance of considering these variables when estimating mammal
population sizes using distance sampling technique.
Keywords: Atlantic Forest; distance sampling; linear transects; poaching.
INTRODUCTION
Estimates of population size and density are
fundamental to any effort of conser vation of
endangered species. These estimates provide basic
support for several purposes related to conservation
programs and political decisions, such as to evaluate
habitat loss, to identify priority areas for conservation,
to evaluate minimum viable populations, to determine
the conservation status of a target species, among
others. (e.g., Tomas et al. 2004, Cardillo et al. 2006,
Cunha & Loyola 2011, IUCN 2015, Buckland et al.
2016). However, long-term studies that monitor
population sizes are rare for most taxa, including
endangered species, especially in the Neotropics
(Cardillo et al. 2006, Cunha & Loyola 2011, IUCN
2015).
Among the many existing techniques to estimate
density and population size (e.g., Capture-Mark-
Recapture methods; Seber 1986, Sutherland 2006), the
distance sampling technique is one of the most
frequently used (Buckland et al. 2001, 2004). This
technique is based on the detection of animals along
transects (e.g., linear transects; Buckland et al. 2001).
This method is often used to assess populations of
medium and large mammals in tropical forests (Peres
1999, Chiarello 2000, Gonzalez-Solis et al. 2002, Galetti
et al. 2009, Desbiez et al. 2010, Gopalaswamy et al.
2012, Norris et al. 2012, Ferreguetti et al. 2015, 2016,
2017). The distance sampling is a simple and
inexpensive method that can cover large areas in a
short period of time (Cullen Jr. & Valladares-Pádua
1997, Cullen Jr. & Rudran 2004), with the assumption
that target species can be directly observed and there
are no misidentifications (Buckland et al. 2001). In
the distance sampling technique, the main estimated
parameter is the density of a population in a given study
area. Furthermore, this method is also considered more
Mammalian Detectability in Transect Surveys 423
Oecol. Aust., 21(4): 422-430, 2017
accurate than methods that do not account for imperfect
detection, even if the assumption that there are no errors
in the distance measurements is violated (Buckland et
al. 2001).
Distance sampling considers the imperfect
detection of individuals of the target species during
trans ect surve ys (Ma ckenzi e et al. 200 6),
considering that not all individuals are recorded. The
individuals that are exactly on the transect line are
recorded, so that the detection probability decreases
as the object distance increases from the observer
(Buckland et al. 2001, 2004). In general, distance
sampling involves a series of models, which adjust
detection functions for the observed distances, and
uses these functions to estimate the proportion of
objects missed during sampling (Buckland et al.
2001).
Despite being a technique widely used over the
years, information on how different factors (i.e., speed
of observers, microhabitat, weather, method of
detection) influence observations while using distance
sampling are still scarce. Mateos (2002) noted that
altitude was the only variable that influenced the
distribution of mammalian species in the Atlantic
Forest. However, factors such as sighting time and
speed of the observer had a quantitative effect on the
encounter rate.
We aimed to evaluate the effect of various
factors on the observations of mammalian species
when conducting distance sampling technique using
transects in an Atlantic Forest area. We tested how
the way in which and when (sighting time) the study
objects were detected affected the encounter rates of
mammals. We also tested the effects of climate
conditions (weather and wind) on the frequency of
detections. We tested four hypotheses: (1) encounter
rates will be higher for larger species during daytime
observations, because it is easier to detect large
individuals; (2) climatic conditions will negatively
influence the detection of species, because individuals
would avoid extreme weather conditions; (3) encounter
rates will be higher in southern than northern parts of
the island, because the northern side of the island is
more densely populated; and (4) mid-sized mammals
will be more abundant in less-disturbed areas in the
island’s south than in the north.
MATERIAL AND METHODS
Study area
Our study was carried out in the Ilha Grande
State Park (PEIG hereafter) and in the Biological
Reserve Praia do Sul (ReBio hereafter), in Ilha
Grande island off the southwestern coast of Rio de
Janeiro State, Brazil (Figure 1). PEIG is the second
largest insular Biological park in Brazil and covers
120 km², over half (62%) of the island, which has
193 km². ReBio covers an area of 35.02 km² (INEA
2010). The climate is hot humid tropical without a
dry season. Ilha Grande is the top of a submerged
mountain and has two dominant types of topography,
mountain and coastal plain (INEA 2010). Mountain
peaks occur in the center of the island. Almost half
of the area (47%) is covered by dense, relatively
pristine Atlantic rainforest. Disturbed forests, in an
advanced successional stage, are the second major
habitat type (43%). The remaining areas comprise
rocky outcrops with herbaceous vegetation (7%), salt
marshes, mangroves and beaches (2%). Human
settlements occupy 1% of the island (Alho et al. 2002)
and is concentrated around the northern coastline of
Ilha Grande Bay and in Abraão village. These areas
are undergoing much anthropic disturbances due to
tourism development, with new buildings, port
facilities and expanding infrastructure (Alho et al.
2002).
Sampling design
During the period between December 2003
and May 2005, 128 transects were performed,
totalling 401.3 km walked in 382 hours of effort.
The transects were surveyed in five existing dirt
trails in Ilha Grande in order to minimize the impact
of opening new trails (Figure 1). Two of those trails
were located in the northern part of the island,
connecting Abraão Village to Palmas and Feiticeira
beaches (respectively T01 and T02). The other three
trails were on the south side of the island, connecting
Dois Rios Village to Caxadaço and Parnaióca
beaches, and to Jararaca locality (respectively T03,
T04 and T05). Transects ranged in length from 2.1
424 Pereira et al.
Oecol. Aust., 21(4): 422-430, 2017
Figure 1. Transect locations (T01 to T05) of the mammal sampling in Ilha Grande, state of Rio de Janeiro, Brazil. The black
triangle indicates the location of Abraão Village.
Table 1. Characteristics of transects, number of times each transect was walked (N samples), total kilometers walked in Ilha
Grande, state of Rio de Janeiro, Brazil.
to 6.7 km (Table 1). All transects were marked at
50 m intervals. We recorded for each transect the
evidence of poaching (e.g., hunting traps), and a
Human density index (measured by the number of
inhabitants in the nearest village divided by the
distance to the neares t human settlement) to
compare transects located in each region of Ilha
Grande (north and south) (Table 1).
Transect T01 T02 T03 T04 T05 Total
Extension (km) 2.1 2.3 2.7 6.7 2.1 15.9
N samples
27 23 27 24 27 128
Total Km walked 56.7 52.9 72.9 160.8 56.7 401.3
Island region North North South
South South
Evidence of poaching Yes Yes Yes No No
Human density index 405 412 444 134 103
Minimum altitude (m) 0 10 10 0 20
Maximum altitude (m) 190 160 170 170 250
Average altitude (m) 125.1 106.3 106.4
81.3 136.9
Mammalian Detectability in Transect Surveys 425
Oecol. Aust., 21(4): 422-430, 2017
Transects were walked by the observer during
the activity time of the animals at dawn and twilight
(Chiarello 2000). Transects were walked at an
average speed of 1.1 km/h (± 0.5), and under different
climatic conditions divided into three categories by
weather (clear sky, cloudy or rainy) and four
categories of wind speed (no wind, weak, medium
and strong). For each transect walked, the following
information were recorded: sample size, number of
transect, date, start time, end time, weather, and wind
conditions.
The A/T (animal x transect) perpendicular
distance was measured considering the exact location
where the animal was first detected. In the case of
animals that used the tree layer, the distance was
measured from the trunk of the tree where the animal
was observed. When a group was observed, we
considered the first animal detected in the group.
Whenever an animal was observed, the following
information was recorded: sighting time, species, A/
T distance, number of individuals (group size), location
in the transect, and form of detection (visual or
hearing). Hearing detections were registered by
vocalizations (warning cries), noise caused by
movements in the vertical strata (movements in twigs
and branches), and noise caused by movements in
the litter (movements on the ground). Visual
detections were registered for animal movements
without any associated noise and by the reflection of
light from flashlights in their eyes at night. Sighting
time was divided into six groups: group 1 (4:00 to
6:00 h), group 2 (06:01 to 08:00 h), group 3 (08:01 to
10:00 h), group 4 (16:00 to 18:00 h), group 5 (18:01 to
20:00 h) and group 6 (20:01 to 23:00 h).
We used the encounter rate as the dependent
variable to evaluate the differences between the forms
of detection and the sighting time of the mammalian
species. Encounter rates were calculated using the
number of individuals (or groups) by the total length
walked in the transects, and were expressed as the
number of individuals or groups every 10 km walked.
We used the frequency of detection (i.e., which
consists of presence and absence data, that is 1 for
detected or 0 for not detected) of each species as
the dependent variable to evaluate the effects of the
climate conditions, because it was not possible to
estimate encounter rates for each time that the
transect was walked.
Data analysis
We assessed the relationship between the
forms of detection on mammalian species encounter
rates with a two-way analysis of variance (ANOVA)
(forms of detection x species). When our models
were significant we used Tukey post-hoc tests ( =
0.05) to compare means. We used Kruskal-Wallis
test when the ass umptions of normali ty and
homoscedasticity were not met, which was the case
of the sighting time of each species. We used a chi-
square test to evaluate the effect of climate conditions
on the frequencies of detection for the most frequent
species using each time that the transect was walked.
As there were cells with values below five, we used
the Cochran correction in this analysis (Cochran
1977). All statistical analyses were performed in
SYSTAT 11® program.
RESULTS
We recorded 163 individuals of nine species
of mammals in 382 h of observation: the common
opossum Didelphis aurita (Wied-Neuwied, 1826)
(Didelphimorphia, Didelphidae; n = 21), the nine-
banded armadillo Dasypus novemcinctus Linnaeus,
1758 (Cingulata, Dasypodidae; n = 13), the brown
howler monkey Alouatta guariba (Humboldt, 1812)
(Primates, Atelidae; n = 16), the common marmoset
Callithrix jacchus (Linnaeus, 1766) (Primates,
Callitrichidae; n = 25), the spotted paca Cuniculus
paca (Linnaeus, 1766) (Rodentia, Cuniculidae; n =
35), the agouti Dasyprocta leporina (Linnaeus,
1758) (Rodentia, Dasyproctidae; n = 4), the
southeastern squirrel Guerlinguetus brasiliensis
(Thomas, 1901) (Rodentia, Sciuridae; n = 36); the
capybara Hydrochaeris hydrochaeris Linnaeus,
1766 (Rodentia, Caviidae; n = 2), and the orange-
spiny hairy dwarf porcupine Coendou spinosus (F.
Cuvier, 1823) (Rodentia, Erethizontidae; n = 10).
The number of species stabilized around an effort
of 167 h. The T04 transect was the only one where
all nine species were observed. T01 and T02
426 Pereira et al.
Oecol. Aust., 21(4): 422-430, 2017
transects had the lowest richness, with only three
species observed: D. aurita, G. brasiliensis, and
C. jacc hus (Ta ble 2) . Th e tota l avera ge of
mammal’s encounter rate was 4.06 encounters every
10 km walked, and the highest encounter rate was
for G. brasili ens is (0.92 en count ers/10 km),
followed by C. paca (0.87 encounters/10 km). The
T05 transect presented the highest encounter rate
(5.29 encounters/10 km; Table 2). Transects located
on the south area (T03, T04 and T05) had higher
richness than the northern area (T01 and T02). In
T01 and T02, both located nearby Abraão Village,
we only observed three species that were present
in all transects (D. aurita, C. jacchus, and G.
brasiliensis). During this study, tourists were found
with some frequency in transects T01 and T02, and
with less frequency in transects T03 and T04. No
tourist was found in T05, since the access is
prohibited. Signs of poaching were observed in
transects T01, T02 and with less evidence in T03
and T04.
Eye reflection and movement were the two
most frequent forms of detection, with eye reflection
restricted to nocturnal species. Warning cries were
mostly restricted to diurnal species such as G.
brasiliensis and C. jacchus. Significant differences
were found in encounter rates among the five forms
of detection (F = 3.432, p = 0.011) and among species
(F = 4.115, p = 0.009). The Tukey test a posteriori
indicated that there was a difference between
detections by eye reflection and by movement on the
ground, with higher encounter rates for the common
opossum and for the spotted paca by eye reflection
(Table 3).
Table 3. Total number of observations for each species according to the form of detection and significance level of the two-
way ANOVA in Ilha Grande, state of Rio de Janeiro, Brazil.
Table 2. Encounter rates of each mammal species per transect in Ilha Grande, state of Rio de Janeiro, Brazil.
Species T01 T02 T03 T04 T05 Total
Alouatta guariba 0 0.94 1.23 0.74 0.18 0.92
Callithrix jacchus 1.05 0.75 0.1 0.5 0.89 0.53
Coendou spinosus 0 0 0 0.06 0.18 0.05
Cuniculus paca 0 2.26 0.41 0.18 0.18 0.62
Dasyprocta leporina 0 0 0 0.5 0.89 0.33
Dasypus novemcinctus 0 0 0.14 0.37 1.58 0.39
Didelphis aurita 0.52 0 0.28 0.12 0 0.09
Guerlinguetus brasiliensis 1.76 0 0.41 1.62 1.06 0.87
Hydrochoerus hydrochaeris 0 0 0.41 0.31 0.35 0.25
Total 3.35 3.97 3.13 4.42 5.29 4.06
Species Warning
cries
Movement
in branches
Movement
on the ground
Motion
detection
Eye
reflection
Alouatta guariba
- 6 - 10 -
Callithrix jacchus 10 9 - 6
Coendou spinosus - 3 - 2 5
Cuniculus paca 1 - 12 4 18
Dasyprocta leporina
- - 4 - -
Dasypus
novemcinctus - - 5 2 6
Didelphis aurita
- 2 3 4 12
Guerlinguetus brasiliensis 11 10 5 11 -
Hydrochoerus hydrochaeris
- - - 2 -
Total of observations 22 30 29 41 41
Mammalian Detectability in Transect Surveys 427
Oeco l. Aust., 21(4): 422-4 30, 2017
Only D. aurita and C. jacchus had their
frequencies of detection affected by the weather,
which were more detected under cloudy days (X2 =
5.608, p = 0.018 and X2 = 6.862, p = 0.008; Table
4). Cuniculus paca was more detected in days with
no wind and D. aurita in days of weak wind (X2 =
4.154, p = 0.042 and X2 = 17.757, p = < 0.001; Table
4). Only two species were detected on days of
strong wind: D. aurita and A. guariba. (Table 4).
In relation to the sighting time, the Kruskal
Wallis test indicated the existence of significant
differences between the encounter rates among the
groups of sighting time (KW = 11377, p = 0.044;
Table 5). Most of the records were made between
06:01 to 08:00 h (Tukey test a posteriori: p = 0.03)
an d be t w e en 18 : 0 1 to 20:00 h (Tukey test a
posteriori: p = 0.04). Cuniculus paca was detected
only after 16:00 h, and even then, only one out of 35
obs e rvat i ons w a s b e fore 18 : 00 h . Dasy pus
nove m cinct us an d D. aur ita a l so pre s ent e d
crepuscular and nocturnal habits, but were also
recorded in the period close to dawn. Pri mate
species showed activity time between 06:00 and
18:00 h, and only one record of A. guariba occurred
before 6:00 h. This case was a single individual found
in the ground.
Table 5. Number of observations for each species according to the sighting time and encounter rates (individual or group
/ 10 km) in Ilha Grande, state of Rio de Janeiro, Brazil.
Table 4. Frequency of detection of each species and chi-square test results with p values according to different climate
conditions. df = 1 for all the analyses in Ilha Grande, state of Rio de Janeiro, Brazil. Significant values for the chi-square test
are in bold.
Species
04:00-06:00
06:01– 08:00
08:01-10:00
16:00- 18:00
18:01-20:00
20:01-23:00
Alouatta guariba
1 9 0 6 0 0
Callithrix jacchus 0 16 5 4 0 0
Coendou spinosus 2 1 0 0 4 3
Cuniculus paca 0 0 0 1 18 16
Dasyprocta leporina
0 1 3 0 0 0
Dasypus
novemcinctus 5 0 0 0 3 5
Didelphis aurita
4 0 0 0 13 4
Guerlinguetus brasiliensis 0 22 11 4 0 0
Hydrochoerus hydrochaeris
0 0 1 1 0 0
Total of observations 12 49 20 16 38 28
Encounter rate 0.29
1.22
0.49
0.39
0.95
0.69
Species Weather Wind
Clear Cloudy Rainy X
2
(p) No
wind Weak Medium Strong X
2
(p)
Alouatta guariba 7 7 2 0.268 (0.604) 4 9 2 1 1.801 (0.180)
Callithrix jacchus 9 15 1 6.862 (0.008) 8 15 2 0 0.198 (0.656)
Coendou spinosus 4 5 1 - 5 4 1 0 -
Cuniculus paca 19 14 2 1.294 (0.255) 25 6 4 0 4.154 (0.042)
Dasyprocta leporina 1 2 1 0.001 (0.982) 3 0 1 0 2.77 (0.096)
Dasypus novemcinctus 10 3 0 0.569 (0.451) 8 3 2 0 3.077 (0.079)
Didelphis aurita 8 10 3 5.608 (0.018) 8 9 3 1 17.757 (< 0.001)
Guerlinguetus brasiliensis 16 19 2 6.862 (0.008) 12 18 7 0 0.198 (0.656)
Hydrochoerus hydrochaeris 1 1 0 - 1 1 0 0 -
428 Pereira et al.
Oecol. Aust., 21(4): 422-430, 2017
DISCUSSION
The tree species present in all transects (D.
aurita, C. jacchus, and G. brasiliensis) are considered
as generalist or opportunistic species. Didelphis aurita
is a generalist species (Cáceres 2003) as well as C.
jacchus (Cunha 2005). Both are able to live in altered
habitats and under the most different conditions,
including near human habitations. In addition, C. jacchus
is an invasive species introduced in southeastern Brazil
(Cerqueira et al. 1998), and its presence has been
reported in both urban and preserved forest areas. In
Ilha Grande, we had higher encounter rates of C.
jacchus in the northern area of the island (near Abraão
Village). Guerlinguetus brasiliensis is an opportunistic
species (Alvarenga & Talamoni 2006), easily detected,
with high encounter rates (Chiarello 2000, Marques
2004), and may occur in secondary forests, farms and
parks (Emmons & Feer 1997).
The lower encounter rates observed in T01, T02,
and T03 (south) when compared to T04 and T05 (north)
may be due to human population densities, tourism, and
poaching. Although considered an alternative for
sustainable use in some protected areas, tourism can
have an impact on habitat and natural populations
(Rocha et al. 2012, Habibullah et al. 2016), and Ilha
Grande receives a considerable amount of tourists
throughout the year. The island has a network of trails
that consists of 16 units used by tourists to reach the
various parts of the island. However, since Abraão
Village is the largest settlement in Ilha Grande (i.e.,
located in the north), where most of the hotels are
located, the nearby trails are more frequently used by
tourists. On the other hand, the southern trails are more
isolated and less frequented. Despite a large portion
of Ilha Grande is inserted in protected areas, such as
the Ilha Grande State Park, poaching is also a common
activity in the region. In fact, mammals species whose
meat are much appreciated for food by the local
people have become rare nearby the village, such as
C. paca, D. leporina, and D. novemcin ct us.
Several studies have shown changes in the
abundance of species, and even behavioural changes
in some animals due to poaching pressure (Galetti et
al. 2015, Ferreguetti et al. 2015, 2016, 2017). In fact,
some species may become more skittish and difficult to
see in environments where the practice of poaching is
frequent (Peres & Lake 2003, Ferreguetti et al. 2015,
2016, 2017). This may even affect their activity time,
because some species tend to forage at night in areas
with human presence (Cullen Jr. et al. 2001, Di Bitetti
et al. 2008, Ferreguetti et al. 2015). Thus, the encounter
rates could be lower in T01 and T02 transects because
of the interference of tourists and the poaching pressure,
which must be associated with the higher human densities
in the north of the island, which would inhibit the
presence of certain species.
The form of detection affected encounter rates.
A higher detectability related to eye reflection and
movement was expected, since eye reflection is
restricted to nocturnal species, and the movement
detection (visual) is facilitated for diurnal species. This
may also explain the differences between the
encounter rates depending on the time of observation.
If we add up the six sighting time groups into two,
day and night, night observations would have a higher
number of records. Morgia et al. (2015) defend the
benefits of distance sampling at night, mainly because
the estimates generated in the analysis can be more
precise and accurate, due to the easily detection of
the animals by eye reflection. On the other hand,
Duckworth (1998) mentions the difficulties in
performing distance samplings at night, especially to
detect more cryptic species, with weak eye reflection.
In this study, the detection by eye reflection was very
effective for nocturnal species. The night samplings
in the south area provided data on species that
occurred only or mostly in this period, such as D.
novemcinctus and C. paca. Cuniculus paca is a
highly poached species by the local population, so
few observations were expected, but it was the
second most sighted species and easily detected even
over long distances by its intense eye reflection. On
the other hand, the night samplings on the north side
showed a low success of observations, where the
only sighted species was D. aurita. According to Di
Bitetti et al. (2008), some species change their
behaviour when under poaching pressure because of
the flashlights used by hunters, acquiri ng a
“photophobia” and running away before being
detected. This could explain the low frequency of
observations or even the non-detection of certain
Mammalian Detectability in Transect Surveys 429
Oecol. Aust., 21(4): 422-430, 2017
species in the north transects. This supports the
hypothesis that low species richness in the north area
transects may be due to poaching pressure. On the
other hand, on the southern area, where poaching is
lower, hunted species were more frequently observed
(C. paca, D. leporina, and D. novencimctus).
Although some authors avoid collecting data
at night (Duckworth 1998, Marques 2004), this study
has shown that they provide a good amount of data
for species that are generally less frequently
observed. Since most of the Neotropical mammals
have predominantly nocturnal habits, a higher sampling
effort during the night is required to obtain sufficient
data to estimate the density of these species. Thus,
we did not corroborate the hypothesis that the species
are less detected at night samplings because of the
limitation of the observer’s view (i.e., limited by the
flashlight range). All nocturnal species recorded here
were mainly detected by the light reflection in their
eyes, and were less dependent on motion or noise
for detection. We observed that even species of small
mammals, such as arboreal marsupials, could be
detected at night by the eye shine.
Climate and wind also affected the frequency
of detection, as expected. Peres (1999) does not
recommend transects on rainy days because the
weather would affect the ability of the observer to
detect animals, both visually (i.e, animals tend to
decrease their activity), and acoustically (i.e., difficulty
in hearing noises caused by animal motion or alert).
The same may apply in days of strong winds. The
number of observations on rainy days was, as expected,
much lower than on cloudy days, with few observations
of A. guariba and D. agouti. Weather, however, did
not affect the observation of nocturnal species, because
it is possible to see the eye shine even under rain.
Several factors can affect the encounter rate
estimates in studies using distance sampling by linear
transects. In the present study, we detected the
influence of animal activity period (i.e., object of study),
followed by climate conditions, and transect location
as important variables for estimating encounter rates
in mammals. This study hopes to call attention of these
variables when using this methodology widely applied
in the study of mammals and to contribute to the
experimental design of similar studies.
ACKNOWLEDGEMENTS
We than k th e Centr o de Estudo Ambi e ntais e
Desenvolvimento Sustentável (CEADS) and the Rio de Janeiro
State University for the logistical support during the execution of
this research. We also thank the Instituto Biomas for financial
support. BCP is also grateful to Coordenação de Aperfeiçoamente
de Pessoal de Nível Superior (CAPES) for a graduate scholarship.
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Submitted: 30 March 2017
Accepted: 03 October 2017
Associate Editor: Rosana Gentile
